From 6d887b7fb7f576bb304c5f2d644733cbca034a86 Mon Sep 17 00:00:00 2001 From: Andrew Rohne Date: Mon, 15 Aug 2022 18:51:38 -0400 Subject: [PATCH 01/61] Added mwcog small area --- activitysim/examples/example_manifest.yaml | 15 + .../examples/prototype_mwcog/.gitignore | 2 + .../examples/prototype_mwcog/README.MD | 3 + .../configs/_dummy_coefficients.csv | 2 + .../prototype_mwcog/configs/accessibility.csv | 59 + .../configs/accessibility.yaml | 13 + .../configs/annotate_households.csv | 42 + .../configs/annotate_households_cdap.csv | 9 + .../configs/annotate_households_workplace.csv | 5 + .../configs/annotate_landuse.csv | 9 + .../configs/annotate_persons.csv | 68 + .../configs/annotate_persons_after_hh.csv | 23 + .../configs/annotate_persons_cdap.csv | 6 + .../configs/annotate_persons_jtp.csv | 3 + .../configs/annotate_persons_mtf.csv | 10 + .../configs/annotate_persons_nmtf.csv | 15 + .../configs/annotate_persons_school.csv | 7 + .../configs/annotate_persons_workplace.csv | 32 + 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..._parking_annotate_persons_preprocessor.csv | 2 + .../configs/free_parking_coeffs.csv | 9 + .../configs/initialize_households.yaml | 21 + .../configs/initialize_landuse.yaml | 7 + .../configs/joint_tour_composition.csv | 22 + .../configs/joint_tour_composition.yaml | 11 + ...ition_annotate_households_preprocessor.csv | 22 + .../configs/joint_tour_composition_coeffs.csv | 32 + .../configs/joint_tour_destination.csv | 17 + .../configs/joint_tour_destination.yaml | 54 + .../configs/joint_tour_destination_coeffs.csv | 39 + .../configs/joint_tour_destination_sample.csv | 15 + .../configs/joint_tour_frequency.csv | 78 + .../configs/joint_tour_frequency.yaml | 11 + .../joint_tour_frequency_alternatives.csv | 23 + ...uency_annotate_households_preprocessor.csv | 32 + .../configs/joint_tour_frequency_coeffs.csv | 106 + .../configs/joint_tour_participation.csv | 67 + .../configs/joint_tour_participation.yaml | 20 + ...ion_annotate_participants_preprocessor.csv | 24 + 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.../configs/telecommute_frequency_coeffs.csv | 61 + ...ur_departure_and_duration_alternatives.csv | 1177 + .../tour_departure_and_duration_segments.csv | 50 + .../configs/tour_mode_choice.csv | 335 + .../configs/tour_mode_choice.yaml | 114 + ..._choice_annotate_choosers_preprocessor.csv | 88 + .../configs/tour_mode_choice_coeffs.csv | 454 + .../tour_mode_choice_coeffs_template.csv | 118 + .../configs/tour_scheduling_atwork.csv | 50 + .../configs/tour_scheduling_atwork.yaml | 16 + .../configs/tour_scheduling_atwork_coeffs.csv | 47 + .../tour_scheduling_atwork_preprocessor.csv | 3 + .../configs/tour_scheduling_joint.csv | 315 + .../configs/tour_scheduling_joint_coeffs.csv | 307 + .../tour_scheduling_nonmandatory_eatout.csv | 60 + ...uling_nonmandatory_eatout_coefficients.csv | 59 + .../tour_scheduling_nonmandatory_escort.csv | 76 + ...uling_nonmandatory_escort_coefficients.csv | 72 + .../tour_scheduling_nonmandatory_othdiscr.csv | 55 + ...ing_nonmandatory_othdiscr_coefficients.csv | 53 + 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...estination_annotate_trips_preprocessor.csv | 9 + .../configs/trip_destination_coefficients.csv | 19 + .../configs/trip_destination_sample.csv | 18 + .../configs/trip_mode_choice.csv | 455 + .../configs/trip_mode_choice.yaml | 148 + ...ode_choice_annotate_trips_preprocessor.csv | 101 + .../configs/trip_mode_choice_coefficients.csv | 557 + ...trip_mode_choice_coefficients_template.csv | 88 + .../prototype_mwcog/configs/trip_purpose.yaml | 7 + .../configs/trip_purpose_and_destination.yaml | 6 + ...ip_purpose_annotate_trips_preprocessor.csv | 5 + .../configs/trip_purpose_probs.csv | 132 + .../configs/trip_scheduling.yaml | 10 + .../configs/trip_scheduling_probs.csv | 3457 ++ .../configs/work_from_home.csv | 15 + .../configs/work_from_home.yaml | 12 + .../configs/work_from_home_coeffs.csv | 15 + .../configs/workplace_location.csv | 20 + .../configs/workplace_location.yaml | 81 + .../configs/workplace_location_coeffs.csv | 15 + .../configs/workplace_location_sample.csv | 17 + .../configs/write_trip_matrices.yaml | 259 + ...p_matrices_annotate_trips_preprocessor.csv | 109 + .../prototype_mwcog/configs_mp/logging.yaml | 57 + .../prototype_mwcog/configs_mp/settings.yaml | 92 + .../configs_mp/settings_source.yaml | 95 + .../configs_mp/shadow_pricing.yaml | 37 + .../LU_taz3722_rnd91a_2018_adj_enrollment.csv | 54 + .../data/combined_synthetic_hh_2018.csv | 29973 ++++++++++++ .../data/combined_synthetic_per_2018.csv | 40138 ++++++++++++++++ .../prototype_mwcog/data/land_use.csv | 54 + .../examples/prototype_mwcog/data/skims.omx | Bin 0 -> 5728575 bytes .../prototype_mwcog/data/taz_skims.omx | Bin 0 -> 8630453 bytes .../prototype_mwcog/extensions/__init__.py | 4 + .../extensions/telecommute_frequency.py | 101 + .../extensions/transit_pass_ownership.py | 90 + .../extensions/transit_pass_subsidy.py | 90 + .../extensions/work_from_home.py | 104 + .../prototype_mwcog/scripts/mwcog_crop.py | 274 + .../examples/prototype_mwcog/simulation.py | 17 + 199 files changed, 87489 insertions(+) create mode 100644 activitysim/examples/prototype_mwcog/.gitignore create mode 100644 activitysim/examples/prototype_mwcog/README.MD create mode 100644 activitysim/examples/prototype_mwcog/configs/_dummy_coefficients.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/accessibility.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/accessibility.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/annotate_households.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/annotate_households_cdap.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/annotate_households_workplace.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/annotate_landuse.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/annotate_persons.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/annotate_persons_after_hh.csv create mode 100644 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activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint_coefficients.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping_coefficients.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social_coefficients.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_school.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_school_coeffs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_university.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_university_coeffs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_work.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/tour_scheduling_work_coeffs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/transit_pass_ownership_coeffs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy_coeffs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_destination.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_destination.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_destination_annotate_trips_preprocessor.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_destination_coefficients.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_destination_sample.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_mode_choice.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_mode_choice.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_mode_choice_annotate_trips_preprocessor.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients_template.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_purpose.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_purpose_and_destination.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_purpose_annotate_trips_preprocessor.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_purpose_probs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_scheduling.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/trip_scheduling_probs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/work_from_home.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/work_from_home.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/work_from_home_coeffs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/workplace_location.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/workplace_location.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/workplace_location_coeffs.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/workplace_location_sample.csv create mode 100644 activitysim/examples/prototype_mwcog/configs/write_trip_matrices.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs/write_trip_matrices_annotate_trips_preprocessor.csv create mode 100644 activitysim/examples/prototype_mwcog/configs_mp/logging.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs_mp/settings.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs_mp/settings_source.yaml create mode 100644 activitysim/examples/prototype_mwcog/configs_mp/shadow_pricing.yaml create mode 100644 activitysim/examples/prototype_mwcog/data/LU_taz3722_rnd91a_2018_adj_enrollment.csv create mode 100644 activitysim/examples/prototype_mwcog/data/combined_synthetic_hh_2018.csv create mode 100644 activitysim/examples/prototype_mwcog/data/combined_synthetic_per_2018.csv create mode 100644 activitysim/examples/prototype_mwcog/data/land_use.csv create mode 100644 activitysim/examples/prototype_mwcog/data/skims.omx create mode 100644 activitysim/examples/prototype_mwcog/data/taz_skims.omx create mode 100644 activitysim/examples/prototype_mwcog/extensions/__init__.py create mode 100644 activitysim/examples/prototype_mwcog/extensions/telecommute_frequency.py create mode 100644 activitysim/examples/prototype_mwcog/extensions/transit_pass_ownership.py create mode 100644 activitysim/examples/prototype_mwcog/extensions/transit_pass_subsidy.py create mode 100644 activitysim/examples/prototype_mwcog/extensions/work_from_home.py create mode 100644 activitysim/examples/prototype_mwcog/scripts/mwcog_crop.py create mode 100644 activitysim/examples/prototype_mwcog/simulation.py diff --git a/activitysim/examples/example_manifest.yaml b/activitysim/examples/example_manifest.yaml index f9b7b50a1..e1a5d591a 100644 --- a/activitysim/examples/example_manifest.yaml +++ b/activitysim/examples/example_manifest.yaml @@ -894,3 +894,18 @@ - https://media.githubusercontent.com/media/activitysim/activitysim_resources/master/sandag_xborder/traffic_skims_xborder_PM.omx data/traffic_skims_xborder_PM.omx 87544b59488c4ca654ae8d9756dfb3a8226b85faa21e631339d86fae5dc60feb + +- name: prototype_mwcog + description: 53 zone test example for the SEMCOG region + # activitysim create -e prototype_mwcog -d test_prototype_mwcog + # cd test_prototype_mwcog + # python simulation.py -c configs -o output -d data + # cd .. + include: + - prototype_mwcog/extensions + - prototype_mwcog/data + - prototype_mwcog/configs + - prototype_mwcog/configs_mp + - prototype_mwcog/output + - prototype_mwcog/README.MD + - prototype_mwcog/simulation.py \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/.gitignore b/activitysim/examples/prototype_mwcog/.gitignore new file mode 100644 index 000000000..443919a09 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/.gitignore @@ -0,0 +1,2 @@ +data_*/ +output_*/ diff --git a/activitysim/examples/prototype_mwcog/README.MD b/activitysim/examples/prototype_mwcog/README.MD new file mode 100644 index 000000000..07bca00ad --- /dev/null +++ b/activitysim/examples/prototype_mwcog/README.MD @@ -0,0 +1,3 @@ +### MWCOG Example + +This is an example of the Metropolitan Washington Council of Governments ActivitySim model. This is a 53 zone portion of the model, centered on the National Mall. \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/_dummy_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/_dummy_coefficients.csv new file mode 100644 index 000000000..2b8df5025 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/_dummy_coefficients.csv @@ -0,0 +1,2 @@ +coefficient_name,value,constrain +coef_one,1,T diff --git a/activitysim/examples/prototype_mwcog/configs/accessibility.csv b/activitysim/examples/prototype_mwcog/configs/accessibility.csv new file mode 100644 index 000000000..c7dcc7782 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/accessibility.csv @@ -0,0 +1,59 @@ +Description,Target,Expression +#,, +#,, auto peak +#,, +#,, assume peak occurs in AM for outbound and PM for inbound +peak round trip time,_auPkTime,"skim_od[('SOV_TIME', 'AM')] + skim_do[('SOV_TIME', 'PM')]" +decay function,_decay, exp(_auPkTime * dispersion_parameter_automobile) +auto peak retail,auPkRetail,df.RETEMP * _decay +auto peak total,auPkTotal,df.TOTEMP * _decay +#,, +#,, auto off-peak +#,, +#,, assume midday occurs entirely in the midday period +off-peak round trip time,_auOpTime,"skim_od[('SOV_TIME', 'MD')] + skim_do[('SOV_TIME', 'MD')]" +decay function,_decay, exp(_auOpTime * dispersion_parameter_automobile) +auto off-peak retail,auOpRetail,df.RETEMP * _decay +auto off-peak total,auOpTotal,df.TOTEMP * _decay +#,, +#,, transit peak +#,, +#,, assume peak outbound transit occurs in AM +o-d peak transit ivt,_inVehicleTime,"skim_od[('WK_TRN_WK_TOTIVT', 'AM')]" +o-d peak transit ovt,_outOfVehicleTime,"skim_od[('WK_TRN_WK_IWAIT', 'AM')] + skim_od[('WK_TRN_WK_XWAIT', 'AM')] + skim_od[('WK_TRN_WK_WACC_EGR', 'AM')] + skim_od[('WK_TRN_WK_WAUX', 'AM')]" +o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) +#,, assume peak inbound transit occurs in PM +d-o peak transit ivt,_inVehicleTime,"skim_od[('WK_TRN_WK_TOTIVT', 'PM')]" +d-o peak transit ovt,_outOfVehicleTime,"skim_od[('WK_TRN_WK_IWAIT', 'PM')] + skim_od[('WK_TRN_WK_XWAIT', 'PM')] + skim_od[('WK_TRN_WK_WACC_EGR', 'PM')] + skim_od[('WK_TRN_WK_WAUX', 'PM')]" +d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) +peak transit time,_trPkTime,_trPkTime_od + _trPkTime_do +round trip path is available,_rt_available,(_trPkTime_od > 0) & (_trPkTime_do > 0) +decay function,_decay,_rt_available * exp(_trPkTime * dispersion_parameter_transit) +transit peak retail,trPkRetail,df.RETEMP * _decay +transit peak total,trPkTotal,df.TOTEMP * _decay +#,, +#,, transit off-peak +#,, +#,, assume off-peak outbound transit occurs in the MD time period +o-d off-peak transit ivt,_inVehicleTime,"skim_od[('WK_TRN_WK_TOTIVT', 'MD')]" +o-d off-peak transit ovt,_outOfVehicleTime,"skim_od[('WK_TRN_WK_IWAIT', 'MD')] + skim_od[('WK_TRN_WK_XWAIT', 'MD')] + skim_od[('WK_TRN_WK_WACC_EGR', 'MD')] + skim_od[('WK_TRN_WK_WAUX', 'MD')]" +o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) +#,, assume off-peak inbound transit occurs in the MD time period +d-o off-peak transit ivt,_inVehicleTime,"skim_do[('WK_TRN_WK_TOTIVT', 'MD')]" +d-o off-peak transit ovt,_outOfVehicleTime,"skim_do[('WK_TRN_WK_IWAIT', 'MD')] + skim_do[('WK_TRN_WK_XWAIT', 'MD')] + skim_do[('WK_TRN_WK_WACC_EGR', 'MD')] + skim_do[('WK_TRN_WK_WAUX', 'MD')]" +d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) +peak transit time,_trOpTime,_trOpTime_od + _trOpTime_do +#,,FIXME - _rt_available calculation appears to be wrong in mtctm1 accessibility.job +#round trip path is available,_rt_available,(_trOpTime > 0) +round trip path is available,_rt_available,(_trOpTime_od > 0) & (_trOpTime_do > 0) +decay function,_decay,_rt_available * exp(_trOpTime * dispersion_parameter_transit) +transit off-peak retail,trOpRetail,df.RETEMP * _decay +transit off-peak total,trOpTotal,df.TOTEMP * _decay +#,, +#,, non motorized +#,, +non-motorized round trip distance,_nmDist,skim_od['DISTWALK'] + skim_do['DISTWALK'] +round trip path is available,_rt_available,_nmDist <= maximum_walk_distance +decay function,_decay,_rt_available * exp(_nmDist * dispersion_parameter_walk) +retail accessibility,nmRetail,df.RETEMP * _decay +total accessibility,nmTotal,df.TOTEMP * _decay diff --git a/activitysim/examples/prototype_mwcog/configs/accessibility.yaml b/activitysim/examples/prototype_mwcog/configs/accessibility.yaml new file mode 100644 index 000000000..b52c69ee1 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/accessibility.yaml @@ -0,0 +1,13 @@ + +# columns from land_use table to add to df +land_use_columns: ['RETEMP', 'TOTEMP'] + +CONSTANTS: + # dispersion parameters + dispersion_parameter_automobile: -0.05 + dispersion_parameter_transit: -0.05 + dispersion_parameter_walk: -1.00 + # maximum walk distance in miles + maximum_walk_distance: 3.0 + # perceived minute of in-vehicle time for every minute of out-of-vehicle time + out_of_vehicle_time_weight: 2.0 diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_households.csv b/activitysim/examples/prototype_mwcog/configs/annotate_households.csv new file mode 100644 index 000000000..c1383d174 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_households.csv @@ -0,0 +1,42 @@ +Description,Target,Expression +#,, annotate households table after import +,_PERSON_COUNT,"lambda query, persons, households: persons.query(query).groupby('household_id').size().reindex(households.index).fillna(0).astype(np.int8)" +#,,FIXME households.income can be negative - so we clip? +income,income,households.hhincadj.fillna(0) +income_in_thousands,income_in_thousands,(income / 1000).clip(lower=0) +income_segment,income_segment,"pd.cut(income_in_thousands, bins=[-np.inf, 50, 100, 150, np.inf], labels=[1, 2, 3, 4]).astype(int)" +#,, +,_MIN_VOT,setting('min_value_of_time') +,_MAX_VOT,setting('max_value_of_time') +,_MU,setting('distributed_vot_mu') +,_SIGMA,setting('distributed_vot_sigma') +median_value_of_time,median_value_of_time,"income_segment.map({k: v for k, v in setting('household_median_value_of_time').items()})" +hh_value_of_time,hh_value_of_time,"rng.lognormal_for_df(df, mu=np.log(median_value_of_time * _MU), sigma=_SIGMA).clip(_MIN_VOT, _MAX_VOT)" +#,, +#num_workers was renamed in import,, +,num_workers,"_PERSON_COUNT('(ESR==1)|(ESR==2)|(ESR==4)|(ESR==5)', persons, households)" +number of non_workers,num_non_workers,households.hhsize - num_workers +#,, +#,,we assume that everyone 16 and older is a potential driver +number of drivers,num_drivers,"_PERSON_COUNT('16 <= age', persons, households)" +num_adults,num_adults,"_PERSON_COUNT('18 <= age', persons, households)" +num_children,num_children,"_PERSON_COUNT('18 > age', persons, households)" +num_young_children,num_young_children,"_PERSON_COUNT('age <= 5', persons, households)" +num_children_5_to_15,num_children_5_to_15,"_PERSON_COUNT('5 <= age <= 15', persons, households)" +num_children_6_to_12,num_children_6_to_12,"_PERSON_COUNT('6 <= age <= 12', persons, households)" +num_children_16_to_17,num_children_16_to_17,"_PERSON_COUNT('16 <= age <= 17', persons, households)" +num_college_age,num_college_age,"_PERSON_COUNT('18 <= age <= 24', persons, households)" +num_young_adults,num_young_adults,"_PERSON_COUNT('25 <= age <= 34', persons, households)" +non_family,non_family,households.HHT.isin(HHT_NONFAMILY) +family,family,households.HHT.isin(HHT_FAMILY) +home_is_urban,home_is_urban,"reindex(land_use.AREATYPE, households.home_zone_id) < setting('urban_threshold')" +home_is_rural,home_is_rural,"reindex(land_use.AREATYPE, households.home_zone_id) > setting('rural_threshold')" +#,, default for work and school location logsums before auto_ownership model is run +,auto_ownership,households.auto_ownership +TAZ column to match settings file,TAZ,households.home_zone_id +number of pre-driving age children in the household,num_predrive_child,"_PERSON_COUNT('ptype == 7', persons, households)" +number of non-working adult in the household,num_nonworker_adults,"_PERSON_COUNT('ptype == 4', persons, households)" +number of full time workers,num_fullTime_workers,"_PERSON_COUNT('is_fulltime_worker', persons, households)" +number of part time workers,num_partTime_workers,"_PERSON_COUNT('is_parttime_worker', persons, households)" +number of retired adults in the household,_num_retired_adults,"_PERSON_COUNT('ptype == 5', persons, households)" +Retired Adults Only Households,retired_adults_only_hh,(households.hhsize > 0) & (households.hhsize == _num_retired_adults) diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_households_cdap.csv b/activitysim/examples/prototype_mwcog/configs/annotate_households_cdap.csv new file mode 100644 index 000000000..44b4fdcbf --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_households_cdap.csv @@ -0,0 +1,9 @@ +Description,Target,Expression +#,, annotate households table after cdap model has run +num_under16_not_at_school,num_under16_not_at_school,persons.under16_not_at_school.astype(int).groupby(persons.household_id).sum().reindex(households.index).fillna(0).astype(np.int8) +num_travel_active,num_travel_active,persons.travel_active.astype(int).groupby(persons.household_id).sum().reindex(households.index).fillna(0).astype(np.int8) +num_travel_active_adults,num_travel_active_adults,(persons.adult & persons.travel_active).astype(int).groupby(persons.household_id).sum().reindex(households.index).fillna(0).astype(np.int8) +num_travel_active_preschoolers,num_travel_active_preschoolers,((persons.ptype == PTYPE_PRESCHOOL) & persons.travel_active).astype(int).groupby(persons.household_id).sum().reindex(households.index).fillna(0).astype(np.int8) +num_travel_active_children,num_travel_active_children,num_travel_active - num_travel_active_adults +num_travel_active_non_preschoolers,num_travel_active_non_preschoolers,num_travel_active - num_travel_active_preschoolers +participates_in_jtf_model,participates_in_jtf_model,(num_travel_active > 1) & (num_travel_active_non_preschoolers > 0) diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_households_workplace.csv b/activitysim/examples/prototype_mwcog/configs/annotate_households_workplace.csv new file mode 100644 index 000000000..1b53e91da --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_households_workplace.csv @@ -0,0 +1,5 @@ +Description,Target,Expression +#,, annotate households table after workplace_location model has run +#,, hh_work_auto_savings_ratio is sum of persons work_auto_savings_ratio +,hh_work_auto_savings_ratio,persons.work_auto_savings_ratio.groupby(persons.household_id).sum().reindex(households.index).fillna(0.0) +#,,handle persons with no locatcion diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_landuse.csv b/activitysim/examples/prototype_mwcog/configs/annotate_landuse.csv new file mode 100644 index 000000000..8cb7aab08 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_landuse.csv @@ -0,0 +1,9 @@ +Description,Target,Expression +#,, annotate landuse table after import +household_density,household_density,land_use.HH / (land_use.LANDAREA * 640) +employment_density,employment_density,land_use.TOTEMP / (land_use.LANDAREA * 640) +,employment_density,employment_density.fillna(0) +density_index,density_index,(household_density *employment_density) / (household_density + employment_density).clip(lower=1) +topology (assume flat),TOPOLOGY,1 +zero out land use for zero area,Park_Acres,"np.where(land_use.LANDAREA==0,0,land_use.Park_Acres)" +zero out land use for zero area,GC_Acres,"np.where(land_use.LANDAREA==0,0,land_use.GC_Acres)" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons.csv new file mode 100644 index 000000000..df047862c --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons.csv @@ -0,0 +1,68 @@ +Description,Target,Expression +#,, annotate persons table after import +age_0_to_5,age_0_to_5,"persons.age.between(0,5)" +age_6_to_12,age_6_to_12,"persons.age.between(6,12)" +age_16_to_19,age_16_to_19,"persons.age.between(16, 19)" +age_16_p,age_16_p,persons.age >= 16 +adult,adult,persons.age >= 18 +young,young,persons.age <= 25 +old,old,persons.age >= 65 +male,male,persons.SEX == 1 +female,female,persons.SEX == 2 +,esr,persons.ESR.fillna(0) +,wkhp,persons.WKHP.fillna(0) +,wkw,persons.WKW.fillna(0) +,schg,persons.SCHG.fillna(0) +,mil,persons.MIL.fillna(0) +employment status type,pemploy,np.zeros(len(persons)) +,pemploy,"np.where(persons.age < 16, PEMPLOY_CHILD, PEMPLOY_PART)" +,pemploy,"np.where((persons['age'] >= 16) & ((esr == 3) | (esr == 6)), PEMPLOY_NOT, pemploy)" +,pemploy,"np.where((persons.age>=16)&((esr != 3)&(esr != 6))&(wkhp >= 35) & (wkw >= 1) & (wkw <= 4), PEMPLOY_FULL, pemploy)" +student category,pstudent,np.zeros(len(persons)) +,pstudent,"np.where((pemploy == 1) & (persons.age >= 16), PSTUDENT_NOT, pstudent)" +,pstudent,"np.where((pemploy == 1) & (persons.age < 16), PSTUDENT_GRADE_OR_HIGH, pstudent)" +,pstudent,"np.where((schg < 1) & (persons.age >= 16), PSTUDENT_NOT, pstudent)" +,pstudent,"np.where((schg < 1) & (persons.age < 16), PSTUDENT_GRADE_OR_HIGH, pstudent)" +,pstudent,"np.where((schg >= 15) & (persons.age >= 16) & (pemploy != 1), PSTUDENT_UNIVERSITY, pstudent)" +,pstudent,"np.where((schg >= 15) & (persons.age < 16) & (pemploy != 1), PSTUDENT_GRADE_OR_HIGH, pstudent)" +,pstudent,"np.where((persons.age <= 19) & (pemploy != 1) & (schg >=1) & (schg<=14), PSTUDENT_GRADE_OR_HIGH, pstudent)" +,pstudent,"np.where((persons.age > 19) & (pemploy != 1) & (schg >=1) & (schg<=14), PSTUDENT_UNIVERSITY, pstudent)" +,pstudent,"np.where(pstudent == 0, 3, pstudent)" +person type,ptype,np.zeros(len(persons)) +,ptype,"np.where((pemploy == 1), PTYPE_FULL, PTYPE_NONWORK)" +,ptype,"np.where((pstudent == 3) & (pemploy == 2), PTYPE_PART, ptype)" +,ptype,"np.where((pstudent == 3) & (persons['age'] >= 65) & ((pemploy == 3) | (pemploy == 4)), PTYPE_RETIRED, ptype)" +,ptype,"np.where((pstudent == 3) & (persons['age'] < 6) & ((pemploy == 3) | (pemploy == 4)), PTYPE_PRESCHOOL, ptype)" +,ptype,"np.where((pstudent == 3) & (persons['age'] >= 6) & (persons['age'] <= 64) & ((pemploy == 3) | (pemploy == 4)), PTYPE_NONWORK, ptype)" +,ptype,"np.where((pstudent == 2) & ((pemploy == 2) | (pemploy == 3) | (pemploy == 4)), PTYPE_UNIVERSITY, ptype)" +,ptype,"np.where((pstudent == 1) & (persons['age'] < 6) & ((pemploy == 2) | (pemploy == 3) | (pemploy == 4)), PTYPE_PRESCHOOL, ptype)" +,ptype,"np.where((pstudent == 1) & (persons['age'] >= 16) & ((pemploy == 2) | (pemploy == 3) | (pemploy == 4)), PTYPE_DRIVING, ptype)" +,ptype,"np.where((pstudent == 1) & (persons['age'] >= 6) & (persons['age'] < 16) & ((pemploy == 2) | (pemploy == 3) | (pemploy == 4)), PTYPE_SCHOOL, ptype)" +presence of non_worker other than self in household,has_non_worker,"other_than(persons.household_id, ptype == PTYPE_NONWORK)" +presence of retiree other than self in household,has_retiree,"other_than(persons.household_id, ptype == PTYPE_RETIRED)" +presence of preschooler other than self in household,has_preschool_kid,"other_than(persons.household_id, ptype == PTYPE_PRESCHOOL)" +presence of driving_kid other than self in household,has_driving_kid,"other_than(persons.household_id, ptype == PTYPE_DRIVING)" +presence of school_kid other than self in household,has_school_kid,"other_than(persons.household_id, ptype == PTYPE_SCHOOL)" +presence of full_time worker other than self in household (independent of person type),has_full_time,"other_than(persons.household_id, pemploy==PEMPLOY_FULL)" +presence of part_time worker other than self in household (independent of person type),has_part_time,"other_than(persons.household_id, pemploy==PEMPLOY_PART)" +presence of university student other than self in household,has_university,"other_than(persons.household_id, ptype == PTYPE_UNIVERSITY)" +student_is_employed,student_is_employed,"np.where(((ptype == PTYPE_UNIVERSITY) | (ptype == PTYPE_DRIVING)) & ((pemploy == PEMPLOY_FULL) | (pemploy == PEMPLOY_PART)), True, False)" +nonstudent_to_school,nonstudent_to_school,"np.where(((ptype == PTYPE_FULL) | (ptype == PTYPE_PART) | (ptype == PTYPE_NONWORK) | (ptype == PTYPE_RETIRED)) & ((pstudent == PSTUDENT_GRADE_OR_HIGH) | (pstudent == PSTUDENT_UNIVERSITY)), True, False)" +is_student,is_student,"np.where((pstudent == PSTUDENT_GRADE_OR_HIGH) | (pstudent == PSTUDENT_UNIVERSITY), True, False)" +preschool age can go to preschool,is_student,"np.where((pstudent == PSTUDENT_GRADE_OR_HIGH) | (pstudent == PSTUDENT_UNIVERSITY) & (persons.age > GRADE_SCHOOL_MIN_AGE), True, is_student)" +is_gradeschool,is_gradeschool,(pstudent == PSTUDENT_GRADE_OR_HIGH) & (persons.age <= GRADE_SCHOOL_MAX_AGE) +is_highschool,is_highschool,(pstudent == PSTUDENT_GRADE_OR_HIGH) & (persons.age > GRADE_SCHOOL_MAX_AGE) +is_university,is_university,pstudent == PSTUDENT_UNIVERSITY +school_segment gradeschool,school_segment,"np.where(is_gradeschool, SCHOOL_SEGMENT_GRADE, SCHOOL_SEGMENT_NONE)" +school_segment highschool,school_segment,"np.where(is_highschool, SCHOOL_SEGMENT_HIGH, school_segment)" +school_segment university,school_segment,"np.where(is_university, SCHOOL_SEGMENT_UNIV, school_segment).astype(np.int8)" +#,, +is_worker,is_worker,"np.where((pemploy == PEMPLOY_FULL) |( pemploy == PEMPLOY_PART), True, False)" +#,, +home_zone_id,home_zone_id,"reindex(households.home_zone_id, persons.household_id)" +person number,PNUM,persons.per_num +income,income,"reindex(households.hhincadj, persons.household_id)" +income_in_thousands,income_in_thousands,(income / 1000).clip(lower=0) +income_segment,income_segment,"pd.cut(income_in_thousands, bins=[-np.inf, 50, 100, 150, np.inf], labels=[1, 2, 3, 4]).astype(int)" +is_fulltime_worker,is_fulltime_worker,"((age_16_p) & (wkhp >=35) & (wkw>=1) & (wkw<=4) & (~esr.isin([3,6])))" +is_parttime_worker,is_parttime_worker,"((age_16_p) & (~esr.isin([3,6])) & (is_fulltime_worker == False))" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons_after_hh.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons_after_hh.csv new file mode 100644 index 000000000..d3fe7f160 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons_after_hh.csv @@ -0,0 +1,23 @@ +Description,Target,Expression +#,, annotate persons table after annotate_households +#,, adults get full hh_value_of_time and children get 60% +,_hh_vot,"reindex(households.hh_value_of_time, persons.household_id)" +,value_of_time,"_hh_vot.where(persons.age>=18, _hh_vot * 0.667)" +,_hh_income,"reindex(households.hhincadj, persons.household_id)" +,_num_adults,"reindex(households.num_adults, persons.household_id)" +,_num_predrive_child,"reindex(households.num_predrive_child, persons.household_id)" +,_num_nonworker_adults,"reindex(households.num_nonworker_adults, persons.household_id)" +,_num_full_time_workers,"reindex(households.num_fullTime_workers, persons.household_id)" +Income less than 25K,is_income_less25K,(_hh_income)<25000 +Income 25K to 60K,is_income_25K_to_60K,((_hh_income)>=25000) & ((_hh_income)<60000) +Income 60K to 120K,is_income_60K_to_120K, ((_hh_income)>=60000) & ((_hh_income)<120000) +Income greater than 60K,is_income_greater60K,((_hh_income)>=60000) +Income greater than 120K,is_income_greater120K,((_hh_income)>=120000) +Presence of nonworker in HHs,is_non_worker_in_HH,_num_nonworker_adults>0 +all the adults in the HH are full time workers,is_all_adults_full_time_workers,(_num_adults) == (_num_full_time_workers) +Presence of predrive child in HHs,is_pre_drive_child_in_HH,_num_predrive_child>0 +,_has_young_children,"reindex(households.num_young_children, persons.household_id)" +,_has_children_6_to_12,"reindex(households.num_children_6_to_12, persons.household_id)" +has_young_children,has_young_children,_has_young_children>0 +has_children_6_to_12,has_children_6_to_12,_has_children_6_to_12>0 +hh_child,hh_child,"reindex(households.num_children, persons.household_id)" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons_cdap.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons_cdap.csv new file mode 100644 index 000000000..2ad5e56a6 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons_cdap.csv @@ -0,0 +1,6 @@ +Description,Target,Expression +#,, annotate persons table after cdap model has run +travel_active,travel_active,persons.cdap_activity != CDAP_ACTIVITY_HOME +under16_not_at_school,under16_not_at_school,"persons.ptype.isin([PTYPE_SCHOOL, PTYPE_PRESCHOOL]) & persons.cdap_activity.isin(['N', 'H'])" +has_preschool_kid_at_home,has_preschool_kid_at_home,"other_than(persons.household_id, (persons.ptype == PTYPE_PRESCHOOL) & (persons.cdap_activity == 'H'))" +has_school_kid_at_home,has_school_kid_at_home,"other_than(persons.household_id, (persons.ptype == PTYPE_SCHOOL) & (persons.cdap_activity == 'H'))" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons_jtp.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons_jtp.csv new file mode 100644 index 000000000..a72c86605 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons_jtp.csv @@ -0,0 +1,3 @@ +Description,Target,Expression +#,, annotate persons table after joint_tour_participation model has run +num_joint_tours,num_joint_tours,"joint_tour_participants.groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8)" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons_mtf.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons_mtf.csv new file mode 100644 index 000000000..4f8f5a8b0 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons_mtf.csv @@ -0,0 +1,10 @@ +Description,Target,Expression +#,, annotate persons table after mandatory_tour_frequency model has run +,_PERSON_TOUR_COUNT,"lambda exp, persons, tours: tours.query(exp).groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8)" +,_Q,"lambda s: ""'{}'"".format(s)" +work_and_school_and_worker,work_and_school_and_worker,(persons.mandatory_tour_frequency == 'work_and_school') & persons.is_worker +work_and_school_and_student,work_and_school_and_student,(persons.mandatory_tour_frequency == 'work_and_school') & persons.is_student +number of mandatory tours for each person,num_mand,"_PERSON_TOUR_COUNT('tour_category==%s' % _Q('mandatory'), persons, tours).fillna(0)" +number of work tours for each person,num_work_tours,"_PERSON_TOUR_COUNT('tour_type==%s' % _Q('work'), persons, tours).fillna(0)" +presence of pre school kid with mandatory tours,has_pre_school_child_with_mandatory,"other_than(persons.household_id, (persons.ptype == 8) & (num_mand > 0))" +presense of driving age school children with mandatory tours,has_driving_age_child_with_mandatory,"other_than(persons.household_id, (persons.ptype == 6) & (num_mand > 0))" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons_nmtf.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons_nmtf.csv new file mode 100644 index 000000000..11f8b111e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons_nmtf.csv @@ -0,0 +1,15 @@ +Description,Target,Expression +#,, annotate persons table after non_mandatory_tour_frequency model has run +num_non_mand,num_non_mand,tours[tours.tour_category=='non_mandatory'].groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8) +num_escort_tours,num_escort_tours,tours[tours.tour_type == 'escort'].groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8) +num_eatout_tours,num_eatout_tours,tours[tours.tour_type == 'eatout'].groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8) +num_shop_tours,num_shop_tours,tours[tours.tour_type == 'shopping'].groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8) +num_maint_tours,num_maint_tours,tours[tours.tour_type == 'othmaint'].groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8) +num_discr_tours,num_discr_tours,tours[tours.tour_type == 'othdiscr'].groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8) +num_social_tours,num_social_tours,tours[tours.tour_type == 'social'].groupby('person_id').size().reindex(persons.index).fillna(0).astype(np.int8) +num_non_escort_tours,num_non_escort_tours,num_non_mand-num_escort_tours +total shopping and maintenance tours,num_shop_maint_tours,num_shop_tours + num_maint_tours +"total shopping, maintenance and escort tours",num_shop_maint_escort_tours,num_shop_tours + num_maint_tours + num_escort_tours +number of additional shopping and maintenance tours,num_add_shop_maint_tours,"np.where (num_shop_maint_tours>0, 1, 0) * (num_shop_maint_tours - 1)" +total social and discretionary tours,num_soc_discr_tours,num_social_tours + num_discr_tours +number of additional social and discretionary,num_add_soc_discr_tours,"np.where (num_soc_discr_tours>0, 1, 0) * (num_soc_discr_tours - 1)" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons_school.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons_school.csv new file mode 100644 index 000000000..553b124c3 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons_school.csv @@ -0,0 +1,7 @@ +Description,Target,Expression +#,, annotate persons table after school_location model has run +,distance_to_school,"np.where(persons.school_zone_id>=0,skim_dict.lookup(persons.home_zone_id, persons.school_zone_id, 'DIST'),np.nan)" +#,, this uses the free flow travel time in both directions. MTC TM1 was MD and MD +temp auto_time_to_school,_auto_time_to_school,"skim_dict.lookup(persons.home_zone_id, persons.school_zone_id, ('SOV_TIME', 'MD'))" +temp auto_time_return,_auto_time_return,"skim_dict.lookup(persons.school_zone_id, persons.home_zone_id, ('SOV_TIME', 'MD'))" +free flow roundtrip_auto_time_to_school,roundtrip_auto_time_to_school,"np.where(persons.school_zone_id>=0,_auto_time_to_school + _auto_time_return,0)" diff --git a/activitysim/examples/prototype_mwcog/configs/annotate_persons_workplace.csv b/activitysim/examples/prototype_mwcog/configs/annotate_persons_workplace.csv new file mode 100644 index 000000000..707b30ab3 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/annotate_persons_workplace.csv @@ -0,0 +1,32 @@ +Description,Target,Expression +#,, annotate persons table after workplace_location model has run +,distance_to_work,"np.where(persons.workplace_zone_id>=0,skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, 'DIST'),np.nan)" +workplace_in_cbd,workplace_in_cbd,"reindex(land_use.AREATYPE, persons.workplace_zone_id) < setting('cbd_threshold')" +work_zone_area_type,work_zone_area_type,"reindex(land_use.AREATYPE, persons.workplace_zone_id)" +#,, auto time to work - free flow travel time in both directions. MTC TM1 was MD and MD +#,,roundtrip_auto_time_to_work +,_auto_time_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('SOV_TIME', 'MD'))" +,_auto_time_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('SOV_TIME', 'MD'))" +,roundtrip_auto_time_to_work,"np.where(persons.workplace_zone_id>=0,_auto_time_home_to_work + _auto_time_work_to_home,0)" +#,,_roundtrip_walk_time_to_work +,_MAX_TIME_TO_WORK,999 +,_WALK_SPEED_MPH,3 +,_walk_time_home_to_work,"60 * skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, 'DISTWALK')/_WALK_SPEED_MPH" +,_walk_time_work_to_home,"60 * skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, 'DISTWALK')/_WALK_SPEED_MPH" +,_work_walk_available,(_walk_time_home_to_work > 0) & (_walk_time_work_to_home > 0) +,_roundtrip_walk_time_to_work,"np.where(_work_walk_available, _walk_time_home_to_work + _walk_time_work_to_home, _MAX_TIME_TO_WORK)" +#,,_roundtrip_transit_time_to_work +,_transit_ivt_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WK_TRN_WK_TOTIVT', 'MD'))" +,_transit_ivt_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WK_TRN_WK_TOTIVT', 'MD'))" +,_work_transit_available,(_transit_ivt_home_to_work > 0) & (_transit_ivt_work_to_home > 0) +,_transit_iwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WK_TRN_WK_IWAIT', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WK_TRN_WK_IWAIT', 'MD'))" +,_transit_xwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WK_TRN_WK_XWAIT', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WK_TRN_WK_XWAIT', 'MD'))" +,_transit_waux,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WK_TRN_WK_WAUX', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WK_TRN_WK_WAUX', 'MD'))" +,_transit_wacc,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WK_TRN_WK_WACC_EGR', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WK_TRN_WK_WACC_EGR', 'MD'))" +,_transit_wegr,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WK_TRN_WK_WACC_EGR', 'MD')) + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WK_TRN_WK_WACC_EGR', 'MD'))" +,_roundtrip_transit_time_to_work,_transit_ivt_home_to_work + _transit_ivt_work_to_home + _transit_iwait + _transit_xwait + _transit_waux + _transit_wacc + _transit_wegr +#,,work_auto_savings_ratio +,_min_work_walk_transit,"np.where(_work_transit_available, np.minimum(_roundtrip_transit_time_to_work, _roundtrip_walk_time_to_work), _roundtrip_walk_time_to_work)" +,work_auto_savings,"np.where(persons.is_worker, _min_work_walk_transit - roundtrip_auto_time_to_work, 0)" +#,,auto savings over walk or transit capped at 120 and normalized to unity +,work_auto_savings_ratio,"(work_auto_savings / 120.0).clip(-1.0, 1.0)" diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination.csv b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination.csv new file mode 100644 index 000000000..76162b48b --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination.csv @@ -0,0 +1,18 @@ +Label,Description,Expression,atwork +local_dist,local_dist,_DIST@skims['DIST'],1 +util_dist,util_dist,@_DIST,coef_dist_atwork +util_dist_squared,"Distance squared, capped at 30 miles",@(_DIST)**2,coef_dist_squared_atwork +util_dist_cubed,"Distance cubed, capped at 30 miles",@(_DIST)**3,coef_dist_cubed_atwork +util_dist_logged,util_dist_logged,@(_DIST).apply(np.log1p),coef_dist_logged_atwork +util_dist_female,"Distance,female",@(df['female']==True) * _DIST,coef_dist_female_atwork +util_dist_zero_auto,"Distance,zero auto HH",@(df['auto_ownership']==0) * _DIST,coef_dist_zero_auto_atwork +util_dist_calibration_0_1,util_dist_calibration_0_1,@((_DIST>0) & (_DIST<=1)),coef_calib_0_1_dist_atwork +util_dist_calibration_1_3,util_dist_calibration_1_3,@((_DIST>1) & (_DIST<=3)),coef_calib_1_3_dist_atwork +util_dist_calibration_3_6,util_dist_calibration_3_6,@((_DIST>3) & (_DIST<=6)),coef_calib_3_6_dist_atwork +util_dist_calibration_6_10,util_dist_calibration_6_10,@((_DIST>6) & (_DIST<=10)),coef_calib_6_10_dist_atwork +util_dist_calibration_10_15,util_dist_calibration_10_15,@((_DIST>10) & (_DIST<=15)),coef_calib_10_15_dist_atwork +util_dist_calibration_15_pl,util_dist_calibration_15_pl,@(_DIST>15),coef_calib_15_pl_dist_atwork +util_size_variable_atwork,Size variable atwork,@df['size_term'].apply(np.log1p),coef_size_variable_atwork +util_no_attractions_atwork_size_variable_is_0,"No attractions, atwork size variable is 0",size_term==0,coef_no_attractions_atwork_size_variable_is_0 +util_mode_choice_logsum,Mode choice logsum,mode_choice_logsum,coef_mode_choice_logsum_atwork +util_sample_of_alternatives_correction_factor,Sample of alternatives correction factor,"@np.minimum(np.log(df.pick_count/df.prob), 60)",coef_sample_of_alternatives_correction_factor diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination.yaml b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination.yaml new file mode 100644 index 000000000..3448f47de --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination.yaml @@ -0,0 +1,28 @@ + +SPEC: atwork_subtour_destination.csv +SAMPLE_SPEC: atwork_subtour_destination_sample.csv +COEFFICIENTS: atwork_subtour_destination_coeffs.csv + + +SAMPLE_SIZE: 30 + +SIMULATE_CHOOSER_COLUMNS: + - person_id + - income_segment + - workplace_zone_id + - female + - auto_ownership + +LOGSUM_SETTINGS: tour_mode_choice.yaml + +# model-specific logsum-related settings +CHOOSER_ORIG_COL_NAME: workplace_zone_id +ALT_DEST_COL_NAME: alt_dest +IN_PERIOD: 21 +OUT_PERIOD: 19 + +# optional (comment out if not desired) +DEST_CHOICE_LOGSUM_COLUMN_NAME: destination_logsum + +# comment out DEST_CHOICE_LOGSUM_COLUMN_NAME if saved alt logsum table +DEST_CHOICE_SAMPLE_TABLE_NAME: tour_destination_sample diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination_coeffs.csv new file mode 100644 index 000000000..d0d5cb5f4 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination_coeffs.csv @@ -0,0 +1,17 @@ +coefficient_name,value,constrain +coef_dist_atwork,0.487260901,F +coef_dist_squared_atwork,-0.007463552,F +coef_dist_cubed_atwork,2.78E-05,F +coef_dist_logged_atwork,-5.322821417,F +coef_dist_female_atwork,-0.033246111,F +coef_dist_zero_auto_atwork,-0.135191524,F +coef_calib_0_1_dist_atwork,-0.755322501,T +coef_calib_1_3_dist_atwork,-0.283854352, +coef_calib_3_6_dist_atwork,0.964729369, +coef_calib_6_10_dist_atwork,1.476441427, +coef_calib_10_15_dist_atwork,1.189974447, +coef_calib_15_pl_dist_atwork,0.626309631, +coef_size_variable_atwork,1,T +coef_no_attractions_atwork_size_variable_is_0,-999,T +coef_mode_choice_logsum_atwork,0.424,F +coef_sample_of_alternatives_correction_factor,1,T diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination_sample.csv b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination_sample.csv new file mode 100644 index 000000000..4ef4969ec --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_destination_sample.csv @@ -0,0 +1,16 @@ +Label,Description,Expression,atwork +local_dist,local_dist,_DIST@skims['DIST'],1 +util_dist,util_dist,@_DIST,coef_dist_atwork +util_dist_squared,util_dist_squared,@(_DIST)**2,coef_dist_squared_atwork +util_dist_cubed,util_dist_cubed,@(_DIST)**3,coef_dist_cubed_atwork +util_dist_logged,util_dist_logged,@(_DIST).apply(np.log1p),coef_dist_logged_atwork +util_dist_female,"Distance,female",@(df['female']==True) * _DIST,coef_dist_female_atwork +util_dist_zero_auto,"Distance,zero auto HH",@(df['auto_ownership']==0) * _DIST,coef_dist_zero_auto_atwork +util_dist_calibration_0_1,util_dist_calibration_0_1,@((_DIST>0) & (_DIST<=1)),coef_calib_0_1_dist_atwork +util_dist_calibration_1_3,util_dist_calibration_1_3,@((_DIST>1) & (_DIST<=3)),coef_calib_1_3_dist_atwork +util_dist_calibration_3_6,util_dist_calibration_3_6,@((_DIST>3) & (_DIST<=6)),coef_calib_3_6_dist_atwork +util_dist_calibration_6_10,util_dist_calibration_6_10,@((_DIST>6) & (_DIST<=10)),coef_calib_6_10_dist_atwork +util_dist_calibration_10_15,util_dist_calibration_10_15,@((_DIST>10) & (_DIST<=15)),coef_calib_10_15_dist_atwork +util_dist_calibration_15_pl,util_dist_calibration_15_pl,@(_DIST>15),coef_calib_15_pl_dist_atwork +util_size_variable_atwork,Size variable atwork,@df['size_term'].apply(np.log1p),coef_size_variable_atwork +util_no_attractions_atwork_size_variable_is_0,"No attractions, atwork size variable is 0",size_term==0,coef_no_attractions_atwork_size_variable_is_0 diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency.csv b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency.csv new file mode 100644 index 000000000..a4eec1a88 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency.csv @@ -0,0 +1,23 @@ +Label,Expression,no_subtours,eat,business1,maint,business2,eat_business +util_dummy_for_full_time_worker,pemploy==1,coefficient_dummy_for_full_time_worker_no_subtours,coefficient_dummy_for_full_time_worker_eat,coefficient_dummy_for_full_time_worker_business1,coefficient_dummy_for_full_time_worker_maint,coefficient_dummy_for_full_time_worker_business2,coefficient_dummy_for_full_time_worker_eat_business +util_dummy_for_non_full_time_worker,pemploy!=1,coefficient_dummy_for_non_full_time_worker_no_subtours,coefficient_dummy_for_non_full_time_worker_eat,coefficient_dummy_for_non_full_time_worker_business1,coefficient_dummy_for_non_full_time_worker_maint,coefficient_dummy_for_non_full_time_worker_business2,coefficient_dummy_for_non_full_time_worker_eat_business +util_dummy_for_non_workers,"ptype in [4, 5]",coefficient_dummy_for_non_workers_no_subtours,coefficient_dummy_for_non_workers_eat,coefficient_dummy_for_non_workers_business1,coefficient_dummy_for_non_workers_maint,coefficient_dummy_for_non_workers_business2,coefficient_dummy_for_non_workers_eat_business +util_medium_hh_income_dummy,income_segment == 2,coefficient_medium_hh_income_dummy_no_subtours,coefficient_medium_hh_income_dummy_eat,coefficient_medium_hh_income_dummy_business1,coefficient_medium_hh_income_dummy_maint,coefficient_medium_hh_income_dummy_business2,coefficient_medium_hh_income_dummy_eat_business +util_high_hh_income_dummy,(income_segment > 2) & (income_segment < 5),coefficient_high_hh_income_dummy_no_subtours,coefficient_high_hh_income_dummy_eat,coefficient_high_hh_income_dummy_business1,coefficient_high_hh_income_dummy_maint,coefficient_high_hh_income_dummy_business2,coefficient_high_hh_income_dummy_eat_business +util_zero_cars_owned_by_hh_dummy, auto_ownership == 0,coefficient_zero_cars_owned_by_hh_dummy_no_subtours,coefficient_zero_cars_owned_by_hh_dummy_eat,coefficient_zero_cars_owned_by_hh_dummy_business1,coefficient_zero_cars_owned_by_hh_dummy_maint,coefficient_zero_cars_owned_by_hh_dummy_business2,coefficient_zero_cars_owned_by_hh_dummy_eat_business +util_individual_discretionary_tours_made_by_full_time_worker,@(df.pemploy==1)*df.num_discr_tours,coefficient_individual_discretionary_tours_made_by_full_time_worker_no_subtours,coefficient_individual_discretionary_tours_made_by_full_time_worker_eat,coefficient_individual_discretionary_tours_made_by_full_time_worker_business1,coefficient_individual_discretionary_tours_made_by_full_time_worker_maint,coefficient_individual_discretionary_tours_made_by_full_time_worker_business2,coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business +util_individual_discretionary_tours_made_by_part_time_worker,@(df.pemploy==2)*df.num_discr_tours,coefficient_individual_discretionary_tours_made_by_part_time_worker_no_subtours,coefficient_individual_discretionary_tours_made_by_part_time_worker_eat,coefficient_individual_discretionary_tours_made_by_part_time_worker_business1,coefficient_individual_discretionary_tours_made_by_part_time_worker_maint,coefficient_individual_discretionary_tours_made_by_part_time_worker_business2,coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business +util_individual_eating_out_tours_made_by_person,num_eatout_tours,coefficient_individual_eating_out_tours_made_by_person_no_subtours,coefficient_individual_eating_out_tours_made_by_person_eat,coefficient_individual_eating_out_tours_made_by_person_business1,coefficient_individual_eating_out_tours_made_by_person_maint,coefficient_individual_eating_out_tours_made_by_person_business2,coefficient_individual_eating_out_tours_made_by_person_eat_business +util_main_shop_escort_tours_allocated_to_full_time_worker,@(df.pemploy==1)*df.num_maint_shop_escort,coefficient_main_shop_escort_tours_allocated_to_full_time_worker_no_subtours,coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat,coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business1,coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint,coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2,coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business +util_main_shop_escort_tours_allocated_to_part_time_worker,@(df.pemploy==2)*df.num_maint_shop_escort,coefficient_main_shop_escort_tours_allocated_to_part_time_worker_no_subtours,coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat,coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1,coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint,coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2,coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business +util_participation_in_joint_shop_main_eat_tours,num_joint_maint_shop_eat,coefficient_participation_in_joint_shop_main_eat_tours_no_subtours,coefficient_participation_in_joint_shop_main_eat_tours_eat,coefficient_participation_in_joint_shop_main_eat_tours_business1,coefficient_participation_in_joint_shop_main_eat_tours_maint,coefficient_participation_in_joint_shop_main_eat_tours_business2,coefficient_participation_in_joint_shop_main_eat_tours_eat_business +util_participation_in_joint_discretionary_tours,num_joint_discr,coefficient_participation_in_joint_discretionary_tours_no_subtours,coefficient_participation_in_joint_discretionary_tours_eat,coefficient_participation_in_joint_discretionary_tours_business1,coefficient_participation_in_joint_discretionary_tours_maint,coefficient_participation_in_joint_discretionary_tours_business2,coefficient_participation_in_joint_discretionary_tours_eat_business +util_log_of_the_work_tour_duration,@np.log((df.duration/2.25)+0.5),coefficient_log_of_the_work_tour_duration_no_subtours,coefficient_log_of_the_work_tour_duration_eat,coefficient_log_of_the_work_tour_duration_business1,coefficient_log_of_the_work_tour_duration_maint,coefficient_log_of_the_work_tour_duration_business2,coefficient_log_of_the_work_tour_duration_eat_business +util_dummy_for_drive_alone_mode_for_work_tour,work_tour_is_SOV,coefficient_dummy_for_drive_alone_mode_for_work_tour_no_subtours,coefficient_dummy_for_drive_alone_mode_for_work_tour_eat,coefficient_dummy_for_drive_alone_mode_for_work_tour_business1,coefficient_dummy_for_drive_alone_mode_for_work_tour_maint,coefficient_dummy_for_drive_alone_mode_for_work_tour_business2,coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business +util_two_work_tours_by_person,num_work_tours==2,coefficient_two_work_tours_by_person_no_subtours,coefficient_two_work_tours_by_person_eat,coefficient_two_work_tours_by_person_business1,coefficient_two_work_tours_by_person_maint,coefficient_two_work_tours_by_person_business2,coefficient_two_work_tours_by_person_eat_business +util_workplace_urban_area_dummy,work_zone_area_type<4,coefficient_workplace_urban_area_dummy_no_subtours,coefficient_workplace_urban_area_dummy_eat,coefficient_workplace_urban_area_dummy_business1,coefficient_workplace_urban_area_dummy_maint,coefficient_workplace_urban_area_dummy_business2,coefficient_workplace_urban_area_dummy_eat_business +util_workplace_suburban_area_dummy,(work_zone_area_type>3) & (work_zone_area_type<6),coefficient_workplace_suburban_area_dummy_no_subtours,coefficient_workplace_suburban_area_dummy_eat,coefficient_workplace_suburban_area_dummy_business1,coefficient_workplace_suburban_area_dummy_maint,coefficient_workplace_suburban_area_dummy_business2,coefficient_workplace_suburban_area_dummy_eat_business +util_auto_accessibility_to_retail_for_work_taz,auOpRetail,coefficient_auto_accessibility_to_retail_for_work_taz_no_subtours,coefficient_auto_accessibility_to_retail_for_work_taz_eat,coefficient_auto_accessibility_to_retail_for_work_taz_business1,coefficient_auto_accessibility_to_retail_for_work_taz_maint,coefficient_auto_accessibility_to_retail_for_work_taz_business2,coefficient_auto_accessibility_to_retail_for_work_taz_eat_business +util_walk_accessibility_to_retail_for_work_taz,nmRetail,coefficient_walk_accessibility_to_retail_for_work_taz_no_subtours,coefficient_walk_accessibility_to_retail_for_work_taz_eat,coefficient_walk_accessibility_to_retail_for_work_taz_business1,coefficient_walk_accessibility_to_retail_for_work_taz_maint,coefficient_walk_accessibility_to_retail_for_work_taz_business2,coefficient_walk_accessibility_to_retail_for_work_taz_eat_business +util_dummy_for_worker_or_student_with_non_mandatory_tour,(is_worker | is_student) * num_non_mand,coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_no_subtours,coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat,coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business1,coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint,coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business2,coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat_business +util_at_work_sub_tour_alternative_specific_constant,1,coefficient_at_work_sub_tour_alternative_specific_constant_no_subtours,coefficient_at_work_sub_tour_alternative_specific_constant_eat,coefficient_at_work_sub_tour_alternative_specific_constant_business1,coefficient_at_work_sub_tour_alternative_specific_constant_maint,coefficient_at_work_sub_tour_alternative_specific_constant_business2,coefficient_at_work_sub_tour_alternative_specific_constant_eat_business diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency.yaml b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency.yaml new file mode 100644 index 000000000..1b5d27101 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency.yaml @@ -0,0 +1,11 @@ + +SPEC: atwork_subtour_frequency.csv +COEFFICIENTS: atwork_subtour_frequency_coeffs.csv + +preprocessor: + SPEC: atwork_subtour_frequency_annotate_tours_preprocessor + DF: df + TABLES: + - land_use + - tours + - joint_tour_participants diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_alternatives.csv b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_alternatives.csv new file mode 100644 index 000000000..ba9941919 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_alternatives.csv @@ -0,0 +1,8 @@ +#,,,alt file for building tours even though simulation is simple_simulate not interaction_simulate +alt,eat,business,maint +no_subtours,0,0,0 +eat,1,0,0 +business1,0,1,0 +maint,0,0,1 +business2,0,2,0 +eat_business,1,1,0 diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_annotate_tours_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_annotate_tours_preprocessor.csv new file mode 100644 index 000000000..ec500df50 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_annotate_tours_preprocessor.csv @@ -0,0 +1,9 @@ +Description,Target,Expression +,num_maint_shop_escort,df.num_maint_tours+df.num_shop_tours+df.num_escort_tours +#,num_joint_maint_shop_eat,"reindex_i(tours[(tours.tour_category=='joint') & tours.tour_type.isin(['othmaint', 'shopping', 'eatout'])].groupby('person_id').size(), df.person_id)" +#,num_eatout_tours,"reindex_i(tours[~tours.is_joint & (tours.tour_type==EATOUT_TOUR)].groupby('person_id').size(), df.person_id)" +joint tour participants annotated with tour type,_PARTICIPANTS,"pd.merge(joint_tour_participants[['tour_id', 'person_id']], tours[['tour_type']], left_on='tour_id', right_index=True, how='left')" +,num_joint_discr,"reindex_i(_PARTICIPANTS[_PARTICIPANTS.tour_type=='othdiscr'].groupby('person_id').size(), df.person_id)" +,num_joint_maint_shop_eat,"reindex_i(_PARTICIPANTS[_PARTICIPANTS.tour_type.isin(['othmaint', 'shopping', 'eatout'])].groupby('person_id').size(), df.person_id)" +#,, +,work_tour_is_SOV,df.tour_mode.isin(['DRIVEALONE']) diff --git a/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_coeffs.csv new file mode 100644 index 000000000..c59a4e2ee --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/atwork_subtour_frequency_coeffs.csv @@ -0,0 +1,133 @@ +coefficient_name,value,constrain +coefficient_dummy_for_full_time_worker_business1,-7.375,F +coefficient_dummy_for_full_time_worker_business2,-14.28,F +coefficient_dummy_for_full_time_worker_eat,-7.28,F +coefficient_dummy_for_full_time_worker_eat_business,-14.79,F +coefficient_dummy_for_full_time_worker_maint,-8.093,F +coefficient_dummy_for_full_time_worker_no_subtours,-0.6,F +coefficient_dummy_for_non_full_time_worker_business1,-8.319,F +coefficient_dummy_for_non_full_time_worker_business2,-14.28,F +coefficient_dummy_for_non_full_time_worker_eat,-8.604,F +coefficient_dummy_for_non_full_time_worker_eat_business,-14.79,F +coefficient_dummy_for_non_full_time_worker_maint,-8.214,F +coefficient_dummy_for_non_full_time_worker_no_subtours,-0.6,F +coefficient_dummy_for_non_workers_business1,-5,T +coefficient_dummy_for_non_workers_business2,-5,T +coefficient_dummy_for_non_workers_eat,0,T +coefficient_dummy_for_non_workers_eat_business,-5,T +coefficient_dummy_for_non_workers_maint,-5,T +coefficient_dummy_for_non_workers_no_subtours,0,T +coefficient_medium_hh_income_dummy_business1,0.5555,F +coefficient_medium_hh_income_dummy_business2,1.111,F +coefficient_medium_hh_income_dummy_eat,0.61,F +coefficient_medium_hh_income_dummy_eat_business,1.1655,F +coefficient_medium_hh_income_dummy_maint,0.1527,F +coefficient_medium_hh_income_dummy_no_subtours,0,T +coefficient_high_hh_income_dummy_business1,1.066,F +coefficient_high_hh_income_dummy_business2,2.132,F +coefficient_high_hh_income_dummy_eat,0.8693,F +coefficient_high_hh_income_dummy_eat_business,1.9353,F +coefficient_high_hh_income_dummy_maint,0.1651,F +coefficient_high_hh_income_dummy_no_subtours,0,T +coefficient_zero_cars_owned_by_hh_dummy_business1,-0.3391,F +coefficient_zero_cars_owned_by_hh_dummy_business2,0,T +coefficient_zero_cars_owned_by_hh_dummy_eat,0,T +coefficient_zero_cars_owned_by_hh_dummy_eat_business,-0.3391,F +coefficient_zero_cars_owned_by_hh_dummy_maint,0.1762,F +coefficient_zero_cars_owned_by_hh_dummy_no_subtours,0,T +coefficient_individual_discretionary_tours_made_by_full_time_worker_business1,0.7045,F +coefficient_individual_discretionary_tours_made_by_full_time_worker_business2,1.409,F +coefficient_individual_discretionary_tours_made_by_full_time_worker_eat,0.2334,F +coefficient_individual_discretionary_tours_made_by_full_time_worker_eat_business,0.9379,F +coefficient_individual_discretionary_tours_made_by_full_time_worker_maint,0.5061,F +coefficient_individual_discretionary_tours_made_by_full_time_worker_no_subtours,0,T +coefficient_individual_discretionary_tours_made_by_part_time_worker_business1,0.7045,F +coefficient_individual_discretionary_tours_made_by_part_time_worker_business2,1.409,F +coefficient_individual_discretionary_tours_made_by_part_time_worker_eat,0.6776,F +coefficient_individual_discretionary_tours_made_by_part_time_worker_eat_business,1.3821,F +coefficient_individual_discretionary_tours_made_by_part_time_worker_maint,0.5061,F +coefficient_individual_discretionary_tours_made_by_part_time_worker_no_subtours,0,T +coefficient_individual_eating_out_tours_made_by_person_business1,0.5434,F +coefficient_individual_eating_out_tours_made_by_person_business2,1.0868,F +coefficient_individual_eating_out_tours_made_by_person_eat,0.5491,F +coefficient_individual_eating_out_tours_made_by_person_eat_business,1.0925,F +coefficient_individual_eating_out_tours_made_by_person_maint,0.9166,F +coefficient_individual_eating_out_tours_made_by_person_no_subtours,0,T +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business1,-0.1903,F +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_business2,-0.3806,F +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat,0.052,F +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_eat_business,-0.2423,F +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_maint,0.1446,F +coefficient_main_shop_escort_tours_allocated_to_full_time_worker_no_subtours,0,T +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business1,-0.1903,F +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_business2,-0.3806,F +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat,-0.3099,F +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_eat_business,-0.5002,F +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_maint,-0.2723,F +coefficient_main_shop_escort_tours_allocated_to_part_time_worker_no_subtours,0,T +coefficient_participation_in_joint_shop_main_eat_tours_business1,0.083,F +coefficient_participation_in_joint_shop_main_eat_tours_business2,0.166,F +coefficient_participation_in_joint_shop_main_eat_tours_eat,0.2458,F +coefficient_participation_in_joint_shop_main_eat_tours_eat_business,0.3288,F +coefficient_participation_in_joint_shop_main_eat_tours_maint,0.0803,F +coefficient_participation_in_joint_shop_main_eat_tours_no_subtours,0,T +coefficient_participation_in_joint_discretionary_tours_business1,-0.2637,F +coefficient_participation_in_joint_discretionary_tours_business2,-0.5274,F +coefficient_participation_in_joint_discretionary_tours_eat,0.3588,F +coefficient_participation_in_joint_discretionary_tours_eat_business,0.0951,F +coefficient_participation_in_joint_discretionary_tours_maint,0.5822,F +coefficient_participation_in_joint_discretionary_tours_no_subtours,0,T +coefficient_log_of_the_work_tour_duration_business1,1.142,F +coefficient_log_of_the_work_tour_duration_business2,2.284,F +coefficient_log_of_the_work_tour_duration_eat,1.55,F +coefficient_log_of_the_work_tour_duration_eat_business,2.692,F +coefficient_log_of_the_work_tour_duration_maint,1.659,F +coefficient_log_of_the_work_tour_duration_no_subtours,0,T +coefficient_dummy_for_drive_alone_mode_for_work_tour_business1,0.9901,F +coefficient_dummy_for_drive_alone_mode_for_work_tour_business2,1.9802,F +coefficient_dummy_for_drive_alone_mode_for_work_tour_eat,0.4804,F +coefficient_dummy_for_drive_alone_mode_for_work_tour_eat_business,1.4705,F +coefficient_dummy_for_drive_alone_mode_for_work_tour_maint,1.153,F +coefficient_dummy_for_drive_alone_mode_for_work_tour_no_subtours,0,T +coefficient_two_work_tours_by_person_business1,0.3753,F +coefficient_two_work_tours_by_person_business2,0.7506,F +coefficient_two_work_tours_by_person_eat,-0.9862,F +coefficient_two_work_tours_by_person_eat_business,-0.6109,F +coefficient_two_work_tours_by_person_maint,-0.2312,F +coefficient_two_work_tours_by_person_no_subtours,0,T +coefficient_workplace_urban_area_dummy_business1,-0.2235,F +coefficient_workplace_urban_area_dummy_business2,-0.447,F +coefficient_workplace_urban_area_dummy_eat,-0.4182,F +coefficient_workplace_urban_area_dummy_eat_business,-0.6417,F +coefficient_workplace_urban_area_dummy_maint,-0.1479,F +coefficient_workplace_urban_area_dummy_no_subtours,0,T +coefficient_workplace_suburban_area_dummy_business1,-0.1102,F +coefficient_workplace_suburban_area_dummy_business2,-0.2204,F +coefficient_workplace_suburban_area_dummy_eat,-0.2916,F +coefficient_workplace_suburban_area_dummy_eat_business,-0.4018,F +coefficient_workplace_suburban_area_dummy_maint,0,T +coefficient_workplace_suburban_area_dummy_no_subtours,0,T +coefficient_auto_accessibility_to_retail_for_work_taz_business1,0.0534,F +coefficient_auto_accessibility_to_retail_for_work_taz_business2,0.1067,F +coefficient_auto_accessibility_to_retail_for_work_taz_eat,0.015,F +coefficient_auto_accessibility_to_retail_for_work_taz_eat_business,0.0683,F +coefficient_auto_accessibility_to_retail_for_work_taz_maint,0.0265,F +coefficient_auto_accessibility_to_retail_for_work_taz_no_subtours,0,T +coefficient_walk_accessibility_to_retail_for_work_taz_business1,0,T +coefficient_walk_accessibility_to_retail_for_work_taz_business2,0,T +coefficient_walk_accessibility_to_retail_for_work_taz_eat,0.06,F +coefficient_walk_accessibility_to_retail_for_work_taz_eat_business,0.06,F +coefficient_walk_accessibility_to_retail_for_work_taz_maint,0.04,F +coefficient_walk_accessibility_to_retail_for_work_taz_no_subtours,0,T +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business1,0,T +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_business2,0,T +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat,0,T +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_eat_business,0,T +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_maint,-0.3573,F +coefficient_dummy_for_worker_or_student_with_non_mandatory_tour_no_subtours,0,T +coefficient_at_work_sub_tour_alternative_specific_constant_business1,-0.5372,F +coefficient_at_work_sub_tour_alternative_specific_constant_business2,-2.1337,F +coefficient_at_work_sub_tour_alternative_specific_constant_eat,0.8576,F +coefficient_at_work_sub_tour_alternative_specific_constant_eat_business,-0.9721,F +coefficient_at_work_sub_tour_alternative_specific_constant_maint,-0.6198,F +coefficient_at_work_sub_tour_alternative_specific_constant_no_subtours,0,T \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/auto_ownership.csv b/activitysim/examples/prototype_mwcog/configs/auto_ownership.csv new file mode 100644 index 000000000..e9ad2c58e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/auto_ownership.csv @@ -0,0 +1,25 @@ +Label,Description,Expression,cars0,cars1,cars2,cars3,cars4 +util_drivers_2,2 Adults (age 16+),num_drivers==2,,coef_cars1_drivers_2,coef_cars2_drivers_2,coef_cars3_drivers_2,coef_cars4_drivers_2 +util_drivers_3,3 Adults (age 16+),num_drivers==3,,coef_cars1_drivers_3,coef_cars2_drivers_3,coef_cars3_drivers_3,coef_cars4_drivers_3 +util_drivers_4_up,4+ Adults (age 16+),num_drivers>3,,coef_cars1_drivers_4_up,coef_cars2_drivers_4_up,coef_cars3_drivers_4_up,coef_cars4_drivers_4_up +util_persons_16_17,Persons age 16-17,num_children_16_to_17,,coef_cars1_persons_16_17,coef_cars2_persons_16_17,coef_cars34_persons_16_17,coef_cars34_persons_16_17 +util_persons_18_24,Persons age 18-24,num_college_age,,coef_cars1_persons_18_24,coef_cars2_persons_18_24,coef_cars34_persons_18_24,coef_cars34_persons_18_24 +util_persons_25_34,Persons age 35-34,num_young_adults,,coef_cars1_persons_25_34,coef_cars2_persons_25_34,coef_cars34_persons_25_34,coef_cars34_persons_25_34 +util_presence_children_0_4,Presence of children age 0-4,num_young_children>0,,coef_cars1_presence_children_0_4,coef_cars234_presence_children_0_4,coef_cars234_presence_children_0_4,coef_cars234_presence_children_0_4 +util_presence_children_5_17,Presence of children age 5-17,(num_children_5_to_15+num_children_16_to_17)>0,,coef_cars1_presence_children_5_17,coef_cars2_presence_children_5_17,coef_cars34_presence_children_5_17,coef_cars34_presence_children_5_17 +util_num_workers_clip_3,"Number of workers, capped at 3",@df.num_workers.clip(upper=3),,coef_cars1_num_workers_clip_3,coef_cars2_num_workers_clip_3,coef_cars3_num_workers_clip_3,coef_cars4_num_workers_clip_3 +util_hh_income_0_30k,"Piecewise Linear household income, $0-30k","@df.income_in_thousands.clip(0, 30)",,coef_cars1_hh_income_0_30k,coef_cars2_hh_income_0_30k,coef_cars3_hh_income_0_30k,coef_cars4_hh_income_0_30k +util_hh_income_30_75k,"Piecewise Linear household income, $30-75k","@(df.income_in_thousands-30).clip(0, 45)",,coef_cars1_hh_income_30_up,coef_cars2_hh_income_30_up,coef_cars3_hh_income_30_up,coef_cars4_hh_income_30_up +util_hh_income_75k_up,"Piecewise Linear household income, $75k+, capped at $125k","@(df.income_in_thousands-75).clip(0, 50)",,coef_cars1_hh_income_30_up,coef_cars2_hh_income_30_up,coef_cars3_hh_income_30_up,coef_cars4_hh_income_30_up +util_density_0_10_no_workers,"Density index up to 10, if 0 workers","@(df.num_workers==0)*df.density_index.clip(0, 10)",,coef_cars1_density_0_10_no_workers,coef_cars2_density_0_10_no_workers,coef_cars34_density_0_10_no_workers,coef_cars34_density_0_10_no_workers +util_density_10_up_no_workers,"Density index in excess of 10, if 0 workers",@(df.num_workers==0)*(df.density_index-10).clip(0),,coef_cars1_density_10_up_no_workers,coef_cars2_density_10_up_no_workers,coef_cars34_density_10_up_no_workers,coef_cars34_density_10_up_no_workers +util_density_0_10_workers,"Density index up to 10, if 1+ workers","@(df.num_workers>0)*df.density_index.clip(0, 10)",,coef_cars1_density_0_10_no_workers,coef_cars2_density_0_10_no_workers,coef_cars34_density_0_10_no_workers,coef_cars34_density_0_10_no_workers +util_density_10_up_workers,"Density index in excess of 10, if 1+ workers",@(df.num_workers>0)*(df.density_index-10).clip(0),,coef_cars1_density_10_up_workers,coef_cars2_density_10_up_no_workers,coef_cars34_density_10_up_no_workers,coef_cars34_density_10_up_no_workers +util_asc,Constants,1,,coef_cars1_asc,coef_cars2_asc,coef_cars3_asc,coef_cars4_asc +util_retail_auto_no_workers,"Retail accessibility (0.66*PK + 0.34*OP) by auto, if 0 workers",(num_workers==0)*(0.66*auPkRetail+0.34*auOpRetail),,coef_retail_auto_no_workers,coef_retail_auto_no_workers,coef_retail_auto_no_workers,coef_retail_auto_no_workers +util_retail_auto_workers,"Retail accessibility (0.66*PK + 0.34*OP) by auto, if 1+ workers",(num_workers>0)*(0.66*auPkRetail+0.34*auOpRetail),,coef_retail_auto_workers,coef_retail_auto_workers,coef_retail_auto_workers,coef_retail_auto_workers +util_retail_transit_no_workers,"Retail accessibility (0.66*PK + 0.34*OP) by transit, if 0 workers",(num_workers==0)*(0.66*trPkRetail+0.34*trOpRetail),,coef_retail_transit_no_workers,coef_retail_transit_no_workers,coef_retail_transit_no_workers,coef_retail_transit_no_workers +util_retail_transit_workers,"Retail accessibility (0.66*PK + 0.34*OP) by transit, if 1+ workers",(num_workers>0)*(0.66*trPkRetail+0.34*trOpRetail),,coef_retail_transit_workers,coef_retail_transit_workers,coef_retail_transit_workers,coef_retail_transit_workers +util_retail_non_motor_no_workers,"Retail accessibility by non-motorized, if 0 workers",(num_workers==0)*nmRetail,,coef_retail_non_motor,coef_retail_non_motor,coef_retail_non_motor,coef_retail_non_motor +util_retail_non_motor_workers,"Retail accessibility by non-motorized, if 1+ workers",(num_workers>0)*nmRetail,,coef_retail_non_motor,coef_retail_non_motor,coef_retail_non_motor,coef_retail_non_motor +util_auto_time_saving_per_worker,Auto time savings per worker to work,"@np.where(df.num_workers > 0, df.hh_work_auto_savings_ratio / df.num_workers, 0)",,coef_cars1_auto_time_saving_per_worker,coef_cars2_auto_time_saving_per_worker,coef_cars3_auto_time_saving_per_worker,coef_cars4_auto_time_saving_per_worker diff --git a/activitysim/examples/prototype_mwcog/configs/auto_ownership.yaml b/activitysim/examples/prototype_mwcog/configs/auto_ownership.yaml new file mode 100644 index 000000000..25f3249e6 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/auto_ownership.yaml @@ -0,0 +1,6 @@ + +SPEC: auto_ownership.csv +COEFFICIENTS: auto_ownership_coeffs.csv + +#LOGIT_TYPE: NL +LOGIT_TYPE: MNL diff --git a/activitysim/examples/prototype_mwcog/configs/auto_ownership_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/auto_ownership_coeffs.csv new file mode 100644 index 000000000..a173d345c --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/auto_ownership_coeffs.csv @@ -0,0 +1,68 @@ +coefficient_name,value,constrain +coef_cars1_drivers_2,0,T +coef_cars1_drivers_3,0,T +coef_cars1_persons_16_17,0,T +coef_cars234_asc_marin,0,T +coef_cars1_persons_25_34,0,T +coef_cars1_num_workers_clip_3,0,T +coef_cars1_hh_income_30_up,0,T +coef_cars1_density_0_10_no_workers,0,T +coef_cars1_density_10_up_workers,-0.000691606,F +coef_retail_non_motor,-0.03,T +coef_cars4_asc,-2.261638434,F +coef_cars3_asc,-0.673762698,F +coef_cars34_persons_16_17,-1.013171309,F +coef_cars2_asc,0.565146715,F +coef_cars34_persons_18_24,-0.226330826,F +coef_cars2_persons_18_24,-0.277986366,F +coef_cars2_persons_16_17,-0.849990546,F +coef_cars34_persons_25_34,-0.507269783,F +coef_cars1_asc_county,-0.566,F +coef_retail_transit_workers,-0.265994069,F +coef_cars2_persons_25_34,-0.284585751,F +coef_cars2_asc_county,-0.4429,F +coef_cars1_persons_18_24,0.312283469,F +coef_cars34_density_0_10_no_workers,-1.061191084,F +coef_retail_transit_no_workers,-0.461089186,F +coef_cars1_asc_marin,-0.2434,F +coef_cars34_asc_county,-0.2372,F +coef_cars2_density_0_10_no_workers,-0.433456601,F +coef_cars34_density_10_up_no_workers,-0.1766,T +coef_cars2_density_10_up_no_workers,0.223494727,F +coef_cars2_density_10_up_workers,-0.1106,F +coef_cars1_density_10_up_no_workers,-0.627879618,F +coef_cars2_hh_income_30_up,0.013802348,F +coef_cars3_hh_income_30_up,0.017568266,F +coef_cars4_hh_income_30_up,0.020241067,F +coef_cars1_presence_children_5_17,0.220192925,F +coef_cars1_hh_income_0_30k,0.087548177,F +coef_cars2_hh_income_0_30k,0.113631992,F +coef_cars3_hh_income_0_30k,0.109196449,F +coef_cars4_hh_income_0_30k,0.123715611,F +coef_retail_auto_no_workers,-0.27201648,F +coef_cars34_asc_san_francisco,0.1458,F +coef_retail_auto_workers,-0.344050452,F +coef_cars2_presence_children_5_17,0.326754993,F +coef_cars2_num_workers_clip_3,0.713126665,F +coef_cars1_presence_children_0_4,-0.134103303,F +coef_cars1_asc_san_francisco,0.4259,F +coef_cars2_asc_san_francisco,0.4683,F +coef_cars1_auto_time_saving_per_worker,1.313894714,F +coef_cars34_presence_children_5_17,0.092889725,F +coef_cars3_auto_time_saving_per_worker,0.983048236,F +coef_cars2_auto_time_saving_per_worker,1.090225147,F +coef_cars3_num_workers_clip_3,1.000861535,F +coef_cars234_presence_children_0_4,0.049938988,F +coef_cars4_auto_time_saving_per_worker,0.899014851,F +coef_cars4_num_workers_clip_3,1.079450658,F +coef_cars1_asc,3.525287666,F +coef_cars1_drivers_4_up,-1.451519292,F +coef_cars4_drivers_2,2.405668371,F +coef_cars2_drivers_2,2.817372734,F +coef_cars3_drivers_2,2.680131012,F +coef_cars2_drivers_3,2.581972363,F +coef_cars4_drivers_3,3.964857311,F +coef_cars3_drivers_3,4.277120564,F +coef_cars2_drivers_4_up,1.518205653,F +coef_cars3_drivers_4_up,3.49162912,F +coef_cars4_drivers_4_up,4.509213244,F diff --git a/activitysim/examples/prototype_mwcog/configs/cdap.yaml b/activitysim/examples/prototype_mwcog/configs/cdap.yaml new file mode 100644 index 000000000..9ce3a1d2b --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/cdap.yaml @@ -0,0 +1,34 @@ +COEFFICIENTS: _dummy_coefficients.csv +INDIV_AND_HHSIZE1_SPEC: cdap_indiv_and_hhsize1.csv + +FIXED_RELATIVE_PROPORTIONS_SPEC: cdap_fixed_relative_proportions.csv + +CONSTANTS: + FULL: 1 + PART: 2 + UNIVERSITY: 3 + NONWORK: 4 + RETIRED: 5 + DRIVING: 6 + SCHOOL: 7 + PRESCHOOL: 8 + +PERSON_TYPE_MAP: + WORKER: + - 1 + - 2 + CHILD: + - 6 + - 7 + - 8 + +annotate_persons: + SPEC: annotate_persons_cdap + DF: persons + + +annotate_households: + SPEC: annotate_households_cdap + DF: households + TABLES: + - persons diff --git a/activitysim/examples/prototype_mwcog/configs/cdap_fixed_relative_proportions.csv b/activitysim/examples/prototype_mwcog/configs/cdap_fixed_relative_proportions.csv new file mode 100644 index 000000000..788f398b6 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/cdap_fixed_relative_proportions.csv @@ -0,0 +1,9 @@ +Description,Expression,M,N,H +Full-time worker,ptype == 1,0.79647,0.09368,0.10985 +Part-time worker,ptype == 2,0.61678,0.25757,0.12565 +University student,ptype == 3,0.69229,0.15641,0.1513 +Non-working adult,ptype == 4,0,0.67169,0.32831 +Retired,ptype == 5,0,0.54295,0.45705 +Driving-age child who is in school,ptype == 6,0.77609,0.06004,0.16387 +Pre-driving-age child who is in school,ptype == 7,0.68514,0.09144,0.22342 +Child who is too young for school,ptype == 8,0.14056,0.06512,0.79432 diff --git a/activitysim/examples/prototype_mwcog/configs/cdap_indiv_and_hhsize1.csv b/activitysim/examples/prototype_mwcog/configs/cdap_indiv_and_hhsize1.csv new file mode 100644 index 000000000..3d4ad55bc --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/cdap_indiv_and_hhsize1.csv @@ -0,0 +1,70 @@ +Description,Expression,M,N,H +Full-time worker alternative-specific constants,ptype == 1,1.378734579,0.622662391, +Part-time worker alternative-specific constants,ptype == 2,-0.718823738,0.636032467, +University student alternative-specific constants,ptype == 3,2.353595176,0.609709846, +Non-working adult alternative-specific constants,ptype == 4,-999,0.594645386, +Retired alternative-specific constants,ptype == 5,-999,0.408202071, +Driving-age child who is in school alternative-specific constants,ptype == 6,2.330918685,-0.599119112, +Pre-driving-age child who is in school alternative-specific constants,ptype == 7,3.295863529,0.57142434, +Pre-driving-age child who is in school interaction with age 6 to 9,(ptype == 7) & (age >= 6) & (age <= 9),-0.2943,, +Pre-driving-age child who is in school interaction with age 13 to 15,(ptype == 7) & (age >= 13) & (age <= 15),-0.7141,-0.672, +Pre-driving-age child who is too young for school alternative-specific constants,ptype == 8,1.052531189,-0.837567776, +# corrected tm1 age bug,,,, +Pre-driving-age child who is too young for school interaction with age 0 to 1,(ptype == 8) & (age >= 0) & (age <= 1),-0.4515,, +Pre-driving-age child who is too young for school interaction with age 4 to 5,(ptype == 8) & (age >= 4) & (age <= 5),0.6107,, +#,,,, +Full-time worker interaction with age less than 40,(ptype == 1) & (age < 40),0.2091,, +Retired interaction with age more than 80,(ptype == 5) & (age > 80),,,0.7666 +Full-time worker interaction with female gender,(ptype == 1) & (SEX == 2),-0.1259,, +Non-working adult interaction with female gender,(ptype == 4) & (SEX == 2),-0.743,, +Retired interaction with female,(ptype == 5) & (SEX == 2),0.4769,, +Non-working adult interaction with more cars than workers,(ptype == 4) & (auto_ownership > num_workers),0.6515,0.8168, +Retired interaction with more cars than workers,(ptype == 5) & (auto_ownership > num_workers),2.992,1.056, +Pre-driving-age child who is too young for school interaction with more cars than workers,(ptype == 8) & (auto_ownership > num_workers),,0.2991, +Full-time worker interaction with fewer cars than workers,(ptype == 1) & (auto_ownership < num_workers),,,0.5039 +Non-working adult interaction with fewer cars than workers,(ptype == 4) & (auto_ownership < num_workers),,,0.8965 +Retired interaction with fewer cars than workers,(ptype == 5) & (auto_ownership < num_workers),,,0.5496 +Driving-age child who is in school interaction with fewer cars than workers,(ptype == 6) & (auto_ownership < num_workers),,,0.6475 +Pre-driving-age child who is in school interaction with fewer cars than workers,(ptype == 7) & (auto_ownership < num_workers),,,0.5862 +Pre-driving-age child who is too young for school interaction with fewer cars than workers,(ptype == 8) & (auto_ownership < num_workers),,,0.5061 +Full-time worker interaction with income less than $20k,(ptype == 1) & (income_in_thousands < 20),,,0.5313 +Retired interaction with income less than $20k,(ptype == 5) & (income_in_thousands < 20),,,0.533 +Part-time worker interaction with income less than $20k,(ptype == 2) & (income_in_thousands < 20),,,0.3232 +Part-time worker interaction with income between $50k and $100k,(ptype == 2) & (income_in_thousands >= 50) & (income_in_thousands <= 100),,,-0.4032 +Part-time worker interaction with income more than $100k,(ptype == 2) & (income_in_thousands >= 100),,0.4207,-0.3534 +Non-working adult interaction with income between $50k and $100k,(ptype == 4) & (income_in_thousands >= 50) & (income_in_thousands <= 100),,,-0.5602 +Non-working adult interaction with income more than $100k,(ptype == 4) & (income_in_thousands >= 100),,,-0.7188 +Driving-age child who is in school interaction with less than $20k,(ptype == 6) & (income_in_thousands < 20),,,1.307 +Driving-age child who is in school interaction income between $50k and $100k,(ptype == 6) & (income_in_thousands >= 50) & (income_in_thousands <= 100),,,-0.5031 +Driving-age child who is in school interaction with income more than $100k,(ptype == 6) & (income_in_thousands >= 100),,,-2.046 +Pre-driving-age child who is too young for school interaction with income between $50k and $100k,(ptype == 8) & (income_in_thousands >= 50) & (income_in_thousands <= 100),,,-0.5708 +Pre-driving-age child who is too young for school interaction with income more than $100k,(ptype == 8) & (income_in_thousands >= 100),,,-0.6186 +Full-time worker intraction with peak accessibility to all employment,(ptype == 1) * auPkTotal,0.1212,, +Part-time worker interaction with peak accessibility to all employment,(ptype == 2) * auPkTotal,0.2004,, +Non-working adult interaction with peak accessibility to all employment,(ptype == 4) * auPkTotal,0.2314,, +Retired interaction with peak accessibility to all employment,(ptype == 5) * auPkTotal,0.2792,, +Non-working adult interaction with off-peak accessibility to retail,(ptype == 4) * auOpRetail,,0.07207, +Retired interaction with off-peak accessibility to retail,(ptype == 5) * auOpRetail,,0.07207, +University student interaction with off-peak accessibility to retail,(ptype == 3) * auOpRetail,,0.07207, +Driving-age child who is in school interaction with off-peak accessibility to retail,(ptype == 6) * auOpRetail,,0.08233, +Pre-driving-age child who is in school interaction with off-peak accessibility to retail,(ptype == 7) * auOpRetail,,0.08233, +Pre-driving-age child who is too young for school interaction with off-peak accessibility to retail,(ptype == 8) * auOpRetail,,0.08233, +# commented out because not used in mtctm1,,,, +# Full-time worker interaction with usual work location is home,(ptype == 1) * usualWorkLocationIsHome,-1.758,,0.1813 +# Part-time worker interaction with usual work location is home,(ptype == 2) * usualWorkLocationIsHome,-1.758,,0.1813 +# Full-time worker interaction with no usual work location,(ptype == 1) * noUsualWorkLocation,-0.5935,, +# Part-time worker interaction with no usual work location,(ptype == 2) * noUsualWorkLocation,-0.5935,, +# Driving-age child who is in school interaction with no usual school location,(ptype == 6) * noUsualWorkLocation,-0.866,, +# Pre-driving age child who is in school interaction with no usual school location,(ptype == 7) * noUsualWorkLocation,-0.866,, +#tm1 scenario test,,,, +#Simulate telecommuting by reducing mandatory patterns,(ptype == 1) * (income_in_thousands >= 50),-0.142930042,, +Telecommutes 1 day per week,telecommute_frequency=='1_day_week',,0.526,0.496 +Telecommutes 2-3 days per week,telecommute_frequency=='2_3_days_week',,1.387,1.584 +Telecommutes 4 days per week,telecommute_frequency=='4_days_week',,1.848,1.711 +#Turning Mandatory pattern off for FT and PT who work from home (sandag),,,, +"Full time worker, works from home",(ptype == 1) & (work_from_home),-999,, +"Part time worker, works from home",(ptype == 2) & (work_from_home),-999,, +Part-time worker cdap calibration constants,ptype == 2,-0.692991088,-0.557605681, +Non-working adult cdap calibration constants,ptype == 4,-999,-1.465030036, +Retired cdap calibration constants,ptype == 5,-999,-0.734499235, +Preschoolers cdap calibration constants,ptype == 8,-3.624275591,0.705578326, diff --git a/activitysim/examples/prototype_mwcog/configs/cdap_interaction_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/cdap_interaction_coefficients.csv new file mode 100644 index 000000000..f2d3b025c --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/cdap_interaction_coefficients.csv @@ -0,0 +1,140 @@ +activity,interaction_ptypes,coefficient +# 2-way interactions,, +H,11,1.626 +H,12,0.7407 +H,13,1.183 +H,14,0.9436 +H,15,1.298 +H,16,2.064 +H,17,1.501 +H,18,0.9912 +H,22,0.8911 +H,23,1.642 +H,24,0.7057 +H,25,0.463 +H,26,3.057 +H,27,0.7685 +H,28,1.07 +H,33,1.018 +H,34,1.781 +H,35,0.4835 +H,36,1.546 +H,37,1.552 +H,38,1.34 +H,44,1.352 +H,45,1.209 +H,46,0.5243 +H,47,0.8112 +H,48,1.167 +H,55,1.407 +H,56,0.8632 +H,57,0.8632 +H,58,0.8632 +H,66,2.198 +H,67,0.977 +H,68,1.467 +H,77,2.8 +H,78,1.434 +H,88,1.378 +M,11,0.141 +M,12,0.08845 +M,13,0.4273 +M,16,0.3842 +M,17,0.2623 +M,18,0.5118 +M,22,1.135 +M,23,0.173 +M,26,1.103 +M,27,0.3079 +M,28,0.5074 +M,33,0.8726 +M,36,-0.0021 +M,37,0.2975 +M,38,0.2254 +M,66,0.4794 +M,67,0.5151 +M,68,0.5516 +M,77,0.9731 +M,78,0.5961 +M,88,1.651 +N,11,1.123 +N,12,0.4947 +N,13,0.5523 +N,14,0.02186 +N,15,0.3115 +N,16,0.4095 +N,17,0.6008 +N,18,0.751 +N,22,1.032 +N,23,0.3355 +N,24,0.7477 +N,25,0.09831 +N,26,0.495 +N,27,0.8984 +N,28,1.452 +N,33,1.054 +N,34,0.193 +N,35,0.4065 +N,36,1.62 +N,37,0.5165 +N,38,0.8973 +N,44,0.6984 +N,45,0.1864 +N,46,0.6801 +N,47,0.5646 +N,48,1.164 +N,55,0.7291 +N,56,0.2919 +N,57,0.2919 +N,58,0.2919 +N,66,1.512 +N,67,1.422 +N,68,1.273 +N,77,1.553 +N,78,0.6184 +N,88,0.8771 +# 3-way interactions,, +H,124,0.9573 +H,122,0.9573 +H,144,0.9573 +H,126,0.2939 +H,146,0.2939 +H,222,0.9881 +H,224,0.9881 +H,244,0.9881 +H,226,0.4374 +H,246,0.4374 +H,446,0.4374 +H,266,0.4747 +H,466,0.4747 +M,111,0.3133 +M,112,0.3495 +M,114,0.3495 +M,666,-0.3906 +N,112,0.4637 +N,114,0.4637 +N,124,0.3491 +N,122,0.3491 +N,144,0.3491 +N,166,0.3553 +N,222,-1.386 +N,224,-1.386 +N,444,-1.386 +N,246,-0.8571 +N,226,-0.8571 +N,446,-0.8571 +# cdap_final_rules,, +M,5,-999 +M,4,-999 +# cdap_all_people,, +M,***,-0.0671 +N,***,-0.3653 +H,***,-1.1810 +M,****,-0.6104 +N,****,-1.3460 +H,****,-3.7330 +M,*****,-1.5280 +N,*****,-3.4530 +H,*****,-8.6210 + + diff --git a/activitysim/examples/prototype_mwcog/configs/constants.yaml b/activitysim/examples/prototype_mwcog/configs/constants.yaml new file mode 100644 index 000000000..41ccfdb73 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/constants.yaml @@ -0,0 +1,144 @@ +## ActivitySim +## See full license in LICENSE.txt. + + +#HHT_NONE: 0 +#HHT_FAMILY_MARRIED: 1 +#HHT_FAMILY_MALE: 2 +#HHT_FAMILY_FEMALE: 3 +#HHT_NONFAMILY_MALE_ALONE: 4 +#HHT_NONFAMILY_MALE_NOTALONE: 5 +#HHT_NONFAMILY_FEMALE_ALONE: 6 +#HHT_NONFAMILY_FEMALE_NOTALONE: 7 + +# convenience for expression files +HHT_NONFAMILY: [4, 5, 6, 7] +HHT_FAMILY: [1, 2, 3] + +PSTUDENT_GRADE_OR_HIGH: 1 +PSTUDENT_UNIVERSITY: 2 +PSTUDENT_NOT: 3 + +GRADE_SCHOOL_MAX_AGE: 14 +GRADE_SCHOOL_MIN_AGE: 5 + +SCHOOL_SEGMENT_NONE: 0 +SCHOOL_SEGMENT_GRADE: 1 +SCHOOL_SEGMENT_HIGH: 2 +SCHOOL_SEGMENT_UNIV: 3 + +INCOME_SEGMENT_LOW: 1 +INCOME_SEGMENT_MED: 2 +INCOME_SEGMENT_HIGH: 3 +INCOME_SEGMENT_VERYHIGH: 4 + +PEMPLOY_FULL: 1 +PEMPLOY_PART: 2 +PEMPLOY_NOT: 3 +PEMPLOY_CHILD: 4 + +PTYPE_FULL: &ptype_full 1 +PTYPE_PART: &ptype_part 2 +PTYPE_UNIVERSITY: &ptype_university 3 +PTYPE_NONWORK: &ptype_nonwork 4 +PTYPE_RETIRED: &ptype_retired 5 +PTYPE_DRIVING: &ptype_driving 6 +PTYPE_SCHOOL: &ptype_school 7 +PTYPE_PRESCHOOL: &ptype_preschool 8 + +# these appear as column headers in non_mandatory_tour_frequency.csv +PTYPE_NAME: + *ptype_full: PTYPE_FULL + *ptype_part: PTYPE_PART + *ptype_university: PTYPE_UNIVERSITY + *ptype_nonwork: PTYPE_NONWORK + *ptype_retired: PTYPE_RETIRED + *ptype_driving: PTYPE_DRIVING + *ptype_school: PTYPE_SCHOOL + *ptype_preschool: PTYPE_PRESCHOOL + + +CDAP_ACTIVITY_MANDATORY: M +CDAP_ACTIVITY_NONMANDATORY: N +CDAP_ACTIVITY_HOME: H + +# Mode Choice +#CONSTANTS: +#valueOfTime: 8.00 +# AAA:https://exchange.aaa.com/wp-content/uploads/2018/09/18-0090_2018-Your-Driving-Costs-Brochure_FNL-Lo-5-2.pdf +costPerMile: 19.26 +costShareSr2: 1.75 +costShareSr3: 2.50 +waitThresh: 10.00 +shortWalk: 0.333 +longWalk: 0.667 +walkSpeed: 3.00 +bikeThresh: 6.00 +bikeSpeed: 12.00 +# RIDEHAIL Settings +Taxi_baseFare: 2.20 +Taxi_costPerMile: 2.30 +Taxi_costPerMinute: 0.10 + +TNC_single_baseFare: 2.20 +TNC_single_costPerMile: 1.33 +TNC_single_costPerMinute: 0.24 +TNC_single_costMinimum: 7.20 +TNC_single_waitTime_mean: + 1: 3.0 + 2: 6.3 + 3: 8.4 + 4: 8.5 + 5: 10.3 +TNC_single_waitTime_sd: + 1: 0 + 2: 0 + 3: 0 + 4: 0 + 5: 0 +TNC_shared_baseFare: 2.20 +TNC_shared_costPerMile: 0.53 +TNC_shared_costPerMinute: 0.10 +TNC_shared_costMinimum: 3.00 +TNC_shared_IVTFactor: 1.5 +TNC_shared_waitTime_mean: + 1: 5.0 + 2: 8.0 + 3: 11.0 + 4: 15.0 + 5: 15.0 +TNC_shared_waitTime_sd: + 1: 0 + 2: 0 + 3: 0 + 4: 0 + 5: 0 +min_waitTime: 0 +max_waitTime: 50 +ivt_cost_multiplier: 0.6 +topology_bike_multiplier: 20 +topology_trn_multiplier: 2.20 +topology_walk_multiplier: 15 +ridehail_wait_time_multiplier: 1.5 +dacc_ratio_multiplier: 0 +origin_density_index_multiplier: -15 +origin_density_index_max: -15 +#FIXME: Check these +ivt_LB_multiplier: 1.0 +ivt_XB_multiplier: 0.9 +ivt_BR_multiplier: 0.9 +ivt_LR_multiplier: 0.9 +ivt_MR_multiplier: 0.8 +ivt_CR_multiplier: 0.7 +ivt_com_multiplier: 0.80 +ivt_hvy_multiplier: 0.80 +short_i_wait_multiplier: 2 +long_i_wait_multiplier: 1 +wacc_multiplier: 2 +wegr_multiplier: 2 +waux_multiplier: 2 +dtim_multiplier: 2 +xwait_multiplier: 2 +dacc_ratio: 0 +drvtrn_distpen_0_multiplier: 270 +drvtrn_distpen_max: 15 diff --git a/activitysim/examples/prototype_mwcog/configs/destination_choice_size_terms.csv b/activitysim/examples/prototype_mwcog/configs/destination_choice_size_terms.csv new file mode 100644 index 000000000..9706d64a3 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/destination_choice_size_terms.csv @@ -0,0 +1,26 @@ +model_selector,segment,HH,TOTEMP,INDEMP,RETEMP,OTHEMP,OFFEMP,K_8,G9_12,COLLEGE,Park_Acres,GC_Acres +workplace,work_low,0,0,1,2.3131,2.2566,1,0,0,0,0,0 +workplace,work_med,0,0,0.2828,0.5745,1.3069,1,0,0,0,0,0 +workplace,work_high,0,0,0.3528,0.2593,0.81,1,0,0,0,0,0 +workplace,work_veryhigh,0,0,0.1523,0.1345,0.81,1,0,0,0,0,0 +school,university,0,0,0,0,0,0,0,0,1,0,0 +school,gradeschool,0,0,0,0,0,0,1,0,0,0,0 +school,highschool,0,0,0,0,0,0,0,1,0,0,0 +non_mandatory,escort,0.3564,0,0.4562,0.2672,0.7392,0.0876,1,0.5518,0,0,0 +non_mandatory,shopping,0,0,0,1,0,0.6418,0,0,0,0,0 +non_mandatory,eatout,0.0286,0,0,1,0.0877,0,0,0,0,0,0 +non_mandatory,othmaint,0.1122,0,0.0183,1,0.5016,0.2158,0,0,0,0,0 +non_mandatory,social,1,0,0,0.3833,0,0,0,0,0,0,0 +non_mandatory,othdiscr,0.3429,0,0,0.268,1,0.268,0,0,0,0.3429,1.6185 +atwork,atwork,0,0,0,1,0,0.5399,0,0,0,0,0 +trip,work,0,1,1,1,1,1,0,0,0,0,0 +trip,escort,0.001,0,0,0.225,0,0,0.465,0.166,0,0,0 +trip,shopping,0.001,0,0,0.999,0,0,0,0,0,0,0 +trip,eatout,0,0,0,0.742,0,0,0,0,0,0,0 +trip,othmaint,0.001,0,0,0.481,0,0,0,0,0,0,0 +trip,social,0.001,0,0,0.521,0,0,0,0,0,0,0 +trip,othdiscr,0.252,0,0,0.212,0.165,0.165,0,0.098,0,0,0 +trip,univ,0,0,0,0,0,0,0,0,1,0,0 +# not needed as school is not chosen as an intermediate trip destination,,,,,,,,,,0,0,0 +#trip,gradeschool,0,0,0,0,0,0,0,0,0,0,0 +#trip,highschool,0,0,0,0,0,0,1,1,0,0,0 diff --git a/activitysim/examples/prototype_mwcog/configs/free_parking.csv b/activitysim/examples/prototype_mwcog/configs/free_parking.csv new file mode 100644 index 000000000..2505a9bf7 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/free_parking.csv @@ -0,0 +1,6 @@ +Label,Description,Expression,free,pay +util_income_very_high,Very high income household dummy,@df.income>=100000,coef_income_very_high,0 +util_income_high,High income housheold dummy,@(df.income>=60000) & (df.income<100000),coef_income_high,0 +util_hh_size_4_up,Household size is greater than 3 dummy,@df.hhsize>3,coef_hh_size_4_up,0 +util_more_autos_than_workers,More automobiles than workers dummy,@df.auto_ownership>df.num_workers,coef_more_autos_than_workers,0 +util_fewer_autos_than_workers,Fewer automobiles than workers dummy,@df.auto_ownership=30) & (income_in_thousands<60),coef_medium_income_households,, +util_household_has_more_cars_than_workers,Household has more cars than workers (dummy),more_cars_than_workers,coef_household_has_more_cars_than_workers_adults,,coef_household_has_more_cars_than_workers_mixed +util_household_in_urban_area,Household is located in an urban area type (dummy),home_is_urban,coef_household_in_urban_area,, +util_household_in_suburban_area,Household is located in a suburban area type (dummy),~(home_is_urban | home_is_rural),coef_household_in_suburban_area_adults,,coef_household_in_suburban_area_mixed +util_log_max_overlap_of_adults_time_windows,Log of max pair-wise overlap of household adults time windows,log_time_window_overlap_adult,coef_log_max_overlap_of_adults_time_windows,, +util_log_max_overlap_of_childrens_time_windows,Log of max pair-wise overlap of household childrens time windows,log_time_window_overlap_child,,coef_log_max_overlap_of_childrens_time_windows, +util_log_max_overlap_of_time_windows,Log of max pair-wise overlap of household adults and childrens time windows,log_time_window_overlap_adult_child,,,coef_log_max_overlap_of_time_windows +util_two_acive_adults,Two adults must have Mand or Non Mand activity patterns to have adult-only joint travel,num_travel_active_adults<2,coef_unavailable,, +util_two_active_children,Two children must have Mand or Non Mand activity patterns to have children-only joint travel,num_travel_active_children<2,,coef_unavailable, +util_travel_active_adult,At least one adult and at least one child must have Mand or Non Mand activity patterns to have adult/child joint travel,(num_travel_active_adults == 0) | (num_travel_active_children == 0),,,coef_unavailable \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_composition.yaml b/activitysim/examples/prototype_mwcog/configs/joint_tour_composition.yaml new file mode 100644 index 000000000..a699bb337 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_composition.yaml @@ -0,0 +1,11 @@ +LOGIT_TYPE: MNL + +SPEC: joint_tour_composition.csv +COEFFICIENTS: joint_tour_composition_coeffs.csv + +preprocessor: + SPEC: joint_tour_composition_annotate_households_preprocessor + DF: households +# TABLES: +# - persons +# - accessibility diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_composition_annotate_households_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_composition_annotate_households_preprocessor.csv new file mode 100644 index 000000000..3267e3793 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_composition_annotate_households_preprocessor.csv @@ -0,0 +1,22 @@ +Description,Target,Expression +#,, +,_HH_OVERLAPS,"hh_time_window_overlap(households, persons)" +,time_window_overlap_adult,_HH_OVERLAPS['aa']/2.25 +,time_window_overlap_child,_HH_OVERLAPS['cc']/2.25 +,time_window_overlap_adult_child,_HH_OVERLAPS['ac']/2.25 +logTimeWindowOverlapAdult,log_time_window_overlap_adult,np.log1p(time_window_overlap_adult) +logTimeWindowOverlapChild,log_time_window_overlap_child,np.log1p(time_window_overlap_child) +logTimeWindowOverlapAdultChild,log_time_window_overlap_adult_child,np.log1p(time_window_overlap_adult_child) +#,, +,_HH_PERSON_COUNT,"lambda exp, households, persons: persons.query(exp).groupby('household_id').size().reindex(households.index).fillna(0)" +,_num_full,"_HH_PERSON_COUNT('ptype == %s' % PTYPE_FULL, households, persons)" +,_num_part,"_HH_PERSON_COUNT('ptype == %s' % PTYPE_PART, households, persons)" +,num_full_max3,"_num_full.clip(0,3)" +,num_part_max3,"_num_part.clip(0,3)" +,num_univ_max3,"_HH_PERSON_COUNT('ptype == %s' % PTYPE_UNIVERSITY, households, persons).clip(0,3)" +,num_nonwork_max3,"_HH_PERSON_COUNT('ptype == %s' % PTYPE_NONWORK, households, persons).clip(0,3)" +,num_preschool_max3,"_HH_PERSON_COUNT('ptype == %s' % PTYPE_PRESCHOOL, households, persons).clip(0,3)" +,num_school_max3,"_HH_PERSON_COUNT('ptype == %s' % PTYPE_SCHOOL, households, persons).clip(0,3)" +,num_driving_max3,"_HH_PERSON_COUNT('ptype == %s' % PTYPE_DRIVING, households, persons).clip(0,3)" +#,, +,more_cars_than_workers,households.auto_ownership > (_num_full + _num_part) diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_composition_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_composition_coeffs.csv new file mode 100644 index 000000000..4d929c2b5 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_composition_coeffs.csv @@ -0,0 +1,32 @@ +coefficient_name,value,constrain +coef_unavailable,-999,T +coef_asc_children,5.3517,F +coef_asc_mixed,5.6290,fF +coef_tour_purpose_is_eating_out_children,-0.9678,F +coef_tour_purpose_is_eating_out_mixed,-0.8027,F +coef_tour_purpose_is_discretionary_adults,0.7648,F +coef_tour_purpose_is_discretionary_children,0.5101,F +coef_number_of_full_time_workers_adults,1.024,F +coef_number_of_full_time_workers_mixed,0.3624,F +coef_number_of_part_time_workers_adults,0.5412,F +coef_number_of_part_time_workers_mixed,0.3164,F +coef_number_of_university_students,0.8245,F +coef_number_of_non_workers_adults,0.6263,F +coef_number_of_non_workers_mixed,-0.3724,F +coef_number_of_children_too_young_for_school_children,0.7306,F +coef_number_of_children_too_young_for_school_mixed,0.7906,F +coef_number_of_pre_driving_age_children_children,0.7306,F +coef_number_of_pre_driving_age_children_mixed,0.3532,F +coef_number_of_driving_age_children_children,-0.2667,F +coef_number_of_driving_age_children_mixed,-0.9399,F +coef_low_income_households_adults,1.248,F +coef_low_income_households_mixed,0.5755,F +coef_medium_income_households,0.8369,F +coef_household_has_more_cars_than_workers_adults,1.386,F +coef_household_has_more_cars_than_workers_mixed,0.751,F +coef_household_in_urban_area,0.5741,F +coef_household_in_suburban_area_adults,0.5105,F +coef_household_in_suburban_area_mixed,0.1283,F +coef_log_max_overlap_of_adults_time_windows,1.192,F +coef_log_max_overlap_of_childrens_time_windows,1.841,F +coef_log_max_overlap_of_time_windows,1.958,F diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_destination.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination.csv new file mode 100644 index 000000000..96cd1c29f --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination.csv @@ -0,0 +1,17 @@ +Description,Expression,escort,shopping,eatout,othmaint,social,othdiscr +local_dist,_DIST@skims['DIST'],1,1,1,1,1,1 +util_dist,@_DIST,coef_dist_escort,coef_dist_shopping,0,coef_dist_othmaint,0,coef_dist_othdiscr +util_dist_squared,"@(_DIST).clip(0,20)**2",0,coef_dist_squared_shopping,0,0,0,coef_dist_squared_othdiscr +util_dist_cubed,"@(_DIST).clip(0,20)**3",0,coef_dist_cubed_shopping,0,0,0,coef_dist_cubed_othdiscr +util_dist_squared,"@(_DIST).clip(0,15)**2",0,0,0,coef_dist_squared_othmaint,0,0 +util_dist_logged,@(_DIST).apply(np.log1p),coef_dist_logged_escort,coef_dist_logged_shopping,coef_dist_logged_eatout,coef_dist_logged_othmaint,coef_dist_logged_social,coef_dist_logged_othdiscr +util_dist_hh_child,@(df['hh_child']>0) * _DIST,coef_dist_hh_child_escort,0,coef_dist_hh_child_eatout,0,0,coef_dist_hh_child_othdiscr +util_dist_zero_auto,@(df['auto_ownership']==0) * _DIST,0,0,0,0,0,coef_dist_zero_auto_othdiscr +util_dist_low,@(df['income_segment']==WORK_LOW_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_med,@(df['income_segment']==WORK_MED_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_very_high,@(df['income_segment']==WORK_VERYHIGH_SEGMENT_ID) * _DIST,0,0,coef_dist_veryhigh_inc_eatout,0,coef_dist_veryhigh_inc_social,coef_dist_veryhigh_inc_othdiscr +util_dist_joint_tour,@(df['tour_type']=='joint') * _DIST,0,coef_dist_joint_tour_shopping,0,coef_dist_joint_tour_othmaint,0,coef_dist_joint_tour_othdiscr +Size variable,@df['size_term'].apply(np.log1p),1,1,1,1,1,1 +No attractions,@df['size_term']==0,-999,-999,-999,-999,-999,-999 +Mode choice logsum,mode_choice_logsum,coef_mode_logsum_escort,coef_mode_logsum_shopping,coef_mode_logsum_eatout,coef_mode_logsum_othmaint,coef_mode_logsum_social,coef_mode_logsum_othdiscr +Sample of alternatives correction factor,"@np.minimum(np.log(df.pick_count/df.prob), 60)",1,1,1,1,1,1 diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_destination.yaml b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination.yaml new file mode 100644 index 000000000..5fe0c0636 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination.yaml @@ -0,0 +1,54 @@ + +SAMPLE_SPEC: joint_tour_destination_sample.csv +SPEC: joint_tour_destination.csv +COEFFICIENTS: joint_tour_destination_coeffs.csv + +SEGMENTS: + - shopping + - othmaint + - othdiscr + - eatout + - social + + +SAMPLE_SIZE: 30 + +# we can't use use household income_segment as this will also be set for non-workers +CHOOSER_SEGMENT_COLUMN_NAME: tour_type + +SIMULATE_CHOOSER_COLUMNS: + - tour_type + - TAZ + - person_id + - income_segment + - num_children + - hh_child + - auto_ownership + +LOGSUM_SETTINGS: tour_mode_choice.yaml + +# model-specific logsum-related settings +CHOOSER_ORIG_COL_NAME: TAZ +ALT_DEST_COL_NAME: alt_dest +IN_PERIOD: 15 +OUT_PERIOD: 19 + +SIZE_TERM_SELECTOR: non_mandatory + +# optional (comment out if not desired) +DEST_CHOICE_LOGSUM_COLUMN_NAME: destination_logsum + +# comment out DEST_CHOICE_LOGSUM_COLUMN_NAME if saved alt logsum table +DEST_CHOICE_SAMPLE_TABLE_NAME: tour_destination_sample + +SEGMENT_IDS: + work_low: 1 + work_med: 2 + work_high: 3 + work_veryhigh: 4 + +CONSTANTS: + WORK_LOW_SEGMENT_ID: 1 + WORK_MED_SEGMENT_ID: 2 + WORK_HIGH_SEGMENT_ID: 3 + WORK_VERYHIGH_SEGMENT_ID: 4 diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_destination_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination_coeffs.csv new file mode 100644 index 000000000..0c4e5fee2 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination_coeffs.csv @@ -0,0 +1,39 @@ +coefficient_name,value,constrain +coef_mode_logsum_escort,0.676,F +coef_dist_escort,0.046736802,F +coef_dist_squared_escort,0,F +coef_dist_cubed_escort,0,F +coef_dist_logged_escort,-2.403808965,F +coef_dist_hh_child_escort,-0.078449805,F +coef_mode_logsum_shopping,0.676,F +coef_dist_shopping,-0.045383662,F +coef_dist_squared_shopping,-0.001019621,F +coef_dist_cubed_shopping,0,F +coef_dist_logged_shopping,-2.184394753,F +coef_dist_joint_tour_shopping,0,F +coef_mode_logsum_eatout,0.79,F +coef_dist_eatout,0,F +coef_dist_squared_eatout,0,F +coef_dist_cubed_eatout,0,F +coef_dist_logged_eatout,-1.904643053,F +coef_dist_hh_child_eatout,-0.034067726,F +coef_dist_veryhigh_inc_eatout,-0.03079323,F +coef_mode_logsum_othmaint,0.676,F +coef_dist_othmaint,-0.04055464,F +coef_dist_squared_othmaint,-0.001372519,F +coef_dist_cubed_othmaint,0,F +coef_dist_logged_othmaint,-1.270318612,F +coef_dist_joint_tour_othmaint,0.020235681,F +coef_mode_logsum_social,0.79,F +coef_dist_social,0,F +coef_dist_logged_social,-1.408912476,F +coef_dist_veryhigh_inc_social,-0.018940702,F +coef_mode_logsum_othdiscr,0.79,F +coef_dist_othdiscr,0.016951123,F +coef_dist_squared_othdiscr,-0.00183013,F +coef_dist_cubed_othdiscr,0,F +coef_dist_logged_othdiscr,-1.692232511,F +coef_dist_hh_child_othdiscr,-0.016330734,F +coef_dist_zero_auto_othdiscr,0.064871626,F +coef_dist_veryhigh_inc_othdiscr,-0.008650825,F +coef_dist_joint_tour_othdiscr,0.013751855,F diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_destination_sample.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination_sample.csv new file mode 100644 index 000000000..4052c5040 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_destination_sample.csv @@ -0,0 +1,15 @@ +Description,Expression,escort,shopping,eatout,othmaint,social,othdiscr +local_dist,_DIST@skims['DIST'],1,1,1,1,1,1 +util_dist,@_DIST,coef_dist_escort,coef_dist_shopping,0,coef_dist_othmaint,0,coef_dist_othdiscr +util_dist_squared,"@(_DIST).clip(0,20)**2",0,coef_dist_squared_shopping,0,0,0,coef_dist_squared_othdiscr +util_dist_cubed,"@(_DIST).clip(0,20)**3",0,coef_dist_cubed_shopping,0,0,0,coef_dist_cubed_othdiscr +util_dist_squared,"@(_DIST).clip(0,15)**2",0,0,0,coef_dist_squared_othmaint,0,0 +util_dist_logged,@(_DIST).apply(np.log1p),coef_dist_logged_escort,coef_dist_logged_shopping,coef_dist_logged_eatout,coef_dist_logged_othmaint,coef_dist_logged_social,coef_dist_logged_othdiscr +util_dist_hh_child,@(df['hh_child']>0) * _DIST,coef_dist_hh_child_escort,0,coef_dist_hh_child_eatout,0,0,coef_dist_hh_child_othdiscr +util_dist_zero_auto,@(df['auto_ownership']==0) * _DIST,0,0,0,0,0,coef_dist_zero_auto_othdiscr +util_dist_low,@(df['income_segment']==WORK_LOW_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_med,@(df['income_segment']==WORK_MED_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_very_high,@(df['income_segment']==WORK_VERYHIGH_SEGMENT_ID) * _DIST,0,0,coef_dist_veryhigh_inc_eatout,0,coef_dist_veryhigh_inc_social,coef_dist_veryhigh_inc_othdiscr +util_dist_joint_tour,@(df['tour_type']=='joint') * _DIST,0,coef_dist_joint_tour_shopping,0,coef_dist_joint_tour_othmaint,0,coef_dist_joint_tour_othdiscr +Size variable,@df['size_term'].apply(np.log1p),1,1,1,1,1,1 +No attractions,@df['size_term']==0,-999,-999,-999,-999,-999,-999 diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency.csv new file mode 100644 index 000000000..48d46a8fb --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency.csv @@ -0,0 +1,78 @@ +Label,Description,Expression,0_tours,1_Shop,1_Main,1_Eat,1_Visit,1_Disc,2_SS,2_SM,2_SE,2_SV,2_SD,2_MM,2_ME,2_MV,2_MD,2_EE,2_EV,2_ED,2_VV,2_VD,2_DD +util_alternative_specific_constants,alternative_specific_constants,1,coef_asc_0_tours,coef_asc_1_Shop,coef_asc_1_Main,coef_asc_1_Eat,coef_asc_1_Visit,coef_asc_1_Disc,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours,coef_asc_2_tours +util_alternative_specific_constants_calibration,alternative_specific_constants_calibration,1,asc_calib_0_tours,asc_calib_1_Shop,asc_calib_1_Main,asc_calib_1_Eat,asc_calib_1_Visit,asc_calib_1_Disc,asc_calib_2_SS,asc_calib_2_SM,asc_calib_2_SE,asc_calib_2_SV,asc_calib_2_SD,asc_calib_2_MM,asc_calib_2_ME,asc_calib_2_MV,asc_calib_2_MD,asc_calib_2_EE,asc_calib_2_EV,asc_calib_2_ED,asc_calib_2_VV,asc_calib_2_VD,asc_calib_2_DD +#_zero_tours,,,,,,,,,,,,,,,,,,,,,,, +util_fullTimeHomeMaxThree_zero_tours,fullTimeHomeMaxThree_zero_tours,cdap_home_full_max3,coef_fullTimeHomeMaxThree_zero_tours,,,,,,,,,,,,,,,,,,,, +util_partTimeHomeMaxThree_zero_tours,partTimeHomeMaxThree_zero_tours,cdap_home_part_max3,coef_partTimeHomeMaxThree_zero_tours,,,,,,,,,,,,,,,,,,,, +util_nonWorkerHomeMaxThree_zero_tours,nonWorkerHomeMaxThree_zero_tours,cdap_home_nonwork_max3,coef_nonWorkerHomeMaxThree_zero_tours,,,,,,,,,,,,,,,,,,,, +util_retireeHomeMaxThree_zero_tours,retireeHomeMaxThree_zero_tours,cdap_home_retired_max3,coef_retireeHomeMaxThree_zero_tours,,,,,,,,,,,,,,,,,,,, +util_universityHomeMaxThree_univ_and_driving_zero_tours,universityHomeMaxThree_univ_and_driving_zero_tours,cdap_home_univ_driving_max3,coef_universityHomeMaxThree_univ_and_driving_zero_tours,,,,,,,,,,,,,,,,,,,, +util_preDrivingHomeMaxThree_preschool_and_school_zero_tours,preDrivingHomeMaxThree_preschool_and_school_zero_tours,cdap_home_nondriving_child_max3,coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours,,,,,,,,,,,,,,,,,,,, +#_shopping,,,,,,,,,,,,,,,,,,,,,,, +util_fullTimeNonMandMaxThree_shopping,fullTimeNonMandMaxThree_shopping,cdap_nonmand_full_max3,,coef_fullTimeNonMandMaxThree_shopping,,,,,2 * coef_fullTimeNonMandMaxThree_shopping,coef_fullTimeNonMandMaxThree_shopping,coef_fullTimeNonMandMaxThree_shopping,coef_fullTimeNonMandMaxThree_shopping,coef_fullTimeNonMandMaxThree_shopping,,,,,,,,,, +util_partTimeNonMandMaxThree_shopping,partTimeNonMandMaxThree_shopping,cdap_nonmand_part_max3,,coef_partTimeNonMandMaxThree_shopping,,,,,2 * coef_partTimeNonMandMaxThree_shopping,coef_partTimeNonMandMaxThree_shopping,coef_partTimeNonMandMaxThree_shopping,coef_partTimeNonMandMaxThree_shopping,coef_partTimeNonMandMaxThree_shopping,,,,,,,,,, +util_nonWorkerNonMandMaxThree_shopping,nonWorkerNonMandMaxThree_shopping,cdap_nonmand_nonwork_max3,,coef_nonWorkerNonMandMaxThree_shopping,,,,,2 * coef_nonWorkerNonMandMaxThree_shopping,coef_nonWorkerNonMandMaxThree_shopping,coef_nonWorkerNonMandMaxThree_shopping,coef_nonWorkerNonMandMaxThree_shopping,coef_nonWorkerNonMandMaxThree_shopping,,,,,,,,,, +util_retireeNonMandMaxThree_shopping,retireeNonMandMaxThree_shopping,cdap_nonmand_retired_max3,,coef_retireeNonMandMaxThree_shopping,,,,,2 * coef_retireeNonMandMaxThree_shopping,coef_retireeNonMandMaxThree_shopping,coef_retireeNonMandMaxThree_shopping,coef_retireeNonMandMaxThree_shopping,coef_retireeNonMandMaxThree_shopping,,,,,,,,,, +util_universityNonMandMaxThree_shopping,universityNonMandMaxThree_shopping,cdap_nonmand_univ_driving_max3,,coef_universityNonMandMaxThree_shopping,,,,,2 * coef_universityNonMandMaxThree_shopping,coef_universityNonMandMaxThree_shopping,coef_universityNonMandMaxThree_shopping,coef_universityNonMandMaxThree_shopping,coef_universityNonMandMaxThree_shopping,,,,,,,,,, +util_preDrivingNonMandMaxThree_shopping,preDrivingNonMandMaxThree_shopping,cdap_nonmand_nondriving_child_max3,,coef_preDrivingNonMandMaxThree_shopping,,,,,2 * coef_preDrivingNonMandMaxThree_shopping,coef_preDrivingNonMandMaxThree_shopping,coef_preDrivingNonMandMaxThree_shopping,coef_preDrivingNonMandMaxThree_shopping,coef_preDrivingNonMandMaxThree_shopping,,,,,,,,,, +util_fullTimeMandMaxThree_shopping,fullTimeMandMaxThree_shopping,cdap_mand_full_max3,,coef_fullTimeMandMaxThree_shopping,,,,,2 * coef_fullTimeMandMaxThree_shopping,coef_fullTimeMandMaxThree_shopping,coef_fullTimeMandMaxThree_shopping,coef_fullTimeMandMaxThree_shopping,coef_fullTimeMandMaxThree_shopping,,,,,,,,,, +util_logTimeWindowOverlapAdult_shopping,logTimeWindowOverlapAdult_shopping,log_time_window_overlap_adult,,coef_logTimeWindowOverlapAdult_shopping,,,,,2 * coef_logTimeWindowOverlapAdult_shopping,coef_logTimeWindowOverlapAdult_shopping,coef_logTimeWindowOverlapAdult_shopping,coef_logTimeWindowOverlapAdult_shopping,coef_logTimeWindowOverlapAdult_shopping,,,,,,,,,, +util_logTimeWindowOverlapChild_shopping,logTimeWindowOverlapChild_shopping,log_time_window_overlap_child,,coef_logTimeWindowOverlapChild_shopping,,,,,2 * coef_logTimeWindowOverlapChild_shopping,coef_logTimeWindowOverlapChild_shopping,coef_logTimeWindowOverlapChild_shopping,coef_logTimeWindowOverlapChild_shopping,coef_logTimeWindowOverlapChild_shopping,,,,,,,,,, +util_logTimeWindowOverlapAdultChild_shopping,logTimeWindowOverlapAdultChild_shopping,log_time_window_overlap_adult_child,,coef_logTimeWindowOverlapAdultChild_shopping,,,,,2 * coef_logTimeWindowOverlapAdultChild_shopping,coef_logTimeWindowOverlapAdultChild_shopping,coef_logTimeWindowOverlapAdultChild_shopping,coef_logTimeWindowOverlapAdultChild_shopping,coef_logTimeWindowOverlapAdultChild_shopping,,,,,,,,,, +util_fewerCarsThanDrivers_shopping,fewerCarsThanDrivers_shopping,(auto_ownership > 0) & (auto_ownership < num_drivers),,coef_fewerCarsThanDrivers_shopping,,,,,2 * coef_fewerCarsThanDrivers_shopping,coef_fewerCarsThanDrivers_shopping,coef_fewerCarsThanDrivers_shopping,coef_fewerCarsThanDrivers_shopping,coef_fewerCarsThanDrivers_shopping,,,,,,,,,, +util_moreCarsThanWorkers_shopping,moreCarsThanWorkers_shopping,auto_ownership > num_workers,,coef_moreCarsThanWorkers_shopping,,,,,2 * coef_moreCarsThanWorkers_shopping,coef_moreCarsThanWorkers_shopping,coef_moreCarsThanWorkers_shopping,coef_moreCarsThanWorkers_shopping,coef_moreCarsThanWorkers_shopping,,,,,,,,,, +#_Maintenance,,,,,,,,,,,,,,,,,,,,,,, +util_fullTimeNonMandMaxThree_Maintenance,fullTimeNonMandMaxThree_Maintenance,cdap_nonmand_full_max3,,,coef_fullTimeNonMandMaxThree_maint,,,,,coef_fullTimeNonMandMaxThree_maint,,,,2 * coef_fullTimeNonMandMaxThree_maint,coef_fullTimeNonMandMaxThree_maint,coef_fullTimeNonMandMaxThree_maint,coef_fullTimeNonMandMaxThree_maint,,,,,, +util_partTimeNonMandMaxThree_Maintenance,partTimeNonMandMaxThree_Maintenance,cdap_nonmand_part_max3,,,coef_partTimeNonMandMaxThree_maint,,,,,coef_partTimeNonMandMaxThree_maint,,,,2 * coef_partTimeNonMandMaxThree_maint,coef_partTimeNonMandMaxThree_maint,coef_partTimeNonMandMaxThree_maint,coef_partTimeNonMandMaxThree_maint,,,,,, +util_nonWorkerNonMandMaxThree_Maintenance,nonWorkerNonMandMaxThree_Maintenance,cdap_nonmand_nonwork_max3,,,coef_nonWorkerNonMandMaxThree_maint,,,,,coef_nonWorkerNonMandMaxThree_maint,,,,2 * coef_nonWorkerNonMandMaxThree_maint,coef_nonWorkerNonMandMaxThree_maint,coef_nonWorkerNonMandMaxThree_maint,coef_nonWorkerNonMandMaxThree_maint,,,,,, +util_retireeNonMandMaxThree_Maintenance,retireeNonMandMaxThree_Maintenance,cdap_nonmand_retired_max3,,,coef_retireeNonMandMaxThree_maint,,,,,coef_retireeNonMandMaxThree_maint,,,,2 * coef_retireeNonMandMaxThree_maint,coef_retireeNonMandMaxThree_maint,coef_retireeNonMandMaxThree_maint,coef_retireeNonMandMaxThree_maint,,,,,, +util_universityNonMandMaxThree_Maintenance,universityNonMandMaxThree_Maintenance,cdap_nonmand_univ_driving_max3,,,coef_universityNonMandMaxThree_maint,,,,,coef_universityNonMandMaxThree_maint,,,,2 * coef_universityNonMandMaxThree_maint,coef_universityNonMandMaxThree_maint,coef_universityNonMandMaxThree_maint,coef_universityNonMandMaxThree_maint,,,,,, +util_preDrivingNonMandMaxThree_Maintenance,preDrivingNonMandMaxThree_Maintenance,cdap_nonmand_nondriving_child_max3,,,coef_preDrivingNonMandMaxThree_maint,,,,,coef_preDrivingNonMandMaxThree_maint,,,,2 * coef_preDrivingNonMandMaxThree_maint,coef_preDrivingNonMandMaxThree_maint,coef_preDrivingNonMandMaxThree_maint,coef_preDrivingNonMandMaxThree_maint,,,,,, +util_fullTimeMandMaxThree_Maintenance,fullTimeMandMaxThree_Maintenance,cdap_mand_full_max3,,,coef_fullTimeMandMaxThree_maint,,,,,coef_fullTimeMandMaxThree_maint,,,,2 * coef_fullTimeMandMaxThree_maint,coef_fullTimeMandMaxThree_maint,coef_fullTimeMandMaxThree_maint,coef_fullTimeMandMaxThree_maint,,,,,, +util_drivingAgeStuMandMaxThree_Maintenance,drivingAgeStuMandMaxThree_Maintenance,cdap_mand_univ_driving_max3,,,coef_drivingAgeStuMandMaxThree_maint,,,,,coef_drivingAgeStuMandMaxThree_maint,,,,2 * coef_drivingAgeStuMandMaxThree_maint,coef_drivingAgeStuMandMaxThree_maint,coef_drivingAgeStuMandMaxThree_maint,coef_drivingAgeStuMandMaxThree_maint,,,,,, +util_preDrivingAgeMandMaxThree_Maintenance,preDrivingAgeMandMaxThree_Maintenance,cdap_mand_nondriving_child_max3,,,coef_preDrivingAgeMandMaxThree_maint,,,,,coef_preDrivingAgeMandMaxThree_maint,,,,2 * coef_preDrivingAgeMandMaxThree_maint,coef_preDrivingAgeMandMaxThree_maint,coef_preDrivingAgeMandMaxThree_maint,coef_preDrivingAgeMandMaxThree_maint,,,,,, +util_logTimeWindowOverlapAdult_Maintenance,logTimeWindowOverlapAdult_Maintenance,log_time_window_overlap_adult,,,coef_logTimeWindowOverlapAdult_maint,,,,,coef_logTimeWindowOverlapAdult_maint,,,,2 * coef_logTimeWindowOverlapAdult_maint,coef_logTimeWindowOverlapAdult_maint,coef_logTimeWindowOverlapAdult_maint,coef_logTimeWindowOverlapAdult_maint,,,,,, +util_logTimeWindowOverlapChild_Maintenance,logTimeWindowOverlapChild_Maintenance,log_time_window_overlap_child,,,coef_logTimeWindowOverlapChild_maint,,,,,coef_logTimeWindowOverlapChild_maint,,,,2 * coef_logTimeWindowOverlapChild_maint,coef_logTimeWindowOverlapChild_maint,coef_logTimeWindowOverlapChild_maint,coef_logTimeWindowOverlapChild_maint,,,,,, +util_logTimeWindowOverlapAdultChild_Maintenance,logTimeWindowOverlapAdultChild_Maintenance,log_time_window_overlap_adult_child,,,coef_logTimeWindowOverlapAdultChild_maint,,,,,coef_logTimeWindowOverlapAdultChild_maint,,,,2 * coef_logTimeWindowOverlapAdultChild_maint,coef_logTimeWindowOverlapAdultChild_maint,coef_logTimeWindowOverlapAdultChild_maint,coef_logTimeWindowOverlapAdultChild_maint,,,,,, +util_fewerCarsThanDrivers_Maintenance,fewerCarsThanDrivers_Maintenance,(auto_ownership > 0) & (auto_ownership < num_drivers),,,coef_fewerCarsThanDrivers_maint,,,,,coef_fewerCarsThanDrivers_maint,,,,2 * coef_fewerCarsThanDrivers_maint,coef_fewerCarsThanDrivers_maint,coef_fewerCarsThanDrivers_maint,coef_fewerCarsThanDrivers_maint,,,,,, +#_eatout,,,,,,,,,,,,,,,,,,,,,,, +util_fullTimeNonMandMaxThree_eatout,fullTimeNonMandMaxThree_eatout,cdap_nonmand_full_max3,,,,coef_fullTimeNonMandMaxThree_eatout,,,,,coef_fullTimeNonMandMaxThree_eatout,,,,coef_fullTimeNonMandMaxThree_eatout,,,2 * coef_fullTimeNonMandMaxThree_eatout,coef_fullTimeNonMandMaxThree_eatout,coef_fullTimeNonMandMaxThree_eatout,,, +util_partTimeNonMandMaxThree_eatout,partTimeNonMandMaxThree_eatout,cdap_nonmand_part_max3,,,,coef_partTimeNonMandMaxThree_eatout,,,,,coef_partTimeNonMandMaxThree_eatout,,,,coef_partTimeNonMandMaxThree_eatout,,,2 * coef_partTimeNonMandMaxThree_eatout,coef_partTimeNonMandMaxThree_eatout,coef_partTimeNonMandMaxThree_eatout,,, +util_nonWorkerNonMandMaxThree_eatout,nonWorkerNonMandMaxThree_eatout,cdap_nonmand_nonwork_max3,,,,coef_nonWorkerNonMandMaxThree_eatout,,,,,coef_nonWorkerNonMandMaxThree_eatout,,,,coef_nonWorkerNonMandMaxThree_eatout,,,2 * coef_nonWorkerNonMandMaxThree_eatout,coef_nonWorkerNonMandMaxThree_eatout,coef_nonWorkerNonMandMaxThree_eatout,,, +util_retireeNonMandMaxThree_eatout,retireeNonMandMaxThree_eatout,cdap_nonmand_retired_max3,,,,coef_retireeNonMandMaxThree_eatout,,,,,coef_retireeNonMandMaxThree_eatout,,,,coef_retireeNonMandMaxThree_eatout,,,2 * coef_retireeNonMandMaxThree_eatout,coef_retireeNonMandMaxThree_eatout,coef_retireeNonMandMaxThree_eatout,,, +util_universityNonMandMaxThree_eatout,universityNonMandMaxThree_eatout,cdap_nonmand_univ_driving_max3,,,,coef_universityNonMandMaxThree_eatout,,,,,coef_universityNonMandMaxThree_eatout,,,,coef_universityNonMandMaxThree_eatout,,,2 * coef_universityNonMandMaxThree_eatout,coef_universityNonMandMaxThree_eatout,coef_universityNonMandMaxThree_eatout,,, +util_preDrivingNonMandMaxThree_eatout,preDrivingNonMandMaxThree_eatout,cdap_nonmand_nondriving_child_max3,,,,coef_preDrivingNonMandMaxThree_eatout,,,,,coef_preDrivingNonMandMaxThree_eatout,,,,coef_preDrivingNonMandMaxThree_eatout,,,2 * coef_preDrivingNonMandMaxThree_eatout,coef_preDrivingNonMandMaxThree_eatout,coef_preDrivingNonMandMaxThree_eatout,,, +util_logTimeWindowOverlapAdult_eatout,logTimeWindowOverlapAdult_eatout,log_time_window_overlap_adult,,,,coef_logTimeWindowOverlapAdult_eatout,,,,,coef_logTimeWindowOverlapAdult_eatout,,,,coef_logTimeWindowOverlapAdult_eatout,,,2 * coef_logTimeWindowOverlapAdult_eatout,coef_logTimeWindowOverlapAdult_eatout,coef_logTimeWindowOverlapAdult_eatout,,, +util_logTimeWindowOverlapAdultChild_eatout,logTimeWindowOverlapAdultChild_eatout,log_time_window_overlap_adult_child,,,,coef_logTimeWindowOverlapAdultChild_eatout,,,,,coef_logTimeWindowOverlapAdultChild_eatout,,,,coef_logTimeWindowOverlapAdultChild_eatout,,,2 * coef_logTimeWindowOverlapAdultChild_eatout,coef_logTimeWindowOverlapAdultChild_eatout,coef_logTimeWindowOverlapAdultChild_eatout,,, +util_incomeBetween50And100_eatout,incomeBetween50And100_eatout,income_between_50_and_100,,,,coef_incomeBetween50And100_eatout,,,,,coef_incomeBetween50And100_eatout,,,,coef_incomeBetween50And100_eatout,,,2 * coef_incomeBetween50And100_eatout,coef_incomeBetween50And100_eatout,coef_incomeBetween50And100_eatout,,, +util_incomeGreaterThan100_eatout,incomeGreaterThan100_eatout,income_greater_than_100,,,,coef_incomeGreaterThan100_eatout,,,,,coef_incomeGreaterThan100_eatout,,,,coef_incomeGreaterThan100_eatout,,,2 * coef_incomeGreaterThan100_eatout,coef_incomeGreaterThan100_eatout,coef_incomeGreaterThan100_eatout,,, +util_incomeMissing_dummy_always_zero_eatout,incomeMissing_dummy_always_zero_eatout,income_missing,,,,coef_incomeMissing_dummy_always_zero_eatout,,,,,coef_incomeMissing_dummy_always_zero_eatout,,,,coef_incomeMissing_dummy_always_zero_eatout,,,2 * coef_incomeMissing_dummy_always_zero_eatout,coef_incomeMissing_dummy_always_zero_eatout,coef_incomeMissing_dummy_always_zero_eatout,,, +util_moreCarsThanWorkers_eatout,moreCarsThanWorkers_eatout,auto_ownership > num_workers,,,,coef_moreCarsThanWorkers_eatout,,,,,coef_moreCarsThanWorkers_eatout,,,,coef_moreCarsThanWorkers_eatout,,,2 * coef_moreCarsThanWorkers_eatout,coef_moreCarsThanWorkers_eatout,coef_moreCarsThanWorkers_eatout,,, +util_walkRetailAccessibility_eatout,walkRetailAccessibility_eatout,non_motorized_retail_accessibility,,,,coef_walkRetailAccessibility_eatout,,,,,coef_walkRetailAccessibility_eatout,,,,coef_walkRetailAccessibility_eatout,,,2 * coef_walkRetailAccessibility_eatout,coef_walkRetailAccessibility_eatout,coef_walkRetailAccessibility_eatout,,, +#_visiting,,,,,,,,,,,,,,,,,,,,,,, +util_fullTimeNonMandMaxThree_visiting,fullTimeNonMandMaxThree_visiting,cdap_nonmand_full_max3,,,,,coef_fullTimeNonMandMaxThree_visiting,,,,,coef_fullTimeNonMandMaxThree_visiting,,,,coef_fullTimeNonMandMaxThree_visiting,,,coef_fullTimeNonMandMaxThree_visiting,,2 * coef_fullTimeNonMandMaxThree_visiting,coef_fullTimeNonMandMaxThree_visiting, +util_partTimeNonMandMaxThree_visiting,partTimeNonMandMaxThree_visiting,cdap_nonmand_part_max3,,,,,coef_partTimeNonMandMaxThree_visiting,,,,,coef_partTimeNonMandMaxThree_visiting,,,,coef_partTimeNonMandMaxThree_visiting,,,coef_partTimeNonMandMaxThree_visiting,,2 * coef_partTimeNonMandMaxThree_visiting,coef_partTimeNonMandMaxThree_visiting, +util_nonWorkerNonMandMaxThree_visiting,nonWorkerNonMandMaxThree_visiting,cdap_nonmand_nonwork_max3,,,,,coef_nonWorkerNonMandMaxThree_visiting,,,,,coef_nonWorkerNonMandMaxThree_visiting,,,,coef_nonWorkerNonMandMaxThree_visiting,,,coef_nonWorkerNonMandMaxThree_visiting,,2 * coef_nonWorkerNonMandMaxThree_visiting,coef_nonWorkerNonMandMaxThree_visiting, +util_retireeNonMandMaxThree_visiting,retireeNonMandMaxThree_visiting,cdap_nonmand_retired_max3,,,,,coef_retireeNonMandMaxThree_visiting,,,,,coef_retireeNonMandMaxThree_visiting,,,,coef_retireeNonMandMaxThree_visiting,,,coef_retireeNonMandMaxThree_visiting,,2 * coef_retireeNonMandMaxThree_visiting,coef_retireeNonMandMaxThree_visiting, +util_universityNonMandMaxThree_visiting,universityNonMandMaxThree_visiting,cdap_nonmand_univ_driving_max3,,,,,coef_universityNonMandMaxThree_visiting,,,,,coef_universityNonMandMaxThree_visiting,,,,coef_universityNonMandMaxThree_visiting,,,coef_universityNonMandMaxThree_visiting,,2 * coef_universityNonMandMaxThree_visiting,coef_universityNonMandMaxThree_visiting, +util_preDrivingNonMandMaxThree_visiting,preDrivingNonMandMaxThree_visiting,cdap_nonmand_nondriving_child_max3,,,,,coef_preDrivingNonMandMaxThree_visiting,,,,,coef_preDrivingNonMandMaxThree_visiting,,,,coef_preDrivingNonMandMaxThree_visiting,,,coef_preDrivingNonMandMaxThree_visiting,,2 * coef_preDrivingNonMandMaxThree_visiting,coef_preDrivingNonMandMaxThree_visiting, +util_timeWindowOverlapAdult_visiting,timeWindowOverlapAdult_visiting,time_window_overlap_adult,,,,,coef_timeWindowOverlapAdult_visiting,,,,,coef_timeWindowOverlapAdult_visiting,,,,coef_timeWindowOverlapAdult_visiting,,,coef_timeWindowOverlapAdult_visiting,,2 * coef_timeWindowOverlapAdult_visiting,coef_timeWindowOverlapAdult_visiting, +util_timeWindowOverlapChild_visiting,timeWindowOverlapChild_visiting,time_window_overlap_child,,,,,coef_timeWindowOverlapChild_visiting,,,,,coef_timeWindowOverlapChild_visiting,,,,coef_timeWindowOverlapChild_visiting,,,coef_timeWindowOverlapChild_visiting,,2 * coef_timeWindowOverlapChild_visiting,coef_timeWindowOverlapChild_visiting, +util_timeWindowOverlapAdultChild_visiting,timeWindowOverlapAdultChild_visiting,time_window_overlap_adult_child,,,,,coef_timeWindowOverlapAdultChild_visiting,,,,,coef_timeWindowOverlapAdultChild_visiting,,,,coef_timeWindowOverlapAdultChild_visiting,,,coef_timeWindowOverlapAdultChild_visiting,,2 * coef_timeWindowOverlapAdultChild_visiting,coef_timeWindowOverlapAdultChild_visiting, +util_zeroAutomobiles_visiting,zeroAutomobiles_visiting,auto_ownership == 0,,,,,coef_zeroAutomobiles_visiting,,,,,coef_zeroAutomobiles_visiting,,,,coef_zeroAutomobiles_visiting,,,coef_zeroAutomobiles_visiting,,2 * coef_zeroAutomobiles_visiting,coef_zeroAutomobiles_visiting, +#_discretionary,,,,,,,,,,,,,,,,,,,,,,, +util_fullTimeNonMandMaxThree_disc,fullTimeNonMandMaxThree_disc,cdap_nonmand_full_max3,,,,,,coef_fullTimeNonMandMaxThree_disc,,,,,coef_fullTimeNonMandMaxThree_disc,,,,coef_fullTimeNonMandMaxThree_disc,,,coef_fullTimeNonMandMaxThree_disc,,coef_fullTimeNonMandMaxThree_disc,2 * coef_fullTimeNonMandMaxThree_disc +util_partTimeNonMandMaxThree_disc,partTimeNonMandMaxThree_disc,cdap_nonmand_part_max3,,,,,,coef_partTimeNonMandMaxThree_disc,,,,,coef_partTimeNonMandMaxThree_disc,,,,coef_partTimeNonMandMaxThree_disc,,,coef_partTimeNonMandMaxThree_disc,,coef_partTimeNonMandMaxThree_disc,2 * coef_partTimeNonMandMaxThree_disc +util_nonWorkerNonMandMaxThree_disc,nonWorkerNonMandMaxThree_disc,cdap_nonmand_nonwork_max3,,,,,,coef_nonWorkerNonMandMaxThree_disc,,,,,coef_nonWorkerNonMandMaxThree_disc,,,,coef_nonWorkerNonMandMaxThree_disc,,,coef_nonWorkerNonMandMaxThree_disc,,coef_nonWorkerNonMandMaxThree_disc,2 * coef_nonWorkerNonMandMaxThree_disc +util_retireeNonMandMaxThree_disc,retireeNonMandMaxThree_disc,cdap_nonmand_retired_max3,,,,,,coef_retireeNonMandMaxThree_disc,,,,,coef_retireeNonMandMaxThree_disc,,,,coef_retireeNonMandMaxThree_disc,,,coef_retireeNonMandMaxThree_disc,,coef_retireeNonMandMaxThree_disc,2 * coef_retireeNonMandMaxThree_disc +util_universityNonMandMaxThree_disc,universityNonMandMaxThree_disc,cdap_nonmand_univ_driving_max3,,,,,,coef_universityNonMandMaxThree_disc,,,,,coef_universityNonMandMaxThree_disc,,,,coef_universityNonMandMaxThree_disc,,,coef_universityNonMandMaxThree_disc,,coef_universityNonMandMaxThree_disc,2 * coef_universityNonMandMaxThree_disc +util_preDrivingNonMandMaxThree_disc,preDrivingNonMandMaxThree_disc,cdap_nonmand_nondriving_child_max3,,,,,,coef_preDrivingNonMandMaxThree_disc,,,,,coef_preDrivingNonMandMaxThree_disc,,,,coef_preDrivingNonMandMaxThree_disc,,,coef_preDrivingNonMandMaxThree_disc,,coef_preDrivingNonMandMaxThree_disc,2 * coef_preDrivingNonMandMaxThree_disc +util_drivingAgeStuMandMaxThree_disc,drivingAgeStuMandMaxThree_disc,cdap_mand_univ_driving_max3,,,,,,coef_drivingAgeStuMandMaxThree_disc,,,,,coef_drivingAgeStuMandMaxThree_disc,,,,coef_drivingAgeStuMandMaxThree_disc,,,coef_drivingAgeStuMandMaxThree_disc,,coef_drivingAgeStuMandMaxThree_disc,2 * coef_drivingAgeStuMandMaxThree_disc +util_preDrivingAgeMandMaxThree_disc,preDrivingAgeMandMaxThree_disc,cdap_mand_nondriving_child_max3,,,,,,coef_preDrivingAgeMandMaxThree_disc,,,,,coef_preDrivingAgeMandMaxThree_disc,,,,coef_preDrivingAgeMandMaxThree_disc,,,coef_preDrivingAgeMandMaxThree_disc,,coef_preDrivingAgeMandMaxThree_disc,2 * coef_preDrivingAgeMandMaxThree_disc +util_logTimeWindowOverlapAdult_disc,logTimeWindowOverlapAdult_disc,log_time_window_overlap_adult,,,,,,coef_logTimeWindowOverlapAdult_disc,,,,,coef_logTimeWindowOverlapAdult_disc,,,,coef_logTimeWindowOverlapAdult_disc,,,coef_logTimeWindowOverlapAdult_disc,,coef_logTimeWindowOverlapAdult_disc,2 * coef_logTimeWindowOverlapAdult_disc +util_logTimeWindowOverlapChild_disc,logTimeWindowOverlapChild_disc,log_time_window_overlap_child,,,,,,coef_logTimeWindowOverlapChild_disc,,,,,coef_logTimeWindowOverlapChild_disc,,,,coef_logTimeWindowOverlapChild_disc,,,coef_logTimeWindowOverlapChild_disc,,coef_logTimeWindowOverlapChild_disc,2 * coef_logTimeWindowOverlapChild_disc +util_logTimeWindowOverlapAdultChild_disc,logTimeWindowOverlapAdultChild_disc,log_time_window_overlap_adult_child,,,,,,coef_logTimeWindowOverlapAdultChild_disc,,,,,coef_logTimeWindowOverlapAdultChild_disc,,,,coef_logTimeWindowOverlapAdultChild_disc,,,coef_logTimeWindowOverlapAdultChild_disc,,coef_logTimeWindowOverlapAdultChild_disc,2 * coef_logTimeWindowOverlapAdultChild_disc +util_incomeBetween50And100_disc,incomeBetween50And100_disc,income_between_50_and_100,,,,,,coef_incomeBetween50And100_disc,,,,,coef_incomeBetween50And100_disc,,,,coef_incomeBetween50And100_disc,,,coef_incomeBetween50And100_disc,,coef_incomeBetween50And100_disc,2 * coef_incomeBetween50And100_disc +util_incomeGreaterThan100_disc,incomeGreaterThan100_disc,income_greater_than_100,,,,,,coef_incomeGreaterThan100_disc,,,,,coef_incomeGreaterThan100_disc,,,,coef_incomeGreaterThan100_disc,,,coef_incomeGreaterThan100_disc,,coef_incomeGreaterThan100_disc,2 * coef_incomeGreaterThan100_disc +util_incomeMissing_dummy_always_zero_disc,incomeMissing_dummy_always_zero_disc,income_missing,,,,,,coef_incomeMissing_dummy_always_zero_disc,,,,,coef_incomeMissing_dummy_always_zero_disc,,,,coef_incomeMissing_dummy_always_zero_disc,,,coef_incomeMissing_dummy_always_zero_disc,,coef_incomeMissing_dummy_always_zero_disc,2 * coef_incomeMissing_dummy_always_zero_disc +util_zeroAutomobiles_dis,zeroAutomobiles_disc,auto_ownership == 0,,,,,,coef_zeroAutomobiles_disc,,,,,coef_zeroAutomobiles_disc,,,,coef_zeroAutomobiles_disc,,,coef_zeroAutomobiles_disc,,coef_zeroAutomobiles_disc,2 * coef_zeroAutomobiles_disc diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency.yaml b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency.yaml new file mode 100644 index 000000000..61e1f1bdc --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency.yaml @@ -0,0 +1,11 @@ +LOGIT_TYPE: MNL + +SPEC: joint_tour_frequency.csv +COEFFICIENTS: joint_tour_frequency_coeffs.csv + +preprocessor: + SPEC: joint_tour_frequency_annotate_households_preprocessor + DF: households + TABLES: + #- persons + - accessibility diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_alternatives.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_alternatives.csv new file mode 100644 index 000000000..7bf93731f --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_alternatives.csv @@ -0,0 +1,23 @@ +#,,,,,alt file for building joint tours +alt,shopping,othmaint,eatout,social,othdiscr +0_tours,0,0,0,0,0 +1_Shop,1,0,0,0,0 +1_Main,0,1,0,0,0 +1_Eat,0,0,1,0,0 +1_Visit,0,0,0,1,0 +1_Disc,0,0,0,0,1 +2_SS,2,0,0,0,0 +2_SM,1,1,0,0,0 +2_SE,1,0,1,0,0 +2_SV,1,0,0,1,0 +2_SD,1,0,0,0,1 +2_MM,0,2,0,0,0 +2_ME,0,1,1,0,0 +2_MV,0,1,0,1,0 +2_MD,0,1,0,0,1 +2_EE,0,0,2,0,0 +2_EV,0,0,1,1,0 +2_ED,0,0,1,0,1 +2_VV,0,0,0,2,0 +2_VD,0,0,0,1,1 +2_DD,0,0,0,0,2 diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_annotate_households_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_annotate_households_preprocessor.csv new file mode 100644 index 000000000..c5580ed71 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_annotate_households_preprocessor.csv @@ -0,0 +1,32 @@ +Description,Target,Expression +,_PTYPE_CDAP_PATTERN_COUNT,"lambda ptype, activity, households, persons: persons.query('ptype == %s and cdap_activity==\'%s\'' % (ptype, activity)).groupby('household_id').size().reindex(households.index).fillna(0)" +,_PEMPLOY_CDAP_PATTERN_COUNT,"lambda pemploy, activity, households, persons: persons.query('pemploy == %s and cdap_activity==\'%s\'' % (pemploy, activity)).groupby('household_id').size().reindex(households.index).fillna(0)" +,_2_PTYPE_CDAP_PATTERN_COUNT,"lambda ptype1, ptype2, activity, households, persons: persons.query('(ptype == %s or ptype == %s) and cdap_activity==\'%s\'' % (ptype1, ptype2, activity)).groupby('household_id').size().reindex(households.index).fillna(0)" +#,, +,_HH_OVERLAPS,"hh_time_window_overlap(households, persons)" +,time_window_overlap_adult,_HH_OVERLAPS['aa']/2.25 +,time_window_overlap_child,_HH_OVERLAPS['cc']/2.25 +,time_window_overlap_adult_child,_HH_OVERLAPS['ac']/2.25 +#,, +,cdap_home_full_max3,"_PEMPLOY_CDAP_PATTERN_COUNT(PEMPLOY_FULL, 'H', households, persons).clip(0,3)" +,cdap_home_part_max3,"_PEMPLOY_CDAP_PATTERN_COUNT(PEMPLOY_PART, 'H', households, persons).clip(0,3)" +,cdap_home_nonwork_max3,"_PTYPE_CDAP_PATTERN_COUNT(4, 'H', households, persons).clip(0,3)" +,cdap_home_retired_max3,"_PTYPE_CDAP_PATTERN_COUNT(5, 'H', households, persons).clip(0,3)" +,cdap_home_univ_driving_max3,"_2_PTYPE_CDAP_PATTERN_COUNT(3, 6, 'H', households, persons).clip(0,3)" +,cdap_home_nondriving_child_max3,"_2_PTYPE_CDAP_PATTERN_COUNT(7, 8, 'H', households, persons).clip(0,3)" +,cdap_nonmand_full_max3,"_PEMPLOY_CDAP_PATTERN_COUNT(PEMPLOY_FULL, 'N', households, persons).clip(0,3)" +,cdap_nonmand_part_max3,"_PEMPLOY_CDAP_PATTERN_COUNT(PEMPLOY_PART, 'N', households, persons).clip(0,3)" +,cdap_nonmand_nonwork_max3,"_PTYPE_CDAP_PATTERN_COUNT(4, 'N', households, persons).clip(0,3)" +,cdap_nonmand_retired_max3,"_PTYPE_CDAP_PATTERN_COUNT(5, 'N', households, persons).clip(0,3)" +,cdap_nonmand_univ_driving_max3,"_2_PTYPE_CDAP_PATTERN_COUNT(3, 6, 'N', households, persons).clip(0,3)" +,cdap_nonmand_nondriving_child_max3,"_2_PTYPE_CDAP_PATTERN_COUNT(7, 8, 'N', households, persons).clip(0,3)" +,cdap_mand_full_max3,"_PEMPLOY_CDAP_PATTERN_COUNT(PEMPLOY_FULL, 'M', households, persons).clip(0,3)" +,cdap_mand_univ_driving_max3,"_2_PTYPE_CDAP_PATTERN_COUNT(3, 6, 'M', households, persons).clip(0,3)" +,cdap_mand_nondriving_child_max3,"_2_PTYPE_CDAP_PATTERN_COUNT(7, 8, 'M', households, persons).clip(0,3)" +,income_between_50_and_100,(households.income > 50000) & (households.income <= 100000) +,income_greater_than_100,households.income > 100000 +,income_missing,0 +logTimeWindowOverlapAdult,log_time_window_overlap_adult,np.log1p(time_window_overlap_adult) +logTimeWindowOverlapChild,log_time_window_overlap_child,np.log1p(time_window_overlap_child) +logTimeWindowOverlapAdultChild,log_time_window_overlap_adult_child,np.log1p(time_window_overlap_adult_child) +nmRetail,non_motorized_retail_accessibility,"reindex(accessibility.nmRetail, households.TAZ)" diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_coeffs.csv new file mode 100644 index 000000000..2f7f80365 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_frequency_coeffs.csv @@ -0,0 +1,106 @@ +coefficient_name,value,constrain +# asc,, +coef_asc_0_tours,0,T +coef_asc_1_Shop,-6.0149,F +coef_asc_1_Main,-5.7389,F +coef_asc_1_Eat,-6.3757,F +coef_asc_1_Visit,-5.8818,F +coef_asc_1_Disc,-5.4806,F +coef_asc_2_tours,-14.4576,F +# zero_tours,, +coef_fullTimeHomeMaxThree_zero_tours,1.175,F +coef_partTimeHomeMaxThree_zero_tours,1.447,F +coef_nonWorkerHomeMaxThree_zero_tours,1.514,F +coef_retireeHomeMaxThree_zero_tours,0.6053,F +coef_universityHomeMaxThree_univ_and_driving_zero_tours,0.5685,F +coef_preDrivingHomeMaxThree_preschool_and_school_zero_tours,0.53,F +# shopping,, +coef_fullTimeNonMandMaxThree_shopping,0.2052,F +coef_partTimeNonMandMaxThree_shopping,0.1866,F +coef_nonWorkerNonMandMaxThree_shopping,0.7078,F +coef_retireeNonMandMaxThree_shopping,0.941,F +coef_universityNonMandMaxThree_shopping,0.7648,F +coef_preDrivingNonMandMaxThree_shopping,0.5474,F +coef_fullTimeMandMaxThree_shopping,-0.2424,F +coef_logTimeWindowOverlapAdult_shopping,0.5945,F +coef_logTimeWindowOverlapChild_shopping,0.1416,F +coef_logTimeWindowOverlapAdultChild_shopping,0.1086,F +coef_fewerCarsThanDrivers_shopping,0.2523,F +coef_moreCarsThanWorkers_shopping,-0.3027,F +# maintenance,, +coef_fullTimeNonMandMaxThree_maint,0.3173,F +coef_partTimeNonMandMaxThree_maint,0.2452,F +coef_nonWorkerNonMandMaxThree_maint,0.4643,F +coef_retireeNonMandMaxThree_maint,0.905,F +coef_universityNonMandMaxThree_maint,0.2643,F +coef_preDrivingNonMandMaxThree_maint,0.6482,F +coef_fullTimeMandMaxThree_maint,-0.3009,F +coef_drivingAgeStuMandMaxThree_maint,-0.3237,F +coef_preDrivingAgeMandMaxThree_maint,0.2299,F +coef_logTimeWindowOverlapAdult_maint,0.3714,F +coef_logTimeWindowOverlapChild_maint,0.176,F +coef_logTimeWindowOverlapAdultChild_maint,0.2443,F +coef_fewerCarsThanDrivers_maint,0.461,F +# eatout,, +coef_fullTimeNonMandMaxThree_eatout,0.2275,F +coef_partTimeNonMandMaxThree_eatout,0.3765,F +coef_nonWorkerNonMandMaxThree_eatout,0.182,F +coef_retireeNonMandMaxThree_eatout,0.4264,F +coef_universityNonMandMaxThree_eatout,0.4097,F +coef_preDrivingNonMandMaxThree_eatout,0.3851,F +coef_logTimeWindowOverlapAdult_eatout,0.4856,F +coef_logTimeWindowOverlapAdultChild_eatout,0.0921,F +coef_incomeBetween50And100_eatout,0.2977,F +coef_incomeGreaterThan100_eatout,0.4492,F +coef_incomeMissing_dummy_always_zero_eatout,0.278,F +coef_moreCarsThanWorkers_eatout,0.3825,F +coef_walkRetailAccessibility_eatout,0.062,F +# visiting,, +coef_fullTimeNonMandMaxThree_visiting,0.6445,F +coef_partTimeNonMandMaxThree_visiting,0.1332,F +coef_nonWorkerNonMandMaxThree_visiting,0.5475,F +coef_retireeNonMandMaxThree_visiting,0.5579,F +coef_universityNonMandMaxThree_visiting,0.2809,F +coef_preDrivingNonMandMaxThree_visiting,0.6008,F +coef_timeWindowOverlapAdult_visiting,0.0596,F +coef_timeWindowOverlapChild_visiting,0.0092,F +coef_timeWindowOverlapAdultChild_visiting,0.0256,F +coef_zeroAutomobiles_visiting,-0.98,F +# discretionary,, +coef_fullTimeNonMandMaxThree_disc,0.1275,F +coef_partTimeNonMandMaxThree_disc,0.4979,F +coef_nonWorkerNonMandMaxThree_disc,0.2871,F +coef_retireeNonMandMaxThree_disc,0.6136,F +coef_universityNonMandMaxThree_disc,0.7546,F +coef_preDrivingNonMandMaxThree_disc,0.5331,F +coef_drivingAgeStuMandMaxThree_disc,0.1932,F +coef_preDrivingAgeMandMaxThree_disc,0.3862,F +coef_logTimeWindowOverlapAdult_disc,0.3428,F +coef_logTimeWindowOverlapChild_disc,0.1162,F +coef_logTimeWindowOverlapAdultChild_disc,0.2212,F +coef_incomeBetween50And100_disc,0.3167,F +coef_incomeGreaterThan100_disc,0.486,F +coef_incomeMissing_dummy_always_zero_disc,0.3723,F +coef_zeroAutomobiles_disc,-0.909,F +#Phase1_Calibration,, +asc_calib_0_tours,0,T +asc_calib_1_Shop,1.053698044,F +asc_calib_1_Main,0.732431708,F +asc_calib_1_Eat,0.877259241,F +asc_calib_1_Visit,0.436534239,F +asc_calib_1_Disc,0.619623918,F +asc_calib_2_SS,2.404591356,F +asc_calib_2_SM,2.998240224,F +asc_calib_2_SE,2.042554293,F +asc_calib_2_SV,0.054676458,F +asc_calib_2_SD,2.467068755,F +asc_calib_2_MM,3.614067275,F +asc_calib_2_ME,4.359003674,F +asc_calib_2_MV,5.998710535,F +asc_calib_2_MD,5.114616381,F +asc_calib_2_EE,3.295790528,F +asc_calib_2_EV,5.235744732,F +asc_calib_2_ED,2.359825593,F +asc_calib_2_VV,1.285350946,F +asc_calib_2_VD,4.250918308,F +asc_calib_2_DD,2.958796827,F diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_participation.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation.csv new file mode 100644 index 000000000..cd692d8d2 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation.csv @@ -0,0 +1,67 @@ +Label,Description,Expression,participate,not_participate +util_full_time_worker_mixed_party,"Full-Time Worker, mixed party",person_is_full & tour_composition_is_mixed,coef_full_time_worker_mixed_party,coef_full_time_worker_mixed_party_not +util_part_time_worker_adults_only_party,"Part-Time Worker, adults-only party",person_is_part & tour_composition_is_adults,coef_part_time_worker_adults_only_party,coef_part_time_worker_adults_only_party_not +util_part_time_worker_mixed_party,"Part-Time Worker, mixed party",person_is_part & tour_composition_is_mixed,coef_part_time_worker_mixed_party, +util_university_student_mixed_party,"University Student, mixed party",person_is_univ & tour_composition_is_mixed,coef_university_student_mixed_party, +util_non_worker_adults_only_party,"Non-Worker, adults-only party",person_is_nonwork & tour_composition_is_adults,coef_non_worker_adults_only_party, +util_non_worker_mixed_party,"Non-Worker, mixed party",person_is_nonwork & tour_composition_is_mixed,coef_non_worker_mixed_party, +util_child_too_young_for_school_children_only_party,"Child too Young for School, children-only party",person_is_preschool & tour_composition_is_children,coef_child_too_young_for_school_children_only_party, +util_child_too_young_for_school_mixed_party,"Child too Young for School, mixed party",person_is_preschool & tour_composition_is_mixed,coef_child_too_young_for_school_mixed_party, +util_pre_driving_age_student_children_only_party,"Pre-driving age Student, children-only party",person_is_school & tour_composition_is_children,coef_pre_driving_age_student_children_only_party, +util_pre_driving_age_student_mixed_party,"Pre-driving age Student, mixed party",person_is_school & tour_composition_is_mixed,coef_pre_driving_age_student_mixed_party, +util_driving_age_student_children_only_party,"Driving-age Student, children-only party",person_is_driving & tour_composition_is_children,coef_driving_age_student_children_only_party, +util_driving_age_student_mixed_party,"Driving-age Student, mixed party",person_is_driving & tour_composition_is_mixed,coef_driving_age_student_mixed_party, +#,,,, +util_full_time_worker_specific_to_eating_out_joint_tours,"Full-Time Worker, specific to eating out joint tours",person_is_full & tour_type_is_eat,coef_full_time_worker_specific_to_eating_out_joint_tours,coef_full_time_worker_specific_to_eating_out_joint_tours_not +util_full_time_worker_specific_to_discretionary_joint_tours,"Full-Time Worker, specific to discretionary joint tours",person_is_full & tour_type_is_disc,coef_full_time_worker_specific_to_discretionary_joint_tours,coef_full_time_worker_specific_to_discretionary_joint_tours_not +util_part_time_worker_specific_to_eating_out_joint_tours,"Part-Time Worker, specific to eating out joint tours",person_is_part & tour_type_is_eat,coef_part_time_worker_specific_to_eating_out_joint_tours, +util_part_time_worker_specific_to_discretionary_joint_tours,"Part-Time Worker, specific to discretionary joint tours",person_is_part & tour_type_is_disc,coef_part_time_worker_specific_to_discretionary_joint_tours, +util_university_student_specific_to_eating_out_joint_tours,"University Student, specific to eating out joint tours",person_is_univ & tour_type_is_eat,coef_university_student_specific_to_eating_out_joint_tours, +util_university_student_specific_to_discretionary_joint_tours,"University Student, specific to discretionary joint tours",person_is_univ & tour_type_is_disc,coef_university_student_specific_to_discretionary_joint_tours, +util_non_worker_specific_to_eating_out_joint_tours,"Non-worker, specific to eating out joint tours",person_is_nonwork & tour_type_is_eat,coef_non_worker_specific_to_eating_out_joint_tours, +util_non_worker_specific_to_discretionary_joint_tours,"Non-worker, specific to discretionary joint tours",person_is_nonwork & tour_type_is_disc,coef_non_worker_specific_to_discretionary_joint_tours, +util_child_too_young_for_school_specific_to_eating_out_joint_tours,"Child too Young for School, specific to eating out joint tours",person_is_preschool & tour_type_is_eat,coef_child_too_young_for_school_specific_to_eating_out_joint_tours, +util_child_too_young_for_school_specific_to_discretionary_joint_tours,"Child too Young for School, specific to discretionary joint tours",person_is_preschool & tour_type_is_disc,coef_child_too_young_for_school_specific_to_discretionary_joint_tours, +util_pre_driving_age_student_specific_to_eating_out_joint_tours,"Pre-driving Age Student, specific to eating out joint tours",person_is_school & tour_type_is_eat,coef_pre_driving_age_student_specific_to_eating_out_joint_tours, +util_pre_driving_age_student_specific_to_discretionary_joint_tours,"Pre-driving age Student, specific to discretionary joint tours",person_is_school & tour_type_is_disc,coef_pre_driving_age_student_specific_to_discretionary_joint_tours, +util_driving_age_student_specific_to_eating_out_joint_tours,"Driving-age Student, specific to eating out joint tours",person_is_driving & tour_type_is_eat,coef_driving_age_student_specific_to_eating_out_joint_tours, +util_driving_age_student_specific_to_discretionary_joint_tours,"Driving-age Student, specific to discretionary joint tours",person_is_driving & tour_type_is_disc,coef_driving_age_student_specific_to_discretionary_joint_tours, +#,,,, +util_household_in_urban_area_adult_adult_only_party,"Household in urban area, adult, adult-only party",home_is_urban & adult & tour_composition_is_adults,coef_household_in_urban_area_adult_adult_only_party, +util_household_in_urban_area_adult_mixed_party,"Household in urban area, adult, mixed party",home_is_urban & adult & tour_composition_is_mixed,coef_household_in_urban_area_adult_mixed_party, +util_household_in_urban_area_child_child_only_party,"Household in urban area, child, child-only party",home_is_urban & ~adult & tour_composition_is_children,coef_household_in_urban_area_child_child_only_party, +util_household_in_urban_area_child_mixed_party,"Household in urban area, child, mixed party",home_is_urban & ~adult & tour_composition_is_mixed,coef_household_in_urban_area_child_mixed_party, +util_household_in_suburban_area_adult_adult_only_party,"Household in suburban area, adult, adult-only party",home_is_suburban & adult & tour_composition_is_adults,coef_household_in_suburban_area_adult_adult_only_party, +util_household_in_suburban_area_adult_mixed_party,"Household in suburban area, adult, mixed party",home_is_suburban & adult & tour_composition_is_mixed,coef_household_in_suburban_area_adult_mixed_party, +util_household_in_suburban_area_child_child_only_party,"Household in suburban area, child, child-only party",home_is_suburban & ~adult & tour_composition_is_children,coef_household_in_suburban_area_child_child_only_party, +util_household_in_suburban_area_child_mixed_party,"Household in suburban area, child, mixed party",home_is_suburban & ~adult & tour_composition_is_mixed,coef_household_in_suburban_area_child_mixed_party, +util_adult_more_automobiles_than_workers_adult_only_party,"Adult, more automobiles than workers, adult-only party",adult & more_cars_than_workers & tour_composition_is_adults,coef_adult_more_automobiles_than_workers_adult_only_party, +util_adult_more_automobiles_than_workers_mixed_party,"Adult, more automobiles than workers, mixed party",adult & more_cars_than_workers & tour_composition_is_mixed,coef_adult_more_automobiles_than_workers_mixed_party, +util_child_more_automobiles_than_workers_child_only_party,"Child, more automobiles than workers, child-only party",adult & more_cars_than_workers & tour_composition_is_children,coef_child_more_automobiles_than_workers_child_only_party, +util_child_more_automobiles_than_workers_mixed_party,"Child, more automobiles than workers, mixed party",adult & more_cars_than_workers & tour_composition_is_mixed,coef_child_more_automobiles_than_workers_mixed_party, +#,,,, +util_dummy_for_high_income_for_adult_in_adult_party,Dummy for high income for adult in adult party,high_income & tour_composition_is_adults,coef_dummy_for_high_income_for_adult_in_adult_party, +util_dummy_for_high_income_for_adult_in_mixed_party,Dummy for high income for adult in mixed party,high_income & tour_composition_is_mixed,coef_dummy_for_high_income_for_adult_in_mixed_party, +util_dummy_for_high_income_for_child_in_children_party,Dummy for high income for child in children party,high_income & tour_composition_is_children,coef_dummy_for_high_income_for_child_in_children_party, +util_dummy_for_high_income_for_child_in_mixed_party,Dummy for high income for child in mixed party,high_income & tour_composition_is_mixed,coef_dummy_for_high_income_for_child_in_mixed_party, +util_adult_number_of_joint_tours_adult_only,"Adult, number of joint tours, adult-only",(adult & tour_composition_is_adults) * num_hh_joint_tours,coef_adult_number_of_joint_tours_adult_only, +util_adult_number_of_joint_tours_mixed,"Adult, number of joint tours, mixed",(adult & tour_composition_is_mixed) * num_hh_joint_tours,coef_adult_number_of_joint_tours_mixed, +util_child_number_of_joint_tours_child_only,"Child, number of joint tours, child only",(~adult & tour_composition_is_children) * num_hh_joint_tours,coef_child_number_of_joint_tours_child_only, +util_child_number_of_joint_tours_mixed,"Child, number of joint tours, mixed",(~adult & tour_composition_is_mixed) * num_hh_joint_tours,coef_child_number_of_joint_tours_mixed, +util_adult_number_of_other_adults_in_the_household_adults_only_party,"Adult, number of other adults in the household, adults-only party",(adult & tour_composition_is_adults) * (num_adults - 1),coef_adult_number_of_other_adults_in_the_household_adults_only_party, +util_adult_number_of_other_adults_in_the_household_mixed_party,"Adult, number of other adults in the household, mixed party",(adult & tour_composition_is_mixed) * (num_adults - 1),coef_adult_number_of_other_adults_in_the_household_mixed_party, +util_child_number_of_other_children_in_the_household_child_only_party,"Child, number of other children in the household, child-only party",(~adult & tour_composition_is_children) * (num_children - 1),coef_child_number_of_other_children_in_the_household_child_only_party, +util_child_number_of_other_children_in_the_household_mixed,"Child, number of other children in the household, mixed",(~adult & tour_composition_is_mixed) * (num_children - 1),coef_child_number_of_other_children_in_the_household_mixed, +#,,,, +util_adult_log_of_max_window_overlap_with_an_adult_adult_only_party,"Adult, log of max window overlap with an adult, adult-only party",(adult & tour_composition_is_adults) * log_time_window_overlap_adult,coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party, +util_adult_log_of_max_window_overlap_with_a_child_mixed,"Adult, log of max window overlap with a child, mixed",(adult & tour_composition_is_mixed) * log_time_window_overlap_adult,coef_adult_log_of_max_window_overlap_with_a_child_mixed, +util_child_log_of_max_window_overlap_with_an_adult_mixed,"Child, log of max window overlap with an adult, mixed",(~adult & tour_composition_is_mixed) * log_time_window_overlap_adult,coef_child_log_of_max_window_overlap_with_an_adult_mixed, +util_child_log_of_max_window_overlap_with_a_child_child,"Child, log of max window overlap with a child, child",(~adult & tour_composition_is_children) * log_time_window_overlap_adult,coef_child_log_of_max_window_overlap_with_a_child_child, +#,,,, +util_adults_are_prohibited_in_participating_in_child_only_tours,Adults are prohibited in participating in child-only tours,adult & tour_composition_is_children,coef_unavailable, +util_children_are_prohibited_in_participating_in_adult_only_tours,Children are prohibited in participating in adult-only tours,~adult & tour_composition_is_adults,coef_unavailable, +util_persons_with_home_activity_patterns_are_prohibilted_from_participating,Persons with Home activity patterns are prohibilted from participating,~travel_active,coef_unavailable, +util_if_only_two_available_adults_both_must_participate_in_adult_only_tour,"If only two available adults, both must participate in adult-only tour",adult & travel_active & tour_composition_is_adults & (num_travel_active_adults<3),,coef_unavailable +util_if_only_one_available_adult_traveler_must_participate_in_mixed_tour,"If only one available adult, traveler must participate in mixed tour",adult & travel_active & tour_composition_is_mixed & (num_travel_active_adults<2),,coef_unavailable +util_if_only_two_available_children_both_must_participate_in_child_only_tour,"If only two available children, both must participate in child-only tour",~adult & travel_active & tour_composition_is_children & (num_travel_active_children<3),,coef_unavailable +util_if_only_one_available_child_traveler_must_participate_in_mixed_tour,"If only one available child, traveler must participate in mixed tour",~adult & travel_active & tour_composition_is_mixed & (num_travel_active_children<2),,coef_unavailable diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_participation.yaml b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation.yaml new file mode 100644 index 000000000..59941e832 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation.yaml @@ -0,0 +1,20 @@ + +SPEC: joint_tour_participation.csv +COEFFICIENTS: joint_tour_participation_coeffs.csv + +LOGIT_TYPE: MNL + +#max_participation_choice_iterations: 5000 + +preprocessor: + SPEC: joint_tour_participation_annotate_participants_preprocessor + DF: participants +# TABLES: +# - persons +# - accessibility + +annotate_persons: + SPEC: annotate_persons_jtp + DF: persons + TABLES: + - joint_tour_participants diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_participation_annotate_participants_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation_annotate_participants_preprocessor.csv new file mode 100644 index 000000000..cb78bff30 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation_annotate_participants_preprocessor.csv @@ -0,0 +1,24 @@ +Description,Target,Expression +,_P_OVERLAPS,person_time_window_overlap(persons) +,time_window_overlap_adult,"reindex(_P_OVERLAPS.aa, participants.person_id)/2.25" +,time_window_overlap_child,"reindex(_P_OVERLAPS.cc, participants.person_id)/2.25" +,time_window_overlap_adult_child,"reindex(_P_OVERLAPS.ac, participants.person_id)/2.25" +logTimeWindowOverlapAdult,log_time_window_overlap_adult,np.log1p(time_window_overlap_adult) +logTimeWindowOverlapChild,log_time_window_overlap_child,np.log1p(time_window_overlap_child) +logTimeWindowOverlapAdultChild,log_time_window_overlap_adult_child,np.log1p(time_window_overlap_adult_child) +#,, +,person_is_full,participants.ptype == PTYPE_FULL +,person_is_part,participants.ptype == PTYPE_PART +,person_is_univ,participants.ptype == PTYPE_UNIVERSITY +,person_is_nonwork,participants.ptype == PTYPE_NONWORK +,person_is_driving,participants.ptype == PTYPE_DRIVING +,person_is_school,participants.ptype == PTYPE_SCHOOL +,person_is_preschool,participants.ptype == PTYPE_PRESCHOOL +,tour_type_is_eat,participants.tour_type=='eat' +,tour_type_is_disc,participants.tour_type=='disc' +,tour_composition_is_adults,participants.composition=='adults' +,tour_composition_is_children,participants.composition=='children' +,tour_composition_is_mixed,participants.composition=='mixed' +,home_is_suburban,~(participants.home_is_urban | participants.home_is_rural) +,high_income,participants.income_in_thousands > 60 +,more_cars_than_workers,participants.auto_ownership > participants.num_workers diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_participation_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation_coeffs.csv new file mode 100644 index 000000000..455f08be9 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_participation_coeffs.csv @@ -0,0 +1,68 @@ +coefficient_name,value,constrain +coef_unavailable,-999,T +coef_full_time_worker_mixed_party,-3.566,F +coef_full_time_worker_mixed_party_not,0.5,T +coef_part_time_worker_adults_only_party,-3.566,F +coef_part_time_worker_adults_only_party_not,0.5,T +coef_part_time_worker_mixed_party,-0.3655,F +coef_university_student_mixed_party,-3.041,F +coef_non_worker_adults_only_party,-3.164,F +coef_non_worker_mixed_party,0.7152,F +coef_child_too_young_for_school_children_only_party,-2.786,F +coef_child_too_young_for_school_mixed_party,-1.893,F +coef_pre_driving_age_student_children_only_party,-0.7217,F +coef_pre_driving_age_student_mixed_party,-1.752,F +coef_driving_age_student_children_only_party,-1.822,F +coef_driving_age_student_mixed_party,-1.353,F +#,, +coef_full_time_worker_specific_to_eating_out_joint_tours,0.7157,F +coef_full_time_worker_specific_to_eating_out_joint_tours_not,0.5,T +coef_full_time_worker_specific_to_discretionary_joint_tours,0.4392,F +coef_full_time_worker_specific_to_discretionary_joint_tours_not,0.5,T +coef_part_time_worker_specific_to_eating_out_joint_tours,2.188,F +coef_part_time_worker_specific_to_discretionary_joint_tours,0.285,F +coef_university_student_specific_to_eating_out_joint_tours,-0.82,F +coef_university_student_specific_to_discretionary_joint_tours,0,T +coef_non_worker_specific_to_eating_out_joint_tours,0.1617,F +coef_non_worker_specific_to_discretionary_joint_tours,-0.1835,F +coef_child_too_young_for_school_specific_to_eating_out_joint_tours,0.6589,F +coef_child_too_young_for_school_specific_to_discretionary_joint_tours,0.1284,F +coef_pre_driving_age_student_specific_to_eating_out_joint_tours,1.391,F +coef_pre_driving_age_student_specific_to_discretionary_joint_tours,0.6626,F +coef_driving_age_student_specific_to_eating_out_joint_tours,2.344,F +coef_driving_age_student_specific_to_discretionary_joint_tours,-0.6675,F +#,, +coef_household_in_urban_area_adult_adult_only_party,0,T +coef_household_in_urban_area_adult_mixed_party,-0.137,F +coef_household_in_urban_area_child_child_only_party,1.21,F +coef_household_in_urban_area_child_mixed_party,0.6265,F +coef_household_in_suburban_area_adult_adult_only_party,0,T +coef_household_in_suburban_area_adult_mixed_party,-0.06007,F +coef_household_in_suburban_area_child_child_only_party,0,T +coef_household_in_suburban_area_child_mixed_party,0,T +coef_adult_more_automobiles_than_workers_adult_only_party,-0.2133,F +coef_adult_more_automobiles_than_workers_mixed_party,-0.6031,F +coef_child_more_automobiles_than_workers_child_only_party,-0.4214,F +coef_child_more_automobiles_than_workers_mixed_party,-0.3776,F +#,, +coef_dummy_for_high_income_for_adult_in_adult_party,-0.1682,F +coef_dummy_for_high_income_for_adult_in_mixed_party,-0.02613,F +coef_dummy_for_high_income_for_child_in_children_party,-0.5619,F +coef_dummy_for_high_income_for_child_in_mixed_party,-0.1528,F +coef_adult_number_of_joint_tours_adult_only,-0.3242,F +coef_adult_number_of_joint_tours_mixed,-0.3584,F +coef_child_number_of_joint_tours_child_only,0.1047,F +coef_child_number_of_joint_tours_mixed,-0.5089,F +coef_adult_number_of_other_adults_in_the_household_adults_only_party,0,T +coef_adult_number_of_other_adults_in_the_household_mixed_party,0,T +coef_child_number_of_other_children_in_the_household_child_only_party,0,T +coef_child_number_of_other_children_in_the_household_mixed,0,T +#,, +coef_adult_log_of_max_window_overlap_with_an_adult_adult_only_party,0.8436,F +coef_adult_log_of_max_window_overlap_with_a_child_mixed,2.189,F +coef_child_log_of_max_window_overlap_with_an_adult_mixed,1.538,F +coef_child_log_of_max_window_overlap_with_a_child_child,1.296,F + + + + diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_scheduling.yaml b/activitysim/examples/prototype_mwcog/configs/joint_tour_scheduling.yaml new file mode 100644 index 000000000..e81afe238 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_scheduling.yaml @@ -0,0 +1,12 @@ +LOGIT_TYPE: MNL + +SPEC: tour_scheduling_joint.csv +COEFFICIENTS: tour_scheduling_joint_coeffs.csv + +preprocessor: + SPEC: joint_tour_scheduling_annotate_tours_preprocessor + DF: joint_tours + TABLES: + - land_use + - households + - joint_tour_participants diff --git a/activitysim/examples/prototype_mwcog/configs/joint_tour_scheduling_annotate_tours_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/joint_tour_scheduling_annotate_tours_preprocessor.csv new file mode 100644 index 000000000..594b79624 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/joint_tour_scheduling_annotate_tours_preprocessor.csv @@ -0,0 +1,2 @@ +Description,Target,Expression +,origin_to_destination_distance,"skim_dict.lookup(joint_tours.origin, joint_tours.destination, ('SOV_DIST', 'MD'))" diff --git a/activitysim/examples/prototype_mwcog/configs/logging.yaml b/activitysim/examples/prototype_mwcog/configs/logging.yaml new file mode 100644 index 000000000..6dfca578a --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/logging.yaml @@ -0,0 +1,53 @@ +# Config for logging +# ------------------ +# See http://docs.python.org/2.7/library/logging.config.html#configuration-dictionary-schema + +logging: + version: 1 + disable_existing_loggers: true + + + # Configuring the default (root) logger is highly recommended + root: + level: NOTSET + handlers: [console] + + loggers: + + activitysim: + level: DEBUG + handlers: [console, logfile] + propagate: false + + orca: + level: WARN + handlers: [console, logfile] + propagate: false + + handlers: + + logfile: + class: logging.FileHandler + filename: !!python/object/apply:activitysim.core.config.log_file_path ['activitysim.log'] + mode: w + formatter: fileFormatter + level: NOTSET + + console: + class: logging.StreamHandler + stream: ext://sys.stdout + formatter: simpleFormatter + level: NOTSET + + formatters: + + simpleFormatter: + class: logging.Formatter + # format: '%(levelname)s - %(name)s - %(message)s' + format: '%(levelname)s - %(message)s' + datefmt: '%d/%m/%Y %H:%M:%S' + + fileFormatter: + class: logging.Formatter + format: '%(asctime)s - %(levelname)s - %(name)s - %(message)s' + datefmt: '%d/%m/%Y %H:%M:%S' diff --git a/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency.csv b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency.csv new file mode 100644 index 000000000..848bbf77a --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency.csv @@ -0,0 +1,101 @@ +Label,Description,Expression,work1,work2,school1,school2,work_and_school +util_ft_worker,Full-time worker alternative-specific constants,ptype == 1,0,coef_ft_worker_work2_asc,,, +util_pt_worker,Part-time worker alternative-specific constants,ptype == 2,0,coef_pt_worker_work2_asc,,, +util_univ,University student alternative-specific constants,ptype == 3,coef_univ_work1_asc,coef_univ_work2_asc,0,coef_univ_school2_asc,coef_univ_work_and_school_asc +util_non_working_adult,Non-working adult alternative-specific constants,ptype == 4,,,,, +util_retired,Retired alternative-specific constants,ptype == 5,,,,, +util_driving_age_child,Driving-age child alternative-specific constants,ptype == 6,,,0,coef_driving_age_child_school2_asc,coef_driving_age_child_work_and_school_asc +util_pre_driving_age_child,Pre-driving age child who is in school alternative-specific constants,ptype == 7,,,0,coef_pre_driving_age_child_school2_asc, +util_female_ft_worker,Female - Full-time worker interaction,(ptype == 1) & female,0,coef_female_work2,coef_female_school1,,coef_female_work_and_school +util_female_pt_worker,Female - Part-time worker interaction,(ptype == 2) & female,0,coef_female_work2,coef_female_school1,,coef_female_work_and_school +util_female_univ,Female - University student interaction,(ptype == 3) & female,coef_female_work1,coef_female_work2,coef_female_school1,coef_female_school2,coef_female_work_and_school +util_female_non_working_adult,Female - Non-working adult interaction,(ptype == 4) & female,0,coef_female_work2,coef_female_school1,, +util_female_retired,Female - Retired interaction,(ptype == 5) & female,0,coef_female_work2,coef_female_school1,, +util_female_driving_age_child,Female - Driving-age child interaction,(ptype == 6) & female,coef_female_work1,,0,coef_female_school2,coef_female_work_and_school +util_female_pre_driving,Female - Pre-driving age child who is in school interaction,(ptype == 7) & female,coef_female_work1,,0,coef_female_school2, +util_under_35_ft,Under 35 - Full-time worker interaction,(ptype == 1) & (age <= 35),0,coef_under_35_work2,coef_under_35_school1,,coef_under_35_work_and_school +util_under_35_pt,Under 35 - Part-time worker interaction,(ptype == 2) & (age <= 35),0,coef_under_35_work2,coef_under_35_school1,,coef_under_35_work_and_school +util_under_35_univ,Under 35 - University student interaction,(ptype == 3) & (age <= 35),coef_under_35_work1,coef_under_35_work2,0,coef_under_35_school2,coef_under_35_work_and_school +util_under_35_non_working,Under 35 - Non-working adult interaction,(ptype == 4) & (age <= 35),0,coef_under_35_work2,coef_under_35_school1,, +util_can_walk_to_work_ft,Can walk to work - Full-time worker interaction,(ptype == 1) & (distance_to_work < 3),,coef_can_walk_to_work_work2,,, +util_can_walk_to_work_pt,Can walk to work - Part-time worker interaction,(ptype == 2) & (distance_to_work < 3),,coef_can_walk_to_work_work2,,, +util_can_walk_to_work_univ,Can walk to work - University student interaction,(ptype == 3) & (distance_to_work < 3),,coef_can_walk_to_work_work2,,, +util_can_walk_to_work_non_working_adult,Can walk to work - Non-working adult interaction,(ptype == 4) & (distance_to_work < 3),,coef_can_walk_to_work_work2,,, +util_can_walk_to_work_retired,Can walk to work - Retired interaction,(ptype == 5) & (distance_to_work < 3),,coef_can_walk_to_work_work2,,, +util_can_walk_to_school_univ,Can walk to school - University student interaction,(ptype == 3) & (distance_to_school < 3),,,,coef_can_walk_to_work_school2, +util_can_walk_to_school_driving_age_child,Can walk to school - Driving-age child interaction,(ptype == 6) & (distance_to_school < 3),,,,coef_can_walk_to_work_school2, +util_can_walk_to_school_pre_driving_age_child,Can walk to school - Pre-driving age child who is in school interaction,(ptype == 7) & (distance_to_school < 3),,,,coef_can_walk_to_work_school2, +util_can_walk_to_work_or_school_ft,Can walk to work or school - Full-time worker interaction,(ptype == 1) & (distance_to_work < 3 | distance_to_school < 3),,,,,coef_can_walk_to_work_and_school +util_can_walk_to_work_or_school_pt,Can walk to work or school - Part-time worker interaction,(ptype == 2) & (distance_to_work < 3 | distance_to_school < 3),,,,,coef_can_walk_to_work_and_school +util_can_walk_to_work_or_school_univ,Can walk to work or school - University student interaction,(ptype == 3) & (distance_to_work < 3 | distance_to_school < 3),,,,,coef_can_walk_to_work_and_school +util_can_walk_to_work_or_school_driving_age_child,Can walk to work or school - Driving-age child interaction,(ptype == 6) & (distance_to_work < 3 | distance_to_school < 3),,,,,coef_can_walk_to_work_and_school +util_round_trip_auto_time_to_work_ft,Round trip auto time to work - Full-time worker interaction,(ptype == 1) * roundtrip_auto_time_to_work,,coef_round_trip_auto_time_to_work_work2,,,coef_round_trip_auto_time_to_work_school2 +util_round_trip_auto_time_to_work_pt,Round trip auto time to work - Part-time worker interaction,(ptype == 2) * roundtrip_auto_time_to_work,,coef_round_trip_auto_time_to_work_work2,,,coef_round_trip_auto_time_to_work_school2 +util_round_trip_auto_time_to_work_univ,Round trip auto time to work - University student interaction,(ptype == 3) * roundtrip_auto_time_to_work,,coef_round_trip_auto_time_to_work_work2,,,coef_round_trip_auto_time_to_work_school2 +util_round_trip_auto_time_to_work_non_working_adult,Round trip auto time to work - Non-working adult interaction,(ptype == 4) * roundtrip_auto_time_to_work,,coef_round_trip_auto_time_to_work_work2,,, +util_round_trip_auto_time_to_work_retired,Round trip auto time to work - Retired,(ptype == 5) * roundtrip_auto_time_to_work,,coef_round_trip_auto_time_to_work_work2,,, +util_round_trip_auto_time_to_school_univ,Round trip auto time to school - University student interaction,(ptype == 3) * roundtrip_auto_time_to_school,,,,coef_round_trip_auto_time_to_work_school2,coef_round_trip_auto_time_to_work_work_and_school +util_round_trip_auto_time_to_school_driving_age_child,Round trip auto time to school - Driving-age child interaction,(ptype == 6) * roundtrip_auto_time_to_school,,,,coef_round_trip_auto_time_to_work_school2,coef_round_trip_auto_time_to_work_work_and_school +util_round_trip_auto_time_to_school_pre_driving_age_child,Round trip auto time to school - Pre-driving age child who is in school interaction,(ptype == 7) * roundtrip_auto_time_to_school,,,,coef_round_trip_auto_time_to_work_school2, +util_student_employted_univ,Student is employed - University student interaction,(ptype == 3) & student_is_employed,coef_student_employed,coef_student_employed,,,coef_student_employed +util_student_employted_driving_age_child,Student is employed - Driving-age child interaction,(ptype == 6) & student_is_employed,coef_student_employed,coef_student_employed,,,coef_student_employed +util_non_student_goes_to_school_ft,Non-student goes to school - Full-time worker interaction,(ptype == 1) & nonstudent_to_school,,,coef_non_student_goes_to_school,,coef_non_student_goes_to_school +util_non_student_goes_to_school_pt,Non-student goes to school - Part-time worker interaction,(ptype == 2) & nonstudent_to_school,,,coef_non_student_goes_to_school,,coef_non_student_goes_to_school +util_non_student_goes_to_school_non_working_adult,Non-student goes to school - Non-working adult interaction,(ptype == 4) & nonstudent_to_school,,,coef_non_student_goes_to_school,, +util_non_student_goes_to_school_retired,Non-student goes to school - Retired interaction,(ptype == 5) & nonstudent_to_school,,,coef_non_student_goes_to_school,, +util_no_cars_in_hh_ft,No cars in household - Full-time worker interaction,(ptype == 1) & (auto_ownership == 0),,coef_no_cars_in_hh_work2,,,coef_no_cars_in_hh_work_and_school +util_no_cars_in_hh_pt,No cars in household - Part-time worker interaction,(ptype == 2) & (auto_ownership == 0),,coef_no_cars_in_hh_work2,,,coef_no_cars_in_hh_work_and_school +util_no_cars_in_hh_unif,No cars in household - University student interaction,(ptype == 3) & (auto_ownership == 0),,coef_no_cars_in_hh_work2,,coef_no_cars_in_hh_school2,coef_no_cars_in_hh_work_and_school +util_no_cars_in_hh_non_working_adult,No cars in household - Non-working adult interaction,(ptype == 4) & (auto_ownership == 0),,coef_no_cars_in_hh_work2,,, +util_no_cars_in_hh_retired,No cars in household - Retired interaction,(ptype == 5) & (auto_ownership == 0),,coef_no_cars_in_hh_work2,,, +util_no_cars_in_hh_driving_age_student,No cars in household - Driving-age student interaction,(ptype == 6) & (auto_ownership == 0),,,,coef_no_cars_in_hh_school2,coef_no_cars_in_hh_work_and_school +util_no_cars_in_hh_pre_driving_age,No cars in household - Pre-driving age child who is in school interaction,(ptype == 7) & (auto_ownership == 0),,,,coef_no_cars_in_hh_school2, +util_fewer_cars_than_drivers_univ,Fewer cars than drivers in household - University student interaction,(ptype == 3) & (auto_ownership < num_drivers),,,,coef_few_cars_than_drivers_school2, +util_fewer_cars_than_drivers_driving_age_student,Fewer cars than drivers in household - Driving-age student interaction,(ptype == 6) & (auto_ownership < num_drivers),,,,coef_few_cars_than_drivers_school2, +util_fewer_cars_than_drivers_pre_driving_age,Fewer cars than drivers in household - Pre-driving age child who is in school interaction,(ptype == 7) & (auto_ownership < num_drivers),,,,coef_few_cars_than_drivers_school2, +util_num_preschool_in_hh_ft,Number of preschool children in household - Full-time worker interaction,(ptype == 1) * (num_young_children),0,coef_num_preschool_in_hh_work2,coef_num_preschool_in_hh_school1,,coef_num_preschool_in_hh_work_and_school +util_num_preschool_in_hh_pt,Number of preschool children in household - Part-time worker interaction,(ptype == 2) * (num_young_children),0,coef_num_preschool_in_hh_work2,coef_num_preschool_in_hh_school1,,coef_num_preschool_in_hh_work_and_school +util_num_preschool_in_hh_univ,Number of preschool children in household - University student interaction,(ptype == 3) * (num_young_children),coef_num_preschool_in_hh_work1,coef_num_preschool_in_hh_work2,0,coef_num_preschool_in_hh_school2,coef_num_preschool_in_hh_work_and_school +util_num_preschool_in_hh_non_working_adult,Number of preschool children in household - Non-working adult interaction,(ptype == 4) * (num_young_children),0,coef_num_preschool_in_hh_work2,coef_num_preschool_in_hh_school1,, +util_num_preschool_in_hh_retired,Number of preschool children in household - Retired interaction,(ptype == 5) * (num_young_children),0,coef_num_preschool_in_hh_work2,coef_num_preschool_in_hh_school1,, +util_num_preschool_in_hh_driving_age_student,Number of preschool children in household - Driving-age student interaction,(ptype == 6) * (num_young_children),coef_num_preschool_in_hh_work1,,0,coef_num_preschool_in_hh_school2,coef_num_preschool_in_hh_work_and_school +util_num_preschool_in_hh_pre_driving_age_in_school,Number of preschool children in household - Pre-driving age child who is in school interaction,(ptype == 7) * (num_young_children),coef_num_preschool_in_hh_work1,,0,coef_num_preschool_in_hh_school2, +util_num_nonworkers_in_hh_ft,Number of non-workers in the household - Full-time worker interaction,(ptype == 1) * num_non_workers,,,coef_num_non_workers_in_hh_school1,, +util_num_nonworkers_in_hh_pt,Number of non-workers in the household - Part-time worker interaction,(ptype == 2) * num_non_workers,,,coef_num_non_workers_in_hh_school1,, +util_hh_income_gt_50k_ft,Household income higher than $50k - Full-time worker interaction,(ptype == 1) & (income_in_thousands > 50),0,,coef_hh_income_gt_50k_school1,,coef_hh_income_gt_50k_worker_work_and_school +util_hh_income_gt_50k_pt,Household income higher than $50k - Part-time worker interaction,(ptype == 2) & (income_in_thousands > 50),0,,coef_hh_income_gt_50k_school1,,coef_hh_income_gt_50k_worker_work_and_school +util_hh_income_gt_50k_univ,Household income higher than $50k - University student interaction,(ptype == 3) & (income_in_thousands > 50),coef_hh_income_gt_50k_work,coef_hh_income_gt_50k_work,0,,coef_hh_income_gt_50k_student_work_and_school +util_hh_income_gt_50k_non_working_adult,Household income higher than $50k - Non-working adult interaction,(ptype == 4) & (income_in_thousands > 50),0,,coef_hh_income_gt_50k_school1,, +util_hh_income_gt_50k_retired,Household income higher than $50k - Retired interaction,(ptype == 5) & (income_in_thousands > 50),0,,coef_hh_income_gt_50k_school1,, +util_hh_income_gt_50k_driving_age_student,Household income higher than $50k - Driving-age student interaction,(ptype == 6) & (income_in_thousands > 50),coef_hh_income_gt_50k_work,,0,,coef_hh_income_gt_50k_student_work_and_school +util_hh_income_gt_50k_pre_driving_age_student,Household income higher than $50k - Pre-driving age child who is in school interaction,(ptype == 7) & (income_in_thousands > 50),coef_hh_income_gt_50k_work,,0,, +util_non_family_hh_ft,Non-family household - Full-time worker interaction,(ptype == 1) & non_family,0,,coef_non_family_hh_category1,,coef_non_family_hh_category1 +util_non_family_hh_pt,Non-family household - Part-time worker interaction,(ptype == 2) & non_family,0,,coef_non_family_hh_category1,,coef_non_family_hh_category1 +util_non_family_hh_univ,Non-family household - University student interaction,(ptype == 3) & non_family,coef_non_family_hh_category2,coef_non_family_hh_category2,0,,coef_non_family_hh_category2 +util_non_family_hh_non_working_adult,Non-family household - Non-working adult interaction,(ptype == 4) & non_family,0,,coef_non_family_hh_category1,, +util_non_family_hh_retired,Non-family household - Retired interaction,(ptype == 5) & non_family,0,,coef_non_family_hh_category1,, +util_non_family_hh_driving_age_student,Non-family household - Driving-age student interaction,(ptype == 6) & non_family,coef_non_family_hh_category2,,0,,coef_non_family_hh_category2 +util_non_family_hh_pre_driving_age_student,Non-family household - Pre-driving age child who is in school interaction,(ptype == 7) & non_family,coef_non_family_hh_category2,,0,, +util_num_under_16_not_at_school_ft,Number of children under 16 not at school - Full-time worker interaction,(ptype == 1) * num_under16_not_at_school,,coef_num_under_16_not_at_school_work2,,,coef_num_under_16_not_at_school_work_and_school +util_num_under_16_not_at_school_pt,Number of children under 16 not at school - Part-time worker interaction,(ptype == 2) * num_under16_not_at_school,,coef_num_under_16_not_at_school_work2,,,coef_num_under_16_not_at_school_work_and_school +util_num_under_16_not_at_school_univ,Number of children under 16 not at school - University student interaction,(ptype == 3) * num_under16_not_at_school,,coef_num_under_16_not_at_school_work2,,coef_num_under_16_not_at_school_school2,coef_num_under_16_not_at_school_work_and_school +util_num_under_16_not_at_school_non_working_adult,Number of children under 16 not at school - Non-working adult interaction,(ptype == 4) * num_under16_not_at_school,,coef_num_under_16_not_at_school_work2,,, +util_num_under_16_not_at_school_retired,Number of children under 16 not at school - Retired,(ptype == 5) * num_under16_not_at_school,,coef_num_under_16_not_at_school_work2,,, +util_num_under_16_not_at_school_driving_age_student,Number of children under 16 not at school - Driving-age student interaction,(ptype == 6) * num_under16_not_at_school,,,,coef_num_under_16_not_at_school_school2,coef_num_under_16_not_at_school_work_and_school +util_num_under_16_not_at_school_pre_driving_age,Number of children under 16 not at school - Pre-driving age child who is in school interaction,(ptype == 7) * num_under16_not_at_school,,,,coef_num_under_16_not_at_school_school2, +util_nome_urban_ft,Home is in urban area - Full-time worker interaction,(ptype == 1) & home_is_urban,0,coef_home_urban_work2,coef_home_urban_school1,,coef_home_urban_work_and_school +util_nome_urban_pt,Home is in urban area - Part-time worker interaction,(ptype == 2) & home_is_urban,0,coef_home_urban_work2,coef_home_urban_school1,,coef_home_urban_work_and_school +util_nome_urban_univ,Home is in urban area - University student interaction,(ptype == 3) & home_is_urban,coef_home_urban_work1,coef_home_urban_work2,0,coef_home_urban_school2,coef_home_urban_work_and_school +util_nome_urban_non_working_adult,Home is in urban area - Non-working adult interaction,(ptype == 4) & home_is_urban,0,coef_home_urban_work2,coef_home_urban_school1,, +util_nome_urban_retired,Home is in urban area - Retired interaction,(ptype == 5) & home_is_urban,0,coef_home_urban_work2,coef_home_urban_school1,, +util_nome_urban_driving_age_student,Home is in urban area - Driving-age student interaction,(ptype == 6) & home_is_urban,coef_home_urban_work1,,0,coef_home_urban_school2,coef_home_urban_work_and_school +util_nome_urban_pre_driving_age_student,Home is in urban area - Pre-driving age child who is in school interaction,(ptype == 7) & home_is_urban,coef_home_urban_work1,,0,coef_home_urban_school2, +util_availability_ft,Unavailable: Full-time worker,ptype == 1,,,,coef_unavailable, +util_availability_pt,Unavailable: Part-time worker,ptype == 2,,,,coef_unavailable, +util_availability_non_working_adult,Unavailable: Non-working adult,ptype == 4,,,,coef_unavailable,coef_unavailable +util_availability_retired,Unavailable: Retired,ptype == 5,,,,coef_unavailable,coef_unavailable +util_availability_driving_age_child,Unavailable: Driving-age child,ptype == 6,coef_unavailable,coef_unavailable,,, +util_availability_pre_driving_age_student,Unavailable: Pre-driving age child who is in school,ptype == 7,,coef_unavailable,,,coef_unavailable +util_availability_pre_driving_age_not_in_school,Unavailable: Pre-driving age child who is not in school,ptype == 8,coef_unavailable,coef_unavailable,,coef_unavailable,coef_unavailable +util_availability_work_tours_no_usual_work_location,Unavailable: Work tours for those with no usual work location,~(workplace_zone_id > -1),coef_unavailable,coef_unavailable,,,coef_unavailable +util_availability_school_tours_no_usual_school_location,Unavailable: School tours for those with no usual school location,~(school_zone_id > -1),,,coef_unavailable,coef_unavailable,coef_unavailable diff --git a/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency.yaml b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency.yaml new file mode 100644 index 000000000..de8e115fd --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency.yaml @@ -0,0 +1,10 @@ + +SPEC: mandatory_tour_frequency.csv +COEFFICIENTS: mandatory_tour_frequency_coeffs.csv + +annotate_persons: + SPEC: annotate_persons_mtf + DF: persons + TABLES: + - tours + diff --git a/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency_alternatives.csv b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency_alternatives.csv new file mode 100644 index 000000000..025decbb1 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency_alternatives.csv @@ -0,0 +1,7 @@ +#,,alt file for building tours even though simulation is simple_simulate not interaction_simulate +alt,work,school +work1,1,0 +work2,2,0 +school1,0,1 +school2,0,2 +work_and_school,1,1 diff --git a/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency_coeffs.csv new file mode 100644 index 000000000..c0909e681 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_frequency_coeffs.csv @@ -0,0 +1,54 @@ +coefficient_name,value,constrain +coef_unavailable,-999,T +coef_ft_worker_work2_asc,-3.3781,F +coef_pt_worker_work2_asc,-3.0476,F +coef_univ_work1_asc,-2.630262534,F +coef_univ_work2_asc,-4.5,F +coef_univ_school2_asc,-3.841285259,F +coef_univ_work_and_school_asc,-4.529863127,F +coef_driving_age_child_school2_asc,-3.136,F +coef_driving_age_child_work_and_school_asc,-4.4362,F +coef_pre_driving_age_child_school2_asc,-3.9703,F +coef_female_work1,0.1737,F +coef_female_work2,-0.2255,F +coef_female_school1,0.1592,F +coef_female_school2,0.114,F +coef_female_work_and_school,-0.3442,F +coef_female_univ_work1,0.1737,F +coef_under_35_work1,-0.4629,F +coef_under_35_work2,-0.1375,F +coef_under_35_school1,0.7218,F +coef_under_35_school2,1.275,F +coef_under_35_work_and_school,0.9761,F +coef_can_walk_to_work_work2,0.5268,F +coef_can_walk_to_work_school2,0.7114,F +coef_can_walk_to_work_and_school,0.1391,F +coef_round_trip_auto_time_to_work_work2,-0.0035,F +coef_round_trip_auto_time_to_work_school2,-0.0034,F +coef_round_trip_auto_time_to_work_work_and_school,-0.0031,F +coef_student_employed,3.014,F +coef_non_student_goes_to_school,3.883,F +coef_no_cars_in_hh_work2,-1.306,F +coef_no_cars_in_hh_school2,-1.413,F +coef_no_cars_in_hh_work_and_school,-1.302,F +coef_few_cars_than_drivers_school2,-0.5759,F +coef_num_preschool_in_hh_work1,0.2191,F +coef_num_preschool_in_hh_work2,-0.1478,F +coef_num_preschool_in_hh_school1,-0.1335,F +coef_num_preschool_in_hh_school2,-0.5577,F +coef_num_preschool_in_hh_work_and_school,-0.1251,F +coef_num_non_workers_in_hh_school1,0.2574,F +coef_hh_income_gt_50k_work,-0.0528,F +coef_hh_income_gt_50k_school1,0.0347,F +coef_hh_income_gt_50k_worker_work_and_school,0.0347,F +coef_hh_income_gt_50k_student_work_and_school,-0.0528,F +coef_non_family_hh_category1,-0.25,F +coef_non_family_hh_category2,-0.1792,F +coef_num_under_16_not_at_school_work2,0.1804, +coef_num_under_16_not_at_school_school2,0.0866, +coef_num_under_16_not_at_school_work_and_school,-0.1955, +coef_home_urban_work1,-0.2831, +coef_home_urban_work2,0.2308, +coef_home_urban_school1,-0.1361, +coef_home_urban_school2,0.317, +coef_home_urban_work_and_school,-0.3509, diff --git a/activitysim/examples/prototype_mwcog/configs/mandatory_tour_scheduling.yaml b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_scheduling.yaml new file mode 100644 index 000000000..120959d36 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_scheduling.yaml @@ -0,0 +1,57 @@ + +SIMULATE_CHOOSER_COLUMNS: + - age + - female + - ptype + - is_university + - is_income_less25K + - is_income_25K_to_60K + - is_income_60K_to_120K + - is_income_greater120K + - is_pre_drive_child_in_HH + - is_non_worker_in_HH + - auto_ownership + - is_all_adults_full_time_workers + - distance_to_school + - roundtrip_auto_time_to_work + - roundtrip_auto_time_to_school + - free_parking_at_work + - workplace_zone_id + - school_zone_id + - home_zone_id + - TAZ + +LOGSUM_SETTINGS: tour_mode_choice.yaml + +TOUR_SPEC_SEGMENTS: + work: work + school: school + univ: univ + +ALTS_PREPROCESSOR: + work: + SPEC: mandatory_tour_scheduling_annotate_tours_preprocessor.csv + DF: alt_tdd + +SPEC_SEGMENTS: + work: + 'SPEC': tour_scheduling_work.csv + 'COEFFICIENTS': tour_scheduling_work_coeffs.csv + school: + 'SPEC': tour_scheduling_school.csv + 'COEFFICIENTS': tour_scheduling_school_coeffs.csv + univ: + 'SPEC': tour_scheduling_university.csv + 'COEFFICIENTS': tour_scheduling_university_coeffs.csv + +#SPEC: +# work: tour_scheduling_work.csv +# school: tour_scheduling_school.csv +# univ: tour_scheduling_university.csv + +#CHOOSER_ORIG_COL_NAME: TAZ + +DESTINATION_FOR_TOUR_PURPOSE: + work: workplace_zone_id + school: school_zone_id + univ: school_zone_id diff --git a/activitysim/examples/prototype_mwcog/configs/mandatory_tour_scheduling_annotate_tours_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_scheduling_annotate_tours_preprocessor.csv new file mode 100644 index 000000000..6c2089653 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/mandatory_tour_scheduling_annotate_tours_preprocessor.csv @@ -0,0 +1,4 @@ +Description,Target,Expression +departure_shift,departureLinearShift1,"np.minimum(9-df.start,48)*(df.start<=9) + np.minimum(df.start-9,21)*(df.start>9)" +arrival_shift,arrivalLinearShift1,"np.minimum(30-df.end,48)*(df.end<=30) + np.minimum(df.end-30,21)*(df.end>30)" +duration_shift,durationShift,"(np.minimum(21-df.duration,47)*(df.duration<=20)) + (np.minimum(df.duration-21,20)*(df.duration>21))" diff --git a/activitysim/examples/prototype_mwcog/configs/network_los.yaml b/activitysim/examples/prototype_mwcog/configs/network_los.yaml new file mode 100644 index 000000000..3e4862903 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/network_los.yaml @@ -0,0 +1,19 @@ +# read cached skims (using numpy memmap) from output directory (memmap is faster than omx ) +read_skim_cache: False +# write memmapped cached skims to output directory after reading from omx, for use in subsequent runs +write_skim_cache: False + +#alternate dir to read/write skim cache (defaults to output_dir) +#cache_dir: data/cache + +zone_system: 1 + +taz_skims: skims.omx + +skim_time_periods: + time_window: 1440 + period_minutes: 30 + periods: [0, 6, 12, 24, 32, 48] + labels: ['NT', 'AM', 'MD', 'PM', 'NT'] + +#NT is repeated twice as it's on both sides of the day. \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination.csv new file mode 100644 index 000000000..090e480b8 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination.csv @@ -0,0 +1,21 @@ +Description,Expression,escort,shopping,eatout,othmaint,social,othdiscr +local_dist,_DIST@skims['DIST'],1,1,1,1,1,1 +util_dist,@_DIST,coef_dist_escort,coef_dist_shopping,0,coef_dist_othmaint,0,coef_dist_othdiscr +util_dist_squared,"@(_DIST).clip(0,20)**2",0,coef_dist_squared_shopping,0,0,0,coef_dist_squared_othdiscr +util_dist_cubed,"@(_DIST).clip(0,20)**3",0,coef_dist_cubed_shopping,0,0,0,coef_dist_cubed_othdiscr +util_dist_squared,"@(_DIST).clip(0,15)**2",0,0,0,coef_dist_squared_othmaint,0,0 +util_dist_logged,@(_DIST).apply(np.log1p),coef_dist_logged_escort,coef_dist_logged_shopping,coef_dist_logged_eatout,coef_dist_logged_othmaint,coef_dist_logged_social,coef_dist_logged_othdiscr +util_dist_young,@(df['young']==True) * _DIST,0,coef_dist_young_shopping,coef_dist_young_eatout,coef_dist_young_othmaint,0,coef_dist_young_othdiscr +util_dist_old,@(df['old']==True) * _DIST,0,0,0,0,0,0 +util_dist_female,@(df['female']==True) * _DIST,0,coef_dist_female_shopping,0,0,coef_dist_female_social,coef_dist_female_othdiscr +util_dist_part_time,@(df['pemploy']==2) * _DIST,0,0,coef_dist_part_time_eatout,coef_dist_part_time_othmaint,0,0 +util_dist_student,@(df['is_student']==True) * _DIST,0,0,0,0,0,0 +util_dist_hh_child,@(df['hh_child']>0) * _DIST,coef_dist_hh_child_escort,0,coef_dist_hh_child_eatout,0,0,coef_dist_hh_child_othdiscr +util_dist_zero_auto,@(df['auto_ownership']==0) * _DIST,0,0,0,0,0,coef_dist_zero_auto_othdiscr +util_dist_low,@(df['income_segment']==WORK_LOW_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_med,@(df['income_segment']==WORK_MED_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_very_high,@(df['income_segment']==WORK_VERYHIGH_SEGMENT_ID) * _DIST,0,0,coef_dist_veryhigh_inc_eatout,0,coef_dist_veryhigh_inc_social,coef_dist_veryhigh_inc_othdiscr +Size variable,@df['size_term'].apply(np.log1p),1,1,1,1,1,1 +No attractions,@df['size_term']==0,-999,-999,-999,-999,-999,-999 +Mode choice logsum,mode_choice_logsum,coef_mode_logsum_escort,coef_mode_logsum_shopping,coef_mode_logsum_eatout,coef_mode_logsum_othmaint,coef_mode_logsum_social,coef_mode_logsum_othdiscr +Sample of alternatives correction factor,"@np.minimum(np.log(df.pick_count/df.prob), 60)",1,1,1,1,1,1 diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination.yaml b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination.yaml new file mode 100644 index 000000000..4f9f144a8 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination.yaml @@ -0,0 +1,79 @@ +SAMPLE_SPEC: non_mandatory_tour_destination_sample.csv +SPEC: non_mandatory_tour_destination.csv +COEFFICIENTS: non_mandatory_tour_destination_coeffs.csv + +SAMPLE_SIZE: 30 + +SIZE_TERM_SELECTOR: non_mandatory + +# we can't use use household income_segment as this will also be set for non-workers +CHOOSER_SEGMENT_COLUMN_NAME: tour_type + +# optional (comment out if not desired) +DEST_CHOICE_LOGSUM_COLUMN_NAME: destination_logsum + +# comment out DEST_CHOICE_LOGSUM_COLUMN_NAME if saved alt logsum table +DEST_CHOICE_SAMPLE_TABLE_NAME: tour_destination_sample + + +SEGMENTS: + - shopping + - othmaint + - othdiscr + - eatout + - social + - escort + +SIMULATE_CHOOSER_COLUMNS: + - tour_type + - TAZ + - person_id + - income_segment + - pemploy + - is_student + - age_0_to_5 + - age_6_to_12 + - hh_child + - young + - old + - female + - auto_ownership + +LOGSUM_SETTINGS: tour_mode_choice.yaml + +# model-specific logsum-related settings +CHOOSER_ORIG_COL_NAME: TAZ +ALT_DEST_COL_NAME: alt_dest +IN_PERIOD: + shopping: 19 + othmaint: 19 + othdiscr: 36 + eatout: 36 + social: 36 + escort: 11 +OUT_PERIOD: + shopping: 15 + othmaint: 15 + othdiscr: 31 + eatout: 31 + social: 31 + escort: 10 + +SEGMENT_IDS: + work_low: 1 + work_med: 2 + work_high: 3 + work_veryhigh: 4 + +CONSTANTS: + WORK_LOW_SEGMENT_ID: 1 + WORK_MED_SEGMENT_ID: 2 + WORK_HIGH_SEGMENT_ID: 3 + WORK_VERYHIGH_SEGMENT_ID: 4 + + +preprocessor: + SPEC: non_mandatory_tour_destination_annotate_tours_preprocessor + DF: tours + TABLES: + - persons \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination_coeffs.csv new file mode 100644 index 000000000..76136fd93 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination_coeffs.csv @@ -0,0 +1,45 @@ +coefficient_name,value,constrain +coef_mode_logsum_escort,0.676,F +coef_dist_escort,0.046736802,F +coef_dist_squared_escort,0,F +coef_dist_cubed_escort,0,F +coef_dist_logged_escort,-2.403808965,F +coef_dist_hh_child_escort,-0.078449805,F +coef_mode_logsum_shopping,0.676,F +coef_dist_shopping,-0.046575944,F +coef_dist_squared_shopping,-0.000953534,F +coef_dist_cubed_shopping,0,F +coef_dist_logged_shopping,-2.297550828,F +coef_dist_young_shopping,0.032022587,F +coef_dist_female_shopping,0.02130081,F +coef_mode_logsum_eatout,0.79,F +coef_dist_eatout,0,F +coef_dist_squared_eatout,0,F +coef_dist_cubed_eatout,0,F +coef_dist_logged_eatout,-1.904643053,F +coef_dist_young_eatout,0.023697451,F +coef_dist_part_time_eatout,0.024375725,F +coef_dist_hh_child_eatout,-0.034067726,F +coef_dist_veryhigh_inc_eatout,-0.03079323,F +coef_mode_logsum_othmaint,0.676,F +coef_dist_othmaint,-0.04955464,F +coef_dist_squared_othmaint,-0.001372519,F +coef_dist_cubed_othmaint,0,F +coef_dist_logged_othmaint,-1.270318612,F +coef_dist_part_time_othmaint,-0.01938104,F +coef_dist_young_othmaint,-0.049119954,F +coef_mode_logsum_social,0.79,F +coef_dist_social,0,F +coef_dist_logged_social,-1.408912476,F +coef_dist_female_social,-0.008330037,F +coef_dist_veryhigh_inc_social,-0.018940702,F +coef_mode_logsum_othdiscr,0.79,F +coef_dist_othdiscr,0.015757703,F +coef_dist_squared_othdiscr,-0.001806674,F +coef_dist_cubed_othdiscr,0,F +coef_dist_logged_othdiscr,-1.688427559,F +coef_dist_young_othdiscr,0.023693922,F +coef_dist_female_othdiscr,-0.008809842,F +coef_dist_hh_child_othdiscr,-0.016829222,F +coef_dist_zero_auto_othdiscr,0.065231488,F +coef_dist_veryhigh_inc_othdiscr,-0.008247062,F diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination_sample.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination_sample.csv new file mode 100644 index 000000000..33d3f6f4e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_destination_sample.csv @@ -0,0 +1,19 @@ +Description,Expression,escort,shopping,eatout,othmaint,social,othdiscr +local_dist,_DIST@skims['DIST'],1,1,1,1,1,1 +util_dist,@_DIST,coef_dist_escort,coef_dist_shopping,0,coef_dist_othmaint,0,coef_dist_othdiscr +util_dist_squared,"@(_DIST).clip(0,20)**2",0,coef_dist_squared_shopping,0,0,0,coef_dist_squared_othdiscr +util_dist_cubed,"@(_DIST).clip(0,20)**3",0,coef_dist_cubed_shopping,0,0,0,coef_dist_cubed_othdiscr +util_dist_squared,"@(_DIST).clip(0,15)**2",0,0,0,coef_dist_squared_othmaint,0,0 +util_dist_logged,@(_DIST).apply(np.log1p),coef_dist_logged_escort,coef_dist_logged_shopping,coef_dist_logged_eatout,coef_dist_logged_othmaint,coef_dist_logged_social,coef_dist_logged_othdiscr +util_dist_young,@(df['young']==True) * _DIST,0,coef_dist_young_shopping,coef_dist_young_eatout,coef_dist_young_othmaint,0,coef_dist_young_othdiscr +util_dist_old,@(df['old']==True) * _DIST,0,0,0,0,0,0 +util_dist_female,@(df['female']==True) * _DIST,0,coef_dist_female_shopping,0,0,coef_dist_female_social,coef_dist_female_othdiscr +util_dist_part_time,@(df['pemploy']==2) * _DIST,0,0,coef_dist_part_time_eatout,coef_dist_part_time_othmaint,0,0 +util_dist_student,@(df['is_student']==True) * _DIST,0,0,0,0,0,0 +util_dist_hh_child,@(df['hh_child']>0) * _DIST,coef_dist_hh_child_escort,0,coef_dist_hh_child_eatout,0,0,coef_dist_hh_child_othdiscr +util_dist_zero_auto,@(df['auto_ownership']==0) * _DIST,0,0,0,0,0,coef_dist_zero_auto_othdiscr +util_dist_low,@(df['income_segment']==WORK_LOW_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_med,@(df['income_segment']==WORK_MED_SEGMENT_ID) * _DIST,0,0,0,0,0,0 +util_dist_very_high,@(df['income_segment']==WORK_VERYHIGH_SEGMENT_ID) * _DIST,0,0,coef_dist_veryhigh_inc_eatout,0,coef_dist_veryhigh_inc_social,coef_dist_veryhigh_inc_othdiscr +Size variable,@df['size_term'].apply(np.log1p),1,1,1,1,1,1 +No attractions,@df['size_term']==0,-999,-999,-999,-999,-999,-999 diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency.csv new file mode 100644 index 000000000..6abd71a70 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency.csv @@ -0,0 +1,223 @@ +Label,Description,Expression,PTYPE_FULL,PTYPE_PART,PTYPE_UNIVERSITY,PTYPE_NONWORK,PTYPE_RETIRED,PTYPE_DRIVING,PTYPE_SCHOOL,PTYPE_PRESCHOOL +util_escorting_tour,Escorting Tour,escort,coef_escorting_tour,coef_escorting_tour,coef_escorting_tour,coef_escorting_tour,coef_escorting_tour,coef_escorting_tour,coef_escorting_tour,coef_escorting_tour +util_discretionary_tour,Discretionary Tour,othdiscr,coef_discretionary_tour,coef_discretionary_tour,coef_discretionary_tour,coef_discretionary_tour,coef_discretionary_tour,coef_discretionary_tour,coef_discretionary_tour,coef_discretionary_tour +util_shopping_tour,Shopping Tour,shopping,coef_shopping_tour,coef_shopping_tour,coef_shopping_tour,coef_shopping_tour,coef_shopping_tour,coef_shopping_tour,coef_shopping_tour,coef_shopping_tour +util_maintenance_tour,Maintenance Tour,othmaint,coef_maintenance_tour,coef_maintenance_tour,coef_maintenance_tour,coef_maintenance_tour,coef_maintenance_tour,coef_maintenance_tour,coef_maintenance_tour,coef_maintenance_tour +util_visiting_or_social_tour,Visiting/Social Tour,social,coef_visiting_or_social_tour,coef_visiting_or_social_tour,coef_visiting_or_social_tour,coef_visiting_or_social_tour,coef_visiting_or_social_tour,coef_visiting_or_social_tour,coef_visiting_or_social_tour,coef_visiting_or_social_tour +util_eating_out_tour,Eating Out Tour,eatout,coef_eating_out_tour,coef_eating_out_tour,coef_eating_out_tour,coef_eating_out_tour,coef_eating_out_tour,coef_eating_out_tour,coef_eating_out_tour,coef_eating_out_tour +util_total_number_of_tours_is_0_no_prior_tours,Total Number of Tours = 0 (No Prior Tours),(tot_tours == 0) & (num_mand == 0) & (num_hh_joint_tours == 0),coef_total_number_of_tours_is_0_no_prior_tours,coef_total_number_of_tours_is_0_no_prior_tours,coef_total_number_of_tours_is_0_no_prior_tours,coef_total_number_of_tours_is_0_no_prior_tours,coef_total_number_of_tours_is_0_no_prior_tours,coef_total_number_of_tours_is_0_no_prior_tours,coef_total_number_of_tours_is_0_no_prior_tours,coef_total_number_of_tours_is_0_no_prior_tours +util_total_number_of_tours_is_0_prior_tours,Total Number of Tours = 0 (1 or more Prior Tours),(tot_tours == 0) & ((num_mand > 0) | (num_hh_joint_tours > 0)),coef_total_number_of_tours_is_0_prior_tours,coef_total_number_of_tours_is_0_prior_tours,coef_total_number_of_tours_is_0_prior_tours,coef_total_number_of_tours_is_0_prior_tours,coef_total_number_of_tours_is_0_prior_tours,coef_total_number_of_tours_is_0_prior_tours,coef_total_number_of_tours_is_0_prior_tours,coef_total_number_of_tours_is_0_prior_tours +util_total_number_of_tours_is_1,Total Number of Tours = 1,tot_tours == 1,coef_total_number_of_tours_is_1,coef_total_number_of_tours_is_1,coef_total_number_of_tours_is_1,coef_total_number_of_tours_is_1,coef_total_number_of_tours_is_1,coef_total_number_of_tours_is_1,coef_total_number_of_tours_is_1,coef_total_number_of_tours_is_1 +util_total_number_of_tours_is_2,Total Number of Tours = 2,tot_tours == 2,coef_total_number_of_tours_is_2,coef_total_number_of_tours_is_2,coef_total_number_of_tours_is_2,coef_total_number_of_tours_is_2,coef_total_number_of_tours_is_2,coef_total_number_of_tours_is_2,coef_total_number_of_tours_is_2,coef_total_number_of_tours_is_2 +util_total_number_of_tours_is_3,Total Number of Tours = 3,tot_tours == 3,coef_total_number_of_tours_is_3,coef_total_number_of_tours_is_3,coef_total_number_of_tours_is_3,coef_total_number_of_tours_is_3,coef_total_number_of_tours_is_3,coef_total_number_of_tours_is_3,coef_total_number_of_tours_is_3,coef_total_number_of_tours_is_3 +util_total_number_of_tours_is_4,Total Number of Tours = 4,tot_tours == 4,coef_total_number_of_tours_is_4,coef_total_number_of_tours_is_4,coef_total_number_of_tours_is_4,coef_total_number_of_tours_is_4,coef_total_number_of_tours_is_4,coef_total_number_of_tours_is_4,coef_total_number_of_tours_is_4,coef_total_number_of_tours_is_4 +util_total_number_of_tours_is_5,Total Number of Tours = 5,tot_tours == 5,coef_total_number_of_tours_is_5,coef_total_number_of_tours_is_5,coef_total_number_of_tours_is_5,coef_total_number_of_tours_is_5,coef_total_number_of_tours_is_5,coef_total_number_of_tours_is_5,coef_total_number_of_tours_is_5,coef_total_number_of_tours_is_5 +util_total_number_of_tours_is_6_plus,Total Number of Tours = 6+,tot_tours > 5,coef_total_number_of_tours_is_6_plus,coef_total_number_of_tours_is_6_plus,coef_total_number_of_tours_is_6_plus,coef_total_number_of_tours_is_6_plus,coef_total_number_of_tours_is_6_plus,coef_total_number_of_tours_is_6_plus,coef_total_number_of_tours_is_6_plus,coef_total_number_of_tours_is_6_plus +util_number_of_mandatory_tours_and_tour_frequency_is_0,Number of Mandatory tours & tour frequency =0,num_mand*(tot_tours == 0),coef_number_of_mandatory_tours_and_tour_frequency_is_0,coef_number_of_mandatory_tours_and_tour_frequency_is_0,coef_number_of_mandatory_tours_and_tour_frequency_is_0,coef_number_of_mandatory_tours_and_tour_frequency_is_0,coef_number_of_mandatory_tours_and_tour_frequency_is_0,coef_number_of_mandatory_tours_and_tour_frequency_is_0,coef_number_of_mandatory_tours_and_tour_frequency_is_0,coef_number_of_mandatory_tours_and_tour_frequency_is_0 +util_number_of_mandatory_tours_and_tour_frequency_is_1,Number of Mandatory tours & tour frequency =1,num_mand*(tot_tours == 1),coef_number_of_mandatory_tours_and_tour_frequency_is_1,coef_number_of_mandatory_tours_and_tour_frequency_is_1,coef_number_of_mandatory_tours_and_tour_frequency_is_1,coef_number_of_mandatory_tours_and_tour_frequency_is_1,coef_number_of_mandatory_tours_and_tour_frequency_is_1,coef_number_of_mandatory_tours_and_tour_frequency_is_1,coef_number_of_mandatory_tours_and_tour_frequency_is_1,coef_number_of_mandatory_tours_and_tour_frequency_is_1 +util_number_of_mandatory_tours_and_tour_frequency_is_2,Number of Mandatory tours & tour frequency =2,num_mand*(tot_tours == 2),coef_number_of_mandatory_tours_and_tour_frequency_is_2,coef_number_of_mandatory_tours_and_tour_frequency_is_2,coef_number_of_mandatory_tours_and_tour_frequency_is_2,coef_number_of_mandatory_tours_and_tour_frequency_is_2,coef_number_of_mandatory_tours_and_tour_frequency_is_2,coef_number_of_mandatory_tours_and_tour_frequency_is_2,coef_number_of_mandatory_tours_and_tour_frequency_is_2,coef_number_of_mandatory_tours_and_tour_frequency_is_2 +util_number_of_mandatory_tours_and_tour_frequency_is_3,Number of Mandatory tours & tour frequency =3,num_mand*(tot_tours == 3),coef_number_of_mandatory_tours_and_tour_frequency_is_3,coef_number_of_mandatory_tours_and_tour_frequency_is_3,coef_number_of_mandatory_tours_and_tour_frequency_is_3,coef_number_of_mandatory_tours_and_tour_frequency_is_3,coef_number_of_mandatory_tours_and_tour_frequency_is_3,coef_number_of_mandatory_tours_and_tour_frequency_is_3,coef_number_of_mandatory_tours_and_tour_frequency_is_3,coef_number_of_mandatory_tours_and_tour_frequency_is_3 +util_number_of_mandatory_tours_and_tour_frequency_is_4,Number of Mandatory tours & tour frequency =4,num_mand*(tot_tours == 4),coef_number_of_mandatory_tours_and_tour_frequency_is_4,coef_number_of_mandatory_tours_and_tour_frequency_is_4,coef_number_of_mandatory_tours_and_tour_frequency_is_4,coef_number_of_mandatory_tours_and_tour_frequency_is_4,coef_number_of_mandatory_tours_and_tour_frequency_is_4,coef_number_of_mandatory_tours_and_tour_frequency_is_4,coef_number_of_mandatory_tours_and_tour_frequency_is_4,coef_number_of_mandatory_tours_and_tour_frequency_is_4 +util_number_of_mandatory_tours_and_tour_frequency_is_5_plus,Number of Mandatory tours & tour frequency = 5+,num_mand*(tot_tours > 4),coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus +util_number_of_joint_tours_and_tour_frequency_is_0,Number of Joint tours & tour frequency =0,num_hh_joint_tours*(tot_tours == 0),coef_number_of_joint_tours_and_tour_frequency_is_0,coef_number_of_joint_tours_and_tour_frequency_is_0,coef_number_of_joint_tours_and_tour_frequency_is_0,coef_number_of_joint_tours_and_tour_frequency_is_0,coef_number_of_joint_tours_and_tour_frequency_is_0,coef_number_of_joint_tours_and_tour_frequency_is_0,coef_number_of_joint_tours_and_tour_frequency_is_0,coef_number_of_joint_tours_and_tour_frequency_is_0 +util_number_of_joint_tours_and_tour_frequency_is_1,Number of Joint tours & tour frequency =1,num_hh_joint_tours*(tot_tours == 1),coef_number_of_joint_tours_and_tour_frequency_is_1,coef_number_of_joint_tours_and_tour_frequency_is_1,coef_number_of_joint_tours_and_tour_frequency_is_1,coef_number_of_joint_tours_and_tour_frequency_is_1,coef_number_of_joint_tours_and_tour_frequency_is_1,coef_number_of_joint_tours_and_tour_frequency_is_1,coef_number_of_joint_tours_and_tour_frequency_is_1,coef_number_of_joint_tours_and_tour_frequency_is_1 +util_number_of_joint_tours_and_tour_frequency_is_2,Number of Joint tours & tour frequency =2,num_hh_joint_tours*(tot_tours == 2),coef_number_of_joint_tours_and_tour_frequency_is_2,coef_number_of_joint_tours_and_tour_frequency_is_2,coef_number_of_joint_tours_and_tour_frequency_is_2,coef_number_of_joint_tours_and_tour_frequency_is_2,coef_number_of_joint_tours_and_tour_frequency_is_2,coef_number_of_joint_tours_and_tour_frequency_is_2,coef_number_of_joint_tours_and_tour_frequency_is_2,coef_number_of_joint_tours_and_tour_frequency_is_2 +util_number_of_joint_tours_and_tour_frequency_is_3,Number of Joint tours & tour frequency =3,num_hh_joint_tours*(tot_tours == 3),coef_number_of_joint_tours_and_tour_frequency_is_3,coef_number_of_joint_tours_and_tour_frequency_is_3,coef_number_of_joint_tours_and_tour_frequency_is_3,coef_number_of_joint_tours_and_tour_frequency_is_3,coef_number_of_joint_tours_and_tour_frequency_is_3,coef_number_of_joint_tours_and_tour_frequency_is_3,coef_number_of_joint_tours_and_tour_frequency_is_3,coef_number_of_joint_tours_and_tour_frequency_is_3 +util_number_of_joint_tours_and_tour_frequency_is_4,Number of Joint tours & tour frequency =4,num_hh_joint_tours*(tot_tours == 4),coef_number_of_joint_tours_and_tour_frequency_is_4,coef_number_of_joint_tours_and_tour_frequency_is_4,coef_number_of_joint_tours_and_tour_frequency_is_4,coef_number_of_joint_tours_and_tour_frequency_is_4,coef_number_of_joint_tours_and_tour_frequency_is_4,coef_number_of_joint_tours_and_tour_frequency_is_4,coef_number_of_joint_tours_and_tour_frequency_is_4,coef_number_of_joint_tours_and_tour_frequency_is_4 +util_number_of_joint_tours_and_tour_frequency_is_5_plus,Number of Joint tours & tour frequency = 5+,num_hh_joint_tours*(tot_tours > 4),coef_number_of_joint_tours_and_tour_frequency_is_5_plus,coef_number_of_joint_tours_and_tour_frequency_is_5_plus,coef_number_of_joint_tours_and_tour_frequency_is_5_plus,coef_number_of_joint_tours_and_tour_frequency_is_5_plus,coef_number_of_joint_tours_and_tour_frequency_is_5_plus,coef_number_of_joint_tours_and_tour_frequency_is_5_plus,coef_number_of_joint_tours_and_tour_frequency_is_5_plus,coef_number_of_joint_tours_and_tour_frequency_is_5_plus +util_number_of_joint_shopping_tours,Number of Joint Shopping tours,shopping * num_hh_joint_shop_tours,coef_number_of_joint_shopping_tours,coef_number_of_joint_shopping_tours,coef_number_of_joint_shopping_tours,coef_number_of_joint_shopping_tours,coef_number_of_joint_shopping_tours,coef_number_of_joint_shopping_tours,coef_number_of_joint_shopping_tours,coef_number_of_joint_shopping_tours +util_number_of_joint_maintenance_tours,Number of Joint Maintenance tours,othmaint * num_hh_joint_maint_tours,coef_number_of_joint_maintenance_tours,coef_number_of_joint_maintenance_tours,coef_number_of_joint_maintenance_tours,coef_number_of_joint_maintenance_tours,coef_number_of_joint_maintenance_tours,coef_number_of_joint_maintenance_tours,coef_number_of_joint_maintenance_tours,coef_number_of_joint_maintenance_tours +util_number_of_joint_eating_out_tours,Number of Joint Eating Out tours,eatout * num_hh_joint_eatout_tours,coef_number_of_joint_eating_out_tours,coef_number_of_joint_eating_out_tours,coef_number_of_joint_eating_out_tours,coef_number_of_joint_eating_out_tours,coef_number_of_joint_eating_out_tours,coef_number_of_joint_eating_out_tours,coef_number_of_joint_eating_out_tours,coef_number_of_joint_eating_out_tours +util_number_of_joint_visit_tours,Number of Joint Visit tours,social * num_hh_joint_social_tours,coef_number_of_joint_visit_tours,coef_number_of_joint_visit_tours,coef_number_of_joint_visit_tours,coef_number_of_joint_visit_tours,coef_number_of_joint_visit_tours,coef_number_of_joint_visit_tours,coef_number_of_joint_visit_tours,coef_number_of_joint_visit_tours +util_number_of_joint_discretionary_tours,Number of Joint Discretionary tours,othdiscr * num_hh_joint_othdiscr_tours,coef_number_of_joint_discretionary_tours,coef_number_of_joint_discretionary_tours,coef_number_of_joint_discretionary_tours,coef_number_of_joint_discretionary_tours,coef_number_of_joint_discretionary_tours,coef_number_of_joint_discretionary_tours,coef_number_of_joint_discretionary_tours,coef_number_of_joint_discretionary_tours +util_logged_maximum_residual_window_tour_frequency_is_0,"Logged Maximum Residual Window, tour frequency =0",((num_mand > 0) | (num_hh_joint_tours > 0)) * log_max_window*(tot_tours == 0),coef_logged_maximum_residual_window_tour_frequency_is_0,coef_logged_maximum_residual_window_tour_frequency_is_0,coef_logged_maximum_residual_window_tour_frequency_is_0,coef_logged_maximum_residual_window_tour_frequency_is_0,coef_logged_maximum_residual_window_tour_frequency_is_0,coef_logged_maximum_residual_window_tour_frequency_is_0,coef_logged_maximum_residual_window_tour_frequency_is_0,coef_logged_maximum_residual_window_tour_frequency_is_0 +util_logged_maximum_residual_window_tour_frequency_is_1,"Logged Maximum Residual Window, tour frequency =1",((num_mand > 0) | (num_hh_joint_tours > 0)) * log_max_window*(tot_tours == 1),coef_logged_maximum_residual_window_tour_frequency_is_1,coef_logged_maximum_residual_window_tour_frequency_is_1,coef_logged_maximum_residual_window_tour_frequency_is_1,coef_logged_maximum_residual_window_tour_frequency_is_1,coef_logged_maximum_residual_window_tour_frequency_is_1,coef_logged_maximum_residual_window_tour_frequency_is_1,coef_logged_maximum_residual_window_tour_frequency_is_1,coef_logged_maximum_residual_window_tour_frequency_is_1 +util_logged_maximum_residual_window_tour_frequency_is_2,"Logged Maximum Residual Window, tour frequency =2",((num_mand > 0) | (num_hh_joint_tours > 0)) * log_max_window*(tot_tours == 2),coef_logged_maximum_residual_window_tour_frequency_is_2,coef_logged_maximum_residual_window_tour_frequency_is_2,coef_logged_maximum_residual_window_tour_frequency_is_2,coef_logged_maximum_residual_window_tour_frequency_is_2,coef_logged_maximum_residual_window_tour_frequency_is_2,coef_logged_maximum_residual_window_tour_frequency_is_2,coef_logged_maximum_residual_window_tour_frequency_is_2,coef_logged_maximum_residual_window_tour_frequency_is_2 +util_logged_maximum_residual_window_tour_frequency_is_3,"Logged Maximum Residual Window, tour frequency =3",((num_mand > 0) | (num_hh_joint_tours > 0)) * log_max_window*(tot_tours == 3),coef_logged_maximum_residual_window_tour_frequency_is_3,coef_logged_maximum_residual_window_tour_frequency_is_3,coef_logged_maximum_residual_window_tour_frequency_is_3,coef_logged_maximum_residual_window_tour_frequency_is_3,coef_logged_maximum_residual_window_tour_frequency_is_3,coef_logged_maximum_residual_window_tour_frequency_is_3,coef_logged_maximum_residual_window_tour_frequency_is_3,coef_logged_maximum_residual_window_tour_frequency_is_3 +util_logged_maximum_residual_window_tour_frequency_is_4,"Logged Maximum Residual Window, tour frequency =4",((num_mand > 0) | (num_hh_joint_tours > 0)) * log_max_window*(tot_tours == 4),coef_logged_maximum_residual_window_tour_frequency_is_4,coef_logged_maximum_residual_window_tour_frequency_is_4,coef_logged_maximum_residual_window_tour_frequency_is_4,coef_logged_maximum_residual_window_tour_frequency_is_4,coef_logged_maximum_residual_window_tour_frequency_is_4,coef_logged_maximum_residual_window_tour_frequency_is_4,coef_logged_maximum_residual_window_tour_frequency_is_4,coef_logged_maximum_residual_window_tour_frequency_is_4 +util_logged_maximum_residual_window_tour_frequency_is_5_plus,"Logged Maximum Residual Window, tour frequency =5+",((num_mand > 0) | (num_hh_joint_tours > 0)) * log_max_window*(tot_tours > 4),coef_logged_maximum_residual_window_tour_frequency_is_5_plus,coef_logged_maximum_residual_window_tour_frequency_is_5_plus,coef_logged_maximum_residual_window_tour_frequency_is_5_plus,coef_logged_maximum_residual_window_tour_frequency_is_5_plus,coef_logged_maximum_residual_window_tour_frequency_is_5_plus,coef_logged_maximum_residual_window_tour_frequency_is_5_plus,coef_logged_maximum_residual_window_tour_frequency_is_5_plus,coef_logged_maximum_residual_window_tour_frequency_is_5_plus +util_mediumlow_income_group_and_tour_frequency_is_1,Dummy for Mediumlow Income group (20K-50K) & tour frequency=1,medium_low_income & (tot_tours == 1),coef_mediumlow_income_group_and_tour_frequency_is_1,coef_mediumlow_income_group_and_tour_frequency_is_1,coef_mediumlow_income_group_and_tour_frequency_is_1,coef_mediumlow_income_group_and_tour_frequency_is_1,coef_mediumlow_income_group_and_tour_frequency_is_1,coef_mediumlow_income_group_and_tour_frequency_is_1,coef_mediumlow_income_group_and_tour_frequency_is_1,coef_mediumlow_income_group_and_tour_frequency_is_1 +util_mediumlow_income_group_and_tour_frequency_is_2,Dummy for Mediumlow Income group (20K-50K) & tour frequency=2,medium_low_income & (tot_tours == 2),coef_mediumlow_income_group_and_tour_frequency_is_2,coef_mediumlow_income_group_and_tour_frequency_is_2,coef_mediumlow_income_group_and_tour_frequency_is_2,coef_mediumlow_income_group_and_tour_frequency_is_2,coef_mediumlow_income_group_and_tour_frequency_is_2,coef_mediumlow_income_group_and_tour_frequency_is_2,coef_mediumlow_income_group_and_tour_frequency_is_2,coef_mediumlow_income_group_and_tour_frequency_is_2 +util_mediumlow_income_group_and_tour_frequency_is_3,Dummy for Mediumlow Income group (20K-50K) & tour frequency=3,medium_low_income & (tot_tours == 3),coef_mediumlow_income_group_and_tour_frequency_is_3,coef_mediumlow_income_group_and_tour_frequency_is_3,coef_mediumlow_income_group_and_tour_frequency_is_3,coef_mediumlow_income_group_and_tour_frequency_is_3,coef_mediumlow_income_group_and_tour_frequency_is_3,coef_mediumlow_income_group_and_tour_frequency_is_3,coef_mediumlow_income_group_and_tour_frequency_is_3,coef_mediumlow_income_group_and_tour_frequency_is_3 +util_mediumlow_income_group_and_tour_frequency_is_4,Dummy for Mediumlow Income group (20K-50K) & tour frequency=4,medium_low_income & (tot_tours == 4),coef_mediumlow_income_group_and_tour_frequency_is_4,coef_mediumlow_income_group_and_tour_frequency_is_4,coef_mediumlow_income_group_and_tour_frequency_is_4,coef_mediumlow_income_group_and_tour_frequency_is_4,coef_mediumlow_income_group_and_tour_frequency_is_4,coef_mediumlow_income_group_and_tour_frequency_is_4,coef_mediumlow_income_group_and_tour_frequency_is_4,coef_mediumlow_income_group_and_tour_frequency_is_4 +util_mediumlow_income_group_and_tour_frequency_is_5_plus,Dummy for Mediumlow Income group (20K-50K) & tour frequency=5+,medium_low_income & (tot_tours > 4),coef_mediumlow_income_group_and_tour_frequency_is_5_plus,coef_mediumlow_income_group_and_tour_frequency_is_5_plus,coef_mediumlow_income_group_and_tour_frequency_is_5_plus,coef_mediumlow_income_group_and_tour_frequency_is_5_plus,coef_mediumlow_income_group_and_tour_frequency_is_5_plus,coef_mediumlow_income_group_and_tour_frequency_is_5_plus,coef_mediumlow_income_group_and_tour_frequency_is_5_plus,coef_mediumlow_income_group_and_tour_frequency_is_5_plus +util_mediumhigh_income_group_and_tour_frequency_is_1,Dummy for MediumHigh Income group (50K-100K) & tour frequency=1,medium_high_income & (tot_tours == 1),coef_mediumhigh_income_group_and_tour_frequency_is_1,coef_mediumhigh_income_group_and_tour_frequency_is_1,coef_mediumhigh_income_group_and_tour_frequency_is_1,coef_mediumhigh_income_group_and_tour_frequency_is_1,coef_mediumhigh_income_group_and_tour_frequency_is_1,coef_mediumhigh_income_group_and_tour_frequency_is_1,coef_mediumhigh_income_group_and_tour_frequency_is_1,coef_mediumhigh_income_group_and_tour_frequency_is_1 +util_mediumhigh_income_group_and_tour_frequency_is_2,Dummy for MediumHigh Income group (50K-100K) & tour frequency=2,medium_high_income & (tot_tours == 2),coef_mediumhigh_income_group_and_tour_frequency_is_2,coef_mediumhigh_income_group_and_tour_frequency_is_2,coef_mediumhigh_income_group_and_tour_frequency_is_2,coef_mediumhigh_income_group_and_tour_frequency_is_2,coef_mediumhigh_income_group_and_tour_frequency_is_2,coef_mediumhigh_income_group_and_tour_frequency_is_2,coef_mediumhigh_income_group_and_tour_frequency_is_2,coef_mediumhigh_income_group_and_tour_frequency_is_2 +util_mediumhigh_income_group_and_tour_frequency_is_3,Dummy for MediumHigh Income group (50K-100K) & tour frequency=3,medium_high_income & (tot_tours == 3),coef_mediumhigh_income_group_and_tour_frequency_is_3,coef_mediumhigh_income_group_and_tour_frequency_is_3,coef_mediumhigh_income_group_and_tour_frequency_is_3,coef_mediumhigh_income_group_and_tour_frequency_is_3,coef_mediumhigh_income_group_and_tour_frequency_is_3,coef_mediumhigh_income_group_and_tour_frequency_is_3,coef_mediumhigh_income_group_and_tour_frequency_is_3,coef_mediumhigh_income_group_and_tour_frequency_is_3 +util_mediumhigh_income_group_and_tour_frequency_is_4,Dummy for MediumHigh Income group (50K-100K) & tour frequency=4,medium_high_income & (tot_tours == 4),coef_mediumhigh_income_group_and_tour_frequency_is_4,coef_mediumhigh_income_group_and_tour_frequency_is_4,coef_mediumhigh_income_group_and_tour_frequency_is_4,coef_mediumhigh_income_group_and_tour_frequency_is_4,coef_mediumhigh_income_group_and_tour_frequency_is_4,coef_mediumhigh_income_group_and_tour_frequency_is_4,coef_mediumhigh_income_group_and_tour_frequency_is_4,coef_mediumhigh_income_group_and_tour_frequency_is_4 +util_mediumhigh_income_group_and_tour_frequency_is_5_plus,Dummy for MediumHigh Income group (50K-100K) & tour frequency=5+,medium_high_income & (tot_tours > 4),coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,coef_mediumhigh_income_group_and_tour_frequency_is_5_plus +util_high_income_group_and_tour_frequency_is_1,Dummy for High Income group (>100K) & tour frequency=1,high_income & (tot_tours == 1),coef_high_income_group_and_tour_frequency_is_1,coef_high_income_group_and_tour_frequency_is_1,coef_high_income_group_and_tour_frequency_is_1,coef_high_income_group_and_tour_frequency_is_1,coef_high_income_group_and_tour_frequency_is_1,coef_high_income_group_and_tour_frequency_is_1,coef_high_income_group_and_tour_frequency_is_1,coef_high_income_group_and_tour_frequency_is_1 +util_high_income_group_and_tour_frequency_is_2,Dummy for High Income group (>100K) & tour frequency=2,high_income & (tot_tours == 2),coef_high_income_group_and_tour_frequency_is_2,coef_high_income_group_and_tour_frequency_is_2,coef_high_income_group_and_tour_frequency_is_2,coef_high_income_group_and_tour_frequency_is_2,coef_high_income_group_and_tour_frequency_is_2,coef_high_income_group_and_tour_frequency_is_2,coef_high_income_group_and_tour_frequency_is_2,coef_high_income_group_and_tour_frequency_is_2 +util_high_income_group_and_tour_frequency_is_3,Dummy for High Income group (>100K) & tour frequency=3,high_income & (tot_tours == 3),coef_high_income_group_and_tour_frequency_is_3,coef_high_income_group_and_tour_frequency_is_3,coef_high_income_group_and_tour_frequency_is_3,coef_high_income_group_and_tour_frequency_is_3,coef_high_income_group_and_tour_frequency_is_3,coef_high_income_group_and_tour_frequency_is_3,coef_high_income_group_and_tour_frequency_is_3,coef_high_income_group_and_tour_frequency_is_3 +util_high_income_group_and_tour_frequency_is_4,Dummy for High Income group (>100K) & tour frequency=4,high_income & (tot_tours == 4),coef_high_income_group_and_tour_frequency_is_4,coef_high_income_group_and_tour_frequency_is_4,coef_high_income_group_and_tour_frequency_is_4,coef_high_income_group_and_tour_frequency_is_4,coef_high_income_group_and_tour_frequency_is_4,coef_high_income_group_and_tour_frequency_is_4,coef_high_income_group_and_tour_frequency_is_4,coef_high_income_group_and_tour_frequency_is_4 +util_high_income_group_and_tour_frequency_is_5_plus,Dummy for High Income group (>100K) & tour frequency=5+,high_income & (tot_tours > 4),coef_high_income_group_and_tour_frequency_is_5_plus,coef_high_income_group_and_tour_frequency_is_5_plus,coef_high_income_group_and_tour_frequency_is_5_plus,coef_high_income_group_and_tour_frequency_is_5_plus,coef_high_income_group_and_tour_frequency_is_5_plus,coef_high_income_group_and_tour_frequency_is_5_plus,coef_high_income_group_and_tour_frequency_is_5_plus,coef_high_income_group_and_tour_frequency_is_5_plus +util_mediumlow_income_group_and_shopping_tour,Dummy for Mediumlow Income group (20K-50K) & shopping tour,medium_low_income * shopping,coef_mediumlow_income_group_and_shopping_tour,coef_mediumlow_income_group_and_shopping_tour,coef_mediumlow_income_group_and_shopping_tour,coef_mediumlow_income_group_and_shopping_tour,coef_mediumlow_income_group_and_shopping_tour,coef_mediumlow_income_group_and_shopping_tour,coef_mediumlow_income_group_and_shopping_tour,coef_mediumlow_income_group_and_shopping_tour +util_mediumhigh_income_group_and_shopping_tour,Dummy for Mediumhigh Income group (50K-100K) & shopping tour,medium_high_income * shopping,coef_mediumhigh_income_group_and_shopping_tour,coef_mediumhigh_income_group_and_shopping_tour,coef_mediumhigh_income_group_and_shopping_tour,coef_mediumhigh_income_group_and_shopping_tour,coef_mediumhigh_income_group_and_shopping_tour,coef_mediumhigh_income_group_and_shopping_tour,coef_mediumhigh_income_group_and_shopping_tour,coef_mediumhigh_income_group_and_shopping_tour +util_high_income_group_and_shopping_tour,Dummy for High Income group (>100K) & shopping tour,high_income * shopping,coef_high_income_group_and_shopping_tour,coef_high_income_group_and_shopping_tour,coef_high_income_group_and_shopping_tour,coef_high_income_group_and_shopping_tour,coef_high_income_group_and_shopping_tour,coef_high_income_group_and_shopping_tour,coef_high_income_group_and_shopping_tour,coef_high_income_group_and_shopping_tour +util_mediumlow_income_group_and_maintenance_tour,Dummy for Mediumlow Income group (20K-50K) & maintenance tour,medium_low_income * othmaint,coef_mediumlow_income_group_and_maintenance_tour,coef_mediumlow_income_group_and_maintenance_tour,coef_mediumlow_income_group_and_maintenance_tour,coef_mediumlow_income_group_and_maintenance_tour,coef_mediumlow_income_group_and_maintenance_tour,coef_mediumlow_income_group_and_maintenance_tour,coef_mediumlow_income_group_and_maintenance_tour,coef_mediumlow_income_group_and_maintenance_tour +util_mediumhigh_income_group_and_maintenance_tour,Dummy for Mediumhigh Income group (50K-100K) & maintenance tour,medium_high_income * othmaint,coef_mediumhigh_income_group_and_maintenance_tour,coef_mediumhigh_income_group_and_maintenance_tour,coef_mediumhigh_income_group_and_maintenance_tour,coef_mediumhigh_income_group_and_maintenance_tour,coef_mediumhigh_income_group_and_maintenance_tour,coef_mediumhigh_income_group_and_maintenance_tour,coef_mediumhigh_income_group_and_maintenance_tour,coef_mediumhigh_income_group_and_maintenance_tour +util_high_income_group_and_maintenance_tour,Dummy for High Income group (>100K) & maintenance tour,high_income * othmaint,coef_high_income_group_and_maintenance_tour,coef_high_income_group_and_maintenance_tour,coef_high_income_group_and_maintenance_tour,coef_high_income_group_and_maintenance_tour,coef_high_income_group_and_maintenance_tour,coef_high_income_group_and_maintenance_tour,coef_high_income_group_and_maintenance_tour,coef_high_income_group_and_maintenance_tour +util_mediumlow_income_group_and_eating_out_tour,Dummy for Mediumlow Income group (20K-50K) & Eating out tour,medium_low_income * eatout,coef_mediumlow_income_group_and_eating_out_tour,coef_mediumlow_income_group_and_eating_out_tour,coef_mediumlow_income_group_and_eating_out_tour,coef_mediumlow_income_group_and_eating_out_tour,coef_mediumlow_income_group_and_eating_out_tour,coef_mediumlow_income_group_and_eating_out_tour,coef_mediumlow_income_group_and_eating_out_tour,coef_mediumlow_income_group_and_eating_out_tour +util_mediumhigh_income_group_and_eating_out_tour,Dummy for Mediumhigh Income group (50K-100K) & Eating out tour,medium_high_income * eatout,coef_mediumhigh_income_group_and_eating_out_tour,coef_mediumhigh_income_group_and_eating_out_tour,coef_mediumhigh_income_group_and_eating_out_tour,coef_mediumhigh_income_group_and_eating_out_tour,coef_mediumhigh_income_group_and_eating_out_tour,coef_mediumhigh_income_group_and_eating_out_tour,coef_mediumhigh_income_group_and_eating_out_tour,coef_mediumhigh_income_group_and_eating_out_tour +util_high_income_group_and_eating_out_tour,Dummy for High Income group (>100K) & Eating out tour,high_income * eatout,coef_high_income_group_and_eating_out_tour,coef_high_income_group_and_eating_out_tour,coef_high_income_group_and_eating_out_tour,coef_high_income_group_and_eating_out_tour,coef_high_income_group_and_eating_out_tour,coef_high_income_group_and_eating_out_tour,coef_high_income_group_and_eating_out_tour,coef_high_income_group_and_eating_out_tour +util_mediumlow_income_group_and_discretionary_tour,Dummy for Mediumlow Income group (20K-50K) & Discretionary tour,medium_low_income * othdiscr,coef_mediumlow_income_group_and_discretionary_tour,coef_mediumlow_income_group_and_discretionary_tour,coef_mediumlow_income_group_and_discretionary_tour,coef_mediumlow_income_group_and_discretionary_tour,coef_mediumlow_income_group_and_discretionary_tour,coef_mediumlow_income_group_and_discretionary_tour,coef_mediumlow_income_group_and_discretionary_tour,coef_mediumlow_income_group_and_discretionary_tour +util_mediumhigh_income_group_and_discretionary_tour,Dummy for Mediumhigh Income group (50K-100K) & Discretionary tour,medium_high_income * othdiscr,coef_mediumhigh_income_group_and_discretionary_tour,coef_mediumhigh_income_group_and_discretionary_tour,coef_mediumhigh_income_group_and_discretionary_tour,coef_mediumhigh_income_group_and_discretionary_tour,coef_mediumhigh_income_group_and_discretionary_tour,coef_mediumhigh_income_group_and_discretionary_tour,coef_mediumhigh_income_group_and_discretionary_tour,coef_mediumhigh_income_group_and_discretionary_tour +util_high_income_group_and_discretionary_tour,Dummy for High Income group (>100K) & Discretionary tour,high_income * othdiscr,coef_high_income_group_and_discretionary_tour,coef_high_income_group_and_discretionary_tour,coef_high_income_group_and_discretionary_tour,coef_high_income_group_and_discretionary_tour,coef_high_income_group_and_discretionary_tour,coef_high_income_group_and_discretionary_tour,coef_high_income_group_and_discretionary_tour,coef_high_income_group_and_discretionary_tour +util_mediumlow_income_group_and_visiting_tour,Dummy for Mediumlow Income group (20K-50K) & Visiting tour,medium_low_income * social,coef_mediumlow_income_group_and_visiting_tour,coef_mediumlow_income_group_and_visiting_tour,coef_mediumlow_income_group_and_visiting_tour,coef_mediumlow_income_group_and_visiting_tour,coef_mediumlow_income_group_and_visiting_tour,coef_mediumlow_income_group_and_visiting_tour,coef_mediumlow_income_group_and_visiting_tour,coef_mediumlow_income_group_and_visiting_tour +util_mediumhigh_income_group_and_visiting_tour,Dummy for Mediumhigh Income group (50K-100K) & Visiting tour,medium_high_income * social,coef_mediumhigh_income_group_and_visiting_tour,coef_mediumhigh_income_group_and_visiting_tour,coef_mediumhigh_income_group_and_visiting_tour,coef_mediumhigh_income_group_and_visiting_tour,coef_mediumhigh_income_group_and_visiting_tour,coef_mediumhigh_income_group_and_visiting_tour,coef_mediumhigh_income_group_and_visiting_tour,coef_mediumhigh_income_group_and_visiting_tour +util_high_income_group_and_visiting_tour,Dummy for High Income group (>100K) & Visiting tour,high_income * social,coef_high_income_group_and_visiting_tour,coef_high_income_group_and_visiting_tour,coef_high_income_group_and_visiting_tour,coef_high_income_group_and_visiting_tour,coef_high_income_group_and_visiting_tour,coef_high_income_group_and_visiting_tour,coef_high_income_group_and_visiting_tour,coef_high_income_group_and_visiting_tour +util_female_and_tour_frequency_is_1,Dummy for Female & tour frequency =1,female & (tot_tours == 1),coef_female_and_tour_frequency_is_1,coef_female_and_tour_frequency_is_1,coef_female_and_tour_frequency_is_1,coef_female_and_tour_frequency_is_1,coef_female_and_tour_frequency_is_1,coef_female_and_tour_frequency_is_1,coef_female_and_tour_frequency_is_1,coef_female_and_tour_frequency_is_1 +util_female_and_tour_frequency_is_2,Dummy for Female & tour frequency =2,female & (tot_tours == 2),coef_female_and_tour_frequency_is_2,coef_female_and_tour_frequency_is_2,coef_female_and_tour_frequency_is_2,coef_female_and_tour_frequency_is_2,coef_female_and_tour_frequency_is_2,coef_female_and_tour_frequency_is_2,coef_female_and_tour_frequency_is_2,coef_female_and_tour_frequency_is_2 +util_female_and_tour_frequency_is_3,Dummy for Female & tour frequency =3,female & (tot_tours == 3),coef_female_and_tour_frequency_is_3,coef_female_and_tour_frequency_is_3,coef_female_and_tour_frequency_is_3,coef_female_and_tour_frequency_is_3,coef_female_and_tour_frequency_is_3,coef_female_and_tour_frequency_is_3,coef_female_and_tour_frequency_is_3,coef_female_and_tour_frequency_is_3 +util_female_and_tour_frequency_is_4,Dummy for Female & tour frequency =4,female & (tot_tours == 4),coef_female_and_tour_frequency_is_4,coef_female_and_tour_frequency_is_4,coef_female_and_tour_frequency_is_4,coef_female_and_tour_frequency_is_4,coef_female_and_tour_frequency_is_4,coef_female_and_tour_frequency_is_4,coef_female_and_tour_frequency_is_4,coef_female_and_tour_frequency_is_4 +util_female_and_tour_frequency_is_5,Dummy for Female & tour frequency =5,female & (tot_tours == 5),coef_female_and_tour_frequency_is_5,coef_female_and_tour_frequency_is_5,coef_female_and_tour_frequency_is_5,coef_female_and_tour_frequency_is_5,coef_female_and_tour_frequency_is_5,coef_female_and_tour_frequency_is_5,coef_female_and_tour_frequency_is_5,coef_female_and_tour_frequency_is_5 +util_female_and_escorting_tour,Dummy for Female & Escorting Tour,female * escort,coef_female_and_escorting_tour,coef_female_and_escorting_tour,coef_female_and_escorting_tour,coef_female_and_escorting_tour,coef_female_and_escorting_tour,coef_female_and_escorting_tour,coef_female_and_escorting_tour,coef_female_and_escorting_tour +util_female_and_shopping_tour,Dummy for Female & Shopping Tour,female * shopping,coef_female_and_shopping_tour,coef_female_and_shopping_tour,coef_female_and_shopping_tour,coef_female_and_shopping_tour,coef_female_and_shopping_tour,coef_female_and_shopping_tour,coef_female_and_shopping_tour,coef_female_and_shopping_tour +util_female_and_maintenance_tour,Dummy for Female & Maintenance Tour,female * othmaint,coef_female_and_maintenance_tour,coef_female_and_maintenance_tour,coef_female_and_maintenance_tour,coef_female_and_maintenance_tour,coef_female_and_maintenance_tour,coef_female_and_maintenance_tour,coef_female_and_maintenance_tour,coef_female_and_maintenance_tour +util_female_and_eatingout_tour,Dummy for Female & EatingOut Tour,female * eatout,coef_female_and_eatingout_tour,coef_female_and_eatingout_tour,coef_female_and_eatingout_tour,coef_female_and_eatingout_tour,coef_female_and_eatingout_tour,coef_female_and_eatingout_tour,coef_female_and_eatingout_tour,coef_female_and_eatingout_tour +util_female_and_discretionary_tour,Dummy for Female & Discretionary Tour,female * othdiscr,coef_female_and_discretionary_tour,coef_female_and_discretionary_tour,coef_female_and_discretionary_tour,coef_female_and_discretionary_tour,coef_female_and_discretionary_tour,coef_female_and_discretionary_tour,coef_female_and_discretionary_tour,coef_female_and_discretionary_tour +util_zero_car_ownership_and_tour_frequency_is_1,Dummy for zero car ownership & tour frequency =1,no_cars & (tot_tours == 1),coef_zero_car_ownership_and_tour_frequency_is_1,coef_zero_car_ownership_and_tour_frequency_is_1,coef_zero_car_ownership_and_tour_frequency_is_1,coef_zero_car_ownership_and_tour_frequency_is_1,coef_zero_car_ownership_and_tour_frequency_is_1,coef_zero_car_ownership_and_tour_frequency_is_1,coef_zero_car_ownership_and_tour_frequency_is_1,coef_zero_car_ownership_and_tour_frequency_is_1 +util_zero_car_ownership_and_tour_frequency_is_2,Dummy for zero car ownership & tour frequency =2,no_cars & (tot_tours == 2),coef_zero_car_ownership_and_tour_frequency_is_2,coef_zero_car_ownership_and_tour_frequency_is_2,coef_zero_car_ownership_and_tour_frequency_is_2,coef_zero_car_ownership_and_tour_frequency_is_2,coef_zero_car_ownership_and_tour_frequency_is_2,coef_zero_car_ownership_and_tour_frequency_is_2,coef_zero_car_ownership_and_tour_frequency_is_2,coef_zero_car_ownership_and_tour_frequency_is_2 +util_zero_car_ownership_and_tour_frequency_is_3,Dummy for zero car ownership & tour frequency =3,no_cars & (tot_tours == 3),coef_zero_car_ownership_and_tour_frequency_is_3,coef_zero_car_ownership_and_tour_frequency_is_3,coef_zero_car_ownership_and_tour_frequency_is_3,coef_zero_car_ownership_and_tour_frequency_is_3,coef_zero_car_ownership_and_tour_frequency_is_3,coef_zero_car_ownership_and_tour_frequency_is_3,coef_zero_car_ownership_and_tour_frequency_is_3,coef_zero_car_ownership_and_tour_frequency_is_3 +util_zero_car_ownership_and_tour_frequency_is_4,Dummy for zero car ownership & tour frequency =4,no_cars & (tot_tours == 4),coef_zero_car_ownership_and_tour_frequency_is_4,coef_zero_car_ownership_and_tour_frequency_is_4,coef_zero_car_ownership_and_tour_frequency_is_4,coef_zero_car_ownership_and_tour_frequency_is_4,coef_zero_car_ownership_and_tour_frequency_is_4,coef_zero_car_ownership_and_tour_frequency_is_4,coef_zero_car_ownership_and_tour_frequency_is_4,coef_zero_car_ownership_and_tour_frequency_is_4 +util_zero_car_ownership_and_tour_frequency_is_5_plus,Dummy for zero car ownership & tour frequency =5+,no_cars & (tot_tours > 4),coef_zero_car_ownership_and_tour_frequency_is_5_plus,coef_zero_car_ownership_and_tour_frequency_is_5_plus,coef_zero_car_ownership_and_tour_frequency_is_5_plus,coef_zero_car_ownership_and_tour_frequency_is_5_plus,coef_zero_car_ownership_and_tour_frequency_is_5_plus,coef_zero_car_ownership_and_tour_frequency_is_5_plus,coef_zero_car_ownership_and_tour_frequency_is_5_plus,coef_zero_car_ownership_and_tour_frequency_is_5_plus +util_car_shortage_vs_workers_and_tour_frequency_is_1,Dummy for Car Shortage vs Workers & tour frequency =1,~no_cars & (car_sufficiency < 0) & (tot_tours == 1),coef_car_shortage_vs_workers_and_tour_frequency_is_1,coef_car_shortage_vs_workers_and_tour_frequency_is_1,coef_car_shortage_vs_workers_and_tour_frequency_is_1,coef_car_shortage_vs_workers_and_tour_frequency_is_1,coef_car_shortage_vs_workers_and_tour_frequency_is_1,coef_car_shortage_vs_workers_and_tour_frequency_is_1,coef_car_shortage_vs_workers_and_tour_frequency_is_1,coef_car_shortage_vs_workers_and_tour_frequency_is_1 +util_car_shortage_vs_workers_and_tour_frequency_is_2,Dummy for Car Shortage vs Workers & tour frequency =2,~no_cars & (car_sufficiency < 0) & (tot_tours == 2),coef_car_shortage_vs_workers_and_tour_frequency_is_2,coef_car_shortage_vs_workers_and_tour_frequency_is_2,coef_car_shortage_vs_workers_and_tour_frequency_is_2,coef_car_shortage_vs_workers_and_tour_frequency_is_2,coef_car_shortage_vs_workers_and_tour_frequency_is_2,coef_car_shortage_vs_workers_and_tour_frequency_is_2,coef_car_shortage_vs_workers_and_tour_frequency_is_2,coef_car_shortage_vs_workers_and_tour_frequency_is_2 +util_car_shortage_vs_workers_and_tour_frequency_is_3,Dummy for Car Shortage vs Workers & tour frequency =3,~no_cars & (car_sufficiency < 0) & (tot_tours == 3),coef_car_shortage_vs_workers_and_tour_frequency_is_3,coef_car_shortage_vs_workers_and_tour_frequency_is_3,coef_car_shortage_vs_workers_and_tour_frequency_is_3,coef_car_shortage_vs_workers_and_tour_frequency_is_3,coef_car_shortage_vs_workers_and_tour_frequency_is_3,coef_car_shortage_vs_workers_and_tour_frequency_is_3,coef_car_shortage_vs_workers_and_tour_frequency_is_3,coef_car_shortage_vs_workers_and_tour_frequency_is_3 +util_car_shortage_vs_workers_and_tour_frequency_is_4,Dummy for Car Shortage vs Workers & tour frequency =4,~no_cars & (car_sufficiency < 0) & (tot_tours == 4),coef_car_shortage_vs_workers_and_tour_frequency_is_4,coef_car_shortage_vs_workers_and_tour_frequency_is_4,coef_car_shortage_vs_workers_and_tour_frequency_is_4,coef_car_shortage_vs_workers_and_tour_frequency_is_4,coef_car_shortage_vs_workers_and_tour_frequency_is_4,coef_car_shortage_vs_workers_and_tour_frequency_is_4,coef_car_shortage_vs_workers_and_tour_frequency_is_4,coef_car_shortage_vs_workers_and_tour_frequency_is_4 +util_car_shortage_vs_workers_and_tour_frequency_is_5_plus,Dummy for Car Shortage vs Workers & tour frequency =5+,~no_cars & (car_sufficiency < 0) & (tot_tours > 4),coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus +util_car_surplus_vs_workers_and_tour_frequency_is_1,Dummy for Car Surplus vs Workers & tour frequency =1,~no_cars & (car_sufficiency > 0) & (tot_tours == 1),coef_car_surplus_vs_workers_and_tour_frequency_is_1,coef_car_surplus_vs_workers_and_tour_frequency_is_1,coef_car_surplus_vs_workers_and_tour_frequency_is_1,coef_car_surplus_vs_workers_and_tour_frequency_is_1,coef_car_surplus_vs_workers_and_tour_frequency_is_1,coef_car_surplus_vs_workers_and_tour_frequency_is_1,coef_car_surplus_vs_workers_and_tour_frequency_is_1,coef_car_surplus_vs_workers_and_tour_frequency_is_1 +util_car_surplus_vs_workers_and_tour_frequency_is_2,Dummy for Car Surplus vs Workers & tour frequency =2,~no_cars & (car_sufficiency > 0) & (tot_tours == 2),coef_car_surplus_vs_workers_and_tour_frequency_is_2,coef_car_surplus_vs_workers_and_tour_frequency_is_2,coef_car_surplus_vs_workers_and_tour_frequency_is_2,coef_car_surplus_vs_workers_and_tour_frequency_is_2,coef_car_surplus_vs_workers_and_tour_frequency_is_2,coef_car_surplus_vs_workers_and_tour_frequency_is_2,coef_car_surplus_vs_workers_and_tour_frequency_is_2,coef_car_surplus_vs_workers_and_tour_frequency_is_2 +util_car_surplus_vs_workers_and_tour_frequency_is_3,Dummy for Car Surplus vs Workers & tour frequency =3,~no_cars & (car_sufficiency > 0) & (tot_tours == 3),coef_car_surplus_vs_workers_and_tour_frequency_is_3,coef_car_surplus_vs_workers_and_tour_frequency_is_3,coef_car_surplus_vs_workers_and_tour_frequency_is_3,coef_car_surplus_vs_workers_and_tour_frequency_is_3,coef_car_surplus_vs_workers_and_tour_frequency_is_3,coef_car_surplus_vs_workers_and_tour_frequency_is_3,coef_car_surplus_vs_workers_and_tour_frequency_is_3,coef_car_surplus_vs_workers_and_tour_frequency_is_3 +util_car_surplus_vs_workers_and_tour_frequency_is_4,Dummy for Car Surplus vs Workers & tour frequency =4,~no_cars & (car_sufficiency > 0) & (tot_tours == 4),coef_car_surplus_vs_workers_and_tour_frequency_is_4,coef_car_surplus_vs_workers_and_tour_frequency_is_4,coef_car_surplus_vs_workers_and_tour_frequency_is_4,coef_car_surplus_vs_workers_and_tour_frequency_is_4,coef_car_surplus_vs_workers_and_tour_frequency_is_4,coef_car_surplus_vs_workers_and_tour_frequency_is_4,coef_car_surplus_vs_workers_and_tour_frequency_is_4,coef_car_surplus_vs_workers_and_tour_frequency_is_4 +util_car_surplus_vs_workers_and_tour_frequency_is_5_plus,Dummy for Car Surplus vs Workers & tour frequency =5+,~no_cars & (car_sufficiency > 0) & (tot_tours > 4),coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus +util_presence_of_non_worker_and_tour_frequency_is_1,Dummy for Presence of Non-Worker(other than modeled person) & tour frequency =1,has_non_worker & (tot_tours == 1),coef_presence_of_non_worker_and_tour_frequency_is_1,coef_presence_of_non_worker_and_tour_frequency_is_1,coef_presence_of_non_worker_and_tour_frequency_is_1,coef_presence_of_non_worker_and_tour_frequency_is_1,coef_presence_of_non_worker_and_tour_frequency_is_1,coef_presence_of_non_worker_and_tour_frequency_is_1,coef_presence_of_non_worker_and_tour_frequency_is_1,coef_presence_of_non_worker_and_tour_frequency_is_1 +util_presence_of_non_worker_and_tour_frequency_is_2,Dummy for Presence of Non-Worker(other than modeled person) & tour frequency =2,has_non_worker & (tot_tours == 2),coef_presence_of_non_worker_and_tour_frequency_is_2,coef_presence_of_non_worker_and_tour_frequency_is_2,coef_presence_of_non_worker_and_tour_frequency_is_2,coef_presence_of_non_worker_and_tour_frequency_is_2,coef_presence_of_non_worker_and_tour_frequency_is_2,coef_presence_of_non_worker_and_tour_frequency_is_2,coef_presence_of_non_worker_and_tour_frequency_is_2,coef_presence_of_non_worker_and_tour_frequency_is_2 +util_presence_of_non_worker_and_tour_frequency_is_3,Dummy for Presence of Non-Worker(other than modeled person) & tour frequency =3,has_non_worker & (tot_tours == 3),coef_presence_of_non_worker_and_tour_frequency_is_3,coef_presence_of_non_worker_and_tour_frequency_is_3,coef_presence_of_non_worker_and_tour_frequency_is_3,coef_presence_of_non_worker_and_tour_frequency_is_3,coef_presence_of_non_worker_and_tour_frequency_is_3,coef_presence_of_non_worker_and_tour_frequency_is_3,coef_presence_of_non_worker_and_tour_frequency_is_3,coef_presence_of_non_worker_and_tour_frequency_is_3 +util_presence_of_non_worker_and_tour_frequency_is_4,Dummy for Presence of Non-Worker(other than modeled person) & tour frequency =4,has_non_worker & (tot_tours == 4),coef_presence_of_non_worker_and_tour_frequency_is_4,coef_presence_of_non_worker_and_tour_frequency_is_4,coef_presence_of_non_worker_and_tour_frequency_is_4,coef_presence_of_non_worker_and_tour_frequency_is_4,coef_presence_of_non_worker_and_tour_frequency_is_4,coef_presence_of_non_worker_and_tour_frequency_is_4,coef_presence_of_non_worker_and_tour_frequency_is_4,coef_presence_of_non_worker_and_tour_frequency_is_4 +util_presence_of_non_worker_and_tour_frequency_is_5,Dummy for Presence of Non-Worker(other than modeled person) & tour frequency =5,has_non_worker & (tot_tours == 5),coef_presence_of_non_worker_and_tour_frequency_is_5,coef_presence_of_non_worker_and_tour_frequency_is_5,coef_presence_of_non_worker_and_tour_frequency_is_5,coef_presence_of_non_worker_and_tour_frequency_is_5,coef_presence_of_non_worker_and_tour_frequency_is_5,coef_presence_of_non_worker_and_tour_frequency_is_5,coef_presence_of_non_worker_and_tour_frequency_is_5,coef_presence_of_non_worker_and_tour_frequency_is_5 +util_presence_of_retiree_and_tour_frequency_is_1,Dummy for Presence of Retiree(other than modeled person) & tour frequency =1,has_retiree & (tot_tours == 1),coef_presence_of_retiree_and_tour_frequency_is_1,coef_presence_of_retiree_and_tour_frequency_is_1,coef_presence_of_retiree_and_tour_frequency_is_1,coef_presence_of_retiree_and_tour_frequency_is_1,coef_presence_of_retiree_and_tour_frequency_is_1,coef_presence_of_retiree_and_tour_frequency_is_1,coef_presence_of_retiree_and_tour_frequency_is_1,coef_presence_of_retiree_and_tour_frequency_is_1 +util_presence_of_retiree_and_tour_frequency_is_2,Dummy for Presence of Retiree(other than modeled person) & tour frequency =2,has_retiree & (tot_tours == 2),coef_presence_of_retiree_and_tour_frequency_is_2,coef_presence_of_retiree_and_tour_frequency_is_2,coef_presence_of_retiree_and_tour_frequency_is_2,coef_presence_of_retiree_and_tour_frequency_is_2,coef_presence_of_retiree_and_tour_frequency_is_2,coef_presence_of_retiree_and_tour_frequency_is_2,coef_presence_of_retiree_and_tour_frequency_is_2,coef_presence_of_retiree_and_tour_frequency_is_2 +util_presence_of_retiree_and_tour_frequency_is_3,Dummy for Presence of Retiree(other than modeled person) & tour frequency =3,has_retiree & (tot_tours == 3),coef_presence_of_retiree_and_tour_frequency_is_3,coef_presence_of_retiree_and_tour_frequency_is_3,coef_presence_of_retiree_and_tour_frequency_is_3,coef_presence_of_retiree_and_tour_frequency_is_3,coef_presence_of_retiree_and_tour_frequency_is_3,coef_presence_of_retiree_and_tour_frequency_is_3,coef_presence_of_retiree_and_tour_frequency_is_3,coef_presence_of_retiree_and_tour_frequency_is_3 +util_presence_of_retiree_and_tour_frequency_is_4,Dummy for Presence of Retiree(other than modeled person) & tour frequency =4,has_retiree & (tot_tours == 4),coef_presence_of_retiree_and_tour_frequency_is_4,coef_presence_of_retiree_and_tour_frequency_is_4,coef_presence_of_retiree_and_tour_frequency_is_4,coef_presence_of_retiree_and_tour_frequency_is_4,coef_presence_of_retiree_and_tour_frequency_is_4,coef_presence_of_retiree_and_tour_frequency_is_4,coef_presence_of_retiree_and_tour_frequency_is_4,coef_presence_of_retiree_and_tour_frequency_is_4 +util_presence_of_retiree_and_tour_frequency_is_5,Dummy for Presence of Retiree(other than modeled person) & tour frequency =5,has_retiree & (tot_tours == 5),coef_presence_of_retiree_and_tour_frequency_is_5,coef_presence_of_retiree_and_tour_frequency_is_5,coef_presence_of_retiree_and_tour_frequency_is_5,coef_presence_of_retiree_and_tour_frequency_is_5,coef_presence_of_retiree_and_tour_frequency_is_5,coef_presence_of_retiree_and_tour_frequency_is_5,coef_presence_of_retiree_and_tour_frequency_is_5,coef_presence_of_retiree_and_tour_frequency_is_5 +util_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,Dummy for Presence of PreSchool Kid (other than modeled person) in Household & tour frequency =1,has_preschool_kid & (tot_tours == 1),coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1 +util_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,Dummy for Presence of PreSchool Kid (other than modeled person) in Household & tour frequency =2,has_preschool_kid & (tot_tours == 2),coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2 +util_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,Dummy for Presence of PreSchool Kid (other than modeled person) in Household & tour frequency =3,has_preschool_kid & (tot_tours == 3),coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3 +util_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,Dummy for Presence of PreSchool Kid (other than modeled person) in Household & tour frequency =4,has_preschool_kid & (tot_tours == 4),coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4 +util_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,Dummy for Presence of PreSchool Kid (other than modeled person) in Household & tour frequency =5,has_preschool_kid & (tot_tours == 5),coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5 +util_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,Dummy for Presence of Predriving School Kid (other than modeled person) in Household & tour frequency =1,has_school_kid & (tot_tours == 1),coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1 +util_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,Dummy for Presence of Predriving School Kid (other than modeled person) in Household & tour frequency =2,has_school_kid & (tot_tours == 2),coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2 +util_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,Dummy for Presence of Predriving School Kid (other than modeled person) in Household & tour frequency =3,has_school_kid & (tot_tours == 3),coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3 +util_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,Dummy for Presence of Predriving School Kid (other than modeled person) in Household & tour frequency =4,has_school_kid & (tot_tours == 4),coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4 +util_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,Dummy for Presence of Predriving School Kid (other than modeled person) in Household & tour frequency =5,has_school_kid & (tot_tours == 5),coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5 +util_presence_of_full_time_worker_and_escorting_tour,Dummy for Presence of Full time Worker (other than modeled person) & Escorting tour ,has_full_time * escort,coef_presence_of_full_time_worker_and_escorting_tour,coef_presence_of_full_time_worker_and_escorting_tour,coef_presence_of_full_time_worker_and_escorting_tour,coef_presence_of_full_time_worker_and_escorting_tour,coef_presence_of_full_time_worker_and_escorting_tour,coef_presence_of_full_time_worker_and_escorting_tour,coef_presence_of_full_time_worker_and_escorting_tour,coef_presence_of_full_time_worker_and_escorting_tour +util_presence_of_part_time_worker_and_escorting_tour,Dummy for Presence of Part time Worker (other than modeled person) & Escorting tour ,has_part_time * escort,coef_presence_of_part_time_worker_and_escorting_tour,coef_presence_of_part_time_worker_and_escorting_tour,coef_presence_of_part_time_worker_and_escorting_tour,coef_presence_of_part_time_worker_and_escorting_tour,coef_presence_of_part_time_worker_and_escorting_tour,coef_presence_of_part_time_worker_and_escorting_tour,coef_presence_of_part_time_worker_and_escorting_tour,coef_presence_of_part_time_worker_and_escorting_tour +util_presence_of_non_worker_and_escorting_tour,Dummy for Presence of Non-Worker (other than modeled person) & Escorting tour ,has_non_worker * escort,coef_presence_of_non_worker_and_escorting_tour,coef_presence_of_non_worker_and_escorting_tour,coef_presence_of_non_worker_and_escorting_tour,coef_presence_of_non_worker_and_escorting_tour,coef_presence_of_non_worker_and_escorting_tour,coef_presence_of_non_worker_and_escorting_tour,coef_presence_of_non_worker_and_escorting_tour,coef_presence_of_non_worker_and_escorting_tour +util_presence_of_retiree_and_escorting_tour,Dummy for Presence of Retiree (other than modeled person) & Escorting tour ,has_retiree * escort,coef_presence_of_retiree_and_escorting_tour,coef_presence_of_retiree_and_escorting_tour,coef_presence_of_retiree_and_escorting_tour,coef_presence_of_retiree_and_escorting_tour,coef_presence_of_retiree_and_escorting_tour,coef_presence_of_retiree_and_escorting_tour,coef_presence_of_retiree_and_escorting_tour,coef_presence_of_retiree_and_escorting_tour +util_presence_of_university_student_and_escorting_tour,Dummy for Presence of University Student (other than modeled person) & Escorting tour ,has_university * escort,coef_presence_of_university_student_and_escorting_tour,coef_presence_of_university_student_and_escorting_tour,coef_presence_of_university_student_and_escorting_tour,coef_presence_of_university_student_and_escorting_tour,coef_presence_of_university_student_and_escorting_tour,coef_presence_of_university_student_and_escorting_tour,coef_presence_of_university_student_and_escorting_tour,coef_presence_of_university_student_and_escorting_tour +util_presence_of_driving_school_kid_and_escorting_tour,Dummy for Presence of Driving School Kid (other than modeled person) & Escorting tour ,has_driving_kid * escort,coef_presence_of_driving_school_kid_and_escorting_tour,coef_presence_of_driving_school_kid_and_escorting_tour,coef_presence_of_driving_school_kid_and_escorting_tour,coef_presence_of_driving_school_kid_and_escorting_tour,coef_presence_of_driving_school_kid_and_escorting_tour,coef_presence_of_driving_school_kid_and_escorting_tour,coef_presence_of_driving_school_kid_and_escorting_tour,coef_presence_of_driving_school_kid_and_escorting_tour +util_presence_of_pre_driving_school_kid_and_escorting_tour,Dummy for Presence of Pre-Driving School Kid (other than modeled person) & Escorting tour ,has_school_kid * escort,coef_presence_of_pre_driving_school_kid_and_escorting_tour,coef_presence_of_pre_driving_school_kid_and_escorting_tour,coef_presence_of_pre_driving_school_kid_and_escorting_tour,coef_presence_of_pre_driving_school_kid_and_escorting_tour,coef_presence_of_pre_driving_school_kid_and_escorting_tour,coef_presence_of_pre_driving_school_kid_and_escorting_tour,coef_presence_of_pre_driving_school_kid_and_escorting_tour,coef_presence_of_pre_driving_school_kid_and_escorting_tour +util_presence_of_pre_school_kid_and_escorting_tour,Dummy for Presence of Pre-School Kid (other than modeled person) & Escorting tour ,has_preschool_kid * escort,coef_presence_of_pre_school_kid_and_escorting_tour,coef_presence_of_pre_school_kid_and_escorting_tour,coef_presence_of_pre_school_kid_and_escorting_tour,coef_presence_of_pre_school_kid_and_escorting_tour,coef_presence_of_pre_school_kid_and_escorting_tour,coef_presence_of_pre_school_kid_and_escorting_tour,coef_presence_of_pre_school_kid_and_escorting_tour,coef_presence_of_pre_school_kid_and_escorting_tour +util_at_home_pre_driving_school_kid_and_escorting_tour,Dummy for At home Pre-Driving School Kid & Escorting tour ,has_school_kid_at_home * escort,coef_at_home_pre_driving_school_kid_and_escorting_tour,coef_at_home_pre_driving_school_kid_and_escorting_tour,coef_at_home_pre_driving_school_kid_and_escorting_tour,coef_at_home_pre_driving_school_kid_and_escorting_tour,coef_at_home_pre_driving_school_kid_and_escorting_tour,coef_at_home_pre_driving_school_kid_and_escorting_tour,coef_at_home_pre_driving_school_kid_and_escorting_tour,coef_at_home_pre_driving_school_kid_and_escorting_tour +util_at_home_pre_school_kid_and_escorting_tour,Dummy for At homef Pre-School Kid & Escorting tour ,has_preschool_kid_at_home * escort,coef_at_home_pre_school_kid_and_escorting_tour,coef_at_home_pre_school_kid_and_escorting_tour,coef_at_home_pre_school_kid_and_escorting_tour,coef_at_home_pre_school_kid_and_escorting_tour,coef_at_home_pre_school_kid_and_escorting_tour,coef_at_home_pre_school_kid_and_escorting_tour,coef_at_home_pre_school_kid_and_escorting_tour,coef_at_home_pre_school_kid_and_escorting_tour +util_presence_of_full_time_worker_and_shopping_tour,Dummy for Presence of Full time Worker (other than modeled person) & Shopping tour ,has_full_time * shopping,coef_presence_of_full_time_worker_and_shopping_tour,coef_presence_of_full_time_worker_and_shopping_tour,coef_presence_of_full_time_worker_and_shopping_tour,coef_presence_of_full_time_worker_and_shopping_tour,coef_presence_of_full_time_worker_and_shopping_tour,coef_presence_of_full_time_worker_and_shopping_tour,coef_presence_of_full_time_worker_and_shopping_tour,coef_presence_of_full_time_worker_and_shopping_tour +util_presence_of_part_time_worker_and_shopping_tour,Dummy for Presence of Part time Worker (other than modeled person) & Shopping tour ,has_part_time * shopping,coef_presence_of_part_time_worker_and_shopping_tour,coef_presence_of_part_time_worker_and_shopping_tour,coef_presence_of_part_time_worker_and_shopping_tour,coef_presence_of_part_time_worker_and_shopping_tour,coef_presence_of_part_time_worker_and_shopping_tour,coef_presence_of_part_time_worker_and_shopping_tour,coef_presence_of_part_time_worker_and_shopping_tour,coef_presence_of_part_time_worker_and_shopping_tour +util_presence_of_non_worker_and_shopping_tour,Dummy for Presence of Non-Worker (other than modeled person) & Shopping tour ,has_non_worker * shopping,coef_presence_of_non_worker_and_shopping_tour,coef_presence_of_non_worker_and_shopping_tour,coef_presence_of_non_worker_and_shopping_tour,coef_presence_of_non_worker_and_shopping_tour,coef_presence_of_non_worker_and_shopping_tour,coef_presence_of_non_worker_and_shopping_tour,coef_presence_of_non_worker_and_shopping_tour,coef_presence_of_non_worker_and_shopping_tour +util_presence_of_retiree_and_shopping_tour,Dummy for Presence of Retiree (other than modeled person) & Shopping tour ,has_retiree * shopping,coef_presence_of_retiree_and_shopping_tour,coef_presence_of_retiree_and_shopping_tour,coef_presence_of_retiree_and_shopping_tour,coef_presence_of_retiree_and_shopping_tour,coef_presence_of_retiree_and_shopping_tour,coef_presence_of_retiree_and_shopping_tour,coef_presence_of_retiree_and_shopping_tour,coef_presence_of_retiree_and_shopping_tour +util_presence_of_university_student_and_shopping_tour,Dummy for Presence of University Student (other than modeled person) & Shopping tour ,has_university * shopping,coef_presence_of_university_student_and_shopping_tour,coef_presence_of_university_student_and_shopping_tour,coef_presence_of_university_student_and_shopping_tour,coef_presence_of_university_student_and_shopping_tour,coef_presence_of_university_student_and_shopping_tour,coef_presence_of_university_student_and_shopping_tour,coef_presence_of_university_student_and_shopping_tour,coef_presence_of_university_student_and_shopping_tour +util_presence_of_driving_school_kid_and_shopping_tour,Dummy for Presence of Driving School Kid (other than modeled person) & Shopping tour ,has_driving_kid * shopping,coef_presence_of_driving_school_kid_and_shopping_tour,coef_presence_of_driving_school_kid_and_shopping_tour,coef_presence_of_driving_school_kid_and_shopping_tour,coef_presence_of_driving_school_kid_and_shopping_tour,coef_presence_of_driving_school_kid_and_shopping_tour,coef_presence_of_driving_school_kid_and_shopping_tour,coef_presence_of_driving_school_kid_and_shopping_tour,coef_presence_of_driving_school_kid_and_shopping_tour +util_presence_of_pre_driving_school_kid_and_shopping_tour,Dummy for Presence of Pre-Driving School Kid (other than modeled person) & Shopping tour ,has_school_kid * shopping,coef_presence_of_pre_driving_school_kid_and_shopping_tour,coef_presence_of_pre_driving_school_kid_and_shopping_tour,coef_presence_of_pre_driving_school_kid_and_shopping_tour,coef_presence_of_pre_driving_school_kid_and_shopping_tour,coef_presence_of_pre_driving_school_kid_and_shopping_tour,coef_presence_of_pre_driving_school_kid_and_shopping_tour,coef_presence_of_pre_driving_school_kid_and_shopping_tour,coef_presence_of_pre_driving_school_kid_and_shopping_tour +util_presence_of_pre_school_kid_and_shopping_tour,Dummy for Presence of Pre-School Kid (other than modeled person) & Shopping tour ,has_preschool_kid * shopping,coef_presence_of_pre_school_kid_and_shopping_tour,coef_presence_of_pre_school_kid_and_shopping_tour,coef_presence_of_pre_school_kid_and_shopping_tour,coef_presence_of_pre_school_kid_and_shopping_tour,coef_presence_of_pre_school_kid_and_shopping_tour,coef_presence_of_pre_school_kid_and_shopping_tour,coef_presence_of_pre_school_kid_and_shopping_tour,coef_presence_of_pre_school_kid_and_shopping_tour +util_at_home_pre_driving_school_kid_and_shopping_tour,Dummy for At home Pre-Driving School Kid & Shopping tour ,has_school_kid_at_home * shopping,coef_at_home_pre_driving_school_kid_and_shopping_tour,coef_at_home_pre_driving_school_kid_and_shopping_tour,coef_at_home_pre_driving_school_kid_and_shopping_tour,coef_at_home_pre_driving_school_kid_and_shopping_tour,coef_at_home_pre_driving_school_kid_and_shopping_tour,coef_at_home_pre_driving_school_kid_and_shopping_tour,coef_at_home_pre_driving_school_kid_and_shopping_tour,coef_at_home_pre_driving_school_kid_and_shopping_tour +util_at_home_pre_school_kid_and_shopping_tour,Dummy for At homef Pre-School Kid & Shopping tour ,has_preschool_kid_at_home * shopping,coef_at_home_pre_school_kid_and_shopping_tour,coef_at_home_pre_school_kid_and_shopping_tour,coef_at_home_pre_school_kid_and_shopping_tour,coef_at_home_pre_school_kid_and_shopping_tour,coef_at_home_pre_school_kid_and_shopping_tour,coef_at_home_pre_school_kid_and_shopping_tour,coef_at_home_pre_school_kid_and_shopping_tour,coef_at_home_pre_school_kid_and_shopping_tour +util_presence_of_full_time_worker_and_maintenance_tour,Dummy for Presence of Full time Worker (other than modeled person) & Maintenance tour ,has_full_time * othmaint,coef_presence_of_full_time_worker_and_maintenance_tour,coef_presence_of_full_time_worker_and_maintenance_tour,coef_presence_of_full_time_worker_and_maintenance_tour,coef_presence_of_full_time_worker_and_maintenance_tour,coef_presence_of_full_time_worker_and_maintenance_tour,coef_presence_of_full_time_worker_and_maintenance_tour,coef_presence_of_full_time_worker_and_maintenance_tour,coef_presence_of_full_time_worker_and_maintenance_tour +util_presence_of_part_time_worker_and_maintenance_tour,Dummy for Presence of Part time Worker (other than modeled person) & Maintenance tour ,has_part_time * othmaint,coef_presence_of_part_time_worker_and_maintenance_tour,coef_presence_of_part_time_worker_and_maintenance_tour,coef_presence_of_part_time_worker_and_maintenance_tour,coef_presence_of_part_time_worker_and_maintenance_tour,coef_presence_of_part_time_worker_and_maintenance_tour,coef_presence_of_part_time_worker_and_maintenance_tour,coef_presence_of_part_time_worker_and_maintenance_tour,coef_presence_of_part_time_worker_and_maintenance_tour +util_presence_of_non_worker_and_maintenance_tour,Dummy for Presence of Non-Worker(other than modeled person) & Maintenance tour ,has_non_worker * othmaint,coef_presence_of_non_worker_and_maintenance_tour,coef_presence_of_non_worker_and_maintenance_tour,coef_presence_of_non_worker_and_maintenance_tour,coef_presence_of_non_worker_and_maintenance_tour,coef_presence_of_non_worker_and_maintenance_tour,coef_presence_of_non_worker_and_maintenance_tour,coef_presence_of_non_worker_and_maintenance_tour,coef_presence_of_non_worker_and_maintenance_tour +util_presence_of_retiree_and_maintenance_tour,Dummy for Presence of Retiree (other than modeled person) & Maintenance tour ,has_retiree * othmaint,coef_presence_of_retiree_and_maintenance_tour,coef_presence_of_retiree_and_maintenance_tour,coef_presence_of_retiree_and_maintenance_tour,coef_presence_of_retiree_and_maintenance_tour,coef_presence_of_retiree_and_maintenance_tour,coef_presence_of_retiree_and_maintenance_tour,coef_presence_of_retiree_and_maintenance_tour,coef_presence_of_retiree_and_maintenance_tour +util_presence_of_university_student_and_maintenance_tour,Dummy for Presence of University Student (other than modeled person) & Maintenance tour ,has_university * othmaint,coef_presence_of_university_student_and_maintenance_tour,coef_presence_of_university_student_and_maintenance_tour,coef_presence_of_university_student_and_maintenance_tour,coef_presence_of_university_student_and_maintenance_tour,coef_presence_of_university_student_and_maintenance_tour,coef_presence_of_university_student_and_maintenance_tour,coef_presence_of_university_student_and_maintenance_tour,coef_presence_of_university_student_and_maintenance_tour +util_presence_of_driving_school_kid_and_maintenance_tour,Dummy for Presence of Driving School Kid (other than modeled person) & Maintenance tour ,has_driving_kid * othmaint,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour,coef_presence_of_driving_school_kid_and_maintenance_tour +util_presence_of_pre_driving_school_kid_and_maintenance_tour,Dummy for Presence of Pre-Driving School Kid (other than modeled person) & Maintenance tour ,has_school_kid * othmaint,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour,coef_presence_of_pre_driving_school_kid_and_maintenance_tour +util_presence_of_pre_school_kid_and_maintenance_tour,Dummy for Presence of Pre-School Kid (other than modeled person) & Maintenance tour ,has_preschool_kid * othmaint,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour,coef_presence_of_pre_school_kid_and_maintenance_tour +util_at_home_pre_driving_school_kid_and_maintenance_tour,Dummy for At home Pre-Driving School Kid & Maintenance tour ,has_school_kid_at_home * othmaint,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour,coef_at_home_pre_driving_school_kid_and_maintenance_tour +util_at_home_pre_school_kid_and_maintenance_tour,Dummy for At homef Pre-School Kid & Maintenance tour ,has_preschool_kid_at_home * othmaint,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour,coef_at_home_pre_school_kid_and_maintenance_tour +util_presence_of_full_time_worker_and_eating_out_tour,Dummy for Presence of Full time Worker (other than modeled person) & Eating Out tour ,has_full_time * eatout,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour,coef_presence_of_full_time_worker_and_eating_out_tour +util_presence_of_part_time_worker_and_eating_out_tour,Dummy for Presence of Part time Worker (other than modeled person) & Eating Out tour ,has_part_time * eatout,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour,coef_presence_of_part_time_worker_and_eating_out_tour +util_presence_of_non_worker_and_eating_out_tour,Dummy for Presence of Non-Worker (other than modeled person) & Eating Out tour ,has_non_worker * eatout,coef_presence_of_non_worker_and_eating_out_tour,coef_presence_of_non_worker_and_eating_out_tour,coef_presence_of_non_worker_and_eating_out_tour,coef_presence_of_non_worker_and_eating_out_tour,coef_presence_of_non_worker_and_eating_out_tour,coef_presence_of_non_worker_and_eating_out_tour,coef_presence_of_non_worker_and_eating_out_tour,coef_presence_of_non_worker_and_eating_out_tour +util_presence_of_retiree_and_eating_out_tour,Dummy for Presence of Retiree (other than modeled person) & Eating Out tour ,has_retiree * eatout,coef_presence_of_retiree_and_eating_out_tour,coef_presence_of_retiree_and_eating_out_tour,coef_presence_of_retiree_and_eating_out_tour,coef_presence_of_retiree_and_eating_out_tour,coef_presence_of_retiree_and_eating_out_tour,coef_presence_of_retiree_and_eating_out_tour,coef_presence_of_retiree_and_eating_out_tour,coef_presence_of_retiree_and_eating_out_tour +util_presence_of_university_student_and_eating_out_tour,Dummy for Presence of University Student (other than modeled person) & Eating Out tour ,has_university * eatout,coef_presence_of_university_student_and_eating_out_tour,coef_presence_of_university_student_and_eating_out_tour,coef_presence_of_university_student_and_eating_out_tour,coef_presence_of_university_student_and_eating_out_tour,coef_presence_of_university_student_and_eating_out_tour,coef_presence_of_university_student_and_eating_out_tour,coef_presence_of_university_student_and_eating_out_tour,coef_presence_of_university_student_and_eating_out_tour +util_presence_of_driving_school_kid_and_eating_out_tour,Dummy for Presence of Driving School Kid (other than modeled person) & Eating Out tour ,has_driving_kid * eatout,coef_presence_of_driving_school_kid_and_eating_out_tour,coef_presence_of_driving_school_kid_and_eating_out_tour,coef_presence_of_driving_school_kid_and_eating_out_tour,coef_presence_of_driving_school_kid_and_eating_out_tour,coef_presence_of_driving_school_kid_and_eating_out_tour,coef_presence_of_driving_school_kid_and_eating_out_tour,coef_presence_of_driving_school_kid_and_eating_out_tour,coef_presence_of_driving_school_kid_and_eating_out_tour +util_presence_of_pre_driving_school_kid_and_eating_out_tour,Dummy for Presence of Pre-Driving School Kid (other than modeled person) & Eating Out tour ,has_school_kid * eatout,coef_presence_of_pre_driving_school_kid_and_eating_out_tour,coef_presence_of_pre_driving_school_kid_and_eating_out_tour,coef_presence_of_pre_driving_school_kid_and_eating_out_tour,coef_presence_of_pre_driving_school_kid_and_eating_out_tour,coef_presence_of_pre_driving_school_kid_and_eating_out_tour,coef_presence_of_pre_driving_school_kid_and_eating_out_tour,coef_presence_of_pre_driving_school_kid_and_eating_out_tour,coef_presence_of_pre_driving_school_kid_and_eating_out_tour +util_presence_of_pre_school_kid_and_eating_out_tour,Dummy for Presence of Pre-School Kid (other than modeled person) & Eating Out tour ,has_preschool_kid * eatout,coef_presence_of_pre_school_kid_and_eating_out_tour,coef_presence_of_pre_school_kid_and_eating_out_tour,coef_presence_of_pre_school_kid_and_eating_out_tour,coef_presence_of_pre_school_kid_and_eating_out_tour,coef_presence_of_pre_school_kid_and_eating_out_tour,coef_presence_of_pre_school_kid_and_eating_out_tour,coef_presence_of_pre_school_kid_and_eating_out_tour,coef_presence_of_pre_school_kid_and_eating_out_tour +util_at_home_pre_driving_school_kid_and_eating_out_tour,Dummy for At home Pre-Driving School Kid & Eating Out tour ,has_school_kid_at_home * eatout,coef_at_home_pre_driving_school_kid_and_eating_out_tour,coef_at_home_pre_driving_school_kid_and_eating_out_tour,coef_at_home_pre_driving_school_kid_and_eating_out_tour,coef_at_home_pre_driving_school_kid_and_eating_out_tour,coef_at_home_pre_driving_school_kid_and_eating_out_tour,coef_at_home_pre_driving_school_kid_and_eating_out_tour,coef_at_home_pre_driving_school_kid_and_eating_out_tour,coef_at_home_pre_driving_school_kid_and_eating_out_tour +util_at_home_pre_school_kid_and_eating_out_tour,Dummy for At homef Pre-School Kid & Eating Out tour ,has_preschool_kid_at_home * eatout,coef_at_home_pre_school_kid_and_eating_out_tour,coef_at_home_pre_school_kid_and_eating_out_tour,coef_at_home_pre_school_kid_and_eating_out_tour,coef_at_home_pre_school_kid_and_eating_out_tour,coef_at_home_pre_school_kid_and_eating_out_tour,coef_at_home_pre_school_kid_and_eating_out_tour,coef_at_home_pre_school_kid_and_eating_out_tour,coef_at_home_pre_school_kid_and_eating_out_tour +util_presence_of_full_time_worker_and_discretionary_tour,Dummy for Presence of Full time Worker (other than modeled person) & Discretionary tour ,has_full_time * othdiscr,coef_presence_of_full_time_worker_and_discretionary_tour,coef_presence_of_full_time_worker_and_discretionary_tour,coef_presence_of_full_time_worker_and_discretionary_tour,coef_presence_of_full_time_worker_and_discretionary_tour,coef_presence_of_full_time_worker_and_discretionary_tour,coef_presence_of_full_time_worker_and_discretionary_tour,coef_presence_of_full_time_worker_and_discretionary_tour,coef_presence_of_full_time_worker_and_discretionary_tour +util_presence_of_part_time_worker_and_discretionary_tour,Dummy for Presence of Part time Worker (other than modeled person) & Discretionary tour ,has_part_time * othdiscr,coef_presence_of_part_time_worker_and_discretionary_tour,coef_presence_of_part_time_worker_and_discretionary_tour,coef_presence_of_part_time_worker_and_discretionary_tour,coef_presence_of_part_time_worker_and_discretionary_tour,coef_presence_of_part_time_worker_and_discretionary_tour,coef_presence_of_part_time_worker_and_discretionary_tour,coef_presence_of_part_time_worker_and_discretionary_tour,coef_presence_of_part_time_worker_and_discretionary_tour +util_presence_of_non_worker_and_discretionary_tour,Dummy for Presence of Non-Worker (other than modeled person) & Discretionary tour ,has_non_worker * othdiscr,coef_presence_of_non_worker_and_discretionary_tour,coef_presence_of_non_worker_and_discretionary_tour,coef_presence_of_non_worker_and_discretionary_tour,coef_presence_of_non_worker_and_discretionary_tour,coef_presence_of_non_worker_and_discretionary_tour,coef_presence_of_non_worker_and_discretionary_tour,coef_presence_of_non_worker_and_discretionary_tour,coef_presence_of_non_worker_and_discretionary_tour +util_presence_of_retiree_and_discretionary_tour,Dummy for Presence of Retiree (other than modeled person) & Discretionary tour ,has_retiree * othdiscr,coef_presence_of_retiree_and_discretionary_tour,coef_presence_of_retiree_and_discretionary_tour,coef_presence_of_retiree_and_discretionary_tour,coef_presence_of_retiree_and_discretionary_tour,coef_presence_of_retiree_and_discretionary_tour,coef_presence_of_retiree_and_discretionary_tour,coef_presence_of_retiree_and_discretionary_tour,coef_presence_of_retiree_and_discretionary_tour +util_presence_of_university_student_and_discretionary_tour,Dummy for Presence of University Student (other than modeled person) & Discretionary tour ,has_university * othdiscr,coef_presence_of_university_student_and_discretionary_tour,coef_presence_of_university_student_and_discretionary_tour,coef_presence_of_university_student_and_discretionary_tour,coef_presence_of_university_student_and_discretionary_tour,coef_presence_of_university_student_and_discretionary_tour,coef_presence_of_university_student_and_discretionary_tour,coef_presence_of_university_student_and_discretionary_tour,coef_presence_of_university_student_and_discretionary_tour +util_presence_of_driving_school_kid_and_discretionary_tour,Dummy for Presence of Driving School Kid (other than modeled person) & Discretionary tour ,has_driving_kid * othdiscr,coef_presence_of_driving_school_kid_and_discretionary_tour,coef_presence_of_driving_school_kid_and_discretionary_tour,coef_presence_of_driving_school_kid_and_discretionary_tour,coef_presence_of_driving_school_kid_and_discretionary_tour,coef_presence_of_driving_school_kid_and_discretionary_tour,coef_presence_of_driving_school_kid_and_discretionary_tour,coef_presence_of_driving_school_kid_and_discretionary_tour,coef_presence_of_driving_school_kid_and_discretionary_tour +util_presence_of_pre_driving_school_kid_and_discretionary_tour,Dummy for Presence of Pre-Driving School Kid (other than modeled person) & Discretionary tour ,has_school_kid * othdiscr,coef_presence_of_pre_driving_school_kid_and_discretionary_tour,coef_presence_of_pre_driving_school_kid_and_discretionary_tour,coef_presence_of_pre_driving_school_kid_and_discretionary_tour,coef_presence_of_pre_driving_school_kid_and_discretionary_tour,coef_presence_of_pre_driving_school_kid_and_discretionary_tour,coef_presence_of_pre_driving_school_kid_and_discretionary_tour,coef_presence_of_pre_driving_school_kid_and_discretionary_tour,coef_presence_of_pre_driving_school_kid_and_discretionary_tour +util_presence_of_pre_school_kid_and_discretionary_tour,Dummy for Presence of Pre-School Kid (other than modeled person) & Discretionary tour ,has_preschool_kid * othdiscr,coef_presence_of_pre_school_kid_and_discretionary_tour,coef_presence_of_pre_school_kid_and_discretionary_tour,coef_presence_of_pre_school_kid_and_discretionary_tour,coef_presence_of_pre_school_kid_and_discretionary_tour,coef_presence_of_pre_school_kid_and_discretionary_tour,coef_presence_of_pre_school_kid_and_discretionary_tour,coef_presence_of_pre_school_kid_and_discretionary_tour,coef_presence_of_pre_school_kid_and_discretionary_tour +util_at_home_pre_driving_school_kid_and_discretionary_tour,Dummy for At home Pre-Driving School Kid & Discretionary tour ,has_school_kid_at_home * othdiscr,coef_at_home_pre_driving_school_kid_and_discretionary_tour,coef_at_home_pre_driving_school_kid_and_discretionary_tour,coef_at_home_pre_driving_school_kid_and_discretionary_tour,coef_at_home_pre_driving_school_kid_and_discretionary_tour,coef_at_home_pre_driving_school_kid_and_discretionary_tour,coef_at_home_pre_driving_school_kid_and_discretionary_tour,coef_at_home_pre_driving_school_kid_and_discretionary_tour,coef_at_home_pre_driving_school_kid_and_discretionary_tour +util_at_home_pre_school_kid_and_discretionary_tour,Dummy for At homef Pre-School Kid & Discretionary tour ,has_preschool_kid_at_home * othdiscr,coef_at_home_pre_school_kid_and_discretionary_tour,coef_at_home_pre_school_kid_and_discretionary_tour,coef_at_home_pre_school_kid_and_discretionary_tour,coef_at_home_pre_school_kid_and_discretionary_tour,coef_at_home_pre_school_kid_and_discretionary_tour,coef_at_home_pre_school_kid_and_discretionary_tour,coef_at_home_pre_school_kid_and_discretionary_tour,coef_at_home_pre_school_kid_and_discretionary_tour +util_walk_access_to_retail_and_tour_frequency_is_1,Walk Access to Retail & Tour Frequency =1,nmRetail * (tot_tours == 1),coef_walk_access_to_retail_and_tour_frequency_is_1,coef_walk_access_to_retail_and_tour_frequency_is_1,coef_walk_access_to_retail_and_tour_frequency_is_1,coef_walk_access_to_retail_and_tour_frequency_is_1,coef_walk_access_to_retail_and_tour_frequency_is_1,coef_walk_access_to_retail_and_tour_frequency_is_1,coef_walk_access_to_retail_and_tour_frequency_is_1,coef_walk_access_to_retail_and_tour_frequency_is_1 +util_walk_access_to_retail_and_tour_frequency_is_2,Walk Access to Retail & Tour Frequency =2,nmRetail * (tot_tours == 2),coef_walk_access_to_retail_and_tour_frequency_is_2,coef_walk_access_to_retail_and_tour_frequency_is_2,coef_walk_access_to_retail_and_tour_frequency_is_2,coef_walk_access_to_retail_and_tour_frequency_is_2,coef_walk_access_to_retail_and_tour_frequency_is_2,coef_walk_access_to_retail_and_tour_frequency_is_2,coef_walk_access_to_retail_and_tour_frequency_is_2,coef_walk_access_to_retail_and_tour_frequency_is_2 +util_walk_access_to_retail_and_tour_frequency_is_3,Walk Access to Retail & Tour Frequency =3,nmRetail * (tot_tours == 3),coef_walk_access_to_retail_and_tour_frequency_is_3,coef_walk_access_to_retail_and_tour_frequency_is_3,coef_walk_access_to_retail_and_tour_frequency_is_3,coef_walk_access_to_retail_and_tour_frequency_is_3,coef_walk_access_to_retail_and_tour_frequency_is_3,coef_walk_access_to_retail_and_tour_frequency_is_3,coef_walk_access_to_retail_and_tour_frequency_is_3,coef_walk_access_to_retail_and_tour_frequency_is_3 +util_walk_access_to_retail_and_tour_frequency_is_4,Walk Access to Retail & Tour Frequency =4,nmRetail * (tot_tours == 4),coef_walk_access_to_retail_and_tour_frequency_is_4,coef_walk_access_to_retail_and_tour_frequency_is_4,coef_walk_access_to_retail_and_tour_frequency_is_4,coef_walk_access_to_retail_and_tour_frequency_is_4,coef_walk_access_to_retail_and_tour_frequency_is_4,coef_walk_access_to_retail_and_tour_frequency_is_4,coef_walk_access_to_retail_and_tour_frequency_is_4,coef_walk_access_to_retail_and_tour_frequency_is_4 +util_walk_access_to_retail_and_tour_frequency_is_5_plus,Walk Access to Retail & Tour Frequency =5+,nmRetail * (tot_tours > 4),coef_walk_access_to_retail_and_tour_frequency_is_5_plus,coef_walk_access_to_retail_and_tour_frequency_is_5_plus,coef_walk_access_to_retail_and_tour_frequency_is_5_plus,coef_walk_access_to_retail_and_tour_frequency_is_5_plus,coef_walk_access_to_retail_and_tour_frequency_is_5_plus,coef_walk_access_to_retail_and_tour_frequency_is_5_plus,coef_walk_access_to_retail_and_tour_frequency_is_5_plus,coef_walk_access_to_retail_and_tour_frequency_is_5_plus +util_transit_access_to_retail_and_tour_frequency_is_1,Transit Access to Retail & Tour Frequency =1,trOpRetail * (tot_tours == 1),coef_transit_access_to_retail_and_tour_frequency_is_1,coef_transit_access_to_retail_and_tour_frequency_is_1,coef_transit_access_to_retail_and_tour_frequency_is_1,coef_transit_access_to_retail_and_tour_frequency_is_1,coef_transit_access_to_retail_and_tour_frequency_is_1,coef_transit_access_to_retail_and_tour_frequency_is_1,coef_transit_access_to_retail_and_tour_frequency_is_1,coef_transit_access_to_retail_and_tour_frequency_is_1 +util_transit_access_to_retail_and_tour_frequency_is_2,Transit Access to Retail & Tour Frequency =2,trOpRetail * (tot_tours == 2),coef_transit_access_to_retail_and_tour_frequency_is_2,coef_transit_access_to_retail_and_tour_frequency_is_2,coef_transit_access_to_retail_and_tour_frequency_is_2,coef_transit_access_to_retail_and_tour_frequency_is_2,coef_transit_access_to_retail_and_tour_frequency_is_2,coef_transit_access_to_retail_and_tour_frequency_is_2,coef_transit_access_to_retail_and_tour_frequency_is_2,coef_transit_access_to_retail_and_tour_frequency_is_2 +util_transit_access_to_retail_and_tour_frequency_is_3,Transit Access to Retail & Tour Frequency =3,trOpRetail * (tot_tours == 3),coef_transit_access_to_retail_and_tour_frequency_is_3,coef_transit_access_to_retail_and_tour_frequency_is_3,coef_transit_access_to_retail_and_tour_frequency_is_3,coef_transit_access_to_retail_and_tour_frequency_is_3,coef_transit_access_to_retail_and_tour_frequency_is_3,coef_transit_access_to_retail_and_tour_frequency_is_3,coef_transit_access_to_retail_and_tour_frequency_is_3,coef_transit_access_to_retail_and_tour_frequency_is_3 +util_transit_access_to_retail_and_tour_frequency_is_4,Transit Access to Retail & Tour Frequency =4,trOpRetail * (tot_tours == 4),coef_transit_access_to_retail_and_tour_frequency_is_4,coef_transit_access_to_retail_and_tour_frequency_is_4,coef_transit_access_to_retail_and_tour_frequency_is_4,coef_transit_access_to_retail_and_tour_frequency_is_4,coef_transit_access_to_retail_and_tour_frequency_is_4,coef_transit_access_to_retail_and_tour_frequency_is_4,coef_transit_access_to_retail_and_tour_frequency_is_4,coef_transit_access_to_retail_and_tour_frequency_is_4 +util_transit_access_to_retail_and_tour_frequency_is_5_plus,Transit Access to Retail & Tour Frequency =5+,trOpRetail * (tot_tours > 4),coef_transit_access_to_retail_and_tour_frequency_is_5_plus,coef_transit_access_to_retail_and_tour_frequency_is_5_plus,coef_transit_access_to_retail_and_tour_frequency_is_5_plus,coef_transit_access_to_retail_and_tour_frequency_is_5_plus,coef_transit_access_to_retail_and_tour_frequency_is_5_plus,coef_transit_access_to_retail_and_tour_frequency_is_5_plus,coef_transit_access_to_retail_and_tour_frequency_is_5_plus,coef_transit_access_to_retail_and_tour_frequency_is_5_plus +util_auto_access_to_retail_and_tour_frequency_is_1,Auto Access to Retail & Tour Frequency =1,auOpRetail * (tot_tours == 1),coef_auto_access_to_retail_and_tour_frequency_is_1,coef_auto_access_to_retail_and_tour_frequency_is_1,coef_auto_access_to_retail_and_tour_frequency_is_1,coef_auto_access_to_retail_and_tour_frequency_is_1,coef_auto_access_to_retail_and_tour_frequency_is_1,coef_auto_access_to_retail_and_tour_frequency_is_1,coef_auto_access_to_retail_and_tour_frequency_is_1,coef_auto_access_to_retail_and_tour_frequency_is_1 +util_auto_access_to_retail_and_tour_frequency_is_2,Auto Access to Retail & Tour Frequency =2,auOpRetail * (tot_tours == 2),coef_auto_access_to_retail_and_tour_frequency_is_2,coef_auto_access_to_retail_and_tour_frequency_is_2,coef_auto_access_to_retail_and_tour_frequency_is_2,coef_auto_access_to_retail_and_tour_frequency_is_2,coef_auto_access_to_retail_and_tour_frequency_is_2,coef_auto_access_to_retail_and_tour_frequency_is_2,coef_auto_access_to_retail_and_tour_frequency_is_2,coef_auto_access_to_retail_and_tour_frequency_is_2 +util_auto_access_to_retail_and_tour_frequency_is_3,Auto Access to Retail & Tour Frequency =3,auOpRetail * (tot_tours == 3),coef_auto_access_to_retail_and_tour_frequency_is_3,coef_auto_access_to_retail_and_tour_frequency_is_3,coef_auto_access_to_retail_and_tour_frequency_is_3,coef_auto_access_to_retail_and_tour_frequency_is_3,coef_auto_access_to_retail_and_tour_frequency_is_3,coef_auto_access_to_retail_and_tour_frequency_is_3,coef_auto_access_to_retail_and_tour_frequency_is_3,coef_auto_access_to_retail_and_tour_frequency_is_3 +util_auto_access_to_retail_and_tour_frequency_is_4,Auto Access to Retail & Tour Frequency =4,auOpRetail * (tot_tours == 4),coef_auto_access_to_retail_and_tour_frequency_is_4,coef_auto_access_to_retail_and_tour_frequency_is_4,coef_auto_access_to_retail_and_tour_frequency_is_4,coef_auto_access_to_retail_and_tour_frequency_is_4,coef_auto_access_to_retail_and_tour_frequency_is_4,coef_auto_access_to_retail_and_tour_frequency_is_4,coef_auto_access_to_retail_and_tour_frequency_is_4,coef_auto_access_to_retail_and_tour_frequency_is_4 +util_auto_access_to_retail_and_tour_frequency_is_5_plus,Auto Access to Retail & Tour Frequency =5+,auOpRetail * (tot_tours > 4),coef_auto_access_to_retail_and_tour_frequency_is_5_plus,coef_auto_access_to_retail_and_tour_frequency_is_5_plus,coef_auto_access_to_retail_and_tour_frequency_is_5_plus,coef_auto_access_to_retail_and_tour_frequency_is_5_plus,coef_auto_access_to_retail_and_tour_frequency_is_5_plus,coef_auto_access_to_retail_and_tour_frequency_is_5_plus,coef_auto_access_to_retail_and_tour_frequency_is_5_plus,coef_auto_access_to_retail_and_tour_frequency_is_5_plus +util_walk_access_to_retail_and_escorting,Walk Access to Retail & Escorting ,nmRetail * escort,coef_walk_access_to_retail_and_escorting,coef_walk_access_to_retail_and_escorting,coef_walk_access_to_retail_and_escorting,coef_walk_access_to_retail_and_escorting,coef_walk_access_to_retail_and_escorting,coef_walk_access_to_retail_and_escorting,coef_walk_access_to_retail_and_escorting,coef_walk_access_to_retail_and_escorting +util_transit_access_to_retail_and_escorting,Transit Access to Retail & Escorting ,trOpRetail * escort,coef_transit_access_to_retail_and_escorting,coef_transit_access_to_retail_and_escorting,coef_transit_access_to_retail_and_escorting,coef_transit_access_to_retail_and_escorting,coef_transit_access_to_retail_and_escorting,coef_transit_access_to_retail_and_escorting,coef_transit_access_to_retail_and_escorting,coef_transit_access_to_retail_and_escorting +util_auto_access_to_retail_and_escorting,Auto Access to Retail & Escorting ,auOpRetail * escort,coef_auto_access_to_retail_and_escorting,coef_auto_access_to_retail_and_escorting,coef_auto_access_to_retail_and_escorting,coef_auto_access_to_retail_and_escorting,coef_auto_access_to_retail_and_escorting,coef_auto_access_to_retail_and_escorting,coef_auto_access_to_retail_and_escorting,coef_auto_access_to_retail_and_escorting +util_walk_access_to_retail_and_shopping,Walk Access to Retail & Shopping ,nmRetail * shopping,coef_walk_access_to_retail_and_shopping,coef_walk_access_to_retail_and_shopping,coef_walk_access_to_retail_and_shopping,coef_walk_access_to_retail_and_shopping,coef_walk_access_to_retail_and_shopping,coef_walk_access_to_retail_and_shopping,coef_walk_access_to_retail_and_shopping,coef_walk_access_to_retail_and_shopping +util_transit_access_to_retail_and_shopping,Transit Access to Retail & Shopping ,trOpRetail * shopping,coef_transit_access_to_retail_and_shopping,coef_transit_access_to_retail_and_shopping,coef_transit_access_to_retail_and_shopping,coef_transit_access_to_retail_and_shopping,coef_transit_access_to_retail_and_shopping,coef_transit_access_to_retail_and_shopping,coef_transit_access_to_retail_and_shopping,coef_transit_access_to_retail_and_shopping +util_auto_access_to_retail_and_shopping,Auto Access to Retail & Shopping ,auOpRetail * shopping,coef_auto_access_to_retail_and_shopping,coef_auto_access_to_retail_and_shopping,coef_auto_access_to_retail_and_shopping,coef_auto_access_to_retail_and_shopping,coef_auto_access_to_retail_and_shopping,coef_auto_access_to_retail_and_shopping,coef_auto_access_to_retail_and_shopping,coef_auto_access_to_retail_and_shopping +util_walk_access_to_retail_and_maintenance,Walk Access to Retail & Maintenance ,nmRetail * othmaint,coef_walk_access_to_retail_and_maintenance,coef_walk_access_to_retail_and_maintenance,coef_walk_access_to_retail_and_maintenance,coef_walk_access_to_retail_and_maintenance,coef_walk_access_to_retail_and_maintenance,coef_walk_access_to_retail_and_maintenance,coef_walk_access_to_retail_and_maintenance,coef_walk_access_to_retail_and_maintenance +util_transit_access_to_retail_and_maintenance,Transit Access to Retail & Maintenance ,trOpRetail * othmaint,coef_transit_access_to_retail_and_maintenance,coef_transit_access_to_retail_and_maintenance,coef_transit_access_to_retail_and_maintenance,coef_transit_access_to_retail_and_maintenance,coef_transit_access_to_retail_and_maintenance,coef_transit_access_to_retail_and_maintenance,coef_transit_access_to_retail_and_maintenance,coef_transit_access_to_retail_and_maintenance +util_auto_access_to_retail_and_maintenance,Auto Access to Retail & Maintenance ,auOpRetail * othmaint,coef_auto_access_to_retail_and_maintenance,coef_auto_access_to_retail_and_maintenance,coef_auto_access_to_retail_and_maintenance,coef_auto_access_to_retail_and_maintenance,coef_auto_access_to_retail_and_maintenance,coef_auto_access_to_retail_and_maintenance,coef_auto_access_to_retail_and_maintenance,coef_auto_access_to_retail_and_maintenance +util_walk_access_to_retail_and_eating_out,Walk Access to Retail & Eating Out ,nmRetail * eatout,coef_walk_access_to_retail_and_eating_out,coef_walk_access_to_retail_and_eating_out,coef_walk_access_to_retail_and_eating_out,coef_walk_access_to_retail_and_eating_out,coef_walk_access_to_retail_and_eating_out,coef_walk_access_to_retail_and_eating_out,coef_walk_access_to_retail_and_eating_out,coef_walk_access_to_retail_and_eating_out +util_transit_access_to_retail_and_eating_out,Transit Access to Retail & Eating Out ,trOpRetail * eatout,coef_transit_access_to_retail_and_eating_out,coef_transit_access_to_retail_and_eating_out,coef_transit_access_to_retail_and_eating_out,coef_transit_access_to_retail_and_eating_out,coef_transit_access_to_retail_and_eating_out,coef_transit_access_to_retail_and_eating_out,coef_transit_access_to_retail_and_eating_out,coef_transit_access_to_retail_and_eating_out +util_auto_access_to_retail_and_eating_out,Auto Access to Retail & Eating Out ,auOpRetail * eatout,coef_auto_access_to_retail_and_eating_out,coef_auto_access_to_retail_and_eating_out,coef_auto_access_to_retail_and_eating_out,coef_auto_access_to_retail_and_eating_out,coef_auto_access_to_retail_and_eating_out,coef_auto_access_to_retail_and_eating_out,coef_auto_access_to_retail_and_eating_out,coef_auto_access_to_retail_and_eating_out +util_walk_access_to_retail_and_discretionary,Walk Access to Retail & Discretionary ,nmRetail * othdiscr,coef_walk_access_to_retail_and_discretionary,coef_walk_access_to_retail_and_discretionary,coef_walk_access_to_retail_and_discretionary,coef_walk_access_to_retail_and_discretionary,coef_walk_access_to_retail_and_discretionary,coef_walk_access_to_retail_and_discretionary,coef_walk_access_to_retail_and_discretionary,coef_walk_access_to_retail_and_discretionary +util_transit_access_to_retail_and_discretionary,Transit Access to Retail & Discretionary ,trOpRetail * othdiscr,coef_transit_access_to_retail_and_discretionary,coef_transit_access_to_retail_and_discretionary,coef_transit_access_to_retail_and_discretionary,coef_transit_access_to_retail_and_discretionary,coef_transit_access_to_retail_and_discretionary,coef_transit_access_to_retail_and_discretionary,coef_transit_access_to_retail_and_discretionary,coef_transit_access_to_retail_and_discretionary +util_auto_access_to_retail_and_discretionary,Auto Access to Retail & Discretionary ,auOpRetail * othdiscr,coef_auto_access_to_retail_and_discretionary,coef_auto_access_to_retail_and_discretionary,coef_auto_access_to_retail_and_discretionary,coef_auto_access_to_retail_and_discretionary,coef_auto_access_to_retail_and_discretionary,coef_auto_access_to_retail_and_discretionary,coef_auto_access_to_retail_and_discretionary,coef_auto_access_to_retail_and_discretionary +util_urban_and_tour_frequency_is_1,Urban AREATYPE & Tour Frequency =1,home_is_urban & (tot_tours == 1),coef_urban_and_tour_frequency_is_1,coef_urban_and_tour_frequency_is_1,coef_urban_and_tour_frequency_is_1,coef_urban_and_tour_frequency_is_1,coef_urban_and_tour_frequency_is_1,coef_urban_and_tour_frequency_is_1,coef_urban_and_tour_frequency_is_1,coef_urban_and_tour_frequency_is_1 +util_urban_and_tour_frequency_is_2,Urban AREATYPE & Tour Frequency =2,home_is_urban & (tot_tours == 2),coef_urban_and_tour_frequency_is_2,coef_urban_and_tour_frequency_is_2,coef_urban_and_tour_frequency_is_2,coef_urban_and_tour_frequency_is_2,coef_urban_and_tour_frequency_is_2,coef_urban_and_tour_frequency_is_2,coef_urban_and_tour_frequency_is_2,coef_urban_and_tour_frequency_is_2 +util_urban_and_tour_frequency_is_3,Urban AREATYPE & Tour Frequency =3,home_is_urban & (tot_tours == 3),coef_urban_and_tour_frequency_is_3,coef_urban_and_tour_frequency_is_3,coef_urban_and_tour_frequency_is_3,coef_urban_and_tour_frequency_is_3,coef_urban_and_tour_frequency_is_3,coef_urban_and_tour_frequency_is_3,coef_urban_and_tour_frequency_is_3,coef_urban_and_tour_frequency_is_3 +util_urban_and_tour_frequency_is_4,Urban AREATYPE & Tour Frequency =4,home_is_urban & (tot_tours == 4),coef_urban_and_tour_frequency_is_4,coef_urban_and_tour_frequency_is_4,coef_urban_and_tour_frequency_is_4,coef_urban_and_tour_frequency_is_4,coef_urban_and_tour_frequency_is_4,coef_urban_and_tour_frequency_is_4,coef_urban_and_tour_frequency_is_4,coef_urban_and_tour_frequency_is_4 +util_urban_and_tour_frequency_is_5_plus,Urban AREATYPE & Tour Frequency =5+,home_is_urban & (tot_tours > 4),coef_urban_and_tour_frequency_is_5_plus,coef_urban_and_tour_frequency_is_5_plus,coef_urban_and_tour_frequency_is_5_plus,coef_urban_and_tour_frequency_is_5_plus,coef_urban_and_tour_frequency_is_5_plus,coef_urban_and_tour_frequency_is_5_plus,coef_urban_and_tour_frequency_is_5_plus,coef_urban_and_tour_frequency_is_5_plus +util_urban_and_escorting_tour,Urban AREATYPE & Escorting tour,home_is_urban * escort,coef_urban_and_escorting_tour,coef_urban_and_escorting_tour,coef_urban_and_escorting_tour,coef_urban_and_escorting_tour,coef_urban_and_escorting_tour,coef_urban_and_escorting_tour,coef_urban_and_escorting_tour,coef_urban_and_escorting_tour +util_urban_and_shopping_tour,Urban AREATYPE &Shopping tour,home_is_urban * shopping,coef_urban_and_shopping_tour,coef_urban_and_shopping_tour,coef_urban_and_shopping_tour,coef_urban_and_shopping_tour,coef_urban_and_shopping_tour,coef_urban_and_shopping_tour,coef_urban_and_shopping_tour,coef_urban_and_shopping_tour +util_urban_and_maintenance_tour,Urban AREATYPE & Maintenance tour,home_is_urban * othmaint,coef_urban_and_maintenance_tour,coef_urban_and_maintenance_tour,coef_urban_and_maintenance_tour,coef_urban_and_maintenance_tour,coef_urban_and_maintenance_tour,coef_urban_and_maintenance_tour,coef_urban_and_maintenance_tour,coef_urban_and_maintenance_tour +util_urban_and_eatingout_tour,Urban AREATYPE & EatingOut tour,home_is_urban * eatout,coef_urban_and_eatingout_tour,coef_urban_and_eatingout_tour,coef_urban_and_eatingout_tour,coef_urban_and_eatingout_tour,coef_urban_and_eatingout_tour,coef_urban_and_eatingout_tour,coef_urban_and_eatingout_tour,coef_urban_and_eatingout_tour +util_urban_and_discretionary_tour,Urban AREATYPE & Discretionary tour,home_is_urban * othdiscr,coef_urban_and_discretionary_tour,coef_urban_and_discretionary_tour,coef_urban_and_discretionary_tour,coef_urban_and_discretionary_tour,coef_urban_and_discretionary_tour,coef_urban_and_discretionary_tour,coef_urban_and_discretionary_tour,coef_urban_and_discretionary_tour +util_1_escort_tour_constant,1 Escort Tour Constant,escort == 1,coef_1_escort_tour_constant,coef_1_escort_tour_constant,coef_1_escort_tour_constant,coef_1_escort_tour_constant,coef_1_escort_tour_constant,coef_1_escort_tour_constant,coef_1_escort_tour_constant,coef_1_escort_tour_constant +util_2_plus_escort_tours_constant,2+ Escort Tours Constant,escort >= 2,coef_2_plus_escort_tours_constant,coef_2_plus_escort_tours_constant,coef_2_plus_escort_tours_constant,coef_2_plus_escort_tours_constant,coef_2_plus_escort_tours_constant,coef_2_plus_escort_tours_constant,coef_2_plus_escort_tours_constant,coef_2_plus_escort_tours_constant +util_1_plus_shopping_tours_constant,1+ Shopping Tours Constant,shopping >= 1,coef_1_plus_shopping_tours_constant,coef_1_plus_shopping_tours_constant,coef_1_plus_shopping_tours_constant,coef_1_plus_shopping_tours_constant,coef_1_plus_shopping_tours_constant,coef_1_plus_shopping_tours_constant,coef_1_plus_shopping_tours_constant,coef_1_plus_shopping_tours_constant +util_1_plus_maintenance_tours_constant,1+ Maintenance Tours Constant,othmaint >= 1,coef_1_plus_maintenance_tours_constant,coef_1_plus_maintenance_tours_constant,coef_1_plus_maintenance_tours_constant,coef_1_plus_maintenance_tours_constant,coef_1_plus_maintenance_tours_constant,coef_1_plus_maintenance_tours_constant,coef_1_plus_maintenance_tours_constant,coef_1_plus_maintenance_tours_constant +util_1_plus_eating_out_tours_constant,1+ Eating Out Tours Constant,eatout >= 1,coef_1_plus_eating_out_tours_constant,coef_1_plus_eating_out_tours_constant,coef_1_plus_eating_out_tours_constant,coef_1_plus_eating_out_tours_constant,coef_1_plus_eating_out_tours_constant,coef_1_plus_eating_out_tours_constant,coef_1_plus_eating_out_tours_constant,coef_1_plus_eating_out_tours_constant +util_1_plus_visting_tours_constant,1+ Visting Tours Constant,social >= 1,coef_1_plus_visting_tours_constant,coef_1_plus_visting_tours_constant,coef_1_plus_visting_tours_constant,coef_1_plus_visting_tours_constant,coef_1_plus_visting_tours_constant,coef_1_plus_visting_tours_constant,coef_1_plus_visting_tours_constant,coef_1_plus_visting_tours_constant +util_1_plus_other_discretionary_tours_constant,1+ Other Discretionary Tours Constant,othdiscr >= 1,coef_1_plus_other_discretionary_tours_constant,coef_1_plus_other_discretionary_tours_constant,coef_1_plus_other_discretionary_tours_constant,coef_1_plus_other_discretionary_tours_constant,coef_1_plus_other_discretionary_tours_constant,coef_1_plus_other_discretionary_tours_constant,coef_1_plus_other_discretionary_tours_constant,coef_1_plus_other_discretionary_tours_constant +util_0_auto_household_and_escorting_tour,Dummy for 0-auto household & Escorting Tour,escort * no_cars,coef_0_auto_household_and_escorting_tour,coef_0_auto_household_and_escorting_tour,coef_0_auto_household_and_escorting_tour,coef_0_auto_household_and_escorting_tour,coef_0_auto_household_and_escorting_tour,coef_0_auto_household_and_escorting_tour,coef_0_auto_household_and_escorting_tour,coef_0_auto_household_and_escorting_tour +util_calibration_mand_gt0_nonmandtours_1,Mandatory tours > 0 and Non-mandatory tours = 1 Calibration Constant,(num_mand > 0) & (tot_tours == 1),coef_calib_nonmandtours_1_mand_gt0,coef_calib_nonmandtours_1_mand_gt0,coef_calib_nonmandtours_1_mand_gt0,coef_calib_nonmandtours_1_mand_gt0,coef_calib_nonmandtours_1_mand_gt0,coef_calib_nonmandtours_1_mand_gt0,coef_calib_nonmandtours_1_mand_gt0,coef_calib_nonmandtours_1_mand_gt0 +util_calibration_mand_gt0_nonmandtours_2,Mandatory tours > 0 and Non-mandatory tours = 2 Calibration Constant,(num_mand > 0) & (tot_tours == 2),coef_calib_nonmandtours_2_mand_gt0,coef_calib_nonmandtours_2_mand_gt0,coef_calib_nonmandtours_2_mand_gt0,coef_calib_nonmandtours_2_mand_gt0,coef_calib_nonmandtours_2_mand_gt0,coef_calib_nonmandtours_2_mand_gt0,coef_calib_nonmandtours_2_mand_gt0,coef_calib_nonmandtours_2_mand_gt0 +util_calibration_mand_gt0_nonmandtours_gt3,Mandatory tours > 0 and Non-mandatory tours = 3+ Calibration Constant,(num_mand > 0) & (tot_tours >= 3),coef_calib_nonmandtours_gt3_mand_gt0,coef_calib_nonmandtours_gt3_mand_gt0,coef_calib_nonmandtours_gt3_mand_gt0,coef_calib_nonmandtours_gt3_mand_gt0,coef_calib_nonmandtours_gt3_mand_gt0,coef_calib_nonmandtours_gt3_mand_gt0,coef_calib_nonmandtours_gt3_mand_gt0,coef_calib_nonmandtours_gt3_mand_gt0 +util_calibration_mand_0_nonmandtours_2,Mandatory tours = 0 and Non-mandatory tours = 2 Calibration Constant,(num_mand == 0)&(tot_tours == 2),coef_calib_nonmandtours_2_mand_0,coef_calib_nonmandtours_2_mand_0,coef_calib_nonmandtours_2_mand_0,coef_calib_nonmandtours_2_mand_0,coef_calib_nonmandtours_2_mand_0,coef_calib_nonmandtours_2_mand_0,coef_calib_nonmandtours_2_mand_0,coef_calib_nonmandtours_2_mand_0 +util_calibration_mand_0_nonmandtours_3,Mandatory tours = 0 and Non-mandatory tours = 3 Calibration Constant,(num_mand == 0)&(tot_tours == 3),coef_calib_nonmandtours_3_mand_0,coef_calib_nonmandtours_3_mand_0,coef_calib_nonmandtours_3_mand_0,coef_calib_nonmandtours_3_mand_0,coef_calib_nonmandtours_3_mand_0,coef_calib_nonmandtours_3_mand_0,coef_calib_nonmandtours_3_mand_0,coef_calib_nonmandtours_3_mand_0 +util_calibration_mand_0_nonmandtours_gt4,Mandatory tours = 0 and Non-mandatory tours = 4+ Calibration Constant,(num_mand == 0)&(tot_tours >= 4),coef_calib_nonmandtours_gt4_mand_0,coef_calib_nonmandtours_gt4_mand_0,coef_calib_nonmandtours_gt4_mand_0,coef_calib_nonmandtours_gt4_mand_0,coef_calib_nonmandtours_gt4_mand_0,coef_calib_nonmandtours_gt4_mand_0,coef_calib_nonmandtours_gt4_mand_0,coef_calib_nonmandtours_gt4_mand_0 +util_tc_1dayperweek_1,Person that telecommutes 1 day per week,telecommute_frequency=='1_day_week' & tot_tours == 1,coef_tc_1dayperweek_1,coef_tc_1dayperweek_1,coef_tc_1dayperweek_1,0,0,0,0 +util_tc_23dayperweek_1,Person that telecommutes 2 to 3 days per week,telecommute_frequency=='2_3_days_week' & tot_tours == 1,coef_tc_23dayperweek_1,coef_tc_23dayperweek_1,coef_tc_23dayperweek_1,0,0,0,0 +util_tc_4pdayperweek_1,Person that telecommutes 2 to 3 days per week,telecommute_frequency=='4_days_week' & tot_tours == 1,coef_tc_4pdayperweek_1,coef_tc_4pdayperweek_1,coef_tc_4pdayperweek_1,0,0,0,0 +util_tc_1dayperweek_2p,Person that telecommutes 1 day per week,telecommute_frequency=='1_day_week' & tot_tours > 1,coef_tc_1dayperweek_2p,coef_tc_1dayperweek_2p,coef_tc_1dayperweek_2p,0,0,0,0 +util_tc_23dayperweek_2p,Person that telecommutes 2 to 3 days per week,telecommute_frequency=='2_3_days_week' & tot_tours > 1,coef_tc_23dayperweek_2p,coef_tc_23dayperweek_2p,coef_tc_23dayperweek_2p,0,0,0,0 +util_tc_4pdayperweek_2p,Person that telecommutes 2 to 3 days per week,telecommute_frequency=='4_days_week' & tot_tours > 1,coef_tc_4pdayperweek_2p,coef_tc_4pdayperweek_2p,coef_tc_4pdayperweek_2p,0,0,0,0 \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency.yaml b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency.yaml new file mode 100644 index 000000000..239b5a38a --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency.yaml @@ -0,0 +1,42 @@ + +SEGMENT_COL: ptype +SPEC: non_mandatory_tour_frequency.csv + +SPEC_SEGMENTS: + - NAME: PTYPE_FULL + PTYPE: 1 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_FULL.csv + - NAME: PTYPE_PART + PTYPE: 2 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_PART.csv + - NAME: PTYPE_UNIVERSITY + PTYPE: 3 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_UNIVERSITY.csv + - NAME: PTYPE_NONWORK + PTYPE: 4 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_NONWORK.csv + - NAME: PTYPE_RETIRED + PTYPE: 5 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_RETIRED.csv + - NAME: PTYPE_DRIVING + PTYPE: 6 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_DRIVING.csv + - NAME: PTYPE_SCHOOL + PTYPE: 7 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_SCHOOL.csv + - NAME: PTYPE_PRESCHOOL + PTYPE: 8 + COEFFICIENTS: non_mandatory_tour_frequency_coeffs_PTYPE_PRESCHOOL.csv + +annotate_persons: + SPEC: annotate_persons_nmtf + DF: persons + TABLES: + - tours + +preprocessor: + SPEC: non_mandatory_tour_frequency_annotate_persons_preprocessor + DF: persons + TABLES: + - tours +# - accessibility diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_alternatives.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_alternatives.csv new file mode 100644 index 000000000..b9765aa75 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_alternatives.csv @@ -0,0 +1,97 @@ +escort,shopping,othmaint,othdiscr,eatout,social +0,0,0,0,0,0 +0,0,0,1,0,0 +0,0,0,0,0,1 +0,0,0,1,0,1 +0,0,0,0,1,0 +0,0,0,1,1,0 +0,0,0,0,1,1 +0,0,0,1,1,1 +0,0,1,0,0,0 +0,0,1,1,0,0 +0,0,1,0,0,1 +0,0,1,1,0,1 +0,0,1,0,1,0 +0,0,1,1,1,0 +0,0,1,0,1,1 +0,0,1,1,1,1 +0,1,0,0,0,0 +0,1,0,1,0,0 +0,1,0,0,0,1 +0,1,0,1,0,1 +0,1,0,0,1,0 +0,1,0,1,1,0 +0,1,0,0,1,1 +0,1,0,1,1,1 +0,1,1,0,0,0 +0,1,1,1,0,0 +0,1,1,0,0,1 +0,1,1,1,0,1 +0,1,1,0,1,0 +0,1,1,1,1,0 +0,1,1,0,1,1 +0,1,1,1,1,1 +1,0,0,0,0,0 +1,0,0,1,0,0 +1,0,0,0,0,1 +1,0,0,1,0,1 +1,0,0,0,1,0 +1,0,0,1,1,0 +1,0,0,0,1,1 +1,0,0,1,1,1 +1,0,1,0,0,0 +1,0,1,1,0,0 +1,0,1,0,0,1 +1,0,1,1,0,1 +1,0,1,0,1,0 +1,0,1,1,1,0 +1,0,1,0,1,1 +1,0,1,1,1,1 +1,1,0,0,0,0 +1,1,0,1,0,0 +1,1,0,0,0,1 +1,1,0,1,0,1 +1,1,0,0,1,0 +1,1,0,1,1,0 +1,1,0,0,1,1 +1,1,0,1,1,1 +1,1,1,0,0,0 +1,1,1,1,0,0 +1,1,1,0,0,1 +1,1,1,1,0,1 +1,1,1,0,1,0 +1,1,1,1,1,0 +1,1,1,0,1,1 +1,1,1,1,1,1 +2,0,0,0,0,0 +2,0,0,1,0,0 +2,0,0,0,0,1 +2,0,0,1,0,1 +2,0,0,0,1,0 +2,0,0,1,1,0 +2,0,0,0,1,1 +2,0,0,1,1,1 +2,0,1,0,0,0 +2,0,1,1,0,0 +2,0,1,0,0,1 +2,0,1,1,0,1 +2,0,1,0,1,0 +2,0,1,1,1,0 +2,0,1,0,1,1 +2,0,1,1,1,1 +2,1,0,0,0,0 +2,1,0,1,0,0 +2,1,0,0,0,1 +2,1,0,1,0,1 +2,1,0,0,1,0 +2,1,0,1,1,0 +2,1,0,0,1,1 +2,1,0,1,1,1 +2,1,1,0,0,0 +2,1,1,1,0,0 +2,1,1,0,0,1 +2,1,1,1,0,1 +2,1,1,0,1,0 +2,1,1,1,1,0 +2,1,1,0,1,1 +2,1,1,1,1,1 diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_annotate_persons_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_annotate_persons_preprocessor.csv new file mode 100644 index 000000000..fc6616aba --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_annotate_persons_preprocessor.csv @@ -0,0 +1,21 @@ +Description,Target,Expression +#,, +,max_window,person_max_window(persons)/2.25 +,log_max_window,np.log1p(max_window) +,medium_low_income,(persons.income_in_thousands > 20) & (persons.income_in_thousands <= 50) +,medium_high_income,(persons.income_in_thousands > 50) & (persons.income_in_thousands <= 100) +,high_income,(persons.income_in_thousands > 100) +,no_cars,(persons.auto_ownership == 0) +,car_sufficiency,persons.auto_ownership-persons.num_workers +#,, +# UEC file comments says these are joint tour counts per persons but code is for household counts,, +,_JOINT_TOURS,tours[tours.tour_category=='joint'] +,num_hh_joint_tours,"reindex_i(_JOINT_TOURS.groupby('household_id').size(), persons.household_id)" +,num_hh_joint_shop_tours,"reindex_i(_JOINT_TOURS[_JOINT_TOURS.tour_type=='shopping'].groupby('household_id').size(), persons.household_id)" +,num_hh_joint_eatout_tours,"reindex_i(_JOINT_TOURS[_JOINT_TOURS.tour_type=='eatout'].groupby('household_id').size(), persons.household_id)" +,num_hh_joint_maint_tours,"reindex_i(_JOINT_TOURS[_JOINT_TOURS.tour_type=='maint'].groupby('household_id').size(), persons.household_id)" +,num_hh_joint_social_tours,"reindex_i(_JOINT_TOURS[_JOINT_TOURS.tour_type=='social'].groupby('household_id').size(), persons.household_id)" +,num_hh_joint_othdiscr_tours,"reindex_i(_JOINT_TOURS[_JOINT_TOURS.tour_type=='othdiscr'].groupby('household_id').size(), persons.household_id)" +# non_mandatory tour frequency extension,, +,has_mandatory_tour,(persons.num_mand > 0) * 1 +,has_joint_tour,(persons.num_joint_tours > 0) * 1 diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_DRIVING.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_DRIVING.csv new file mode 100644 index 000000000..8f120c97d --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_DRIVING.csv @@ -0,0 +1,217 @@ +coefficient_name,value,constrain +coef_escorting_tour,0,T +coef_discretionary_tour,0,T +coef_shopping_tour,0,T +coef_maintenance_tour,0,T +coef_visiting_or_social_tour,0,T +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-7.1506,F +coef_total_number_of_tours_is_2,-11.1214,F +coef_total_number_of_tours_is_3,-13.175,F +coef_total_number_of_tours_is_4,-999,T +coef_total_number_of_tours_is_5,-999,T +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.234,F +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-0.9231,F +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-6.5835,F +coef_number_of_mandatory_tours_and_tour_frequency_is_4,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,-0.2162,F +coef_number_of_joint_tours_and_tour_frequency_is_2,-0.3587,F +coef_number_of_joint_tours_and_tour_frequency_is_3,-4.2701,F +coef_number_of_joint_tours_and_tour_frequency_is_4,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_shopping_tours,0,T +coef_number_of_joint_maintenance_tours,0,T +coef_number_of_joint_eating_out_tours,0,T +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0,T +coef_logged_maximum_residual_window_tour_frequency_is_0,0,T +coef_logged_maximum_residual_window_tour_frequency_is_1,1.3298,F +coef_logged_maximum_residual_window_tour_frequency_is_2,1.3759,F +coef_logged_maximum_residual_window_tour_frequency_is_3,3.2808,F +coef_logged_maximum_residual_window_tour_frequency_is_4,3.2808,F +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,3.2808,F +coef_mediumlow_income_group_and_tour_frequency_is_1,0,T +coef_mediumlow_income_group_and_tour_frequency_is_2,0,T +coef_mediumlow_income_group_and_tour_frequency_is_3,0,T +coef_mediumlow_income_group_and_tour_frequency_is_4,0,T +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_1,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_2,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_3,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_4,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,0,T +coef_high_income_group_and_tour_frequency_is_1,0,T +coef_high_income_group_and_tour_frequency_is_2,0,T +coef_high_income_group_and_tour_frequency_is_3,0,T +coef_high_income_group_and_tour_frequency_is_4,0,T +coef_high_income_group_and_tour_frequency_is_5_plus,0,T +coef_mediumlow_income_group_and_shopping_tour,0,T +coef_mediumhigh_income_group_and_shopping_tour,0.2443,F +coef_high_income_group_and_shopping_tour,0.2443,F +coef_mediumlow_income_group_and_maintenance_tour,0,T +coef_mediumhigh_income_group_and_maintenance_tour,0.3982,F +coef_high_income_group_and_maintenance_tour,0.3982,F +coef_mediumlow_income_group_and_eating_out_tour,0,T +coef_mediumhigh_income_group_and_eating_out_tour,0.4916,F +coef_high_income_group_and_eating_out_tour,0.4916,F +coef_mediumlow_income_group_and_discretionary_tour,0.9169,F +coef_mediumhigh_income_group_and_discretionary_tour,1.405,F +coef_high_income_group_and_discretionary_tour,2.327,F +coef_mediumlow_income_group_and_visiting_tour,0,T +coef_mediumhigh_income_group_and_visiting_tour,0.2858,F +coef_high_income_group_and_visiting_tour,0.2858,F +coef_female_and_tour_frequency_is_1,0,T +coef_female_and_tour_frequency_is_2,0,T +coef_female_and_tour_frequency_is_3,0,T +coef_female_and_tour_frequency_is_4,0,T +coef_female_and_tour_frequency_is_5,0,T +coef_female_and_escorting_tour,0,T +coef_female_and_shopping_tour,0,T +coef_female_and_maintenance_tour,0,T +coef_female_and_eatingout_tour,0,T +coef_female_and_discretionary_tour,0,T +coef_zero_car_ownership_and_tour_frequency_is_1,-0.6369,F +coef_zero_car_ownership_and_tour_frequency_is_2,-0.6369,F +coef_zero_car_ownership_and_tour_frequency_is_3,-0.6369,F +coef_zero_car_ownership_and_tour_frequency_is_4,-0.6369,F +coef_zero_car_ownership_and_tour_frequency_is_5_plus,-0.6369,F +coef_car_shortage_vs_workers_and_tour_frequency_is_1,-0.6369,F +coef_car_shortage_vs_workers_and_tour_frequency_is_2,-0.6369,F +coef_car_shortage_vs_workers_and_tour_frequency_is_3,-0.6369,F +coef_car_shortage_vs_workers_and_tour_frequency_is_4,-0.6369,F +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-0.6369,F +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0.2902,F +coef_car_surplus_vs_workers_and_tour_frequency_is_2,2.0352,F +coef_car_surplus_vs_workers_and_tour_frequency_is_3,2.0352,F +coef_car_surplus_vs_workers_and_tour_frequency_is_4,2.0352,F +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,2.0352,F +coef_presence_of_non_worker_and_tour_frequency_is_1,0,T +coef_presence_of_non_worker_and_tour_frequency_is_2,-0.6571,F +coef_presence_of_non_worker_and_tour_frequency_is_3,-1.4044,F +coef_presence_of_non_worker_and_tour_frequency_is_4,-1.4044,F +coef_presence_of_non_worker_and_tour_frequency_is_5,-1.4044,F +coef_presence_of_retiree_and_tour_frequency_is_1,0,T +coef_presence_of_retiree_and_tour_frequency_is_2,0,T +coef_presence_of_retiree_and_tour_frequency_is_3,0,T +coef_presence_of_retiree_and_tour_frequency_is_4,0,T +coef_presence_of_retiree_and_tour_frequency_is_5,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,-0.3219,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,-1.0874,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,-1.0874,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,-1.0874,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,-1.0874,F +coef_presence_of_full_time_worker_and_escorting_tour,0,T +coef_presence_of_part_time_worker_and_escorting_tour,0,T +coef_presence_of_non_worker_and_escorting_tour,0,T +coef_presence_of_retiree_and_escorting_tour,0,T +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_school_kid_and_escorting_tour,0,T +coef_at_home_pre_driving_school_kid_and_escorting_tour,0,T +coef_at_home_pre_school_kid_and_escorting_tour,0,T +coef_presence_of_full_time_worker_and_shopping_tour,0,T +coef_presence_of_part_time_worker_and_shopping_tour,0,T +coef_presence_of_non_worker_and_shopping_tour,0,T +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_school_kid_and_shopping_tour,0,T +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,0,T +coef_presence_of_part_time_worker_and_maintenance_tour,0,T +coef_presence_of_non_worker_and_maintenance_tour,0,T +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,0,T +coef_presence_of_part_time_worker_and_eating_out_tour,0,T +coef_presence_of_non_worker_and_eating_out_tour,0,T +coef_presence_of_retiree_and_eating_out_tour,0,T +coef_presence_of_university_student_and_eating_out_tour,0,T +coef_presence_of_driving_school_kid_and_eating_out_tour,-0.6377,F +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,-1.5698,F +coef_presence_of_pre_school_kid_and_eating_out_tour,-0.2987,F +coef_at_home_pre_driving_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_school_kid_and_eating_out_tour,0,T +coef_presence_of_full_time_worker_and_discretionary_tour,0,T +coef_presence_of_part_time_worker_and_discretionary_tour,0,T +coef_presence_of_non_worker_and_discretionary_tour,0,T +coef_presence_of_retiree_and_discretionary_tour,0,T +coef_presence_of_university_student_and_discretionary_tour,-1.2834,F +coef_presence_of_driving_school_kid_and_discretionary_tour,-0.9202,F +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_driving_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_school_kid_and_discretionary_tour,0,T +coef_walk_access_to_retail_and_tour_frequency_is_1,0,T +coef_walk_access_to_retail_and_tour_frequency_is_2,0,T +coef_walk_access_to_retail_and_tour_frequency_is_3,0,T +coef_walk_access_to_retail_and_tour_frequency_is_4,0,T +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_transit_access_to_retail_and_tour_frequency_is_1,0,T +coef_transit_access_to_retail_and_tour_frequency_is_2,0,T +coef_transit_access_to_retail_and_tour_frequency_is_3,0,T +coef_transit_access_to_retail_and_tour_frequency_is_4,0,T +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_auto_access_to_retail_and_tour_frequency_is_1,0.1004,F +coef_auto_access_to_retail_and_tour_frequency_is_2,0.1004,F +coef_auto_access_to_retail_and_tour_frequency_is_3,0.1004,F +coef_auto_access_to_retail_and_tour_frequency_is_4,0.1004,F +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0.1004,F +coef_walk_access_to_retail_and_escorting,0,T +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0,T +coef_walk_access_to_retail_and_shopping,0,T +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0,T +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0,T +coef_auto_access_to_retail_and_maintenance,0,T +coef_walk_access_to_retail_and_eating_out,0,T +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0,T +coef_walk_access_to_retail_and_discretionary,0,T +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0,T +coef_urban_and_tour_frequency_is_1,0,T +coef_urban_and_tour_frequency_is_2,0,T +coef_urban_and_tour_frequency_is_3,0,T +coef_urban_and_tour_frequency_is_4,0,T +coef_urban_and_tour_frequency_is_5_plus,0,T +coef_urban_and_escorting_tour,0,T +coef_urban_and_shopping_tour,0,T +coef_urban_and_maintenance_tour,1.0394,F +coef_urban_and_eatingout_tour,0,T +coef_urban_and_discretionary_tour,0,T +coef_1_escort_tour_constant,-0.4934,F +coef_2_plus_escort_tours_constant,1.4155,F +coef_1_plus_shopping_tours_constant,0.532,F +coef_1_plus_maintenance_tours_constant,-0.4344,F +coef_1_plus_eating_out_tours_constant,-0.0242,F +coef_1_plus_visting_tours_constant,0.2367,F +coef_1_plus_other_discretionary_tours_constant,-0.2602,F +coef_0_auto_household_and_escorting_tour,-2, +coef_calib_nonmandtours_1_mand_gt0,-0.583554487,T +coef_calib_nonmandtours_2_mand_gt0,-5.8999778,T +coef_calib_nonmandtours_gt3_mand_gt0,-0.207059818,T +coef_calib_nonmandtours_2_mand_0,0.087018342,T +coef_calib_nonmandtours_3_mand_0,-0.142844665,T +coef_calib_nonmandtours_gt4_mand_0,-3.578617789,T diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_FULL.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_FULL.csv new file mode 100644 index 000000000..b641b5f2d --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_FULL.csv @@ -0,0 +1,223 @@ +coefficient_name,value,constrain +coef_escorting_tour,0,T +coef_discretionary_tour,0,T +coef_shopping_tour,0,T +coef_maintenance_tour,0,T +coef_visiting_or_social_tour,0,T +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-7.3572,F +coef_total_number_of_tours_is_2,-10.647,F +coef_total_number_of_tours_is_3,-13.5005,F +coef_total_number_of_tours_is_4,-16.3965,F +coef_total_number_of_tours_is_5,-19.6843,F +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-0.8887,F +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-2.3343,F +coef_number_of_mandatory_tours_and_tour_frequency_is_4,-2.3343,F +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-2.3343,F +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,0,T +coef_number_of_joint_tours_and_tour_frequency_is_2,0,T +coef_number_of_joint_tours_and_tour_frequency_is_3,0,T +coef_number_of_joint_tours_and_tour_frequency_is_4,0,T +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,0,T +coef_number_of_joint_shopping_tours,0,T +coef_number_of_joint_maintenance_tours,0,T +coef_number_of_joint_eating_out_tours,-0.5866,F +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0,T +coef_logged_maximum_residual_window_tour_frequency_is_0,0,T +coef_logged_maximum_residual_window_tour_frequency_is_1,1.2562,F +coef_logged_maximum_residual_window_tour_frequency_is_2,1.2868,F +coef_logged_maximum_residual_window_tour_frequency_is_3,1.3993,F +coef_logged_maximum_residual_window_tour_frequency_is_4,1.3993,F +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.3993,F +coef_mediumlow_income_group_and_tour_frequency_is_1,0.4981,F +coef_mediumlow_income_group_and_tour_frequency_is_2,0.8345,F +coef_mediumlow_income_group_and_tour_frequency_is_3,1.0213,F +coef_mediumlow_income_group_and_tour_frequency_is_4,1.0213,F +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,1.0213,F +coef_mediumhigh_income_group_and_tour_frequency_is_1,0.4981,F +coef_mediumhigh_income_group_and_tour_frequency_is_2,0.8345,F +coef_mediumhigh_income_group_and_tour_frequency_is_3,1.0213,F +coef_mediumhigh_income_group_and_tour_frequency_is_4,1.0213,F +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,1.0213,F +coef_high_income_group_and_tour_frequency_is_1,0.5189,F +coef_high_income_group_and_tour_frequency_is_2,1.1336,F +coef_high_income_group_and_tour_frequency_is_3,1.3899,F +coef_high_income_group_and_tour_frequency_is_4,1.3899,F +coef_high_income_group_and_tour_frequency_is_5_plus,1.3899,F +coef_mediumlow_income_group_and_shopping_tour,0,T +coef_mediumhigh_income_group_and_shopping_tour,0,T +coef_high_income_group_and_shopping_tour,0,T +coef_mediumlow_income_group_and_maintenance_tour,0,T +coef_mediumhigh_income_group_and_maintenance_tour,0,T +coef_high_income_group_and_maintenance_tour,0,T +coef_mediumlow_income_group_and_eating_out_tour,0,T +coef_mediumhigh_income_group_and_eating_out_tour,0.5581,F +coef_high_income_group_and_eating_out_tour,0.5581,F +coef_mediumlow_income_group_and_discretionary_tour,0,T +coef_mediumhigh_income_group_and_discretionary_tour,0.2565,F +coef_high_income_group_and_discretionary_tour,0.2565,F +coef_mediumlow_income_group_and_visiting_tour,0,T +coef_mediumhigh_income_group_and_visiting_tour,-0.2423,F +coef_high_income_group_and_visiting_tour,-0.2423,F +coef_female_and_tour_frequency_is_1,-0.0766,F +coef_female_and_tour_frequency_is_2,-0.1062,F +coef_female_and_tour_frequency_is_3,-0.3274,F +coef_female_and_tour_frequency_is_4,-0.3274,F +coef_female_and_tour_frequency_is_5,-0.3274,F +coef_female_and_escorting_tour,0.1824,F +coef_female_and_shopping_tour,0,T +coef_female_and_maintenance_tour,0,T +coef_female_and_eatingout_tour,0,T +coef_female_and_discretionary_tour,0,T +coef_zero_car_ownership_and_tour_frequency_is_1,-0.3486,F +coef_zero_car_ownership_and_tour_frequency_is_2,-0.3486,F +coef_zero_car_ownership_and_tour_frequency_is_3,-0.3486,F +coef_zero_car_ownership_and_tour_frequency_is_4,-0.3486,F +coef_zero_car_ownership_and_tour_frequency_is_5_plus,-0.3486,F +coef_car_shortage_vs_workers_and_tour_frequency_is_1,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_2,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_3,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_4,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0.1304,F +coef_car_surplus_vs_workers_and_tour_frequency_is_2,0.1304,F +coef_car_surplus_vs_workers_and_tour_frequency_is_3,0.1304,F +coef_car_surplus_vs_workers_and_tour_frequency_is_4,0.1304,F +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0.1304,F +coef_presence_of_non_worker_and_tour_frequency_is_1,0,T +coef_presence_of_non_worker_and_tour_frequency_is_2,0,T +coef_presence_of_non_worker_and_tour_frequency_is_3,0,T +coef_presence_of_non_worker_and_tour_frequency_is_4,0,T +coef_presence_of_non_worker_and_tour_frequency_is_5,0,T +coef_presence_of_retiree_and_tour_frequency_is_1,0,T +coef_presence_of_retiree_and_tour_frequency_is_2,0,T +coef_presence_of_retiree_and_tour_frequency_is_3,0,T +coef_presence_of_retiree_and_tour_frequency_is_4,0,T +coef_presence_of_retiree_and_tour_frequency_is_5,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_full_time_worker_and_escorting_tour,0,T +coef_presence_of_part_time_worker_and_escorting_tour,0,T +coef_presence_of_non_worker_and_escorting_tour,-0.4815,F +coef_presence_of_retiree_and_escorting_tour,-0.808,F +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0.3601,F +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.3974,F +coef_presence_of_pre_school_kid_and_escorting_tour,0.6842,F +coef_at_home_pre_driving_school_kid_and_escorting_tour,-0.2746,F +coef_at_home_pre_school_kid_and_escorting_tour,-1.5675,F +coef_presence_of_full_time_worker_and_shopping_tour,-0.3059,F +coef_presence_of_part_time_worker_and_shopping_tour,-0.1541,F +coef_presence_of_non_worker_and_shopping_tour,-0.416,F +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_school_kid_and_shopping_tour,-0.208,F +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,-0.1685,F +coef_presence_of_part_time_worker_and_maintenance_tour,-0.1584,F +coef_presence_of_non_worker_and_maintenance_tour,-0.3237,F +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,-0.3571,F +coef_presence_of_part_time_worker_and_eating_out_tour,0,T +coef_presence_of_non_worker_and_eating_out_tour,-0.2014,F +coef_presence_of_retiree_and_eating_out_tour,-0.5708,F +coef_presence_of_university_student_and_eating_out_tour,0,T +coef_presence_of_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_school_kid_and_eating_out_tour,-0.4225,F +coef_at_home_pre_driving_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_school_kid_and_eating_out_tour,0,T +coef_presence_of_full_time_worker_and_discretionary_tour,-0.667,F +coef_presence_of_part_time_worker_and_discretionary_tour,-0.2102,F +coef_presence_of_non_worker_and_discretionary_tour,-0.4281,F +coef_presence_of_retiree_and_discretionary_tour,-0.9104,F +coef_presence_of_university_student_and_discretionary_tour,-0.8551,F +coef_presence_of_driving_school_kid_and_discretionary_tour,-0.3963,F +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,-0.3959,F +coef_presence_of_pre_school_kid_and_discretionary_tour,-0.5081,F +coef_at_home_pre_driving_school_kid_and_discretionary_tour,-0.4703,F +coef_at_home_pre_school_kid_and_discretionary_tour,-0.4703,F +coef_walk_access_to_retail_and_tour_frequency_is_1,0,T +coef_walk_access_to_retail_and_tour_frequency_is_2,0,T +coef_walk_access_to_retail_and_tour_frequency_is_3,0,T +coef_walk_access_to_retail_and_tour_frequency_is_4,0,T +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_transit_access_to_retail_and_tour_frequency_is_1,0.0226,F +coef_transit_access_to_retail_and_tour_frequency_is_2,0.0226,F +coef_transit_access_to_retail_and_tour_frequency_is_3,0.0226,F +coef_transit_access_to_retail_and_tour_frequency_is_4,0.0226,F +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0.0226,F +coef_auto_access_to_retail_and_tour_frequency_is_1,0,T +coef_auto_access_to_retail_and_tour_frequency_is_2,0,T +coef_auto_access_to_retail_and_tour_frequency_is_3,0,T +coef_auto_access_to_retail_and_tour_frequency_is_4,0,T +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_walk_access_to_retail_and_escorting,0.0451,F +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0,T +coef_walk_access_to_retail_and_shopping,0.033,F +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0.1067,F +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0,T +coef_auto_access_to_retail_and_maintenance,0.0749,F +coef_walk_access_to_retail_and_eating_out,0.145,F +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0,T +coef_walk_access_to_retail_and_discretionary,0.0567,F +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0.0844,F +coef_urban_and_tour_frequency_is_1,0,T +coef_urban_and_tour_frequency_is_2,0,T +coef_urban_and_tour_frequency_is_3,0,T +coef_urban_and_tour_frequency_is_4,0,T +coef_urban_and_tour_frequency_is_5_plus,0,T +coef_urban_and_escorting_tour,-0.4316,F +coef_urban_and_shopping_tour,0,T +coef_urban_and_maintenance_tour,0,T +coef_urban_and_eatingout_tour,0,T +coef_urban_and_discretionary_tour,0,T +coef_1_escort_tour_constant,0.0298,F +coef_2_plus_escort_tours_constant,0.7402,F +coef_1_plus_shopping_tours_constant,0.4774,F +coef_1_plus_maintenance_tours_constant,0.1202,F +coef_1_plus_eating_out_tours_constant,0.0097,F +coef_1_plus_visting_tours_constant,0.0522,F +coef_1_plus_other_discretionary_tours_constant,0.7412,F +coef_0_auto_household_and_escorting_tour,-2,T +coef_calib_nonmandtours_1_mand_gt0,-0.036689277,T +coef_calib_nonmandtours_2_mand_gt0,-0.634072285,T +coef_calib_nonmandtours_gt3_mand_gt0,-1.583991937,T +coef_calib_nonmandtours_2_mand_0,-0.8239916,T +coef_calib_nonmandtours_3_mand_0,-0.826594126,T +coef_calib_nonmandtours_gt4_mand_0,-0.248973454,T +coef_tc_1dayperweek_1,-0.005,F +coef_tc_23dayperweek_1,0.142,F +coef_tc_4pdayperweek_1,-0.406,F +coef_tc_1dayperweek_2p,-0.348,F +coef_tc_23dayperweek_2p,-0.041,F +coef_tc_4pdayperweek_2p,-0.447,F \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_NONWORK.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_NONWORK.csv new file mode 100644 index 000000000..3ad11daf2 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_NONWORK.csv @@ -0,0 +1,217 @@ +coefficient_name,value,constrain +coef_escorting_tour,0,T +coef_discretionary_tour,0,T +coef_shopping_tour,0,T +coef_maintenance_tour,0,T +coef_visiting_or_social_tour,0,T +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-8.9791,F +coef_total_number_of_tours_is_2,-12.0248,F +coef_total_number_of_tours_is_3,-14.8516,F +coef_total_number_of_tours_is_4,-17.7037,F +coef_total_number_of_tours_is_5,-999,T +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.6766,F +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-1.0518,F +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-1.0518,F +coef_number_of_mandatory_tours_and_tour_frequency_is_4,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,-0.1699,F +coef_number_of_joint_tours_and_tour_frequency_is_2,-0.4285,F +coef_number_of_joint_tours_and_tour_frequency_is_3,-0.6551,F +coef_number_of_joint_tours_and_tour_frequency_is_4,-1.0411,F +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-1.0411,F +coef_number_of_joint_shopping_tours,-0.2391,F +coef_number_of_joint_maintenance_tours,0,T +coef_number_of_joint_eating_out_tours,-0.7727,F +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0,T +coef_logged_maximum_residual_window_tour_frequency_is_0,0,T +coef_logged_maximum_residual_window_tour_frequency_is_1,1.7637,F +coef_logged_maximum_residual_window_tour_frequency_is_2,1.7928,F +coef_logged_maximum_residual_window_tour_frequency_is_3,1.7928,F +coef_logged_maximum_residual_window_tour_frequency_is_4,1.7928,F +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.7928,F +coef_mediumlow_income_group_and_tour_frequency_is_1,0.5709,F +coef_mediumlow_income_group_and_tour_frequency_is_2,0.8315,F +coef_mediumlow_income_group_and_tour_frequency_is_3,0.8315,F +coef_mediumlow_income_group_and_tour_frequency_is_4,0.8315,F +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,0.8315,F +coef_mediumhigh_income_group_and_tour_frequency_is_1,0.7426,F +coef_mediumhigh_income_group_and_tour_frequency_is_2,0.8546,F +coef_mediumhigh_income_group_and_tour_frequency_is_3,1.0792,F +coef_mediumhigh_income_group_and_tour_frequency_is_4,1.0792,F +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,1.0792,F +coef_high_income_group_and_tour_frequency_is_1,1.0633,F +coef_high_income_group_and_tour_frequency_is_2,1.0633,F +coef_high_income_group_and_tour_frequency_is_3,1.7742,F +coef_high_income_group_and_tour_frequency_is_4,2.3941,F +coef_high_income_group_and_tour_frequency_is_5_plus,2.3941,F +coef_mediumlow_income_group_and_shopping_tour,0.7734,F +coef_mediumhigh_income_group_and_shopping_tour,0.8906,F +coef_high_income_group_and_shopping_tour,0.9776,F +coef_mediumlow_income_group_and_maintenance_tour,0,T +coef_mediumhigh_income_group_and_maintenance_tour,0,T +coef_high_income_group_and_maintenance_tour,0,T +coef_mediumlow_income_group_and_eating_out_tour,0.2766,F +coef_mediumhigh_income_group_and_eating_out_tour,0.4631,F +coef_high_income_group_and_eating_out_tour,0.7086,F +coef_mediumlow_income_group_and_discretionary_tour,0.1707,F +coef_mediumhigh_income_group_and_discretionary_tour,0.5009,F +coef_high_income_group_and_discretionary_tour,0.8846,F +coef_mediumlow_income_group_and_visiting_tour,-0.267,F +coef_mediumhigh_income_group_and_visiting_tour,-0.267,F +coef_high_income_group_and_visiting_tour,-0.9449,F +coef_female_and_tour_frequency_is_1,0.3902,F +coef_female_and_tour_frequency_is_2,0.5323,F +coef_female_and_tour_frequency_is_3,0.7452,F +coef_female_and_tour_frequency_is_4,1.1294,F +coef_female_and_tour_frequency_is_5,1.1294,F +coef_female_and_escorting_tour,0,T +coef_female_and_shopping_tour,0,T +coef_female_and_maintenance_tour,-0.2464,F +coef_female_and_eatingout_tour,0,T +coef_female_and_discretionary_tour,0,T +coef_zero_car_ownership_and_tour_frequency_is_1,-0.3623,F +coef_zero_car_ownership_and_tour_frequency_is_2,-1.272,F +coef_zero_car_ownership_and_tour_frequency_is_3,-1.9307,F +coef_zero_car_ownership_and_tour_frequency_is_4,-1.9307,F +coef_zero_car_ownership_and_tour_frequency_is_5_plus,-1.9307,F +coef_car_shortage_vs_workers_and_tour_frequency_is_1,-0.3623,F +coef_car_shortage_vs_workers_and_tour_frequency_is_2,-1.272,F +coef_car_shortage_vs_workers_and_tour_frequency_is_3,-1.9307,F +coef_car_shortage_vs_workers_and_tour_frequency_is_4,-1.9307,F +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-1.9307,F +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0.7738,F +coef_car_surplus_vs_workers_and_tour_frequency_is_2,0.7738,F +coef_car_surplus_vs_workers_and_tour_frequency_is_3,0.7738,F +coef_car_surplus_vs_workers_and_tour_frequency_is_4,0.7738,F +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0.7738,F +coef_presence_of_non_worker_and_tour_frequency_is_1,-0.3763,F +coef_presence_of_non_worker_and_tour_frequency_is_2,-0.719,F +coef_presence_of_non_worker_and_tour_frequency_is_3,-1.0229,F +coef_presence_of_non_worker_and_tour_frequency_is_4,-1.0229,F +coef_presence_of_non_worker_and_tour_frequency_is_5,-1.0229,F +coef_presence_of_retiree_and_tour_frequency_is_1,-0.464,F +coef_presence_of_retiree_and_tour_frequency_is_2,-0.4795,F +coef_presence_of_retiree_and_tour_frequency_is_3,-0.4795,F +coef_presence_of_retiree_and_tour_frequency_is_4,-0.4795,F +coef_presence_of_retiree_and_tour_frequency_is_5,-0.4795,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,-0.7161,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,-0.7161,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,-0.7161,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,-0.7161,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-0.7161,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,0.1486,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,0.484,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,0.484,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,0.484,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0.484,F +coef_presence_of_full_time_worker_and_escorting_tour,0.3947,F +coef_presence_of_part_time_worker_and_escorting_tour,-0.5861,F +coef_presence_of_non_worker_and_escorting_tour,0,T +coef_presence_of_retiree_and_escorting_tour,0,T +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.3773,F +coef_presence_of_pre_school_kid_and_escorting_tour,0.7194,F +coef_at_home_pre_driving_school_kid_and_escorting_tour,-1.148,F +coef_at_home_pre_school_kid_and_escorting_tour,-0.1373,F +coef_presence_of_full_time_worker_and_shopping_tour,0,T +coef_presence_of_part_time_worker_and_shopping_tour,0,T +coef_presence_of_non_worker_and_shopping_tour,0,T +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_school_kid_and_shopping_tour,0,T +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,0,T +coef_presence_of_part_time_worker_and_maintenance_tour,0,T +coef_presence_of_non_worker_and_maintenance_tour,0,T +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,-0.4667,F +coef_presence_of_part_time_worker_and_eating_out_tour,0,T +coef_presence_of_non_worker_and_eating_out_tour,-0.4976,F +coef_presence_of_retiree_and_eating_out_tour,-0.6911,F +coef_presence_of_university_student_and_eating_out_tour,0,T +coef_presence_of_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_driving_school_kid_and_eating_out_tour,-0.3926,F +coef_at_home_pre_school_kid_and_eating_out_tour,-0.3926,F +coef_presence_of_full_time_worker_and_discretionary_tour,-0.3545,F +coef_presence_of_part_time_worker_and_discretionary_tour,-0.3545,F +coef_presence_of_non_worker_and_discretionary_tour,0,T +coef_presence_of_retiree_and_discretionary_tour,0,T +coef_presence_of_university_student_and_discretionary_tour,0,T +coef_presence_of_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_driving_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_school_kid_and_discretionary_tour,0,T +coef_walk_access_to_retail_and_tour_frequency_is_1,0.0713,F +coef_walk_access_to_retail_and_tour_frequency_is_2,0.1256,F +coef_walk_access_to_retail_and_tour_frequency_is_3,0.1508,F +coef_walk_access_to_retail_and_tour_frequency_is_4,0.1508,F +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0.1508,F +coef_transit_access_to_retail_and_tour_frequency_is_1,0,T +coef_transit_access_to_retail_and_tour_frequency_is_2,0,T +coef_transit_access_to_retail_and_tour_frequency_is_3,0,T +coef_transit_access_to_retail_and_tour_frequency_is_4,0,T +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_auto_access_to_retail_and_tour_frequency_is_1,0,T +coef_auto_access_to_retail_and_tour_frequency_is_2,0,T +coef_auto_access_to_retail_and_tour_frequency_is_3,0,T +coef_auto_access_to_retail_and_tour_frequency_is_4,0,T +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_walk_access_to_retail_and_escorting,0,T +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0,T +coef_walk_access_to_retail_and_shopping,0.0598,F +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0,T +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0,T +coef_auto_access_to_retail_and_maintenance,0.0956,F +coef_walk_access_to_retail_and_eating_out,0,T +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0,T +coef_walk_access_to_retail_and_discretionary,0.0772,F +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0,T +coef_urban_and_tour_frequency_is_1,0,T +coef_urban_and_tour_frequency_is_2,0,T +coef_urban_and_tour_frequency_is_3,0,T +coef_urban_and_tour_frequency_is_4,0,T +coef_urban_and_tour_frequency_is_5_plus,0,T +coef_urban_and_escorting_tour,0,T +coef_urban_and_shopping_tour,0,T +coef_urban_and_maintenance_tour,0,T +coef_urban_and_eatingout_tour,0,T +coef_urban_and_discretionary_tour,0,T +coef_1_escort_tour_constant,-0.0629,F +coef_2_plus_escort_tours_constant,0.9273,F +coef_1_plus_shopping_tours_constant,0.4683,F +coef_1_plus_maintenance_tours_constant,-0.0653,F +coef_1_plus_eating_out_tours_constant,-0.1429,F +coef_1_plus_visting_tours_constant,-0.1272,F +coef_1_plus_other_discretionary_tours_constant,0.3334,F +coef_0_auto_household_and_escorting_tour,-2,T +coef_calib_nonmandtours_1_mand_gt0,0,T +coef_calib_nonmandtours_2_mand_gt0,0,T +coef_calib_nonmandtours_gt3_mand_gt0,0,T +coef_calib_nonmandtours_2_mand_0,-0.295195996,T +coef_calib_nonmandtours_3_mand_0,-0.883739518,T +coef_calib_nonmandtours_gt4_mand_0,-1.073545808,T diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_PART.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_PART.csv new file mode 100644 index 000000000..d27e5d1f1 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_PART.csv @@ -0,0 +1,223 @@ +coefficient_name,value,constrain +coef_escorting_tour,0,T +coef_discretionary_tour,0,T +coef_shopping_tour,0,T +coef_maintenance_tour,0,T +coef_visiting_or_social_tour,0,T +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-7.6391,F +coef_total_number_of_tours_is_2,-10.4557,F +coef_total_number_of_tours_is_3,-14.0176,F +coef_total_number_of_tours_is_4,-16.9717,F +coef_total_number_of_tours_is_5,-999,T +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.239,F +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-1.8208,F +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-2.5923,F +coef_number_of_mandatory_tours_and_tour_frequency_is_4,-2.5923,F +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-2.5923,F +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,0,T +coef_number_of_joint_tours_and_tour_frequency_is_2,-1.1986,F +coef_number_of_joint_tours_and_tour_frequency_is_3,-1.1986,F +coef_number_of_joint_tours_and_tour_frequency_is_4,-1.1986,F +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_shopping_tours,0,T +coef_number_of_joint_maintenance_tours,0,T +coef_number_of_joint_eating_out_tours,0,T +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0,T +coef_logged_maximum_residual_window_tour_frequency_is_0,0,T +coef_logged_maximum_residual_window_tour_frequency_is_1,1.5748,F +coef_logged_maximum_residual_window_tour_frequency_is_2,2.0026,F +coef_logged_maximum_residual_window_tour_frequency_is_3,2.0026,F +coef_logged_maximum_residual_window_tour_frequency_is_4,2.0026,F +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,2.0026,F +coef_mediumlow_income_group_and_tour_frequency_is_1,0.5981,F +coef_mediumlow_income_group_and_tour_frequency_is_2,0.9178,F +coef_mediumlow_income_group_and_tour_frequency_is_3,1.7539,F +coef_mediumlow_income_group_and_tour_frequency_is_4,1.7539,F +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,1.7539,F +coef_mediumhigh_income_group_and_tour_frequency_is_1,0.8682,F +coef_mediumhigh_income_group_and_tour_frequency_is_2,1.5362,F +coef_mediumhigh_income_group_and_tour_frequency_is_3,1.9331,F +coef_mediumhigh_income_group_and_tour_frequency_is_4,1.9331,F +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,1.9331,F +coef_high_income_group_and_tour_frequency_is_1,0.8682,F +coef_high_income_group_and_tour_frequency_is_2,1.5362,F +coef_high_income_group_and_tour_frequency_is_3,1.9331,F +coef_high_income_group_and_tour_frequency_is_4,1.9331,F +coef_high_income_group_and_tour_frequency_is_5_plus,1.9331,F +coef_mediumlow_income_group_and_shopping_tour,0.4421,F +coef_mediumhigh_income_group_and_shopping_tour,0.4421,F +coef_high_income_group_and_shopping_tour,0.7066,F +coef_mediumlow_income_group_and_maintenance_tour,0.6763,F +coef_mediumhigh_income_group_and_maintenance_tour,0.6763,F +coef_high_income_group_and_maintenance_tour,0.6763,F +coef_mediumlow_income_group_and_eating_out_tour,0,T +coef_mediumhigh_income_group_and_eating_out_tour,0,T +coef_high_income_group_and_eating_out_tour,0,T +coef_mediumlow_income_group_and_discretionary_tour,0.296,F +coef_mediumhigh_income_group_and_discretionary_tour,0.296,F +coef_high_income_group_and_discretionary_tour,0.296,F +coef_mediumlow_income_group_and_visiting_tour,-0.6868,F +coef_mediumhigh_income_group_and_visiting_tour,-0.6868,F +coef_high_income_group_and_visiting_tour,-0.6868,F +coef_female_and_tour_frequency_is_1,0,T +coef_female_and_tour_frequency_is_2,0,T +coef_female_and_tour_frequency_is_3,0,T +coef_female_and_tour_frequency_is_4,0,T +coef_female_and_tour_frequency_is_5,0,T +coef_female_and_escorting_tour,0,T +coef_female_and_shopping_tour,0.4524,F +coef_female_and_maintenance_tour,0,T +coef_female_and_eatingout_tour,0,T +coef_female_and_discretionary_tour,0.3072,F +coef_zero_car_ownership_and_tour_frequency_is_1,-0.5498,F +coef_zero_car_ownership_and_tour_frequency_is_2,-0.5498,F +coef_zero_car_ownership_and_tour_frequency_is_3,-0.5498,F +coef_zero_car_ownership_and_tour_frequency_is_4,-0.5498,F +coef_zero_car_ownership_and_tour_frequency_is_5_plus,-0.5498,F +coef_car_shortage_vs_workers_and_tour_frequency_is_1,-0.5498,F +coef_car_shortage_vs_workers_and_tour_frequency_is_2,-0.5498,F +coef_car_shortage_vs_workers_and_tour_frequency_is_3,-0.5498,F +coef_car_shortage_vs_workers_and_tour_frequency_is_4,-0.5498,F +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-0.5498,F +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_2,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_3,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_4,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_presence_of_non_worker_and_tour_frequency_is_1,0,T +coef_presence_of_non_worker_and_tour_frequency_is_2,0,T +coef_presence_of_non_worker_and_tour_frequency_is_3,0,T +coef_presence_of_non_worker_and_tour_frequency_is_4,0,T +coef_presence_of_non_worker_and_tour_frequency_is_5,0,T +coef_presence_of_retiree_and_tour_frequency_is_1,0,T +coef_presence_of_retiree_and_tour_frequency_is_2,0,T +coef_presence_of_retiree_and_tour_frequency_is_3,0,T +coef_presence_of_retiree_and_tour_frequency_is_4,0,T +coef_presence_of_retiree_and_tour_frequency_is_5,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,-0.1559,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,-0.5681,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,-0.5681,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,-0.5681,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-0.5681,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_full_time_worker_and_escorting_tour,0,T +coef_presence_of_part_time_worker_and_escorting_tour,0,T +coef_presence_of_non_worker_and_escorting_tour,-0.5263,F +coef_presence_of_retiree_and_escorting_tour,-0.7516,F +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0.4164,F +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.5795,F +coef_presence_of_pre_school_kid_and_escorting_tour,0.5414,F +coef_at_home_pre_driving_school_kid_and_escorting_tour,0,T +coef_at_home_pre_school_kid_and_escorting_tour,0,T +coef_presence_of_full_time_worker_and_shopping_tour,0,T +coef_presence_of_part_time_worker_and_shopping_tour,0,T +coef_presence_of_non_worker_and_shopping_tour,0,T +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_school_kid_and_shopping_tour,0,T +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,-0.3131,F +coef_presence_of_part_time_worker_and_maintenance_tour,-0.5621,F +coef_presence_of_non_worker_and_maintenance_tour,0,T +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,0,T +coef_presence_of_part_time_worker_and_eating_out_tour,0,T +coef_presence_of_non_worker_and_eating_out_tour,-0.6545,F +coef_presence_of_retiree_and_eating_out_tour,-1.389,F +coef_presence_of_university_student_and_eating_out_tour,-1.4318,F +coef_presence_of_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_driving_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_school_kid_and_eating_out_tour,0,T +coef_presence_of_full_time_worker_and_discretionary_tour,0,T +coef_presence_of_part_time_worker_and_discretionary_tour,0,T +coef_presence_of_non_worker_and_discretionary_tour,-1.0371,F +coef_presence_of_retiree_and_discretionary_tour,0,T +coef_presence_of_university_student_and_discretionary_tour,0,T +coef_presence_of_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_driving_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_school_kid_and_discretionary_tour,0,T +coef_walk_access_to_retail_and_tour_frequency_is_1,0.0899,F +coef_walk_access_to_retail_and_tour_frequency_is_2,0.1447,F +coef_walk_access_to_retail_and_tour_frequency_is_3,0.3479,F +coef_walk_access_to_retail_and_tour_frequency_is_4,0.3479,F +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0.3479,F +coef_transit_access_to_retail_and_tour_frequency_is_1,0,T +coef_transit_access_to_retail_and_tour_frequency_is_2,0,T +coef_transit_access_to_retail_and_tour_frequency_is_3,0,T +coef_transit_access_to_retail_and_tour_frequency_is_4,0,T +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_auto_access_to_retail_and_tour_frequency_is_1,0,T +coef_auto_access_to_retail_and_tour_frequency_is_2,0,T +coef_auto_access_to_retail_and_tour_frequency_is_3,0,T +coef_auto_access_to_retail_and_tour_frequency_is_4,0,T +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_walk_access_to_retail_and_escorting,0,T +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0,T +coef_walk_access_to_retail_and_shopping,0,T +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0,T +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0,T +coef_auto_access_to_retail_and_maintenance,0,T +coef_walk_access_to_retail_and_eating_out,0,T +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0,T +coef_walk_access_to_retail_and_discretionary,0,T +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0,T +coef_urban_and_tour_frequency_is_1,0,T +coef_urban_and_tour_frequency_is_2,0,T +coef_urban_and_tour_frequency_is_3,0,T +coef_urban_and_tour_frequency_is_4,0,T +coef_urban_and_tour_frequency_is_5_plus,0,T +coef_urban_and_escorting_tour,-0.3929,F +coef_urban_and_shopping_tour,0,T +coef_urban_and_maintenance_tour,0,T +coef_urban_and_eatingout_tour,0,T +coef_urban_and_discretionary_tour,0,T +coef_1_escort_tour_constant,0.5272,F +coef_2_plus_escort_tours_constant,1.5987,F +coef_1_plus_shopping_tours_constant,0.7569,F +coef_1_plus_maintenance_tours_constant,0.5533,F +coef_1_plus_eating_out_tours_constant,0.6914,F +coef_1_plus_visting_tours_constant,0.1405,F +coef_1_plus_other_discretionary_tours_constant,0.7989,F +coef_0_auto_household_and_escorting_tour,-2,T +coef_calib_nonmandtours_1_mand_gt0,-0.960395864,T +coef_calib_nonmandtours_2_mand_gt0,-3.237898437,T +coef_calib_nonmandtours_gt3_mand_gt0,-4.730005533,T +coef_calib_nonmandtours_2_mand_0,-1.289386462,T +coef_calib_nonmandtours_3_mand_0,-2.244022623,T +coef_calib_nonmandtours_gt4_mand_0,-2.739584736,T +coef_tc_1dayperweek_1,-0.005,F +coef_tc_23dayperweek_1,0.142,F +coef_tc_4pdayperweek_1,-0.406,F +coef_tc_1dayperweek_2p,-0.348,F +coef_tc_23dayperweek_2p,-0.041,F +coef_tc_4pdayperweek_2p,-0.447,F \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_PRESCHOOL.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_PRESCHOOL.csv new file mode 100644 index 000000000..d0ed359e2 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_PRESCHOOL.csv @@ -0,0 +1,217 @@ +coefficient_name,value,constrain +coef_escorting_tour,2.491,F +coef_discretionary_tour,0.903,F +coef_shopping_tour,0,T +coef_maintenance_tour,1.022,F +coef_visiting_or_social_tour,0.769,F +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-5.759,F +coef_total_number_of_tours_is_2,-11.517,F +coef_total_number_of_tours_is_3,-17.276,F +coef_total_number_of_tours_is_4,-23.035,F +coef_total_number_of_tours_is_5,-999,T +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_2,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_3,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_4,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,0,T +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,0,T +coef_number_of_joint_tours_and_tour_frequency_is_2,0,T +coef_number_of_joint_tours_and_tour_frequency_is_3,0,T +coef_number_of_joint_tours_and_tour_frequency_is_4,0,T +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,0,T +coef_number_of_joint_shopping_tours,0,T +coef_number_of_joint_maintenance_tours,0,T +coef_number_of_joint_eating_out_tours,0,T +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0,T +coef_logged_maximum_residual_window_tour_frequency_is_0,0,T +coef_logged_maximum_residual_window_tour_frequency_is_1,0,T +coef_logged_maximum_residual_window_tour_frequency_is_2,0,T +coef_logged_maximum_residual_window_tour_frequency_is_3,0,T +coef_logged_maximum_residual_window_tour_frequency_is_4,0,T +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,0,T +coef_mediumlow_income_group_and_tour_frequency_is_1,0,T +coef_mediumlow_income_group_and_tour_frequency_is_2,0,T +coef_mediumlow_income_group_and_tour_frequency_is_3,0,T +coef_mediumlow_income_group_and_tour_frequency_is_4,0,T +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_1,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_2,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_3,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_4,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,0,T +coef_high_income_group_and_tour_frequency_is_1,0,T +coef_high_income_group_and_tour_frequency_is_2,0,T +coef_high_income_group_and_tour_frequency_is_3,0,T +coef_high_income_group_and_tour_frequency_is_4,0,T +coef_high_income_group_and_tour_frequency_is_5_plus,0,T +coef_mediumlow_income_group_and_shopping_tour,0,T +coef_mediumhigh_income_group_and_shopping_tour,0,T +coef_high_income_group_and_shopping_tour,0,T +coef_mediumlow_income_group_and_maintenance_tour,0,T +coef_mediumhigh_income_group_and_maintenance_tour,0,T +coef_high_income_group_and_maintenance_tour,0,T +coef_mediumlow_income_group_and_eating_out_tour,0,T +coef_mediumhigh_income_group_and_eating_out_tour,0,T +coef_high_income_group_and_eating_out_tour,0,T +coef_mediumlow_income_group_and_discretionary_tour,0,T +coef_mediumhigh_income_group_and_discretionary_tour,0,T +coef_high_income_group_and_discretionary_tour,0,T +coef_mediumlow_income_group_and_visiting_tour,0,T +coef_mediumhigh_income_group_and_visiting_tour,0,T +coef_high_income_group_and_visiting_tour,0,T +coef_female_and_tour_frequency_is_1,0,T +coef_female_and_tour_frequency_is_2,0,T +coef_female_and_tour_frequency_is_3,0,T +coef_female_and_tour_frequency_is_4,0,T +coef_female_and_tour_frequency_is_5,0,T +coef_female_and_escorting_tour,0,T +coef_female_and_shopping_tour,0,T +coef_female_and_maintenance_tour,0,T +coef_female_and_eatingout_tour,0,T +coef_female_and_discretionary_tour,0,T +coef_zero_car_ownership_and_tour_frequency_is_1,0,T +coef_zero_car_ownership_and_tour_frequency_is_2,0,T +coef_zero_car_ownership_and_tour_frequency_is_3,0,T +coef_zero_car_ownership_and_tour_frequency_is_4,0,T +coef_zero_car_ownership_and_tour_frequency_is_5_plus,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_1,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_2,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_3,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_4,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_2,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_3,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_4,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_presence_of_non_worker_and_tour_frequency_is_1,0,T +coef_presence_of_non_worker_and_tour_frequency_is_2,0,T +coef_presence_of_non_worker_and_tour_frequency_is_3,0,T +coef_presence_of_non_worker_and_tour_frequency_is_4,0,T +coef_presence_of_non_worker_and_tour_frequency_is_5,0,T +coef_presence_of_retiree_and_tour_frequency_is_1,0,T +coef_presence_of_retiree_and_tour_frequency_is_2,0,T +coef_presence_of_retiree_and_tour_frequency_is_3,0,T +coef_presence_of_retiree_and_tour_frequency_is_4,0,T +coef_presence_of_retiree_and_tour_frequency_is_5,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_full_time_worker_and_escorting_tour,-0.893,F +coef_presence_of_part_time_worker_and_escorting_tour,0,T +coef_presence_of_non_worker_and_escorting_tour,0.89,F +coef_presence_of_retiree_and_escorting_tour,0,T +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_school_kid_and_escorting_tour,0,T +coef_at_home_pre_driving_school_kid_and_escorting_tour,0,T +coef_at_home_pre_school_kid_and_escorting_tour,0,T +coef_presence_of_full_time_worker_and_shopping_tour,0,T +coef_presence_of_part_time_worker_and_shopping_tour,1.155,F +coef_presence_of_non_worker_and_shopping_tour,0.808,F +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_school_kid_and_shopping_tour,0,T +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,0,T +coef_presence_of_part_time_worker_and_maintenance_tour,0,T +coef_presence_of_non_worker_and_maintenance_tour,0,T +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,0,T +coef_presence_of_part_time_worker_and_eating_out_tour,1.037,F +coef_presence_of_non_worker_and_eating_out_tour,1.157,F +coef_presence_of_retiree_and_eating_out_tour,0,T +coef_presence_of_university_student_and_eating_out_tour,0,T +coef_presence_of_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_driving_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_school_kid_and_eating_out_tour,0,T +coef_presence_of_full_time_worker_and_discretionary_tour,0,T +coef_presence_of_part_time_worker_and_discretionary_tour,0,T +coef_presence_of_non_worker_and_discretionary_tour,0.791,F +coef_presence_of_retiree_and_discretionary_tour,0,T +coef_presence_of_university_student_and_discretionary_tour,0,T +coef_presence_of_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_driving_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_school_kid_and_discretionary_tour,0,T +coef_walk_access_to_retail_and_tour_frequency_is_1,0,T +coef_walk_access_to_retail_and_tour_frequency_is_2,0,T +coef_walk_access_to_retail_and_tour_frequency_is_3,0,T +coef_walk_access_to_retail_and_tour_frequency_is_4,0,T +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_transit_access_to_retail_and_tour_frequency_is_1,0,T +coef_transit_access_to_retail_and_tour_frequency_is_2,0,T +coef_transit_access_to_retail_and_tour_frequency_is_3,0,T +coef_transit_access_to_retail_and_tour_frequency_is_4,0,T +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_auto_access_to_retail_and_tour_frequency_is_1,0,T +coef_auto_access_to_retail_and_tour_frequency_is_2,0,T +coef_auto_access_to_retail_and_tour_frequency_is_3,0,T +coef_auto_access_to_retail_and_tour_frequency_is_4,0,T +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_walk_access_to_retail_and_escorting,0,T +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0,T +coef_walk_access_to_retail_and_shopping,0,T +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0,T +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0,T +coef_auto_access_to_retail_and_maintenance,0,T +coef_walk_access_to_retail_and_eating_out,0,T +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0,T +coef_walk_access_to_retail_and_discretionary,0,T +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0,T +coef_urban_and_tour_frequency_is_1,0,T +coef_urban_and_tour_frequency_is_2,0,T +coef_urban_and_tour_frequency_is_3,0,T +coef_urban_and_tour_frequency_is_4,0,T +coef_urban_and_tour_frequency_is_5_plus,0,T +coef_urban_and_escorting_tour,0,T +coef_urban_and_shopping_tour,0,T +coef_urban_and_maintenance_tour,0,T +coef_urban_and_eatingout_tour,0,T +coef_urban_and_discretionary_tour,0,T +coef_1_escort_tour_constant,0.3622,F +coef_2_plus_escort_tours_constant,2.2219,F +coef_1_plus_shopping_tours_constant,1.6919,F +coef_1_plus_maintenance_tours_constant,0.6788,F +coef_1_plus_eating_out_tours_constant,0.9612,F +coef_1_plus_visting_tours_constant,0.4424,F +coef_1_plus_other_discretionary_tours_constant,1.4935,F +coef_0_auto_household_and_escorting_tour,-2,T +coef_calib_nonmandtours_1_mand_gt0,0,T +coef_calib_nonmandtours_2_mand_gt0,0,T +coef_calib_nonmandtours_gt3_mand_gt0,0,T +coef_calib_nonmandtours_2_mand_0,-0.228121764,T +coef_calib_nonmandtours_3_mand_0,-0.38783141,T +coef_calib_nonmandtours_gt4_mand_0,1.093947549,T diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_RETIRED.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_RETIRED.csv new file mode 100644 index 000000000..0be070740 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_RETIRED.csv @@ -0,0 +1,217 @@ +coefficient_name,value,constrain +coef_escorting_tour,0,T +coef_discretionary_tour,0,T +coef_shopping_tour,0,T +coef_maintenance_tour,0,T +coef_visiting_or_social_tour,0,T +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-8.5684,F +coef_total_number_of_tours_is_2,-12.7416,F +coef_total_number_of_tours_is_3,-15.0978,F +coef_total_number_of_tours_is_4,-19.5439,F +coef_total_number_of_tours_is_5,-20.7897,F +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-5.0196,F +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-5.0196,F +coef_number_of_mandatory_tours_and_tour_frequency_is_4,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,0,T +coef_number_of_joint_tours_and_tour_frequency_is_2,-0.95,F +coef_number_of_joint_tours_and_tour_frequency_is_3,-7.143,F +coef_number_of_joint_tours_and_tour_frequency_is_4,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_shopping_tours,-0.8072,F +coef_number_of_joint_maintenance_tours,0,T +coef_number_of_joint_eating_out_tours,0,T +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0,T +coef_logged_maximum_residual_window_tour_frequency_is_0,0,T +coef_logged_maximum_residual_window_tour_frequency_is_1,1.8357,F +coef_logged_maximum_residual_window_tour_frequency_is_2,2.2707,F +coef_logged_maximum_residual_window_tour_frequency_is_3,4.4023,F +coef_logged_maximum_residual_window_tour_frequency_is_4,4.4023,F +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,4.4023,F +coef_mediumlow_income_group_and_tour_frequency_is_1,0,T +coef_mediumlow_income_group_and_tour_frequency_is_2,0,T +coef_mediumlow_income_group_and_tour_frequency_is_3,0,T +coef_mediumlow_income_group_and_tour_frequency_is_4,0,T +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_1,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_2,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_3,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_4,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,0,T +coef_high_income_group_and_tour_frequency_is_1,0,T +coef_high_income_group_and_tour_frequency_is_2,0,T +coef_high_income_group_and_tour_frequency_is_3,0,T +coef_high_income_group_and_tour_frequency_is_4,0,T +coef_high_income_group_and_tour_frequency_is_5_plus,0,T +coef_mediumlow_income_group_and_shopping_tour,1.0949,F +coef_mediumhigh_income_group_and_shopping_tour,1.0949,F +coef_high_income_group_and_shopping_tour,1.0949,F +coef_mediumlow_income_group_and_maintenance_tour,0.7648,F +coef_mediumhigh_income_group_and_maintenance_tour,0.7648,F +coef_high_income_group_and_maintenance_tour,1.3795,F +coef_mediumlow_income_group_and_eating_out_tour,0.9769,F +coef_mediumhigh_income_group_and_eating_out_tour,1.181,F +coef_high_income_group_and_eating_out_tour,1.4842,F +coef_mediumlow_income_group_and_discretionary_tour,1.0095,F +coef_mediumhigh_income_group_and_discretionary_tour,1.0095,F +coef_high_income_group_and_discretionary_tour,1.0095,F +coef_mediumlow_income_group_and_visiting_tour,0,T +coef_mediumhigh_income_group_and_visiting_tour,-0.4368,F +coef_high_income_group_and_visiting_tour,-0.5137,F +coef_female_and_tour_frequency_is_1,-0.9348,F +coef_female_and_tour_frequency_is_2,-1.3028,F +coef_female_and_tour_frequency_is_3,-2.266,F +coef_female_and_tour_frequency_is_4,-2.266,F +coef_female_and_tour_frequency_is_5,-2.266,F +coef_female_and_escorting_tour,0,T +coef_female_and_shopping_tour,0.9688,F +coef_female_and_maintenance_tour,0.7424,F +coef_female_and_eatingout_tour,0,T +coef_female_and_discretionary_tour,0.4954,F +coef_zero_car_ownership_and_tour_frequency_is_1,0,T +coef_zero_car_ownership_and_tour_frequency_is_2,0,T +coef_zero_car_ownership_and_tour_frequency_is_3,0,T +coef_zero_car_ownership_and_tour_frequency_is_4,0,T +coef_zero_car_ownership_and_tour_frequency_is_5_plus,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_1,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_2,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_3,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_4,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0.7965,F +coef_car_surplus_vs_workers_and_tour_frequency_is_2,2.1302,F +coef_car_surplus_vs_workers_and_tour_frequency_is_3,2.1302,F +coef_car_surplus_vs_workers_and_tour_frequency_is_4,2.1302,F +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,2.1302,F +coef_presence_of_non_worker_and_tour_frequency_is_1,0.224,F +coef_presence_of_non_worker_and_tour_frequency_is_2,0.2436,F +coef_presence_of_non_worker_and_tour_frequency_is_3,0.62,F +coef_presence_of_non_worker_and_tour_frequency_is_4,3.3742,F +coef_presence_of_non_worker_and_tour_frequency_is_5,3.3742,F +coef_presence_of_retiree_and_tour_frequency_is_1,-0.4458,F +coef_presence_of_retiree_and_tour_frequency_is_2,-0.5315,F +coef_presence_of_retiree_and_tour_frequency_is_3,-0.5315,F +coef_presence_of_retiree_and_tour_frequency_is_4,-0.5315,F +coef_presence_of_retiree_and_tour_frequency_is_5,-0.5315,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_full_time_worker_and_escorting_tour,0,T +coef_presence_of_part_time_worker_and_escorting_tour,0,T +coef_presence_of_non_worker_and_escorting_tour,0,T +coef_presence_of_retiree_and_escorting_tour,0,T +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_driving_school_kid_and_escorting_tour,1.4903,F +coef_presence_of_pre_school_kid_and_escorting_tour,0.5027,F +coef_at_home_pre_driving_school_kid_and_escorting_tour,0,T +coef_at_home_pre_school_kid_and_escorting_tour,0,T +coef_presence_of_full_time_worker_and_shopping_tour,-0.3609,F +coef_presence_of_part_time_worker_and_shopping_tour,0,T +coef_presence_of_non_worker_and_shopping_tour,0,T +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_school_kid_and_shopping_tour,0,T +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,0,T +coef_presence_of_part_time_worker_and_maintenance_tour,0,T +coef_presence_of_non_worker_and_maintenance_tour,0,T +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,-0.788,F +coef_presence_of_part_time_worker_and_eating_out_tour,-0.788,F +coef_presence_of_non_worker_and_eating_out_tour,-0.788,F +coef_presence_of_retiree_and_eating_out_tour,-0.9282,F +coef_presence_of_university_student_and_eating_out_tour,0,T +coef_presence_of_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_driving_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_school_kid_and_eating_out_tour,0,T +coef_presence_of_full_time_worker_and_discretionary_tour,-0.4835,F +coef_presence_of_part_time_worker_and_discretionary_tour,0,T +coef_presence_of_non_worker_and_discretionary_tour,-0.5603,F +coef_presence_of_retiree_and_discretionary_tour,0,T +coef_presence_of_university_student_and_discretionary_tour,0,T +coef_presence_of_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_driving_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_school_kid_and_discretionary_tour,0,T +coef_walk_access_to_retail_and_tour_frequency_is_1,0.0616,F +coef_walk_access_to_retail_and_tour_frequency_is_2,0.0616,F +coef_walk_access_to_retail_and_tour_frequency_is_3,0.0616,F +coef_walk_access_to_retail_and_tour_frequency_is_4,0.0616,F +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0.0616,F +coef_transit_access_to_retail_and_tour_frequency_is_1,0,T +coef_transit_access_to_retail_and_tour_frequency_is_2,0,T +coef_transit_access_to_retail_and_tour_frequency_is_3,0,T +coef_transit_access_to_retail_and_tour_frequency_is_4,0,T +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_auto_access_to_retail_and_tour_frequency_is_1,0,T +coef_auto_access_to_retail_and_tour_frequency_is_2,0,T +coef_auto_access_to_retail_and_tour_frequency_is_3,0,T +coef_auto_access_to_retail_and_tour_frequency_is_4,0,T +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_walk_access_to_retail_and_escorting,0,T +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0,T +coef_walk_access_to_retail_and_shopping,0,T +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0,T +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0,T +coef_auto_access_to_retail_and_maintenance,0,T +coef_walk_access_to_retail_and_eating_out,0,T +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0,T +coef_walk_access_to_retail_and_discretionary,0,T +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0,T +coef_urban_and_tour_frequency_is_1,0,T +coef_urban_and_tour_frequency_is_2,0,T +coef_urban_and_tour_frequency_is_3,0,T +coef_urban_and_tour_frequency_is_4,0,T +coef_urban_and_tour_frequency_is_5_plus,0,T +coef_urban_and_escorting_tour,0,T +coef_urban_and_shopping_tour,0,T +coef_urban_and_maintenance_tour,0,T +coef_urban_and_eatingout_tour,0,T +coef_urban_and_discretionary_tour,0,T +coef_1_escort_tour_constant,-0.3992,F +coef_2_plus_escort_tours_constant,0.5175,F +coef_1_plus_shopping_tours_constant,0.5947,F +coef_1_plus_maintenance_tours_constant,0.1046,F +coef_1_plus_eating_out_tours_constant,0.0245,F +coef_1_plus_visting_tours_constant,0.2789,F +coef_1_plus_other_discretionary_tours_constant,0.4282,F +coef_0_auto_household_and_escorting_tour,-2,T +coef_calib_nonmandtours_1_mand_gt0,0,T +coef_calib_nonmandtours_2_mand_gt0,0,T +coef_calib_nonmandtours_gt3_mand_gt0,0,T +coef_calib_nonmandtours_2_mand_0,-0.601049675,T +coef_calib_nonmandtours_3_mand_0,-1.047585076,T +coef_calib_nonmandtours_gt4_mand_0,-0.995317712,T diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_SCHOOL.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_SCHOOL.csv new file mode 100644 index 000000000..106322e29 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_SCHOOL.csv @@ -0,0 +1,217 @@ +coefficient_name,value,constrain +coef_escorting_tour,0,T +coef_discretionary_tour,0,T +coef_shopping_tour,0,T +coef_maintenance_tour,0,T +coef_visiting_or_social_tour,0,T +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-7.4863,F +coef_total_number_of_tours_is_2,-10.718,F +coef_total_number_of_tours_is_3,-13.7884,F +coef_total_number_of_tours_is_4,-999,T +coef_total_number_of_tours_is_5,-999,T +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-1.0331,F +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-2.7445,F +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-2.7445,F +coef_number_of_mandatory_tours_and_tour_frequency_is_4,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,-0.6149,F +coef_number_of_joint_tours_and_tour_frequency_is_2,-0.6149,F +coef_number_of_joint_tours_and_tour_frequency_is_3,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_4,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_shopping_tours,0,T +coef_number_of_joint_maintenance_tours,-1.3476,F +coef_number_of_joint_eating_out_tours,0,T +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0,T +coef_logged_maximum_residual_window_tour_frequency_is_0,0,T +coef_logged_maximum_residual_window_tour_frequency_is_1,1.5603,F +coef_logged_maximum_residual_window_tour_frequency_is_2,1.5603,F +coef_logged_maximum_residual_window_tour_frequency_is_3,1.5603,F +coef_logged_maximum_residual_window_tour_frequency_is_4,1.5603,F +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.5603,F +coef_mediumlow_income_group_and_tour_frequency_is_1,1.0873,F +coef_mediumlow_income_group_and_tour_frequency_is_2,1.0873,F +coef_mediumlow_income_group_and_tour_frequency_is_3,1.0873,F +coef_mediumlow_income_group_and_tour_frequency_is_4,1.0873,F +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,1.0873,F +coef_mediumhigh_income_group_and_tour_frequency_is_1,1.5197,F +coef_mediumhigh_income_group_and_tour_frequency_is_2,1.5197,F +coef_mediumhigh_income_group_and_tour_frequency_is_3,1.5197,F +coef_mediumhigh_income_group_and_tour_frequency_is_4,1.5197,F +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,1.5197,F +coef_high_income_group_and_tour_frequency_is_1,2.0175,F +coef_high_income_group_and_tour_frequency_is_2,2.0175,F +coef_high_income_group_and_tour_frequency_is_3,2.0175,F +coef_high_income_group_and_tour_frequency_is_4,2.0175,F +coef_high_income_group_and_tour_frequency_is_5_plus,2.0175,F +coef_mediumlow_income_group_and_shopping_tour,-0.6506,F +coef_mediumhigh_income_group_and_shopping_tour,-0.6506,F +coef_high_income_group_and_shopping_tour,-0.6506,F +coef_mediumlow_income_group_and_maintenance_tour,0,T +coef_mediumhigh_income_group_and_maintenance_tour,0,T +coef_high_income_group_and_maintenance_tour,0,T +coef_mediumlow_income_group_and_eating_out_tour,-0.701,F +coef_mediumhigh_income_group_and_eating_out_tour,-0.701,F +coef_high_income_group_and_eating_out_tour,-0.701,F +coef_mediumlow_income_group_and_discretionary_tour,0,T +coef_mediumhigh_income_group_and_discretionary_tour,0,T +coef_high_income_group_and_discretionary_tour,0,T +coef_mediumlow_income_group_and_visiting_tour,0,T +coef_mediumhigh_income_group_and_visiting_tour,0,T +coef_high_income_group_and_visiting_tour,0,T +coef_female_and_tour_frequency_is_1,0,T +coef_female_and_tour_frequency_is_2,0,T +coef_female_and_tour_frequency_is_3,0,T +coef_female_and_tour_frequency_is_4,0,T +coef_female_and_tour_frequency_is_5,0,T +coef_female_and_escorting_tour,0,T +coef_female_and_shopping_tour,0,T +coef_female_and_maintenance_tour,0,T +coef_female_and_eatingout_tour,0,T +coef_female_and_discretionary_tour,0,T +coef_zero_car_ownership_and_tour_frequency_is_1,0,T +coef_zero_car_ownership_and_tour_frequency_is_2,0,T +coef_zero_car_ownership_and_tour_frequency_is_3,0,T +coef_zero_car_ownership_and_tour_frequency_is_4,0,T +coef_zero_car_ownership_and_tour_frequency_is_5_plus,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_1,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_2,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_3,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_4,0,T +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_2,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_3,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_4,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_presence_of_non_worker_and_tour_frequency_is_1,0.2177,F +coef_presence_of_non_worker_and_tour_frequency_is_2,0.2177,F +coef_presence_of_non_worker_and_tour_frequency_is_3,0.2177,F +coef_presence_of_non_worker_and_tour_frequency_is_4,0.2177,F +coef_presence_of_non_worker_and_tour_frequency_is_5,0.2177,F +coef_presence_of_retiree_and_tour_frequency_is_1,0,T +coef_presence_of_retiree_and_tour_frequency_is_2,0,T +coef_presence_of_retiree_and_tour_frequency_is_3,0,T +coef_presence_of_retiree_and_tour_frequency_is_4,0,T +coef_presence_of_retiree_and_tour_frequency_is_5,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,-0.4439,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,-0.4439,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,-0.4439,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,-0.4439,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-0.4439,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,-0.2264,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,-0.2264,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,-0.2264,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,-0.2264,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,-0.2264,F +coef_presence_of_full_time_worker_and_escorting_tour,0,T +coef_presence_of_part_time_worker_and_escorting_tour,0,T +coef_presence_of_non_worker_and_escorting_tour,0,T +coef_presence_of_retiree_and_escorting_tour,0,T +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_school_kid_and_escorting_tour,0,T +coef_at_home_pre_driving_school_kid_and_escorting_tour,0,T +coef_at_home_pre_school_kid_and_escorting_tour,0,T +coef_presence_of_full_time_worker_and_shopping_tour,0,T +coef_presence_of_part_time_worker_and_shopping_tour,0,T +coef_presence_of_non_worker_and_shopping_tour,-0.645,F +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0.9365,F +coef_presence_of_pre_school_kid_and_shopping_tour,0,T +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,0,T +coef_presence_of_part_time_worker_and_maintenance_tour,0,T +coef_presence_of_non_worker_and_maintenance_tour,0,T +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,0,T +coef_presence_of_part_time_worker_and_eating_out_tour,0,T +coef_presence_of_non_worker_and_eating_out_tour,-1.3074,F +coef_presence_of_retiree_and_eating_out_tour,0,T +coef_presence_of_university_student_and_eating_out_tour,0,T +coef_presence_of_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_driving_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_school_kid_and_eating_out_tour,0,T +coef_presence_of_full_time_worker_and_discretionary_tour,0.7526,F +coef_presence_of_part_time_worker_and_discretionary_tour,0.3721,F +coef_presence_of_non_worker_and_discretionary_tour,0,T +coef_presence_of_retiree_and_discretionary_tour,0,T +coef_presence_of_university_student_and_discretionary_tour,0,T +coef_presence_of_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_driving_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_school_kid_and_discretionary_tour,0,T +coef_walk_access_to_retail_and_tour_frequency_is_1,0,T +coef_walk_access_to_retail_and_tour_frequency_is_2,0,T +coef_walk_access_to_retail_and_tour_frequency_is_3,0,T +coef_walk_access_to_retail_and_tour_frequency_is_4,0,T +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_transit_access_to_retail_and_tour_frequency_is_1,0,T +coef_transit_access_to_retail_and_tour_frequency_is_2,0,T +coef_transit_access_to_retail_and_tour_frequency_is_3,0,T +coef_transit_access_to_retail_and_tour_frequency_is_4,0,T +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_auto_access_to_retail_and_tour_frequency_is_1,0,T +coef_auto_access_to_retail_and_tour_frequency_is_2,0,T +coef_auto_access_to_retail_and_tour_frequency_is_3,0,T +coef_auto_access_to_retail_and_tour_frequency_is_4,0,T +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_walk_access_to_retail_and_escorting,0,T +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0.0629,F +coef_walk_access_to_retail_and_shopping,0,T +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0,T +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0,T +coef_auto_access_to_retail_and_maintenance,0,T +coef_walk_access_to_retail_and_eating_out,0.0738,F +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0,T +coef_walk_access_to_retail_and_discretionary,0,T +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0,T +coef_urban_and_tour_frequency_is_1,0,T +coef_urban_and_tour_frequency_is_2,0,T +coef_urban_and_tour_frequency_is_3,0,T +coef_urban_and_tour_frequency_is_4,0,T +coef_urban_and_tour_frequency_is_5_plus,0,T +coef_urban_and_escorting_tour,0.4352,F +coef_urban_and_shopping_tour,0,T +coef_urban_and_maintenance_tour,0,T +coef_urban_and_eatingout_tour,0,T +coef_urban_and_discretionary_tour,0,T +coef_1_escort_tour_constant,-0.7551,F +coef_2_plus_escort_tours_constant,-0.0086,F +coef_1_plus_shopping_tours_constant,0.4783,F +coef_1_plus_maintenance_tours_constant,-0.506,F +coef_1_plus_eating_out_tours_constant,1.1145,F +coef_1_plus_visting_tours_constant,-0.4006,F +coef_1_plus_other_discretionary_tours_constant,0.4634,F +coef_0_auto_household_and_escorting_tour,-2,T +coef_calib_nonmandtours_1_mand_gt0,-0.156305899,T +coef_calib_nonmandtours_2_mand_gt0,-1.611733765,T +coef_calib_nonmandtours_gt3_mand_gt0,0.625561203,T +coef_calib_nonmandtours_2_mand_0,-1.688433324,T +coef_calib_nonmandtours_3_mand_0,-0.631744091,T +coef_calib_nonmandtours_gt4_mand_0,3.754622037,T diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_UNIVERSITY.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_UNIVERSITY.csv new file mode 100644 index 000000000..75f38dba4 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_coeffs_PTYPE_UNIVERSITY.csv @@ -0,0 +1,223 @@ +coefficient_name,value,constrain +coef_escorting_tour,0,T +coef_discretionary_tour,0,T +coef_shopping_tour,0,T +coef_maintenance_tour,0,T +coef_visiting_or_social_tour,0,T +coef_eating_out_tour,0,T +coef_total_number_of_tours_is_0_no_prior_tours,-999,T +coef_total_number_of_tours_is_0_prior_tours,0,T +coef_total_number_of_tours_is_1,-6.2138,F +coef_total_number_of_tours_is_2,-8.908,F +coef_total_number_of_tours_is_3,-12.3261,F +coef_total_number_of_tours_is_4,-15.8114,F +coef_total_number_of_tours_is_5,-999,T +coef_total_number_of_tours_is_6_plus,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_0,0,T +coef_number_of_mandatory_tours_and_tour_frequency_is_1,-0.1852,F +coef_number_of_mandatory_tours_and_tour_frequency_is_2,-0.8753,F +coef_number_of_mandatory_tours_and_tour_frequency_is_3,-1.6158,F +coef_number_of_mandatory_tours_and_tour_frequency_is_4,-999,T +coef_number_of_mandatory_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_0,0,T +coef_number_of_joint_tours_and_tour_frequency_is_1,0,T +coef_number_of_joint_tours_and_tour_frequency_is_2,-0.3153,F +coef_number_of_joint_tours_and_tour_frequency_is_3,-0.7351,F +coef_number_of_joint_tours_and_tour_frequency_is_4,-999,T +coef_number_of_joint_tours_and_tour_frequency_is_5_plus,-999,T +coef_number_of_joint_shopping_tours,-0.713,F +coef_number_of_joint_maintenance_tours,0,T +coef_number_of_joint_eating_out_tours,0,T +coef_number_of_joint_visit_tours,0,T +coef_number_of_joint_discretionary_tours,0.6713,F +coef_logged_maximum_residual_window_tour_frequency_is_0,1.1858,F +coef_logged_maximum_residual_window_tour_frequency_is_1,1.4842,F +coef_logged_maximum_residual_window_tour_frequency_is_2,1.4842,F +coef_logged_maximum_residual_window_tour_frequency_is_3,1.4842,F +coef_logged_maximum_residual_window_tour_frequency_is_4,1.4842,F +coef_logged_maximum_residual_window_tour_frequency_is_5_plus,1.4842,F +coef_mediumlow_income_group_and_tour_frequency_is_1,0,T +coef_mediumlow_income_group_and_tour_frequency_is_2,0,T +coef_mediumlow_income_group_and_tour_frequency_is_3,0,T +coef_mediumlow_income_group_and_tour_frequency_is_4,0,T +coef_mediumlow_income_group_and_tour_frequency_is_5_plus,0,T +coef_mediumhigh_income_group_and_tour_frequency_is_1,0.1109,F +coef_mediumhigh_income_group_and_tour_frequency_is_2,0.3914,F +coef_mediumhigh_income_group_and_tour_frequency_is_3,0.6137,F +coef_mediumhigh_income_group_and_tour_frequency_is_4,0.6137,F +coef_mediumhigh_income_group_and_tour_frequency_is_5_plus,0.6137,F +coef_high_income_group_and_tour_frequency_is_1,0.3986,F +coef_high_income_group_and_tour_frequency_is_2,0.8009,F +coef_high_income_group_and_tour_frequency_is_3,0.8254,F +coef_high_income_group_and_tour_frequency_is_4,0.8254,F +coef_high_income_group_and_tour_frequency_is_5_plus,0.8254,F +coef_mediumlow_income_group_and_shopping_tour,0.5693,F +coef_mediumhigh_income_group_and_shopping_tour,0.5693,F +coef_high_income_group_and_shopping_tour,0.5693,F +coef_mediumlow_income_group_and_maintenance_tour,0,T +coef_mediumhigh_income_group_and_maintenance_tour,0,T +coef_high_income_group_and_maintenance_tour,0,T +coef_mediumlow_income_group_and_eating_out_tour,0,T +coef_mediumhigh_income_group_and_eating_out_tour,-0.7207,F +coef_high_income_group_and_eating_out_tour,-0.7207,F +coef_mediumlow_income_group_and_discretionary_tour,0,T +coef_mediumhigh_income_group_and_discretionary_tour,0,T +coef_high_income_group_and_discretionary_tour,0,T +coef_mediumlow_income_group_and_visiting_tour,0,T +coef_mediumhigh_income_group_and_visiting_tour,-0.3694,F +coef_high_income_group_and_visiting_tour,-0.3694,F +coef_female_and_tour_frequency_is_1,0.0973,F +coef_female_and_tour_frequency_is_2,0.2361,F +coef_female_and_tour_frequency_is_3,1.9002,F +coef_female_and_tour_frequency_is_4,1.9002,F +coef_female_and_tour_frequency_is_5,1.9002,F +coef_female_and_escorting_tour,0,T +coef_female_and_shopping_tour,0,T +coef_female_and_maintenance_tour,0,T +coef_female_and_eatingout_tour,-0.6568,F +coef_female_and_discretionary_tour,-0.3266,F +coef_zero_car_ownership_and_tour_frequency_is_1,-0.581,F +coef_zero_car_ownership_and_tour_frequency_is_2,-0.581,F +coef_zero_car_ownership_and_tour_frequency_is_3,-0.581,F +coef_zero_car_ownership_and_tour_frequency_is_4,-0.581,F +coef_zero_car_ownership_and_tour_frequency_is_5_plus,-0.581,F +coef_car_shortage_vs_workers_and_tour_frequency_is_1,-0.581,F +coef_car_shortage_vs_workers_and_tour_frequency_is_2,-0.581,F +coef_car_shortage_vs_workers_and_tour_frequency_is_3,-0.581,F +coef_car_shortage_vs_workers_and_tour_frequency_is_4,-0.581,F +coef_car_shortage_vs_workers_and_tour_frequency_is_5_plus,-0.581,F +coef_car_surplus_vs_workers_and_tour_frequency_is_1,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_2,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_3,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_4,0,T +coef_car_surplus_vs_workers_and_tour_frequency_is_5_plus,0,T +coef_presence_of_non_worker_and_tour_frequency_is_1,-0.8506,F +coef_presence_of_non_worker_and_tour_frequency_is_2,-1.1804,F +coef_presence_of_non_worker_and_tour_frequency_is_3,-1.1804,F +coef_presence_of_non_worker_and_tour_frequency_is_4,-1.1804,F +coef_presence_of_non_worker_and_tour_frequency_is_5,-1.1804,F +coef_presence_of_retiree_and_tour_frequency_is_1,0,T +coef_presence_of_retiree_and_tour_frequency_is_2,0,T +coef_presence_of_retiree_and_tour_frequency_is_3,0,T +coef_presence_of_retiree_and_tour_frequency_is_4,0,T +coef_presence_of_retiree_and_tour_frequency_is_5,0,T +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_1,-0.9961,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_2,-1.9096,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_3,-2.8469,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_4,-2.8469,F +coef_presence_of_preschool_kid_in_household_and_tour_frequency_is_5,-2.8469,F +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_1,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_2,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_3,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_4,0,T +coef_presence_of_predriving_school_kid_in_household_and_tour_frequency_is_5,0,T +coef_presence_of_full_time_worker_and_escorting_tour,0,T +coef_presence_of_part_time_worker_and_escorting_tour,-1.8213,F +coef_presence_of_non_worker_and_escorting_tour,0,T +coef_presence_of_retiree_and_escorting_tour,0,T +coef_presence_of_university_student_and_escorting_tour,0,T +coef_presence_of_driving_school_kid_and_escorting_tour,0,T +coef_presence_of_pre_driving_school_kid_and_escorting_tour,0.9489,F +coef_presence_of_pre_school_kid_and_escorting_tour,2.1465,F +coef_at_home_pre_driving_school_kid_and_escorting_tour,0,T +coef_at_home_pre_school_kid_and_escorting_tour,0,T +coef_presence_of_full_time_worker_and_shopping_tour,-0.7728,F +coef_presence_of_part_time_worker_and_shopping_tour,-0.5199,F +coef_presence_of_non_worker_and_shopping_tour,0,T +coef_presence_of_retiree_and_shopping_tour,0,T +coef_presence_of_university_student_and_shopping_tour,0,T +coef_presence_of_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_driving_school_kid_and_shopping_tour,0,T +coef_presence_of_pre_school_kid_and_shopping_tour,1.3135,F +coef_at_home_pre_driving_school_kid_and_shopping_tour,0,T +coef_at_home_pre_school_kid_and_shopping_tour,0,T +coef_presence_of_full_time_worker_and_maintenance_tour,0,T +coef_presence_of_part_time_worker_and_maintenance_tour,0,T +coef_presence_of_non_worker_and_maintenance_tour,0,T +coef_presence_of_retiree_and_maintenance_tour,0,T +coef_presence_of_university_student_and_maintenance_tour,0,T +coef_presence_of_driving_school_kid_and_maintenance_tour,0,T +coef_presence_of_pre_driving_school_kid_and_maintenance_tour,0.3863,F +coef_presence_of_pre_school_kid_and_maintenance_tour,0.9694,F +coef_at_home_pre_driving_school_kid_and_maintenance_tour,0,T +coef_at_home_pre_school_kid_and_maintenance_tour,0,T +coef_presence_of_full_time_worker_and_eating_out_tour,-0.5251,F +coef_presence_of_part_time_worker_and_eating_out_tour,-1.9795,F +coef_presence_of_non_worker_and_eating_out_tour,0,T +coef_presence_of_retiree_and_eating_out_tour,0,T +coef_presence_of_university_student_and_eating_out_tour,-0.6529,F +coef_presence_of_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_driving_school_kid_and_eating_out_tour,0,T +coef_presence_of_pre_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_driving_school_kid_and_eating_out_tour,0,T +coef_at_home_pre_school_kid_and_eating_out_tour,0,T +coef_presence_of_full_time_worker_and_discretionary_tour,-0.4833,F +coef_presence_of_part_time_worker_and_discretionary_tour,0,T +coef_presence_of_non_worker_and_discretionary_tour,0.9781,F +coef_presence_of_retiree_and_discretionary_tour,0,T +coef_presence_of_university_student_and_discretionary_tour,-0.6542,F +coef_presence_of_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_driving_school_kid_and_discretionary_tour,0,T +coef_presence_of_pre_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_driving_school_kid_and_discretionary_tour,0,T +coef_at_home_pre_school_kid_and_discretionary_tour,0,T +coef_walk_access_to_retail_and_tour_frequency_is_1,0,T +coef_walk_access_to_retail_and_tour_frequency_is_2,0,T +coef_walk_access_to_retail_and_tour_frequency_is_3,0,T +coef_walk_access_to_retail_and_tour_frequency_is_4,0,T +coef_walk_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_transit_access_to_retail_and_tour_frequency_is_1,0.0664,F +coef_transit_access_to_retail_and_tour_frequency_is_2,0.0664,F +coef_transit_access_to_retail_and_tour_frequency_is_3,0.0664,F +coef_transit_access_to_retail_and_tour_frequency_is_4,0.0664,F +coef_transit_access_to_retail_and_tour_frequency_is_5_plus,0.0664,F +coef_auto_access_to_retail_and_tour_frequency_is_1,0,T +coef_auto_access_to_retail_and_tour_frequency_is_2,0,T +coef_auto_access_to_retail_and_tour_frequency_is_3,0,T +coef_auto_access_to_retail_and_tour_frequency_is_4,0,T +coef_auto_access_to_retail_and_tour_frequency_is_5_plus,0,T +coef_walk_access_to_retail_and_escorting,0,T +coef_transit_access_to_retail_and_escorting,0,T +coef_auto_access_to_retail_and_escorting,0,T +coef_walk_access_to_retail_and_shopping,0.0972,F +coef_transit_access_to_retail_and_shopping,0,T +coef_auto_access_to_retail_and_shopping,0,T +coef_walk_access_to_retail_and_maintenance,0,T +coef_transit_access_to_retail_and_maintenance,0.0314,F +coef_auto_access_to_retail_and_maintenance,0,T +coef_walk_access_to_retail_and_eating_out,0,T +coef_transit_access_to_retail_and_eating_out,0,T +coef_auto_access_to_retail_and_eating_out,0.1018,F +coef_walk_access_to_retail_and_discretionary,0,T +coef_transit_access_to_retail_and_discretionary,0,T +coef_auto_access_to_retail_and_discretionary,0.094,F +coef_urban_and_tour_frequency_is_1,-1.1648,F +coef_urban_and_tour_frequency_is_2,-2.3177,F +coef_urban_and_tour_frequency_is_3,-2.5027,F +coef_urban_and_tour_frequency_is_4,-2.5027,F +coef_urban_and_tour_frequency_is_5_plus,-2.5027,F +coef_urban_and_escorting_tour,0.8516,F +coef_urban_and_shopping_tour,0.533,F +coef_urban_and_maintenance_tour,1.0316,F +coef_urban_and_eatingout_tour,0.68,F +coef_urban_and_discretionary_tour,0.9563,F +coef_1_escort_tour_constant,1.7028,F +coef_2_plus_escort_tours_constant,2.8379,F +coef_1_plus_shopping_tours_constant,1.8403,F +coef_1_plus_maintenance_tours_constant,0.3348,F +coef_1_plus_eating_out_tours_constant,2.0723,F +coef_1_plus_visting_tours_constant,1.2172,F +coef_1_plus_other_discretionary_tours_constant,1.3389,F +coef_0_auto_household_and_escorting_tour,-2,T +coef_calib_nonmandtours_1_mand_gt0,1.112189691,T +coef_calib_nonmandtours_2_mand_gt0,0.319534579,T +coef_calib_nonmandtours_gt3_mand_gt0,0.738362555,T +coef_calib_nonmandtours_2_mand_0,-1.075998448,T +coef_calib_nonmandtours_3_mand_0,-2.067563956,T +coef_calib_nonmandtours_gt4_mand_0,-3.294051601,T +coef_tc_1dayperweek_1,-0.005,F +coef_tc_23dayperweek_1,0.142,F +coef_tc_4pdayperweek_1,-0.406,F +coef_tc_1dayperweek_2p,-0.348,F +coef_tc_23dayperweek_2p,-0.041,F +coef_tc_4pdayperweek_2p,-0.447,F \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_extension_probs.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_extension_probs.csv new file mode 100644 index 000000000..ec78c4c8e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_frequency_extension_probs.csv @@ -0,0 +1,193 @@ +ptype,has_mandatory_tour,has_joint_tour,nonmandatory_tour_type,0_tours,1_tours,2_tours +1,0,0,1,0.829545455,1,1 +2,0,0,1,0.769230769,1,1 +3,0,0,1,0.893939394,1,1 +4,0,0,1,0.75,1,1 +5,0,0,1,0.842105263,1,1 +6,0,0,1,0.714285714,1,1 +7,0,0,1,0.814814815,1,1 +8,0,0,1,0.75,1,1 +1,1,0,1,0.789473684,1,1 +2,1,0,1,0.6,1,1 +3,1,0,1,1,1,1 +4,1,0,1,1,1,1 +5,1,0,1,0.825910931,1,1 +6,1,0,1,0.837209302,1,1 +7,1,0,1,0.6,1,1 +8,1,0,1,1,1,1 +1,0,1,1,0.842105263,1,1 +2,0,1,1,1,1,1 +3,0,1,1,1,1,1 +4,0,1,1,1,1,1 +5,0,1,1,1,1,1 +6,0,1,1,1,1,1 +7,0,1,1,1,1,1 +8,0,1,1,1,1,1 +1,1,1,1,1,1,1 +2,1,1,1,1,1,1 +3,1,1,1,1,1,1 +4,1,1,1,1,1,1 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+1,1,0,3,0.893333333,0.986666667,1 +2,1,0,3,1,1,1 +3,1,0,3,1,1,1 +4,1,0,3,0.857142857,1,1 +5,1,0,3,0.916071429,0.996428571,1 +6,1,0,3,0.856382979,0.984042553,1 +7,1,0,3,1,1,1 +8,1,0,3,1,1,1 +1,0,1,3,0.916201117,0.991620112,1 +2,0,1,3,0.912280702,0.98245614,1 +3,0,1,3,1,1,1 +4,0,1,3,1,1,1 +5,0,1,3,1,1,1 +6,0,1,3,0.833333333,1,1 +7,0,1,3,0.961538462,1,1 +8,0,1,3,1,1,1 +1,1,1,3,0.97826087,0.989130435,1 +2,1,1,3,0.97260274,1,1 +3,1,1,3,1,1,1 +4,1,1,3,1,1,1 +5,1,1,3,0.995762712,1,1 +6,1,1,3,0.921568627,0.980392157,1 +7,1,1,3,1,1,1 +8,1,1,3,1,1,1 +1,0,0,4,0.9218107,0.995884774,1 +2,0,0,4,0.900900901,1,1 +3,0,0,4,0.997354497,1,1 +4,0,0,4,0.991176471,1,1 +5,0,0,4,0.921568627,0.980392157,1 +6,0,0,4,0.954545455,1,1 +7,0,0,4,1,1,1 +8,0,0,4,0.954545455,1,1 +1,1,0,4,0.941176471,0.970588235,1 +2,1,0,4,0.925925926,1,1 +3,1,0,4,1,1,1 +4,1,0,4,0.875,1,1 +5,1,0,4,0.915322581,1,1 +6,1,0,4,0.947674419,0.994186047,1 +7,1,0,4,0.666666667,1,1 +8,1,0,4,1,1,1 +1,0,1,4,0.925925926,0.987654321,1 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+6,0,0,6,0.925925926,1,1 +7,0,0,6,0.967741935,1,1 +8,0,0,6,0.90625,1,1 +1,1,0,6,0.85915493,1,1 +2,1,0,6,0.818181818,0.96969697,1 +3,1,0,6,1,1,1 +4,1,0,6,0.952380952,1,1 +5,1,0,6,0.879237288,0.997881356,1 +6,1,0,6,0.862944162,0.984771574,1 +7,1,0,6,0.9,1,1 +8,1,0,6,1,1,1 +1,0,1,6,0.927835052,0.996563574,1 +2,0,1,6,0.859375,0.9921875,1 +3,0,1,6,1,1,1 +4,0,1,6,1,1,1 +5,0,1,6,0.92,1,1 +6,0,1,6,1,1,1 +7,0,1,6,0.904761905,1,1 +8,0,1,6,1,1,1 +1,1,1,6,0.982758621,1,1 +2,1,1,6,0.927710843,0.987951807,1 +3,1,1,6,0.982954545,1,1 +4,1,1,6,0.938679245,1,1 +5,1,1,6,1,1,1 +6,1,1,6,0.9375,1,1 +7,1,1,6,1,1,1 +8,1,1,6,1,1,1 diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_scheduling.yaml b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_scheduling.yaml new file mode 100644 index 000000000..34b5a9a8e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_scheduling.yaml @@ -0,0 +1,93 @@ +SPEC: tour_scheduling_nonmandatory.csv +COEFFICIENTS: tour_scheduling_nonmandatory_coeffs.csv + +LOGIT_TYPE: MNL + +preprocessor: + SPEC: non_mandatory_tour_scheduling_annotate_tours_preprocessor + DF: non_mandatory_tours + TABLES: + - land_use + - joint_tour_participants + +SIMULATE_CHOOSER_COLUMNS: + + - age + - female + - adult + - ptype + - has_pre_school_child_with_mandatory + - has_driving_age_child_with_mandatory + - retired_adults_only_hh + - is_income_less25K + - is_income_25K_to_60K + - is_income_60K_to_120K + - auto_ownership + - num_children + - num_adults + - num_mand + - num_joint_tours + - num_escort_tours + - num_non_escort_tours + - num_add_shop_maint_tours + - num_add_soc_discr_tours + +#LOGSUM_SETTINGS: tour_mode_choice.yaml + +# map : : +# segmentation of tours for processing may differ from segmentation of spec +# vectorize_tour_scheduling iterates over +# using to choose spec for scheduling alt chice +# using for logsums (if enabled) +# tour_mode_choice segmentation for logsums is: eatout,escort,othdiscr,othmaint,shopping,social,school,univ,work,atwork +TOUR_SPEC_SEGMENTS: + escort: escort + shopping: shopping + eatout: eatout + othdiscr: othdiscr + othmaint: othmaint + social: social + +# spec keyed by +SPEC_SEGMENTS: + escort: + 'SPEC': tour_scheduling_nonmandatory_escort.csv + 'COEFFICIENTS': tour_scheduling_nonmandatory_escort_coefficients.csv + shopping: + 'SPEC': tour_scheduling_nonmandatory_shopping.csv + 'COEFFICIENTS': tour_scheduling_nonmandatory_shopping_coefficients.csv + eatout: + 'SPEC': tour_scheduling_nonmandatory_eatout.csv + 'COEFFICIENTS': tour_scheduling_nonmandatory_eatout_coefficients.csv + othdiscr: + 'SPEC': tour_scheduling_nonmandatory_othdiscr.csv + 'COEFFICIENTS': tour_scheduling_nonmandatory_othdiscr_coefficients.csv + othmaint: + 'SPEC': tour_scheduling_nonmandatory_othmaint.csv + 'COEFFICIENTS': tour_scheduling_nonmandatory_othmaint_coefficients.csv + social: + 'SPEC': tour_scheduling_nonmandatory_social.csv + 'COEFFICIENTS': tour_scheduling_nonmandatory_social_coefficients.csv + +## alts preprocessor keyed by +#ALTS_PREPROCESSOR: +# escort: +# SPEC: non_mandatory_tour_scheduling_escort_annotate_alts_preprocessor.csv +# DF: alt_tdd +# shopping: +# SPEC: non_mandatory_tour_scheduling_shopping_annotate_alts_preprocessor.csv +# DF: alt_tdd +# eatout: +# SPEC: non_mandatory_tour_scheduling_annotate_alts_preprocessor.csv +# DF: alt_tdd +# othdiscr: +# SPEC: non_mandatory_tour_scheduling_annotate_alts_preprocessor.csv +# DF: alt_tdd +# othmaint: +# SPEC: non_mandatory_tour_scheduling_annotate_alts_preprocessor.csv +# DF: alt_tdd +# social: +# SPEC: non_mandatory_tour_scheduling_annotate_alts_preprocessor.csv +# DF: alt_tdd +# +#DESTINATION_FOR_TOUR_PURPOSE: destination diff --git a/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_scheduling_annotate_tours_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_scheduling_annotate_tours_preprocessor.csv new file mode 100644 index 000000000..616a627d2 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/non_mandatory_tour_scheduling_annotate_tours_preprocessor.csv @@ -0,0 +1,5 @@ +Description,Target,Expression +#,, +number of person joint tours,num_person_joint_tours,"reindex_i(joint_tour_participants.groupby('person_id').size(), non_mandatory_tours.person_id)" +#,, +,origin_to_destination_distance,"skim_dict.lookup(non_mandatory_tours.origin, non_mandatory_tours.destination, ('SOV_DIST', 'MD'))" diff --git a/activitysim/examples/prototype_mwcog/configs/school_location.csv b/activitysim/examples/prototype_mwcog/configs/school_location.csv new file mode 100644 index 000000000..8db3f8056 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/school_location.csv @@ -0,0 +1,22 @@ +Label,Description,Expression,university,highschool,gradeschool +local_dist,,_DIST@skims['DIST'],1,1,1 +util_dist_0_1,"Distance, piecewise linear from 0 to 1 miles","@_DIST.clip(0,1)",coef_univ_dist_0_1,0,0 +util_dist_1_2,"Distance, piecewise linear from 1 to 2 miles","@(_DIST-1).clip(0,1)",coef_univ_dist_1_2,0,0 +util_dist_2_5,"Distance, piecewise linear from 2 to 5 miles","@(_DIST-2).clip(0,3)",coef_univ_dist_2_5,0,0 +util_dist_5_15,"Distance, piecewise linear from 5 to 15 miles","@(_DIST-5).clip(0,10)",coef_univ_dist_5_15,0,0 +util_dist_15_up,"Distance, piecewise linear for 15+ miles",@(_DIST-15.0).clip(0),coef_univ_dist_15_up,0,0 +util_size_variable,Size variable,@(df['size_term'] * df['shadow_price_size_term_adjustment']).apply(np.log1p),1,1,1 +util_utility_adjustment,utility adjustment,@df['shadow_price_utility_adjustment'],1,1,1 +util_no_attractions,No attractions,@df['size_term']==0,-999,-999,-999 +util_mode_choice_logsum,Mode choice logsum,mode_choice_logsum,coef_mode_logsum_uni,coef_mode_logsum,coef_mode_logsum +util_sample_of_corrections_factor,Sample of alternatives correction factor,"@np.minimum(np.log(df.pick_count/df.prob), 60)",1,1,1 +util_dist,Distance,@_DIST,0,coef_dist,coef_dist +util_dist_squared,"Distance squared, capped at 20 miles","@(_DIST).clip(0,20)**2",0,coef_dist_squared,coef_dist_squared +util_dist_cubed,"Distance cubed, capped at 20 miles","@(_DIST).clip(0,20)**3",0,coef_dist_cubed,coef_dist_cubed +util_dist_logged,Distance logged,@(_DIST).apply(np.log1p),0,coef_dist_logged,coef_dist_logged +util_dist_part_time,"Distance,part time",@(df['pemploy']==2) * _DIST,0,coef_dist_part_time,coef_dist_part_time +util_dist_child_0_5,"Distance,child 0 to 5",@(df['age_0_to_5']==True) * _DIST,0,coef_dist_child_0_5,coef_dist_child_0_5 +util_dist_child_6_12,"Distance,child 6 to 12",@(df['age_6_to_12']==True) * _DIST,0,coef_dist_child_6_12,coef_dist_child_6_12 +util_dist_low,"Distance,low income (<50)",@(df['income_segment']==INC_LOW_SEGMENT_ID) * _DIST,0,coef_dist_low_inc,coef_dist_low_inc +util_dist_very_high,"Distance,very high income (>150)",@(df['income_segment']==INC_VERYHIGH_SEGMENT_ID) * _DIST,0,coef_dist_very_high_inc,coef_dist_very_high_inc +util_dist_calib,Distance calibration Gen3,@_DIST,0,coef_dist_calib,coef_dist_calib diff --git a/activitysim/examples/prototype_mwcog/configs/school_location.yaml b/activitysim/examples/prototype_mwcog/configs/school_location.yaml new file mode 100644 index 000000000..4a75198e0 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/school_location.yaml @@ -0,0 +1,70 @@ +SAMPLE_SIZE: 30 + +SIMULATE_CHOOSER_COLUMNS: + - home_zone_id + - school_segment + - household_id + - is_student + - age_0_to_5 + - age_6_to_12 + - pemploy + - income_segment + - auto_ownership + +# model-specific logsum-related settings +CHOOSER_ORIG_COL_NAME: home_zone_id +ALT_DEST_COL_NAME: alt_dest +IN_PERIOD: 26 +OUT_PERIOD: 9 + +DEST_CHOICE_COLUMN_NAME: school_zone_id + +SAMPLE_SPEC: school_location_sample.csv +SPEC: school_location.csv +COEFFICIENTS: school_location_coeffs.csv + +LOGSUM_SETTINGS: tour_mode_choice.yaml +LOGSUM_PREPROCESSOR: nontour_preprocessor + +LOGSUM_TOUR_PURPOSE: + university: univ + highschool: school + gradeschool: school + +annotate_persons: + SPEC: annotate_persons_school + DF: persons + +# - shadow pricing + +# required by initialize_households when creating school_destination_size table +CHOOSER_TABLE_NAME: persons + +# size_terms model_selector +MODEL_SELECTOR: school + +# chooser column with segment_id for this segment type +CHOOSER_SEGMENT_COLUMN_NAME: school_segment + +# boolean column to filter choosers (True means keep) +CHOOSER_FILTER_COLUMN_NAME: is_student + + +# FIXME - these are assigned to persons in annotate_persons. we need a better way to manage this +SEGMENT_IDS: + university: 3 + highschool: 2 + gradeschool: 1 + +CONSTANTS: + INC_LOW_SEGMENT_ID: 1 + INC_MED_SEGMENT_ID: 2 + INC_HIGH_SEGMENT_ID: 3 + INC_VERYHIGH_SEGMENT_ID: 4 + +# model adds these tables (informational - not added if commented out) +SHADOW_PRICE_TABLE: school_shadow_prices +MODELED_SIZE_TABLE: school_modeled_size + +# not loaded if commented out +SAVED_SHADOW_PRICE_TABLE_NAME: final_school_shadow_prices.csv diff --git a/activitysim/examples/prototype_mwcog/configs/school_location_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/school_location_coeffs.csv new file mode 100644 index 000000000..a6041e3d5 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/school_location_coeffs.csv @@ -0,0 +1,18 @@ +coefficient_name,value,constrain +coef_univ_dist_0_1,-3.2451,F +coef_univ_dist_1_2,-2.7011,F +coef_univ_dist_2_5,-0.5707,F +coef_univ_dist_5_15,-0.5002,F +coef_univ_dist_15_up,-0.073,F +coef_mode_logsum_uni,0.5358,F +coef_dist,-0.075971485,F +coef_dist_squared,0,F +coef_dist_cubed,0,F +coef_dist_logged,-2.073546963,F +coef_dist_part_time,-0.049133509,F +coef_dist_child_0_5,0,F +coef_dist_child_6_12,-0.051582555,F +coef_dist_low_inc,-0.028471563,F +coef_dist_very_high_inc,-0.018662186,F +coef_mode_logsum,0.3,F +coef_dist_calib,-0.035,F diff --git a/activitysim/examples/prototype_mwcog/configs/school_location_sample.csv b/activitysim/examples/prototype_mwcog/configs/school_location_sample.csv new file mode 100644 index 000000000..a7d0120ab --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/school_location_sample.csv @@ -0,0 +1,17 @@ +Label,Description,Expression,university,highschool,gradeschool +local_dist,,_DIST@skims['DIST'],1,1,1 +util_dist_0_1,"Distance, piecewise linear from 0 to 1 miles","@_DIST.clip(0,1)",coef_univ_dist_0_1,0,0 +util_dist_1_2,"Distance, piecewise linear from 1 to 2 miles","@(_DIST-1).clip(0,1)",coef_univ_dist_1_2,0,0 +util_dist_2_5,"Distance, piecewise linear from 2 to 5 miles","@(_DIST-2).clip(0,3)",coef_univ_dist_2_5,0,0 +util_dist_5_15,"Distance, piecewise linear from 5 to 15 miles","@(_DIST-5).clip(0,10)",coef_univ_dist_5_15,0,0 +util_dist_15_up,"Distance, piecewise linear for 15+ miles",@(_DIST-15.0).clip(0),coef_univ_dist_15_up,0,0 +util_size_variable,Size variable,@(df['size_term'] * df['shadow_price_size_term_adjustment']).apply(np.log1p),1,1,1 +util_utility_adjustment,utility adjustment,@df['shadow_price_utility_adjustment'],1,1,1 +util_no_attractions,No attractions,@df['size_term']==0,-999,-999,-999 +util_dist,Distance,@_DIST,0,coef_dist,coef_dist +util_dist_squared,"Distance squared, capped at 20 miles","@(_DIST).clip(0,20)**2",0,coef_dist_squared,coef_dist_squared +util_dist_cubed,"Distance cubed, capped at 20 miles","@(_DIST).clip(0,20)**3",0,coef_dist_cubed,coef_dist_cubed +util_dist_logged,Distance logged,@(_DIST).apply(np.log1p),0,coef_dist_logged,coef_dist_logged +util_dist_part_time,"Distance,part time",@(df['pemploy']==2) * _DIST,0,coef_dist_part_time,coef_dist_part_time +util_dist_child_0_5,"Distance,child 0 to 5",@(df['age_0_to_5']==True) * _DIST,0,coef_dist_child_0_5,coef_dist_child_0_5 +util_dist_child_6_12,"Distance,child 6 to 12",@(df['age_6_to_12']==True) * _DIST,0,coef_dist_child_6_12,coef_dist_child_6_12 diff --git a/activitysim/examples/prototype_mwcog/configs/settings.yaml b/activitysim/examples/prototype_mwcog/configs/settings.yaml new file mode 100644 index 000000000..4f8110237 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/settings.yaml @@ -0,0 +1,155 @@ +# input tables +# +# activitysim uses "well-known" index and foreign key names for imported tables (e.g. households, persons, land_use) +# as well as for created tables (tours, joint_tour_participants, trips) +# e.g. the households table must have an index column 'household_id' and the foreign key to households in the +# persons table is also household_id. This naming convention allows activitysim to intuit the relationship +# between tables - for instance, to ensure that multiprocess slicing includes all the persons, tours, and trips +# in the same subprocess pipeline. The same strategy is also when chunking choosers, and to support tracing by +# household_id. +# +# the input_table_list index_col directive instructs activitysim to set the imported table index to zone_id +# you cannot change the well-known name of the index by modifying this directive. However, if your input file +# has a different id column name, you can rename it to the required index name with the rename_columns directive. +# In the settings below, the 'TAZ' column in the imported table is renamed 'zone_id' in the rename_columns settings. +# +# input tables +input_table_list: + # + # households (table index 'household_id') + # + - tablename: households + filename: combined_synthetic_hh_2018.csv + index_col: household_id + rename_columns: + NP: hhsize + VEH: auto_ownership + TAZ: home_zone_id + # + # persons (table index 'person_id') + # + - tablename: persons + filename: combined_synthetic_per_2018.csv + index_col: person_id + rename_columns: + AGEP: age + hh_id: household_id + # + # land_use (table index 'zone_id') + # + - tablename: land_use + filename: LU_taz3722_rnd91a_2018_adj_enrollment.csv + index_col: zone_id + rename_columns: + TAZ: zone_id + +# convert input CSVs to HDF5 format and save to outputs directory +# create_input_store: True + +# number of households to simulate +households_sample_size: 100 +# simulate all households +#households_sample_size: 0 + +#household_ids: override_household_ids.csv + +chunk_size: 0 + +# set false to disable variability check in simple_simulate and interaction_simulate +check_for_variability: False + +# - shadow pricing global switches + +# turn shadow_pricing on and off for all models (e.g. school and work) +# shadow pricing is deprecated for less than full samples +# see shadow_pricing.yaml for additional settings +use_shadow_pricing: False + + +# - tracing + +# trace household id; comment out or leave empty for no trace +# households with all tour types +# [ 728370 1234067 1402924 1594625 1595333 1747572 1896849 1931818 2222690 2344951 2677154] +#trace_hh_id: 94944 + +# trace origin, destination in accessibility calculation; comment out or leave empty for no trace +# trace_od: [5, 11] +trace_od: + + +models: + - initialize_landuse + - compute_accessibility + - initialize_households + - school_location + - workplace_location + - work_from_home + - transit_pass_subsidy + - transit_pass_ownership + - auto_ownership_simulate + - free_parking + - telecommute_frequency + - cdap_simulate + - mandatory_tour_frequency + - mandatory_tour_scheduling + - joint_tour_frequency + - joint_tour_composition + - joint_tour_participation + - joint_tour_destination + - joint_tour_scheduling + - non_mandatory_tour_frequency + - non_mandatory_tour_destination + - non_mandatory_tour_scheduling + - tour_mode_choice_simulate + - atwork_subtour_frequency + - atwork_subtour_destination + - atwork_subtour_scheduling + - atwork_subtour_mode_choice + - stop_frequency + - trip_purpose + - trip_destination + - trip_purpose_and_destination + - trip_scheduling + - trip_mode_choice + - write_data_dictionary + - track_skim_usage + - write_tables + - write_trip_matrices + +# to resume after last successful checkpoint, specify resume_after: _ +resume_after: + +output_tables: + h5_store: False + action: include + prefix: final_ + tables: + - checkpoints + - accessibility + - land_use + - households + - persons + - tours + - trips + - joint_tour_participants + +# area_types less than this are considered urban +urban_threshold: 4 +cbd_threshold: 2 +rural_threshold: 6 + +# - value of time + +# value_of_time = lognormal(np.log(median_value_of_time * mu), sigma).clip(min_vot, max_vot) + +min_value_of_time: 1 +max_value_of_time: 50 +distributed_vot_mu: 0.684 +distributed_vot_sigma: 0.85 + +household_median_value_of_time: + 1: 6.01 + 2: 8.81 + 3: 10.44 + 4: 12.86 diff --git a/activitysim/examples/prototype_mwcog/configs/shadow_pricing.yaml b/activitysim/examples/prototype_mwcog/configs/shadow_pricing.yaml new file mode 100644 index 000000000..b61ec4192 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/shadow_pricing.yaml @@ -0,0 +1,34 @@ +shadow_pricing_models: + school: school_location + workplace: workplace_location + +# global switch to enable/disable loading of saved shadow prices +# (ignored if global use_shadow_pricing switch is False) +LOAD_SAVED_SHADOW_PRICES: True + +# number of shadow price iterations for cold start +MAX_ITERATIONS: 10 + +# number of shadow price iterations for warm start (after loading saved shadow_prices) +MAX_ITERATIONS_SAVED: 1 + +# ignore criteria for zones smaller than size_threshold +SIZE_THRESHOLD: 10 + +# zone passes if modeled is within percent_tolerance of predicted_size +PERCENT_TOLERANCE: 5 + +# max percentage of zones allowed to fail +FAIL_THRESHOLD: 10 + +# CTRAMP or daysim +SHADOW_PRICE_METHOD: ctramp +#SHADOW_PRICE_METHOD: daysim + +# ctramp-style shadow_pricing_method parameters +DAMPING_FACTOR: 1 + +# daysim-style shadow_pricing_method parameters +# FIXME should these be the same as PERCENT_TOLERANCE and FAIL_THRESHOLD above? +DAYSIM_ABSOLUTE_TOLERANCE: 50 +DAYSIM_PERCENT_TOLERANCE: 10 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency.yaml b/activitysim/examples/prototype_mwcog/configs/stop_frequency.yaml new file mode 100644 index 000000000..bc953e8fc --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency.yaml @@ -0,0 +1,83 @@ +LOGIT_TYPE: MNL + +preprocessor: + SPEC: stop_frequency_annotate_tours_preprocessor + DF: tours_merged + TABLES: + - persons + - land_use + - accessibility + +SEGMENT_COL: primary_purpose + +SPEC_SEGMENTS: + - primary_purpose: work + SPEC: stop_frequency_work.csv + COEFFICIENTS: stop_frequency_coefficients_work.csv + - primary_purpose: school + SPEC: stop_frequency_school.csv + COEFFICIENTS: stop_frequency_coefficients_school.csv + - primary_purpose: univ + SPEC: stop_frequency_univ.csv + COEFFICIENTS: stop_frequency_coefficients_univ.csv + - primary_purpose: social + SPEC: stop_frequency_social.csv + COEFFICIENTS: stop_frequency_coefficients_social.csv + - primary_purpose: shopping + SPEC: stop_frequency_shopping.csv + COEFFICIENTS: stop_frequency_coefficients_shopping.csv + - primary_purpose: eatout + SPEC: stop_frequency_eatout.csv + COEFFICIENTS: stop_frequency_coefficients_eatout.csv + - primary_purpose: escort + SPEC: stop_frequency_escort.csv + COEFFICIENTS: stop_frequency_coefficients_escort.csv + - primary_purpose: othmaint + SPEC: stop_frequency_othmaint.csv + COEFFICIENTS: stop_frequency_coefficients_othmaint.csv + - primary_purpose: othdiscr + SPEC: stop_frequency_othdiscr.csv + COEFFICIENTS: stop_frequency_coefficients_othdiscr.csv + - primary_purpose: atwork + SPEC: stop_frequency_atwork.csv + COEFFICIENTS: stop_frequency_coefficients_atwork.csv + +CONSTANTS: + TRANSIT_MODES: + - WALK_AB + - WALK_BM + - WALK_MR + - WALK_CR + - PNR_AB + - PNR_BM + - PNR_MR + - PNR_CR + - KNR_AB + - KNR_BM + - KNR_MR + - KNR_CR + + DRIVE_TO_TRANSIT_MODES: + - PNR_AB + - PNR_BM + - PNR_MR + - PNR_CR + - KNR_AB + - KNR_BM + - KNR_MR + - KNR_CR + NONMOTORIZED_MODES: + - WALK + - BIKE + SHOP_TOUR: shopping + MAINT_TOUR: othmaint + SCHOOL_TOUR: school + EATOUT_TOUR: eatout + SOCIAL_TOUR: social + num_atwork_subtours_map: + no_subtours: 0 + eat: 1 + business1: 1 + maint: 1 + business2: 2 + eat_business: 2 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_alternatives.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_alternatives.csv new file mode 100644 index 000000000..72f49a7c7 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_alternatives.csv @@ -0,0 +1,18 @@ +#,,alt file for building tours even though simulation is simple_simulate not interaction_simulate +alt,out,in +0out_0in,0,0 +0out_1in,0,1 +0out_2in,0,2 +0out_3in,0,3 +1out_0in,1,0 +1out_1in,1,1 +1out_2in,1,2 +1out_3in,1,3 +2out_0in,2,0 +2out_1in,2,1 +2out_2in,2,2 +2out_3in,2,3 +3out_0in,3,0 +3out_1in,3,1 +3out_2in,3,2 +3out_3in,3,3 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_annotate_tours_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_annotate_tours_preprocessor.csv new file mode 100644 index 000000000..f69e1a027 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_annotate_tours_preprocessor.csv @@ -0,0 +1,47 @@ +Description,Target,Expression +#,, +# define primary_purpose to use for slicing choosers with a value that identifies the spec to be used ,, +# e.g. univ segment means there will be a spec called stop_frequency_univ.csv,, +# so the 'school' tour_type can treat univ and non-univ school tours differently,, +,primary_purpose,"df.tour_type.where((df.tour_type != 'school') | ~df.is_university, 'univ')" +,primary_purpose,"primary_purpose.where(df.tour_category!='atwork', 'atwork')" +#,, +,distance_in_miles,od_skims['DIST'] +#,, +,is_joint,df.tour_category=='joint' +,_HH_PERSON_COUNT,"lambda exp, persons: persons.query(exp).groupby('household_id').size()" +,num_full,"reindex_i(_HH_PERSON_COUNT('ptype == %s' % PEMPLOY_FULL, persons), df.household_id)" +,num_part,"reindex_i(_HH_PERSON_COUNT('ptype == %s' % PEMPLOY_PART, persons), df.household_id)" +,num_student,"reindex_i(_HH_PERSON_COUNT('pstudent != %s' % PSTUDENT_NOT, persons), df.household_id)" +Num Kids between 0 and 4 (including) years old,num_age_0_4,"reindex_i(_HH_PERSON_COUNT('age < 5', persons), df.household_id)" +Num kids between 4 and 15 (including) years old,num_age_5_15,"reindex_i(_HH_PERSON_COUNT('(age >= 5) & (age <16)', persons), df.household_id)" +Number of Adults (>= 16 years old),num_adult,"reindex_i(_HH_PERSON_COUNT('age >= 16', persons), df.household_id)" +,more_cars_than_workers,df.auto_ownership >= (num_full + num_part) +,tour_mode_is_transit,df.tour_mode.isin(TRANSIT_MODES) +,tour_mode_is_drive_transit,df.tour_mode.isin(DRIVE_TO_TRANSIT_MODES) +,tour_mode_is_non_motorized,df.tour_mode.isin(NONMOTORIZED_MODES) +#,, +#num_work_tours already defined,, +school but not university,num_school_tours,"reindex_i(df[primary_purpose==SCHOOL_TOUR].groupby('person_id').size(), df.person_id)" +,num_univ_tours,(df.is_university) * num_school_tours +#num_escort_tours already defined,, +# indiv tour counts should not include joint tours by point_person,, +,num_shop_tours,"reindex_i(df[~is_joint & (df.tour_type==SHOP_TOUR)].groupby('person_id').size(), df.person_id)" +,num_maint_tours,"reindex_i(df[~is_joint & (df.tour_type==MAINT_TOUR)].groupby('person_id').size(), df.person_id)" +,num_eatout_tours,"reindex_i(df[~is_joint & (df.tour_type==EATOUT_TOUR)].groupby('person_id').size(), df.person_id)" +,num_social_tours,"reindex_i(df[~is_joint & (df.tour_type==SOCIAL_TOUR)].groupby('person_id').size(), df.person_id)" +#,, +Number of subtours in the tour,num_atwork_subtours,"df.atwork_subtour_frequency.map(num_atwork_subtours_map, na_action='ignore').fillna(0).astype(np.int8)" +#,, +Number of hh shop tours including joint,num_hh_shop_tours,"reindex_i(df[df.tour_type==SHOP_TOUR].groupby('household_id').size(), df.person_id)" +Number of hh maint tours including joint,num_hh_maint_tours,"reindex_i(df[df.tour_type==MAINT_TOUR].groupby('household_id').size(), df.person_id)" +tourStartsInPeakPeriod,_tour_starts_in_peak,(network_los.skim_time_period_label(df.start) == 'AM') | (network_los.skim_time_period_label(df.start) == 'PM') +AccesibilityAtOrigin fallback,hhacc,0 +AccesibilityAtOrigin if transit,hhacc,"hhacc.where(~tour_mode_is_transit, df.trPkRetail.where(_tour_starts_in_peak, df.trOpRetail))" +AccesibilityAtOrigin if non_motorized,hhacc,"hhacc.where(~tour_mode_is_non_motorized, df.nmRetail)" +AccesibilityADestination fallback,pracc,0 +AccesibilityADestination peak transit,_dest_trPkRetail,"reindex(accessibility.trPkRetail, df.destination)" +AccesibilityADestination off-peak transit,_dest_trOpRetail,"reindex(accessibility.trOpRetail, df.destination)" +AccesibilityAtDestination if transit,pracc,"pracc.where(~tour_mode_is_transit, _dest_trPkRetail.where(_tour_starts_in_peak, _dest_trOpRetail))" +AccesibilityAtDestination if non_motorized,pracc,"pracc.where(~tour_mode_is_non_motorized, reindex(accessibility.nmRetail, df.destination))" +,destination_area_type,"reindex(land_use.AREATYPE, df.destination)" diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_atwork.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_atwork.csv new file mode 100644 index 000000000..dbd1c61c5 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_atwork.csv @@ -0,0 +1,13 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh_,Middle to Low Income HH ,income_in_thousands<50000,,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_ +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,num_eatout_tours,,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person,coef_number_of_eating_tours_tours_undertaken_by_the_person +util_subtour_departure_less_than_or_equal_to_11am,Subtour departure less than or equal to 11AM,start<12,,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am,coef_subtour_departure_less_than_or_equal_to_11am +util_subtour_return_time_greater_or_equal_to_2pm,Subtour return time greater or equal to 2PM,end>16,,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm,coef_subtour_return_time_greater_or_equal_to_2pm +util_subtour_duration_in_hours_integer_,Subtour duration in hours (integer),end-start,,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_,coef_subtour_duration_in_hours_integer_ +util_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,dummy for subtour origin (tour destination) at Exurban or Rual (AreaTypes = 6 or 7),destination_area_type >5,,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_ +util_primary_destination_accessibility_log_of_it_,Primary Destination Accessibility (LOG of it),pracc,,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_,coef_primary_destination_accessibility_log_of_it_ +util_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,subtour distance in miles (from tour destination to subtour primary destination one way),distance_in_miles,,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_ +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,1,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,1,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,1,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +util_Phase1_Calibration,Phase1_Calibration,1,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_atwork.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_atwork.csv new file mode 100644 index 000000000..5e1a09627 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_atwork.csv @@ -0,0 +1,32 @@ +Description,value,coefficient_name +Middle to Low Income HH ,0.45,coef_middle_to_low_income_hh_ +Number of eating tours tours undertaken by the person,-0.28,coef_number_of_eating_tours_tours_undertaken_by_the_person +Subtour departure less than or equal to 11AM,0.31,coef_subtour_departure_less_than_or_equal_to_11am +Subtour return time greater or equal to 2PM,0.34,coef_subtour_return_time_greater_or_equal_to_2pm +Subtour duration in hours (integer),0.56,coef_subtour_duration_in_hours_integer_ +dummy for subtour origin (tour destination) at Exurban or Rual (AreaTypes = 6 or 7),0.27,coef_dummy_for_subtour_origin_tour_destination_at_exurban_or_rual_areatypes_6_or_7_ +Primary Destination Accessibility (LOG of it),0.18,coef_primary_destination_accessibility_log_of_it_ +subtour distance in miles (from tour destination to subtour primary destination one way),0.02,coef_subtour_distance_in_miles_from_tour_destination_to_subtour_primary_destination_one_way_ +Alternative specific constant for return stops,-3.671,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops,-5.388,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops,-6.21,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for outbound stops,-3.896,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for the total number of stops,2.127,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for outbound stops,-5.709,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for outbound stops,-7.361,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Calibrated coefficient for stops 0 out and 1 in,-2.63434376,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,-2.784737668,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,-0.489626558,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,-3.622571928,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,-0.718600931,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,-2.115702598,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-4.459844297,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,-3.657486874,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,0.273537757,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,0.252608976,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,-0.50657628,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,-5.084387708,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,0.390308574,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,2.069420944,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,2.886598497,coef_calibration_for_3out_3in diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_eatout.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_eatout.csv new file mode 100644 index 000000000..203b54ba4 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_eatout.csv @@ -0,0 +1,93 @@ +Description,value,coefficient_name +Number of Vehicles,-0.19,coef_number_of_vehicles +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-1.73,coef_dummy_for_walking_to_all_stops +Number of work tours undertaken by the person,-0.28,coef_number_of_work_tours_undertaken_by_the_person +Number of shop tours undertaken by the person,-0.24,coef_number_of_shop_tours_undertaken_by_the_person +At least one kid and one adult participate in the tour,0.37,coef_at_least_one_kid_and_one_adult_participate_in_the_tour +Arrival later than 17:00.,-0.45,coef_arrival_later_than_17_00_ +Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,1.31,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_ +dummy for distance in miles,-0.01,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-1.761,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops on joint tours,-1.329,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in +Dummy for a return visiting tour,-0.64,coef_dummy_for_a_return_visiting_tour +Alternative specific constant for return stops,-3.697,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops on joint tours,-2.796,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in +Alternative specific constant for the total number of stops on joint tours,0,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in +Alternative specific constant for return stops,-4.717,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for return stops on joint tours,-3.379,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +Number of persons participating in the tour.Outgoing stops interaction,-0.46,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction +Alternative specific constant for outbound stops,-2.19,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for outbound stops on joint tours,-1.783,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in +Dummy for an outbound visiting tour,-0.69,coef_dummy_for_an_outbound_visiting_tour +Dummy for a visiting tour with both outbound and return leg,0.44,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg +Alternative specific constant for the total number of stops,0.94,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for the total number of stops on joint tours,0.518,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in +Alternative specific constant for outbound stops,-4.516,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for outbound stops on joint tours,-4.067,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in +Alternative specific constant for the total number of stops,2.026,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for the total number of stops on joint tours,1.497,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +Alternative specific constant for outbound stops,-5.255,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Alternative specific constant for outbound stops on joint tours,-4.998,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +Calibrated coefficient for stops 0 out and 1 in,-0.128986631,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,0.188202401,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,0.418146682,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,0.313324465,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,0.680527273,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,1.928344879,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-0.120616813,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,1.321299113,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,1.707738852,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,1.476132289,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,-0.328929277,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,1.676875153,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,0.767585618,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,1.885405325,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,1.528508267,coef_calibration_for_3out_3in +,-0.126,coef_telecommute1_2 +,-0.301,coef_telecommute1_3 +,-0.301,coef_telecommute1_4 +,-0.126,coef_telecommute1_5 +,-0.301,coef_telecommute1_6 +,-0.301,coef_telecommute1_7 +,-0.611,coef_telecommute1_8 +,-0.301,coef_telecommute1_9 +,-0.301,coef_telecommute1_10 +,-0.611,coef_telecommute1_11 +,-0.611,coef_telecommute1_12 +,-0.301,coef_telecommute1_13 +,-0.611,coef_telecommute1_14 +,-0.611,coef_telecommute1_15 +,-0.611,coef_telecommute1_16 +,-0.149,coef_telecommute23_2 +,-0.768,coef_telecommute23_3 +,-0.768,coef_telecommute23_4 +,-0.768,coef_telecommute23_5 +,-0.768,coef_telecommute23_6 +,-0.768,coef_telecommute23_7 +,-0.909,coef_telecommute23_8 +,-0.768,coef_telecommute23_9 +,-0.768,coef_telecommute23_10 +,-0.909,coef_telecommute23_11 +,-0.909,coef_telecommute23_12 +,-0.768,coef_telecommute23_13 +,-0.909,coef_telecommute23_14 +,-0.909,coef_telecommute23_15 +,-0.909,coef_telecommute23_16 +,-0.158,coef_telecommute4p_2 +,-0.473,coef_telecommute4p_3 +,-0.473,coef_telecommute4p_4 +,-0.473,coef_telecommute4p_5 +,-0.473,coef_telecommute4p_6 +,-0.473,coef_telecommute4p_7 +,-1.47,coef_telecommute4p_8 +,-0.473,coef_telecommute4p_9 +,-0.473,coef_telecommute4p_10 +,-1.47,coef_telecommute4p_11 +,-1.47,coef_telecommute4p_12 +,-0.473,coef_telecommute4p_13 +,-1.47,coef_telecommute4p_14 +,-1.47,coef_telecommute4p_15 +,-1.47,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_escort.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_escort.csv new file mode 100644 index 000000000..4f131a0a2 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_escort.csv @@ -0,0 +1,88 @@ +Description,value,coefficient_name +Number of HH Persons,-0.24,coef_number_of_hh_persons +Number of Students in HH,0.19,coef_number_of_students_in_hh +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-1.91,coef_dummy_for_walking_to_all_stops +Number of work tours undertaken by the person,-0.29,coef_number_of_work_tours_undertaken_by_the_person +Number of escort tours tours undertaken by the person,-0.15,coef_number_of_escort_tours_tours_undertaken_by_the_person +Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,0.59,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +dummy for distance less than 5 Miles,0.32,coef_dummy_for_distance_less_than_5_miles +dummy for distance in miles,0.01,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-0.968,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops on joint tours,-1.329,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in +Alternative specific constant for return stops,-2.41,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops on joint tours,-2.796,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in +Alternative specific constant for the total number of stops on joint tours,0,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in +Alternative specific constant for return stops,-3.024,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for return stops on joint tours,-3.379,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +Alternative specific constant for outbound stops,-2.173,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for outbound stops on joint tours,-1.783,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in +Alternative specific constant for the total number of stops on joint tours,0.518,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in +Alternative specific constant for outbound stops,-4.294,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for outbound stops on joint tours,-4.067,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in +Alternative specific constant for the total number of stops,-1.807,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for the total number of stops on joint tours,1.497,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +Alternative specific constant for outbound stops,-4.758,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Alternative specific constant for outbound stops on joint tours,-4.998,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +Calibrated coefficient for stops 0 out and 1 in,-0.456326296,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,-0.317345391,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,-0.79256653,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,0.030779564,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,-0.082115923,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,-0.236742759,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-0.922620733,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,0.345406346,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,0.713277244,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,-2.170823478,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,1.928143697,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,0.624920575,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,1.181749655,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,1.977311333,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,3.381035483,coef_calibration_for_3out_3in +,-0.126,coef_telecommute1_2 +,-0.301,coef_telecommute1_3 +,-0.301,coef_telecommute1_4 +,-0.126,coef_telecommute1_5 +,-0.301,coef_telecommute1_6 +,-0.301,coef_telecommute1_7 +,-0.611,coef_telecommute1_8 +,-0.301,coef_telecommute1_9 +,-0.301,coef_telecommute1_10 +,-0.611,coef_telecommute1_11 +,-0.611,coef_telecommute1_12 +,-0.301,coef_telecommute1_13 +,-0.611,coef_telecommute1_14 +,-0.611,coef_telecommute1_15 +,-0.611,coef_telecommute1_16 +,-0.149,coef_telecommute23_2 +,-0.768,coef_telecommute23_3 +,-0.768,coef_telecommute23_4 +,-0.768,coef_telecommute23_5 +,-0.768,coef_telecommute23_6 +,-0.768,coef_telecommute23_7 +,-0.909,coef_telecommute23_8 +,-0.768,coef_telecommute23_9 +,-0.768,coef_telecommute23_10 +,-0.909,coef_telecommute23_11 +,-0.909,coef_telecommute23_12 +,-0.768,coef_telecommute23_13 +,-0.909,coef_telecommute23_14 +,-0.909,coef_telecommute23_15 +,-0.909,coef_telecommute23_16 +,-0.158,coef_telecommute4p_2 +,-0.473,coef_telecommute4p_3 +,-0.473,coef_telecommute4p_4 +,-0.473,coef_telecommute4p_5 +,-0.473,coef_telecommute4p_6 +,-0.473,coef_telecommute4p_7 +,-1.47,coef_telecommute4p_8 +,-0.473,coef_telecommute4p_9 +,-0.473,coef_telecommute4p_10 +,-1.47,coef_telecommute4p_11 +,-1.47,coef_telecommute4p_12 +,-0.473,coef_telecommute4p_13 +,-1.47,coef_telecommute4p_14 +,-1.47,coef_telecommute4p_15 +,-1.47,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_othdiscr.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_othdiscr.csv new file mode 100644 index 000000000..4a861dfa6 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_othdiscr.csv @@ -0,0 +1,90 @@ +Description,value,coefficient_name +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-2.4578,coef_dummy_for_walking_to_all_stops +Number of work tours undertaken by the person,-0.6153,coef_number_of_work_tours_undertaken_by_the_person +Number of shool tours tours undertaken by the person,-0.8176,coef_number_of_shool_tours_tours_undertaken_by_the_person +Number of shop tours undertaken by the person,-0.629,coef_number_of_shop_tours_undertaken_by_the_person +Number of maintenace tours tours undertaken by the person,-0.3715,coef_number_of_maintenace_tours_tours_undertaken_by_the_person +Arrival later than 17:00.,-0.6383,coef_arrival_later_than_17_00_ +Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,0.8335,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +dummy for distance less than 10 Miles ,0.3756,coef_dummy_for_distance_less_than_10_miles_ +dummy for distance in miles,-0.0225,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-0.921,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops on joint tours,-1.329,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in +Alternative specific constant for return stops,-2.336,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops on joint tours,-2.796,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in +Alternative specific constant for the total number of stops on joint tours,0,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in +Alternative specific constant for return stops,-2.927,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for return stops on joint tours,-3.379,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +Alternative specific constant for outbound stops,-1.581,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for outbound stops on joint tours,-1.783,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in +Alternative specific constant for the total number of stops,0.863,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for the total number of stops on joint tours,0.518,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in +Alternative specific constant for outbound stops,-3.323,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for outbound stops on joint tours,-4.067,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in +Alternative specific constant for the total number of stops,0.939,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for the total number of stops on joint tours,1.497,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +Alternative specific constant for outbound stops,-4.623,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Alternative specific constant for outbound stops on joint tours,-4.998,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +Calibrated coefficient for stops 0 out and 1 in,0.290792835,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,0.472319542,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,0.76294318,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,0.694317783,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,0.515942097,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,0.691734937,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-0.047773074,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,1.232476585,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,1.267702806,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,0.047365121,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,-1.077060366,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,2.338918384,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,-0.480740616,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,1.10284077,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,2.15563482,coef_calibration_for_3out_3in +,-0.126,coef_telecommute1_2 +,-0.301,coef_telecommute1_3 +,-0.301,coef_telecommute1_4 +,-0.126,coef_telecommute1_5 +,-0.301,coef_telecommute1_6 +,-0.301,coef_telecommute1_7 +,-0.611,coef_telecommute1_8 +,-0.301,coef_telecommute1_9 +,-0.301,coef_telecommute1_10 +,-0.611,coef_telecommute1_11 +,-0.611,coef_telecommute1_12 +,-0.301,coef_telecommute1_13 +,-0.611,coef_telecommute1_14 +,-0.611,coef_telecommute1_15 +,-0.611,coef_telecommute1_16 +,-0.149,coef_telecommute23_2 +,-0.768,coef_telecommute23_3 +,-0.768,coef_telecommute23_4 +,-0.768,coef_telecommute23_5 +,-0.768,coef_telecommute23_6 +,-0.768,coef_telecommute23_7 +,-0.909,coef_telecommute23_8 +,-0.768,coef_telecommute23_9 +,-0.768,coef_telecommute23_10 +,-0.909,coef_telecommute23_11 +,-0.909,coef_telecommute23_12 +,-0.768,coef_telecommute23_13 +,-0.909,coef_telecommute23_14 +,-0.909,coef_telecommute23_15 +,-0.909,coef_telecommute23_16 +,-0.158,coef_telecommute4p_2 +,-0.473,coef_telecommute4p_3 +,-0.473,coef_telecommute4p_4 +,-0.473,coef_telecommute4p_5 +,-0.473,coef_telecommute4p_6 +,-0.473,coef_telecommute4p_7 +,-1.47,coef_telecommute4p_8 +,-0.473,coef_telecommute4p_9 +,-0.473,coef_telecommute4p_10 +,-1.47,coef_telecommute4p_11 +,-1.47,coef_telecommute4p_12 +,-0.473,coef_telecommute4p_13 +,-1.47,coef_telecommute4p_14 +,-1.47,coef_telecommute4p_15 +,-1.47,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_othmaint.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_othmaint.csv new file mode 100644 index 000000000..95fd9b89c --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_othmaint.csv @@ -0,0 +1,98 @@ +Description,value,coefficient_name +Middle to Low Income HH ,0.17,coef_middle_to_low_income_hh_ +Mid to High Income HH,0.23,coef_mid_to_high_income_hh +High Income HH,0.24,coef_high_income_hh +Number of HH Persons,-0.31,coef_number_of_hh_persons +Number of Students in HH,0.21,coef_number_of_students_in_hh +Presence of Kids between 0 and 4 (including) years old,0.74,coef_presence_of_kids_between_0_and_4_including_years_old +Dummy for female,0.3012,coef_dummy_for_female +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-1.4329,coef_dummy_for_walking_to_all_stops +Number of work tours undertaken by the person,-0.364,coef_number_of_work_tours_undertaken_by_the_person +Number of university tours tours undertaken by the person,-0.6252,coef_number_of_university_tours_tours_undertaken_by_the_person +Number of shool tours tours undertaken by the person,-1.4135,coef_number_of_shool_tours_tours_undertaken_by_the_person +Number of shop tours undertaken by the person,-0.1428,coef_number_of_shop_tours_undertaken_by_the_person +Number of maintenace tours undertaken by the houshold,-0.0468,coef_number_of_maintenace_tours_undertaken_by_the_houshold +Number of persons participating in the tour.Return stops interaction,0.4904,coef_number_of_persons_participating_in_the_tour_return_stops_interaction +Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,0.5134,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +dummy for distance less than 20 Miles ,-0.408,coef_dummy_for_distance_less_than_20_miles_ +dummy for distance in miles,0.0273,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-0.585,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops on joint tours,-1.329,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in +Alternative specific constant for return stops,-1.48,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops on joint tours,-2.796,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in +Alternative specific constant for the total number of stops on joint tours,0,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in +Alternative specific constant for return stops,-2.462,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for return stops on joint tours,-3.379,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +Alternative specific constant for outbound stops,-1.761,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for outbound stops on joint tours,-1.783,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in +Alternative specific constant for the total number of stops,0.414,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for the total number of stops on joint tours,0.518,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in +Alternative specific constant for outbound stops,-3.661,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for outbound stops on joint tours,-4.067,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in +Alternative specific constant for the total number of stops,0.488,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for the total number of stops on joint tours,1.497,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +Alternative specific constant for outbound stops,-5.426,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Alternative specific constant for outbound stops on joint tours,-4.998,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +Calibrated coefficient for stops 0 out and 1 in,0.205739686,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,0.210426665,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,0.646983288,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,0.794725126,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,0.796895947,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,0.311667481,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,1.123540292,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,1.103785395,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,0.470492284,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,0.633549942,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,1.884190334,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,1.422429266,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,2.390980042,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,0.863350747,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,1.268073696,coef_calibration_for_3out_3in +,-0.126,coef_telecommute1_2 +,-0.301,coef_telecommute1_3 +,-0.301,coef_telecommute1_4 +,-0.126,coef_telecommute1_5 +,-0.301,coef_telecommute1_6 +,-0.301,coef_telecommute1_7 +,-0.611,coef_telecommute1_8 +,-0.301,coef_telecommute1_9 +,-0.301,coef_telecommute1_10 +,-0.611,coef_telecommute1_11 +,-0.611,coef_telecommute1_12 +,-0.301,coef_telecommute1_13 +,-0.611,coef_telecommute1_14 +,-0.611,coef_telecommute1_15 +,-0.611,coef_telecommute1_16 +,-0.149,coef_telecommute23_2 +,-0.768,coef_telecommute23_3 +,-0.768,coef_telecommute23_4 +,-0.768,coef_telecommute23_5 +,-0.768,coef_telecommute23_6 +,-0.768,coef_telecommute23_7 +,-0.909,coef_telecommute23_8 +,-0.768,coef_telecommute23_9 +,-0.768,coef_telecommute23_10 +,-0.909,coef_telecommute23_11 +,-0.909,coef_telecommute23_12 +,-0.768,coef_telecommute23_13 +,-0.909,coef_telecommute23_14 +,-0.909,coef_telecommute23_15 +,-0.909,coef_telecommute23_16 +,-0.158,coef_telecommute4p_2 +,-0.473,coef_telecommute4p_3 +,-0.473,coef_telecommute4p_4 +,-0.473,coef_telecommute4p_5 +,-0.473,coef_telecommute4p_6 +,-0.473,coef_telecommute4p_7 +,-1.47,coef_telecommute4p_8 +,-0.473,coef_telecommute4p_9 +,-0.473,coef_telecommute4p_10 +,-1.47,coef_telecommute4p_11 +,-1.47,coef_telecommute4p_12 +,-0.473,coef_telecommute4p_13 +,-1.47,coef_telecommute4p_14 +,-1.47,coef_telecommute4p_15 +,-1.47,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_school.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_school.csv new file mode 100644 index 000000000..0a093aa2c --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_school.csv @@ -0,0 +1,36 @@ +Description,value,coefficient_name +Number of HH Persons,-0.506,coef_number_of_hh_persons +Presence of kids between 5 and 15 (including) years old,0.3299,coef_presence_of_kids_between_5_and_15_including_years_old +Number of Cars > Number of Workers,0.5331,coef_number_of_cars_number_of_workers +Dummy for female,0.4099,coef_dummy_for_female +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-1.8163,coef_dummy_for_walking_to_all_stops +Number of escort tours tours undertaken by the person,1.2365,coef_number_of_escort_tours_tours_undertaken_by_the_person +Arrival later than 17:00.,1.8377,coef_arrival_later_than_17_00_ +Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,0.9549,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +dummy for distance in miles,0.0438,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-1.206,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops,-2.672,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops,-3.364,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for outbound stops,-2.123,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for the total number of stops,0.701,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for outbound stops,-3.798,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for the total number of stops,1.135,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for outbound stops,-5.85,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Calibrated coefficient for stops 0 out and 1 in,-2.254972707,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,-2.011200307,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,-2.140534054,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,-2.6157216,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,-2.05970613,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,-1.802894203,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-2.177625735,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,-2.918162565,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,-3.083316079,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,-3.893518401,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,-1.086994529,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,-5.180196121,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,-4.548639536,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,-3.323713083,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,-0.129535785,coef_calibration_for_3out_3in diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_shopping.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_shopping.csv new file mode 100644 index 000000000..8524ebe28 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_shopping.csv @@ -0,0 +1,93 @@ +Description,value,coefficient_name +Number of HH Persons,-0.1522,coef_number_of_hh_persons +Num kids between 5 and 15 (including) years old,0.0482,coef_num_kids_between_5_and_15_including_years_old +Dummy for female,0.1721,coef_dummy_for_female +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-1.4908,coef_dummy_for_walking_to_all_stops +Number of work tours undertaken by the person,-0.548,coef_number_of_work_tours_undertaken_by_the_person +Number of university tours tours undertaken by the person,-0.6709,coef_number_of_university_tours_tours_undertaken_by_the_person +Number of maintenace tours tours undertaken by the person,-0.1977,coef_number_of_maintenace_tours_tours_undertaken_by_the_person +Number of shop tours undertaken by the houshold,-0.0733,coef_number_of_shop_tours_undertaken_by_the_houshold +Dummy for only adults participate in the tour,0.1902,coef_dummy_for_only_adults_participate_in_the_tour +Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,0.9056,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +dummy for distance less than 5 Miles,0.3768,coef_dummy_for_distance_less_than_5_miles +dummy for distance in miles,0.0289,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-1.179,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops on joint tours,-1.329,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in +Alternative specific constant for return stops,-2.305,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops on joint tours,-2.796,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in +Alternative specific constant for the total number of stops on joint tours,0,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in +Alternative specific constant for return stops,-3.024,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for return stops on joint tours,-3.379,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +Alternative specific constant for outbound stops,-1.339,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for outbound stops on joint tours,-1.783,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in +Alternative specific constant for the total number of stops,0.252,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for the total number of stops on joint tours,0.518,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in +Alternative specific constant for outbound stops,-3.11,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for outbound stops on joint tours,-4.067,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in +Alternative specific constant for the total number of stops,0.514,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for the total number of stops on joint tours,1.497,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +Alternative specific constant for outbound stops,-4.487,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Alternative specific constant for outbound stops on joint tours,-4.998,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +Calibrated coefficient for stops 0 out and 1 in,0.017121958,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,0.034817267,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,-0.130330682,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,0.209231,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,0.02414933,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,0.461897472,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,0.158579421,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,0.850102453,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,1.341252395,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,1.18586399,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,-0.041491927,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,1.607200672,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,1.911336809,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,1.065391227,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,1.37891856,coef_calibration_for_3out_3in +,-0.126,coef_telecommute1_2 +,-0.301,coef_telecommute1_3 +,-0.301,coef_telecommute1_4 +,-0.126,coef_telecommute1_5 +,-0.301,coef_telecommute1_6 +,-0.301,coef_telecommute1_7 +,-0.611,coef_telecommute1_8 +,-0.301,coef_telecommute1_9 +,-0.301,coef_telecommute1_10 +,-0.611,coef_telecommute1_11 +,-0.611,coef_telecommute1_12 +,-0.301,coef_telecommute1_13 +,-0.611,coef_telecommute1_14 +,-0.611,coef_telecommute1_15 +,-0.611,coef_telecommute1_16 +,-0.149,coef_telecommute23_2 +,-0.768,coef_telecommute23_3 +,-0.768,coef_telecommute23_4 +,-0.768,coef_telecommute23_5 +,-0.768,coef_telecommute23_6 +,-0.768,coef_telecommute23_7 +,-0.909,coef_telecommute23_8 +,-0.768,coef_telecommute23_9 +,-0.768,coef_telecommute23_10 +,-0.909,coef_telecommute23_11 +,-0.909,coef_telecommute23_12 +,-0.768,coef_telecommute23_13 +,-0.909,coef_telecommute23_14 +,-0.909,coef_telecommute23_15 +,-0.909,coef_telecommute23_16 +,-0.158,coef_telecommute4p_2 +,-0.473,coef_telecommute4p_3 +,-0.473,coef_telecommute4p_4 +,-0.473,coef_telecommute4p_5 +,-0.473,coef_telecommute4p_6 +,-0.473,coef_telecommute4p_7 +,-1.47,coef_telecommute4p_8 +,-0.473,coef_telecommute4p_9 +,-0.473,coef_telecommute4p_10 +,-1.47,coef_telecommute4p_11 +,-1.47,coef_telecommute4p_12 +,-0.473,coef_telecommute4p_13 +,-1.47,coef_telecommute4p_14 +,-1.47,coef_telecommute4p_15 +,-1.47,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_social.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_social.csv new file mode 100644 index 000000000..664ed1e5e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_social.csv @@ -0,0 +1,93 @@ +Description,value,coefficient_name +Number of Vehicles,-0.19,coef_number_of_vehicles +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-1.73,coef_dummy_for_walking_to_all_stops +Number of work tours undertaken by the person,-0.28,coef_number_of_work_tours_undertaken_by_the_person +Number of shop tours undertaken by the person,-0.24,coef_number_of_shop_tours_undertaken_by_the_person +At least one kid and one adult participate in the tour,0.37,coef_at_least_one_kid_and_one_adult_participate_in_the_tour +Arrival later than 17:00.,-0.45,coef_arrival_later_than_17_00_ +Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,1.31,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_ +dummy for distance in miles,-0.01,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-1.12,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops on joint tours,-1.329,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in +Dummy for a return visiting tour,-0.64,coef_dummy_for_a_return_visiting_tour +Alternative specific constant for return stops,-2.764,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops on joint tours,-2.796,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in +Alternative specific constant for the total number of stops on joint tours,0,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in +Alternative specific constant for return stops,-3.451,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for return stops on joint tours,-3.379,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +Number of persons participating in the tour.Outgoing stops interaction,-0.46,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction +Alternative specific constant for outbound stops,-1.081,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for outbound stops on joint tours,-1.783,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in +Dummy for an outbound visiting tour,-0.69,coef_dummy_for_an_outbound_visiting_tour +Dummy for a visiting tour with both outbound and return leg,0.44,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg +Alternative specific constant for the total number of stops,0.496,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for the total number of stops on joint tours,0.518,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in +Alternative specific constant for outbound stops,-2.874,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for outbound stops on joint tours,-4.067,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in +Alternative specific constant for the total number of stops,0.882,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for the total number of stops on joint tours,1.497,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +Alternative specific constant for outbound stops,-4.552,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Alternative specific constant for outbound stops on joint tours,-4.998,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +Calibrated coefficient for stops 0 out and 1 in,-0.22936999,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,0.529587765,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,0.538219032,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,0.218718688,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,-0.318021224,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,1.030756549,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-2.51155013,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,1.386390249,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,-1.163443209,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,0.220714165,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,0.895315224,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,2.965417908,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,0.472314942,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,3.172643171,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,3.347592,coef_calibration_for_3out_3in +,-0.126,coef_telecommute1_2 +,-0.301,coef_telecommute1_3 +,-0.301,coef_telecommute1_4 +,-0.126,coef_telecommute1_5 +,-0.301,coef_telecommute1_6 +,-0.301,coef_telecommute1_7 +,-0.611,coef_telecommute1_8 +,-0.301,coef_telecommute1_9 +,-0.301,coef_telecommute1_10 +,-0.611,coef_telecommute1_11 +,-0.611,coef_telecommute1_12 +,-0.301,coef_telecommute1_13 +,-0.611,coef_telecommute1_14 +,-0.611,coef_telecommute1_15 +,-0.611,coef_telecommute1_16 +,-0.149,coef_telecommute23_2 +,-0.768,coef_telecommute23_3 +,-0.768,coef_telecommute23_4 +,-0.768,coef_telecommute23_5 +,-0.768,coef_telecommute23_6 +,-0.768,coef_telecommute23_7 +,-0.909,coef_telecommute23_8 +,-0.768,coef_telecommute23_9 +,-0.768,coef_telecommute23_10 +,-0.909,coef_telecommute23_11 +,-0.909,coef_telecommute23_12 +,-0.768,coef_telecommute23_13 +,-0.909,coef_telecommute23_14 +,-0.909,coef_telecommute23_15 +,-0.909,coef_telecommute23_16 +,-0.158,coef_telecommute4p_2 +,-0.473,coef_telecommute4p_3 +,-0.473,coef_telecommute4p_4 +,-0.473,coef_telecommute4p_5 +,-0.473,coef_telecommute4p_6 +,-0.473,coef_telecommute4p_7 +,-1.47,coef_telecommute4p_8 +,-0.473,coef_telecommute4p_9 +,-0.473,coef_telecommute4p_10 +,-1.47,coef_telecommute4p_11 +,-1.47,coef_telecommute4p_12 +,-0.473,coef_telecommute4p_13 +,-1.47,coef_telecommute4p_14 +,-1.47,coef_telecommute4p_15 +,-1.47,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_univ.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_univ.csv new file mode 100644 index 000000000..ae51954ae --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_univ.csv @@ -0,0 +1,35 @@ +Description,value,coefficient_name +Number of HH Persons,-0.2827,coef_number_of_hh_persons +Presence of kids between 5 and 15 (including) years old,0.6823,coef_presence_of_kids_between_5_and_15_including_years_old +Number of Vehicles,0.1703,coef_number_of_vehicles +Dummy for female,0.7349,coef_dummy_for_female +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Number of escort tours tours undertaken by the person,0.9018,coef_number_of_escort_tours_tours_undertaken_by_the_person +Arrival later than 17:00.,0.389,coef_arrival_later_than_17_00_ +Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,0.8434,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +HH accesibility for inbound tours. Interaction,0.2481,coef_hh_accesibility_for_inbound_tours_interaction +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-2.003,coef_alternative_specific_constant_for_return_stops_0out_1in +Alternative specific constant for return stops,-3.51,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops,-3.677,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for outbound stops,-2.628,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for the total number of stops,1.272,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in +Alternative specific constant for outbound stops,-3.741,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for the total number of stops,1.871,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for outbound stops,-4.981,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Calibrated coefficient for stops 0 out and 1 in,-0.957893279,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,0.013364686,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,-1.128041828,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,-0.815453021,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,0.36813072,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,1.560091494,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-1.363437784,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,-0.87970088,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,-1.280333926,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,-1.562370933,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,-0.135706787,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,-1.287689684,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,-1.046385509,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,-1.344388242,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,-2.396963195,coef_calibration_for_3out_3in diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_work.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_work.csv new file mode 100644 index 000000000..446c24d97 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_coefficients_work.csv @@ -0,0 +1,49 @@ +Description,value,coefficient_name +Middle to Low Income HH,0.17,coef_middle_to_low_income_hh +Mid to High Income HH,0.23,coef_mid_to_high_income_hh +High Income HH,0.24,coef_high_income_hh +Number of HH Persons,-0.31,coef_number_of_hh_persons +Number of Students in HH,0.21,coef_number_of_students_in_hh +Presence of Kids between 0 and 4 (including) years old,0.74,coef_presence_of_kids_between_0_and_4_including_years_old +Num kids between 5 and 15 (including) years old,0.08,coef_num_kids_between_5_and_15_including_years_old +Presence of kids between 5 and 15 (including) years old,0.26,coef_presence_of_kids_between_5_and_15_including_years_old +Number of Adults (>= 16 years old),0.03,coef_number_of_adults_16_years_old_ +Number of Cars > Number of Workers,0.16,coef_number_of_cars_number_of_workers +Dummy for female,0.22,coef_dummy_for_female +Dummy for all stops made by transit,-0.7,coef_dummy_for_all_stops_made_by_transit +Dummy for walking to all stops,-1.54,coef_dummy_for_walking_to_all_stops +Number of work tours undertaken by the person,-0.15,coef_number_of_work_tours_undertaken_by_the_person +Number of university tours tours undertaken by the person,-0.48,coef_number_of_university_tours_tours_undertaken_by_the_person +Number of school tours tours undertaken by the person,-1.55,coef_number_of_school_tours_tours_undertaken_by_the_person +Number of escort tours tours undertaken by the person,0.2,coef_number_of_escort_tours_tours_undertaken_by_the_person +Number of shop tours undertaken by the houshold,-0.05,coef_number_of_shop_tours_undertaken_by_the_houshold +AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,-1.93,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours +Evening Arrival (>=19:00) Interacted with return tours,0.31,coef_evening_arrival_19_00_interacted_with_return_tours +Dummy for the duration of the tour being equal or greater than or equal to 11 hours,0.6,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours +dummy for distance less than 20 Miles,-0.22,coef_dummy_for_distance_less_than_20_miles +dummy for distance in miles,0.01,coef_dummy_for_distance_in_miles +No stops if tour mode is driveTransit,-999,coef_no_stops_if_tour_mode_is_drivetransit +Alternative specific constant for return stops,-0.445,coef_alternative_specific_constant_for_return_stops_0out_1in +Number of subtours in the tour,0.19,coef_number_of_subtours_in_the_tour +Alternative specific constant for return stops,-1.775,coef_alternative_specific_constant_for_return_stops_0out_2in +Alternative specific constant for the total number of stops,0,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in +Alternative specific constant for return stops,-2.139,coef_alternative_specific_constant_for_return_stops_0out_3in +Alternative specific constant for outbound stops,-0.833,coef_alternative_specific_constant_for_outbound_stops_1out_0in +Alternative specific constant for outbound stops,-2.613,coef_alternative_specific_constant_for_outbound_stops_2out_0in +Alternative specific constant for the total number of stops,0.695,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +Alternative specific constant for outbound stops,-3.934,coef_alternative_specific_constant_for_outbound_stops_3out_0in +Calibrated coefficient for stops 0 out and 1 in,0.282545956,coef_calibration_for_0out_1in +Calibrated coefficient for stops 0 out and 2 in,0.378884046,coef_calibration_for_0out_2in +Calibrated coefficient for stops 0 out and 3 in,-0.14156218,coef_calibration_for_0out_3in +Calibrated coefficient for stops 1 out and 0 in,-0.201468584,coef_calibration_for_1out_0in +Calibrated coefficient for stops 1 out and 1 in,-0.150830082,coef_calibration_for_1out_1in +Calibrated coefficient for stops 1 out and 2 in,-0.038370256,coef_calibration_for_1out_2in +Calibrated coefficient for stops 1 out and 3 in,-0.458167576,coef_calibration_for_1out_3in +Calibrated coefficient for stops 2 out and 0 in,-0.238615836,coef_calibration_for_2out_0in +Calibrated coefficient for stops 2 out and 1 in,-0.366936647,coef_calibration_for_2out_1in +Calibrated coefficient for stops 2 out and 2 in,0.964901262,coef_calibration_for_2out_2in +Calibrated coefficient for stops 2 out and 3 in,-0.052575958,coef_calibration_for_2out_3in +Calibrated coefficient for stops 3 out and 0 in,0.102180805,coef_calibration_for_3out_0in +Calibrated coefficient for stops 3 out and 1 in,-1.078935365,coef_calibration_for_3out_1in +Calibrated coefficient for stops 3 out and 2 in,-0.962167532,coef_calibration_for_3out_2in +Calibrated coefficient for stops 3 out and 3 in,-0.165201068,coef_calibration_for_3out_3in diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_eatout.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_eatout.csv new file mode 100644 index 000000000..479dd8ba7 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_eatout.csv @@ -0,0 +1,56 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh_,Middle to Low Income HH ,(income_in_thousands>19999) & (income_in_thousands<50000),,,,,,,,,,,,,,,, +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,,,,,,,,,,,,,,, +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,,,,,,,,,,,,,,, +util_number_of_hh_persons,Number of HH Persons,hhsize,,,,,,,,,,,,,,,, +util_number_of_full_time_workes_in_hh,Number of full time workes in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,,,,,,,,,,,,,,, +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,,,,,,,,,,,,,,, +util_num_kids_between_4_and_15_including_years_old,Num kids between 4 and 15 (including) years old,num_age_5_15,,,,,,,,,,,,,,,, +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,,,,,,,,,,,,,,, +util_number_of_vehicles,Number of Vehicles,auto_ownership,,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles +util_dummy_for_female,Dummy for female,~is_joint & female,,,,,,,,,,,,,,,, +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,~is_joint * num_work_tours,,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,~is_joint * num_univ_tours,,,,,,,,,,,,,,,, +util_number_of_shool_tours_tours_undertaken_by_the_person,Number of shool tours tours undertaken by the person,~is_joint * num_school_tours,,,,,,,,,,,,,,,, +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,~is_joint * num_escort_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,~is_joint * num_shop_tours,,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,~is_joint * num_maint_tours,,,,,,,,,,,,,,,, +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,~is_joint * num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,~is_joint * num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,,,,,,,,,,,,,,, +util_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,Number of persons participating in the tour.Outgoing stops interaction,is_joint * number_of_participants,,,,,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction +util_number_of_persons_participating_in_the_tour_return_stops_interaction,Number of persons participating in the tour.Return stops interaction,is_joint * number_of_participants,,,,,,,,,,,,,,,, +util_at_least_one_kid_and_one_adult_participate_in_the_tour,At least one kid and one adult participate in the tour,composition=='mixed',,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_ +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_ +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_20_miles_,dummy for distance less than 20 Miles ,(distance_in_miles < 20),,,,,,,,,,,,,,,, +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,~is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,~is_joint,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,~is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_alternative_specific_constant_for_outbound_stops_on_joint_tours,Alternative specific constant for outbound stops on joint tours,is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +util_alternative_specific_constant_for_return_stops_on_joint_tours,Alternative specific constant for return stops on joint tours,is_joint,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours,Alternative specific constant for the total number of stops on joint tours,is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +util_dummy_for_an_outbound_visiting_tour,Dummy for an outbound visiting tour,primary_purpose == 'social',,,,,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour +util_dummy_for_a_return_visiting_tour,Dummy for a return visiting tour,primary_purpose == 'social',,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour +util_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,Dummy for a visiting tour with both outbound and return leg,primary_purpose == 'social',,,,,,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg +util_Phase1_Calibration,Phase1_Calibration,~is_joint,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in +util_telecommute1,(num_work_tours == 0) & (telecommute_frequency=='1_day_week'),,coef_telecommute1_2,coef_telecommute1_3,coef_telecommute1_4,coef_telecommute1_5,coef_telecommute1_6,coef_telecommute1_7,coef_telecommute1_8,coef_telecommute1_9,coef_telecommute1_10,coef_telecommute1_11,coef_telecommute1_12,coef_telecommute1_13,coef_telecommute1_14,coef_telecommute1_15,coef_telecommute1_16 +util_telecommute23,(num_work_tours == 0) & (telecommute_frequency=='2_3_days_week'),,coef_telecommute23_2,coef_telecommute23_3,coef_telecommute23_4,coef_telecommute23_5,coef_telecommute23_6,coef_telecommute23_7,coef_telecommute23_8,coef_telecommute23_9,coef_telecommute23_10,coef_telecommute23_11,coef_telecommute23_12,coef_telecommute23_13,coef_telecommute23_14,coef_telecommute23_15,coef_telecommute23_16 +util_telecommute4p,(num_work_tours == 0) & (telecommute_frequency=='4_days_week'),,coef_telecommute4p_2,coef_telecommute4p_3,coef_telecommute4p_4,coef_telecommute4p_5,coef_telecommute4p_6,coef_telecommute4p_7,coef_telecommute4p_8,coef_telecommute4p_9,coef_telecommute4p_10,coef_telecommute4p_11,coef_telecommute4p_12,coef_telecommute4p_13,coef_telecommute4p_14,coef_telecommute4p_15,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_escort.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_escort.csv new file mode 100644 index 000000000..aab34960b --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_escort.csv @@ -0,0 +1,50 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh,Middle to Low Income HH,(income_in_thousands>19999) & (income_in_thousands<50000),,,,,,,,,,,,,,,, +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,,,,,,,,,,,,,,, +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,,,,,,,,,,,,,,, +util_number_of_hh_persons,Number of HH Persons,hhsize,,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons +util_number_of_full_time_workers_in_hh,Number of full time workers in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,,,,,,,,,,,,,,, +util_num_kids_between_5_and_15_including_years_old,Num kids between 5 and 15 (including) years old,num_age_5_15,,,,,,,,,,,,,,,, +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,,,,,,,,,,,,,,, +util_number_of_vehicles,Number of Vehicles,auto_ownership,,,,,,,,,,,,,,,, +util_dummy_for_female,Dummy for female,female,,,,,,,,,,,,,,,, +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,num_work_tours,,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,num_univ_tours,,,,,,,,,,,,,,,, +util_number_of_school_tours_tours_undertaken_by_the_person,Number of school tours tours undertaken by the person,num_school_tours,,,,,,,,,,,,,,,, +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,num_escort_tours,,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,num_shop_tours,,,,,,,,,,,,,,,, +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,num_maint_tours,,,,,,,,,,,,,,,, +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,,,,,,,,,,,,,,, +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,,,,,,,,,,,,,,, +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,,,,,,,,,,,,,,, +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_5_miles,dummy for distance less than 5 Miles,(distance_in_miles < 5),,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,~is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,~is_joint,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,~is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_alternative_specific_constant_for_outbound_stops_on_joint_tours,Alternative specific constant for outbound stops on joint tours,is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +util_alternative_specific_constant_for_return_stops_on_joint_tours,Alternative specific constant for return stops on joint tours,is_joint,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours,Alternative specific constant for the total number of stops on joint tours,is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +util_Phase1_Calibration,Phase1_Calibration,~is_joint,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in +util_telecommute1,(num_work_tours == 0) & (telecommute_frequency=='1_day_week'),,coef_telecommute1_2,coef_telecommute1_3,coef_telecommute1_4,coef_telecommute1_5,coef_telecommute1_6,coef_telecommute1_7,coef_telecommute1_8,coef_telecommute1_9,coef_telecommute1_10,coef_telecommute1_11,coef_telecommute1_12,coef_telecommute1_13,coef_telecommute1_14,coef_telecommute1_15,coef_telecommute1_16 +util_telecommute23,(num_work_tours == 0) & (telecommute_frequency=='2_3_days_week'),,coef_telecommute23_2,coef_telecommute23_3,coef_telecommute23_4,coef_telecommute23_5,coef_telecommute23_6,coef_telecommute23_7,coef_telecommute23_8,coef_telecommute23_9,coef_telecommute23_10,coef_telecommute23_11,coef_telecommute23_12,coef_telecommute23_13,coef_telecommute23_14,coef_telecommute23_15,coef_telecommute23_16 +util_telecommute4p,(num_work_tours == 0) & (telecommute_frequency=='4_days_week'),,coef_telecommute4p_2,coef_telecommute4p_3,coef_telecommute4p_4,coef_telecommute4p_5,coef_telecommute4p_6,coef_telecommute4p_7,coef_telecommute4p_8,coef_telecommute4p_9,coef_telecommute4p_10,coef_telecommute4p_11,coef_telecommute4p_12,coef_telecommute4p_13,coef_telecommute4p_14,coef_telecommute4p_15,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_othdiscr.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_othdiscr.csv new file mode 100644 index 000000000..098c7b074 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_othdiscr.csv @@ -0,0 +1,52 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh_,Middle to Low Income HH ,(income_in_thousands>19999) & (income_in_thousands<50000),,,,,,,,,,,,,,,, +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,,,,,,,,,,,,,,, +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,,,,,,,,,,,,,,, +util_number_of_hh_persons,Number of HH Persons,hhsize,,,,,,,,,,,,,,,, +util_number_of_full_time_workes_in_hh,Number of full time workes in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,,,,,,,,,,,,,,, +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,,,,,,,,,,,,,,, +util_num_kids_between_4_and_15_including_years_old,Num kids between 4 and 15 (including) years old,num_age_5_15,,,,,,,,,,,,,,,, +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,,,,,,,,,,,,,,, +util_number_of_vehicles,Number of Vehicles,auto_ownership,,,,,,,,,,,,,,,, +util_dummy_for_female,Dummy for female,~is_joint & female,,,,,,,,,,,,,,,, +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,~is_joint * num_work_tours,,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,~is_joint * num_univ_tours,,,,,,,,,,,,,,,, +util_number_of_shool_tours_tours_undertaken_by_the_person,Number of shool tours tours undertaken by the person,~is_joint * num_school_tours,,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,~is_joint * num_escort_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,~is_joint * num_shop_tours,,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,~is_joint * num_maint_tours,,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,~is_joint * num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,~is_joint * num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,,,,,,,,,,,,,,, +util_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,Number of persons participating in the tour.Outgoing stops interaction,is_joint * number_of_participants,,,,,,,,,,,,,,,, +util_number_of_persons_participating_in_the_tour_return_stops_interaction,Number of persons participating in the tour.Return stops interaction,is_joint * number_of_participants,,,,,,,,,,,,,,,, +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_ +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,,,,,,,,,,,,,,, +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_10_miles_,dummy for distance less than 10 Miles ,(distance_in_miles < 10),,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_,coef_dummy_for_distance_less_than_10_miles_ +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,~is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,~is_joint,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,~is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_alternative_specific_constant_for_outbound_stops_on_joint_tours,Alternative specific constant for outbound stops on joint tours,is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +util_alternative_specific_constant_for_return_stops_on_joint_tours,Alternative specific constant for return stops on joint tours,is_joint,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours,Alternative specific constant for the total number of stops on joint tours,is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +util_Phase1_Calibration,Phase1_Calibration,~is_joint,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in +util_telecommute1,(num_work_tours == 0) & (telecommute_frequency=='1_day_week'),,coef_telecommute1_2,coef_telecommute1_3,coef_telecommute1_4,coef_telecommute1_5,coef_telecommute1_6,coef_telecommute1_7,coef_telecommute1_8,coef_telecommute1_9,coef_telecommute1_10,coef_telecommute1_11,coef_telecommute1_12,coef_telecommute1_13,coef_telecommute1_14,coef_telecommute1_15,coef_telecommute1_16 +util_telecommute23,(num_work_tours == 0) & (telecommute_frequency=='2_3_days_week'),,coef_telecommute23_2,coef_telecommute23_3,coef_telecommute23_4,coef_telecommute23_5,coef_telecommute23_6,coef_telecommute23_7,coef_telecommute23_8,coef_telecommute23_9,coef_telecommute23_10,coef_telecommute23_11,coef_telecommute23_12,coef_telecommute23_13,coef_telecommute23_14,coef_telecommute23_15,coef_telecommute23_16 +util_telecommute4p,(num_work_tours == 0) & (telecommute_frequency=='4_days_week'),,coef_telecommute4p_2,coef_telecommute4p_3,coef_telecommute4p_4,coef_telecommute4p_5,coef_telecommute4p_6,coef_telecommute4p_7,coef_telecommute4p_8,coef_telecommute4p_9,coef_telecommute4p_10,coef_telecommute4p_11,coef_telecommute4p_12,coef_telecommute4p_13,coef_telecommute4p_14,coef_telecommute4p_15,coef_telecommute4p_16 \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_othmaint.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_othmaint.csv new file mode 100644 index 000000000..6259d5513 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_othmaint.csv @@ -0,0 +1,53 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh_,Middle to Low Income HH ,(income_in_thousands>19999) & (income_in_thousands<50000),,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_,coef_middle_to_low_income_hh_ +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh +util_number_of_hh_persons,Number of HH Persons,hhsize,,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons +util_number_of_full_time_workes_in_hh,Number of full time workes in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old +util_num_kids_between_4_and_15_including_years_old,Num kids between 4 and 15 (including) years old,num_age_5_15,,,,,,,,,,,,,,,, +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,,,,,,,,,,,,,,, +util_number_of_vehicles,Number of Vehicles,auto_ownership,,,,,,,,,,,,,,,, +util_dummy_for_female,Dummy for female,~is_joint & female,,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,~is_joint * num_work_tours,,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,~is_joint * num_univ_tours,,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person +util_number_of_shool_tours_tours_undertaken_by_the_person,Number of shool tours tours undertaken by the person,~is_joint * num_school_tours,,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person,coef_number_of_shool_tours_tours_undertaken_by_the_person +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,~is_joint * num_escort_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,~is_joint * num_shop_tours,,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,~is_joint * num_maint_tours,,,,,,,,,,,,,,,, +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,~is_joint * num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,~is_joint * num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,,,,,,,,,,,,,,, +util_number_of_maintenace_tours_undertaken_by_the_houshold,Number of maintenace tours undertaken by the houshold,num_hh_maint_tours,,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold,coef_number_of_maintenace_tours_undertaken_by_the_houshold +util_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,Number of persons participating in the tour.Outgoing stops interaction,is_joint * number_of_participants,,,,,,,,,,,,,,,, +util_number_of_persons_participating_in_the_tour_return_stops_interaction,Number of persons participating in the tour.Return stops interaction,is_joint * number_of_participants,,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction,coef_number_of_persons_participating_in_the_tour_return_stops_interaction +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,,,,,,,,,,,,,,, +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,,,,,,,,,,,,,,, +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_20_miles_,dummy for distance less than 20 Miles ,(distance_in_miles < 20),,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_,coef_dummy_for_distance_less_than_20_miles_ +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,~is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,~is_joint,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,~is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_alternative_specific_constant_for_outbound_stops_on_joint_tours,Alternative specific constant for outbound stops on joint tours,is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +util_alternative_specific_constant_for_return_stops_on_joint_tours,Alternative specific constant for return stops on joint tours,is_joint,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours,Alternative specific constant for the total number of stops on joint tours,is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +util_Phase1_Calibration,Phase1_Calibration,~is_joint,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in +util_telecommute1,(num_work_tours == 0) & (telecommute_frequency=='1_day_week'),,coef_telecommute1_2,coef_telecommute1_3,coef_telecommute1_4,coef_telecommute1_5,coef_telecommute1_6,coef_telecommute1_7,coef_telecommute1_8,coef_telecommute1_9,coef_telecommute1_10,coef_telecommute1_11,coef_telecommute1_12,coef_telecommute1_13,coef_telecommute1_14,coef_telecommute1_15,coef_telecommute1_16 +util_telecommute23,(num_work_tours == 0) & (telecommute_frequency=='2_3_days_week'),,coef_telecommute23_2,coef_telecommute23_3,coef_telecommute23_4,coef_telecommute23_5,coef_telecommute23_6,coef_telecommute23_7,coef_telecommute23_8,coef_telecommute23_9,coef_telecommute23_10,coef_telecommute23_11,coef_telecommute23_12,coef_telecommute23_13,coef_telecommute23_14,coef_telecommute23_15,coef_telecommute23_16 +util_telecommute4p,(num_work_tours == 0) & (telecommute_frequency=='4_days_week'),,coef_telecommute4p_2,coef_telecommute4p_3,coef_telecommute4p_4,coef_telecommute4p_5,coef_telecommute4p_6,coef_telecommute4p_7,coef_telecommute4p_8,coef_telecommute4p_9,coef_telecommute4p_10,coef_telecommute4p_11,coef_telecommute4p_12,coef_telecommute4p_13,coef_telecommute4p_14,coef_telecommute4p_15,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_school.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_school.csv new file mode 100644 index 000000000..af33fb5d8 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_school.csv @@ -0,0 +1,44 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh,Middle to Low Income HH,(income_in_thousands>19999) & (income_in_thousands<50000),,,,,,,,,,,,,,,, +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,,,,,,,,,,,,,,, +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,,,,,,,,,,,,,,, +util_number_of_hh_persons,Number of HH Persons,hhsize,,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons +util_number_of_full_time_workers_in_hh,Number of full time workers in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,,,,,,,,,,,,,,, +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,,,,,,,,,,,,,,, +util_num_kids_between_5_and_15_including_years_old,Num kids between 5 and 15 (including) years old,num_age_5_15,,,,,,,,,,,,,,,, +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers +util_number_of_vehicles,Number of Vehicles,auto_ownership,,,,,,,,,,,,,,,, +util_dummy_for_female,Dummy for female,female,,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,num_work_tours,,,,,,,,,,,,,,,, +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,num_univ_tours,,,,,,,,,,,,,,,, +util_number_of_school_tours_tours_undertaken_by_the_person,Number of school tours tours undertaken by the person,num_school_tours,,,,,,,,,,,,,,,, +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,num_escort_tours,,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,num_shop_tours,,,,,,,,,,,,,,,, +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,num_maint_tours,,,,,,,,,,,,,,,, +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,,,,,,,,,,,,,,, +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_ +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,,,,,,,,,,,,,,, +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_15_miles,dummy for distance less than 15 Miles,(distance_in_miles < 15),,,,,,,,,,,,,,,, +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,1,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,1,,coef_alternative_specific_constant_for_return_stops_0out_1in,-2.672,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,-2.672,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,-2.672,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,-2.672,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,1,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_Phase1_Calibration,Phase1_Calibration,1,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_shopping.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_shopping.csv new file mode 100644 index 000000000..b7c022569 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_shopping.csv @@ -0,0 +1,53 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh,Middle to Low Income HH,(income_in_thousands>19999) & (income_in_thousands<50000),,,,,,,,,,,,,,,, +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,,,,,,,,,,,,,,, +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,,,,,,,,,,,,,,, +util_number_of_hh_persons,Number of HH Persons,hhsize,,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons +util_number_of_full_time_workers_in_hh,Number of full time workers in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,,,,,,,,,,,,,,, +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,,,,,,,,,,,,,,, +util_num_kids_between_5_and_15_including_years_old,Num kids between 5 and 15 (including) years old,num_age_5_15,,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,,,,,,,,,,,,,,, +util_number_of_vehicles,Number of Vehicles,auto_ownership,,,,,,,,,,,,,,,, +util_dummy_for_female,Dummy for female,~is_joint & female,,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,~is_joint * num_work_tours,,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,~is_joint * num_univ_tours,,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person +util_number_of_school_tours_tours_undertaken_by_the_person,Number of school tours tours undertaken by the person,~is_joint * num_school_tours,,,,,,,,,,,,,,,, +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,~is_joint * num_escort_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,~is_joint * num_shop_tours,,,,,,,,,,,,,,,, +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,~is_joint * num_maint_tours,,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person,coef_number_of_maintenace_tours_tours_undertaken_by_the_person +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,~is_joint * num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,~is_joint * num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold +util_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,Number of persons participating in the tour.Outgoing stops interaction,is_joint * number_of_participants,,,,,,,,,,,,,,,, +util_number_of_persons_participating_in_the_tour_return_stops_interaction,Number of persons participating in the tour.Return stops interaction,is_joint * number_of_participants,,,,,,,,,,,,,,,, +util_dummy_for_only_adults_participate_in_the_tour,Dummy for only adults participate in the tour,composition=='adults',,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour,coef_dummy_for_only_adults_participate_in_the_tour +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,,,,,,,,,,,,,,, +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,,,,,,,,,,,,,,, +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_5_miles,dummy for distance less than 5 Miles,(distance_in_miles < 5),,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles,coef_dummy_for_distance_less_than_5_miles +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,~is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,~is_joint,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,~is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_alternative_specific_constant_for_outbound_stops_on_joint_tours,Alternative specific constant for outbound stops on joint tours,is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +util_alternative_specific_constant_for_return_stops_on_joint_tours,Alternative specific constant for return stops on joint tours,is_joint,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours,Alternative specific constant for the total number of stops on joint tours,is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +util_Phase1_Calibration,Phase1_Calibration,~is_joint,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in +util_telecommute1,(num_work_tours == 0) & (telecommute_frequency=='1_day_week'),,coef_telecommute1_2,coef_telecommute1_3,coef_telecommute1_4,coef_telecommute1_5,coef_telecommute1_6,coef_telecommute1_7,coef_telecommute1_8,coef_telecommute1_9,coef_telecommute1_10,coef_telecommute1_11,coef_telecommute1_12,coef_telecommute1_13,coef_telecommute1_14,coef_telecommute1_15,coef_telecommute1_16 +util_telecommute23,(num_work_tours == 0) & (telecommute_frequency=='2_3_days_week'),,coef_telecommute23_2,coef_telecommute23_3,coef_telecommute23_4,coef_telecommute23_5,coef_telecommute23_6,coef_telecommute23_7,coef_telecommute23_8,coef_telecommute23_9,coef_telecommute23_10,coef_telecommute23_11,coef_telecommute23_12,coef_telecommute23_13,coef_telecommute23_14,coef_telecommute23_15,coef_telecommute23_16 +util_telecommute4p,(num_work_tours == 0) & (telecommute_frequency=='4_days_week'),,coef_telecommute4p_2,coef_telecommute4p_3,coef_telecommute4p_4,coef_telecommute4p_5,coef_telecommute4p_6,coef_telecommute4p_7,coef_telecommute4p_8,coef_telecommute4p_9,coef_telecommute4p_10,coef_telecommute4p_11,coef_telecommute4p_12,coef_telecommute4p_13,coef_telecommute4p_14,coef_telecommute4p_15,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_social.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_social.csv new file mode 100644 index 000000000..e83689f52 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_social.csv @@ -0,0 +1,56 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh_,Middle to Low Income HH ,(income_in_thousands>19999) & (income_in_thousands<50000),,,,,,,,,,,,,,,, +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,,,,,,,,,,,,,,, +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,,,,,,,,,,,,,,, +util_number_of_hh_persons,Number of HH Persons,hhsize,,,,,,,,,,,,,,,, +util_number_of_full_time_workes_in_hh,Number of full time workes in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,,,,,,,,,,,,,,, +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,,,,,,,,,,,,,,, +util_num_kids_between_4_and_15_including_years_old,Num kids between 4 and 15 (including) years old,num_age_5_15,,,,,,,,,,,,,,,, +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,,,,,,,,,,,,,,, +util_number_of_vehicles,Number of Vehicles,auto_ownership,,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles +util_dummy_for_female,Dummy for female,~is_joint & female,,,,,,,,,,,,,,,, +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,~is_joint * num_work_tours,,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,~is_joint * num_univ_tours,,,,,,,,,,,,,,,, +util_number_of_shool_tours_tours_undertaken_by_the_person,Number of shool tours tours undertaken by the person,~is_joint * num_school_tours,,,,,,,,,,,,,,,, +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,~is_joint * num_escort_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,~is_joint * num_shop_tours,,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person,coef_number_of_shop_tours_undertaken_by_the_person +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,~is_joint * num_maint_tours,,,,,,,,,,,,,,,, +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,~is_joint * num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,~is_joint * num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,,,,,,,,,,,,,,, +util_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,Number of persons participating in the tour.Outgoing stops interaction,is_joint * number_of_participants,,,,,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction,coef_number_of_persons_participating_in_the_tour_outgoing_stops_interaction +util_number_of_persons_participating_in_the_tour_return_stops_interaction,Number of persons participating in the tour.Return stops interaction,is_joint * number_of_participants,,,,,,,,,,,,,,,, +util_at_least_one_kid_and_one_adult_participate_in_the_tour,At least one kid and one adult participate in the tour,composition=='mixed',,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour,coef_at_least_one_kid_and_one_adult_participate_in_the_tour +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_ +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_ +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_20_miles_,dummy for distance less than 20 Miles ,(distance_in_miles < 20),,,,,,,,,,,,,,,, +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,~is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,~is_joint,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,~is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_alternative_specific_constant_for_outbound_stops_on_joint_tours,Alternative specific constant for outbound stops on joint tours,is_joint,,,,,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_1out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_2out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in,coef_alternative_specific_constant_for_outbound_stops_on_joint_tours_3out_0in +util_alternative_specific_constant_for_return_stops_on_joint_tours,Alternative specific constant for return stops on joint tours,is_joint,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in,,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_1in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_return_stops_on_joint_tours_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours,Alternative specific constant for the total number of stops on joint tours,is_joint,,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_on_joint_tours_2out_3in +util_dummy_for_an_outbound_visiting_tour,Dummy for an outbound visiting tour,primary_purpose == 'social',,,,,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour,coef_dummy_for_an_outbound_visiting_tour +util_dummy_for_a_return_visiting_tour,Dummy for a return visiting tour,primary_purpose == 'social',,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour,coef_dummy_for_a_return_visiting_tour +util_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,Dummy for a visiting tour with both outbound and return leg,primary_purpose == 'social',,,,,,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg,coef_dummy_for_a_visiting_tour_with_both_outbound_and_return_leg +util_Phase1_Calibration,Phase1_Calibration,~is_joint,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in +util_telecommute1,(num_work_tours == 0) & (telecommute_frequency=='1_day_week'),,coef_telecommute1_2,coef_telecommute1_3,coef_telecommute1_4,coef_telecommute1_5,coef_telecommute1_6,coef_telecommute1_7,coef_telecommute1_8,coef_telecommute1_9,coef_telecommute1_10,coef_telecommute1_11,coef_telecommute1_12,coef_telecommute1_13,coef_telecommute1_14,coef_telecommute1_15,coef_telecommute1_16 +util_telecommute23,(num_work_tours == 0) & (telecommute_frequency=='2_3_days_week'),,coef_telecommute23_2,coef_telecommute23_3,coef_telecommute23_4,coef_telecommute23_5,coef_telecommute23_6,coef_telecommute23_7,coef_telecommute23_8,coef_telecommute23_9,coef_telecommute23_10,coef_telecommute23_11,coef_telecommute23_12,coef_telecommute23_13,coef_telecommute23_14,coef_telecommute23_15,coef_telecommute23_16 +util_telecommute4p,(num_work_tours == 0) & (telecommute_frequency=='4_days_week'),,coef_telecommute4p_2,coef_telecommute4p_3,coef_telecommute4p_4,coef_telecommute4p_5,coef_telecommute4p_6,coef_telecommute4p_7,coef_telecommute4p_8,coef_telecommute4p_9,coef_telecommute4p_10,coef_telecommute4p_11,coef_telecommute4p_12,coef_telecommute4p_13,coef_telecommute4p_14,coef_telecommute4p_15,coef_telecommute4p_16 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_univ.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_univ.csv new file mode 100644 index 000000000..f0854f242 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_univ.csv @@ -0,0 +1,45 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh,Middle to Low Income HH,(income_in_thousands>19999) & (income_in_thousands<50000),,,,,,,,,,,,,,,, +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,,,,,,,,,,,,,,, +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,,,,,,,,,,,,,,, +util_number_of_hh_persons,Number of HH Persons,hhsize,,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons +util_number_of_full_time_workers_in_hh,Number of full time workers in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,,,,,,,,,,,,,,, +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,,,,,,,,,,,,,,, +util_num_kids_between_5_and_15_including_years_old,Num kids between 5 and 15 (including) years old,num_age_5_15,,,,,,,,,,,,,,,, +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,,,,,,,,,,,,,,, +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,,,,,,,,,,,,,,, +util_number_of_vehicles,Number of Vehicles,auto_ownership,,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles,coef_number_of_vehicles +util_dummy_for_female,Dummy for female,female,,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,,,,,,,,,,,,,,, +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,num_work_tours,,,,,,,,,,,,,,,, +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,num_univ_tours,,,,,,,,,,,,,,,, +util_number_of_school_tours_tours_undertaken_by_the_person,Number of school tours tours undertaken by the person,num_school_tours,,,,,,,,,,,,,,,, +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,num_escort_tours,,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,num_shop_tours,,,,,,,,,,,,,,,, +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,num_maint_tours,,,,,,,,,,,,,,,, +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,,,,,,,,,,,,,,, +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>5) & (start<8),,,,,,,,,,,,,,,, +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 16),,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_,coef_arrival_later_than_17_00_ +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 18),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 10),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 8),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_ +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 2),,,,,,,,,,,,,,,, +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction,coef_hh_accesibility_for_inbound_tours_interaction +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_20_miles,dummy for distance less than 20 Miles,(distance_in_miles < 20),,,,,,,,,,,,,,,, +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,,,,,,,,,,,,,,, +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,1,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,1,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,1,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_1out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_Phase1_Calibration,Phase1_Calibration,1,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in +#util_Major University Calibration,Major University Calibration,is_major_univ_student,,-0.199248949,0.652388897,0.625258509,-1.850257358,-1.049976118,-0.922350027,0.617946267,-1.566065939,-0.401448626,-0.508496898,-0.026438159,-3.878745091,-5,0.876560807,-1.094489763 diff --git a/activitysim/examples/prototype_mwcog/configs/stop_frequency_work.csv b/activitysim/examples/prototype_mwcog/configs/stop_frequency_work.csv new file mode 100644 index 000000000..abd7a4129 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/stop_frequency_work.csv @@ -0,0 +1,45 @@ +Label,Description,Expression,0out_0in,0out_1in,0out_2in,0out_3in,1out_0in,1out_1in,1out_2in,1out_3in,2out_0in,2out_1in,2out_2in,2out_3in,3out_0in,3out_1in,3out_2in,3out_3in +util_middle_to_low_income_hh,Middle to Low Income HH,(income_in_thousands>19999) & (income_in_thousands<50000),,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh,coef_middle_to_low_income_hh +util_mid_to_high_income_hh,Mid to High Income HH,(income_in_thousands>=50000) & (income_in_thousands<100000),,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh,coef_mid_to_high_income_hh +util_high_income_hh,High Income HH,(income_in_thousands>=100000),,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh,coef_high_income_hh +util_number_of_hh_persons,Number of HH Persons,hhsize,,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons,coef_number_of_hh_persons +util_number_of_full_time_workers_in_hh,Number of full time workers in HH,num_full,,,,,,,,,,,,,,,, +util_number_of_students_in_hh,Number of Students in HH,num_student,,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh,coef_number_of_students_in_hh +util_num_kids_between_0_and_4_including_years_old,Num Kids between 0 and 4 (including) years old,num_age_0_4,,,,,,,,,,,,,,,, +util_presence_of_kids_between_0_and_4_including_years_old,Presence of Kids between 0 and 4 (including) years old,(num_age_0_4 > 0),,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old,coef_presence_of_kids_between_0_and_4_including_years_old +util_num_kids_between_5_and_15_including_years_old,Num kids between 5 and 15 (including) years old,num_age_5_15,,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old,coef_num_kids_between_5_and_15_including_years_old +util_presence_of_kids_between_5_and_15_including_years_old,Presence of kids between 5 and 15 (including) years old,(num_age_5_15 > 0),,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old,coef_presence_of_kids_between_5_and_15_including_years_old +util_number_of_adults_16_years_old_,Number of Adults (>= 16 years old),num_adult,,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_,coef_number_of_adults_16_years_old_ +util_dummy_for_single_parent_household,Dummy for single parent household,(num_adult == 1) & (num_age_0_4 + num_age_5_15 > 0),,,,,,,,,,,,,,,, +util_number_of_cars_number_of_workers,Number of Cars > Number of Workers,more_cars_than_workers,,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers,coef_number_of_cars_number_of_workers +util_number_of_vehicles,Number of Vehicles,auto_ownership,,,,,,,,,,,,,,,, +util_dummy_for_female,Dummy for female,female,,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female,coef_dummy_for_female +util_dummy_for_all_stops_made_by_transit,Dummy for all stops made by transit,tour_mode_is_transit,,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit,coef_dummy_for_all_stops_made_by_transit +util_dummy_for_walking_to_all_stops,Dummy for walking to all stops,tour_mode_is_non_motorized,,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops,coef_dummy_for_walking_to_all_stops +util_number_of_work_tours_undertaken_by_the_person,Number of work tours undertaken by the person,num_work_tours,,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person,coef_number_of_work_tours_undertaken_by_the_person +util_number_of_university_tours_tours_undertaken_by_the_person,Number of university tours tours undertaken by the person,num_univ_tours,,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person,coef_number_of_university_tours_tours_undertaken_by_the_person +util_number_of_school_tours_tours_undertaken_by_the_person,Number of school tours tours undertaken by the person,num_school_tours,,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person,coef_number_of_school_tours_tours_undertaken_by_the_person +util_number_of_escort_tours_tours_undertaken_by_the_person,Number of escort tours tours undertaken by the person,num_escort_tours,,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person,coef_number_of_escort_tours_tours_undertaken_by_the_person +util_number_of_shop_tours_undertaken_by_the_person,Number of shop tours undertaken by the person,num_shop_tours,,,,,,,,,,,,,,,, +util_number_of_maintenace_tours_tours_undertaken_by_the_person,Number of maintenace tours tours undertaken by the person,num_maint_tours,,,,,,,,,,,,,,,, +util_number_of_eating_tours_tours_undertaken_by_the_person,Number of eating tours tours undertaken by the person,num_eatout_tours,,,,,,,,,,,,,,,, +util_number_of_visit_tours_tours_undertaken_by_the_person,Number of visit tours tours undertaken by the person,num_social_tours,,,,,,,,,,,,,,,, +util_number_of_shop_tours_undertaken_by_the_houshold,Number of shop tours undertaken by the houshold,num_hh_shop_tours,,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold,coef_number_of_shop_tours_undertaken_by_the_houshold +util_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,AM Peak departure between 6AM and 7 AM (including) Interacted with outbound tours,(start>6) & (start<11),,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours,coef_am_peak_departure_between_6am_and_7_am_including_interacted_with_outbound_tours +util_arrival_later_than_17_00_,Arrival later than 17:00.,(end > 28),,,,,,,,,,,,,,,, +util_evening_arrival_19_00_interacted_with_return_tours,Evening Arrival (>=19:00) Interacted with return tours,(end > 32),,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours,coef_evening_arrival_19_00_interacted_with_return_tours +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,Dummy for the duration of the tour being equal or greater than or equal to 11 hours,(duration > 21),,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours,coef_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_11_hours +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_9_hours_,Dummy for the duration of the tour being equal or greater than or equal to 9 hours ,(duration > 17),,,,,,,,,,,,,,,, +util_dummy_for_the_duration_of_the_tour_being_equal_or_greater_than_or_equal_to_3_hours_,Dummy for the duration of the tour being equal or greater than or equal to 3 hours ,(duration > 5),,,,,,,,,,,,,,,, +util_hh_accesibility_for_outbound_tours_interaction,HH accesibility for outbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_hh_accesibility_for_inbound_tours_interaction,HH accesibility for inbound tours. Interaction,hhacc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_outbound_tours_interaction,Primary Destination Accessibility for outbound tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_primary_destination_accessibility_for_return_tours_interaction,Primary Destination Accessibility for return tours. Interaction,pracc,,,,,,,,,,,,,,,, +util_dummy_for_distance_less_than_20_miles,dummy for distance less than 20 Miles,(distance_in_miles < 20),,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles,coef_dummy_for_distance_less_than_20_miles +util_dummy_for_distance_in_miles,dummy for distance in miles,distance_in_miles,,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles,coef_dummy_for_distance_in_miles +util_no_stops_if_tour_mode_is_drivetransit,No stops if tour mode is driveTransit,tour_mode_is_drive_transit,,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit,coef_no_stops_if_tour_mode_is_drivetransit +util_alternative_specific_constant_for_outbound_stops,Alternative specific constant for outbound stops,1,,,,,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_1out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_2out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in,coef_alternative_specific_constant_for_outbound_stops_3out_0in +util_alternative_specific_constant_for_return_stops,Alternative specific constant for return stops,1,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in,,coef_alternative_specific_constant_for_return_stops_0out_1in,coef_alternative_specific_constant_for_return_stops_0out_2in,coef_alternative_specific_constant_for_return_stops_0out_3in +util_alternative_specific_constant_for_the_total_number_of_stops,Alternative specific constant for the total number of stops,1,,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_0out_2in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in,coef_alternative_specific_constant_for_the_total_number_of_stops_2out_3in +util_number_of_subtours_in_the_tour,Number of subtours in the tour,num_atwork_subtours,,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour,coef_number_of_subtours_in_the_tour +util_Phase1_Calibration,Phase1_Calibration,1,,coef_calibration_for_0out_1in,coef_calibration_for_0out_2in,coef_calibration_for_0out_3in,coef_calibration_for_1out_0in,coef_calibration_for_1out_1in,coef_calibration_for_1out_2in,coef_calibration_for_1out_3in,coef_calibration_for_2out_0in,coef_calibration_for_2out_1in,coef_calibration_for_2out_2in,coef_calibration_for_2out_3in,coef_calibration_for_3out_0in,coef_calibration_for_3out_1in,coef_calibration_for_3out_2in,coef_calibration_for_3out_3in diff --git a/activitysim/examples/prototype_mwcog/configs/telecommute_frequency.csv b/activitysim/examples/prototype_mwcog/configs/telecommute_frequency.csv new file mode 100644 index 000000000..d001f013f --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/telecommute_frequency.csv @@ -0,0 +1,21 @@ +Label,Description,Expression,No_Telecommute,1_day_week,2_3_days_week,4_days_week +#util_Services,Services,@df.occup==52,0,coef_Services_1day,coef_Services_23day,coef_Services_4day +#util_SalesOffice,SalesOffice,@df.occup==53,0,coef_SalesOffice_1day,coef_SalesOffice_23day,coef_SalesOffice_4day +#util_ResourceConstruct,ResourceConstruct,@df.occup==54,0,coef_ResourceConstruct_1day,coef_ResourceConstruct_23day,coef_ResourceConstruct_4day +#util_TransportMat,TransportMat,@df.occup==55,0,coef_TransportMat_1day,coef_TransportMat_23day,coef_TransportMat_4day +util_HasChildren0to5,Has children 0 to 5 years old,@df.has_young_children,0,coef_HasChildren0to5_1day,coef_HasChildren0to5_23day,coef_HasChildren0to5_4day +util_HasChildren6to12,Has children 6 to 12 years old,@df.has_children_6_to_12,0,coef_HasChildren6to12_1day,coef_HasChildren6to12_23day,coef_HasChildren6to12_4day +util_OneAdultInHH,One adult in hh,@df.num_adults==1,0,coef_OneAdultInHH_1day,coef_OneAdultInHH_23day,coef_OneAdultInHH_4day +util_2plusAdultsInHH,2 or more adults in hh,@df.num_adults==2,0,coef_2plusAdultsInHH_1day,coef_2plusAdultsInHH_23day,coef_2plusAdultsInHH_4day +util_Female,female,@df.SEX==2,0,coef_Female_1day,coef_Female_23day,coef_Female_4day +util_PartTimeWorker,Part-time worker,@df.pemploy==PEMPLOY_PART,0,coef_PartTimeWorker_1day,coef_PartTimeWorker_23day,coef_PartTimeWorker_4day +util_CollegeStudent,College student,@df.ptype==PTYPE_UNIVERSITY,0,coef_CollegeStudent_1day,coef_CollegeStudent_23day,coef_CollegeStudent_4day +util_PaysToPark,Pays to park,@~df.free_parking_at_work,0,coef_PaysToPark_1day,coef_PaysToPark_23day,coef_PaysToPark_4day +util_Income60to100k,Income 60-100k,"@df.income.between(60000, 100000)",0,coef_Income60to100k_1day,coef_Income60to100k_23day,coef_Income60to100k_4day +util_Income100to150k,Income 100-150k,"@df.income.between(100000, 150000)",0,coef_Income100to150k_1day,coef_Income100to150k_23day,coef_Income100to150k_4day +util_Income150kplus,Income 150k+,@df.income > 150000,0,coef_Income150kplus_1day,coef_Income150kplus_23day,coef_Income150kplus_4day +util_0Autos,0 Autos,@df.auto_ownership==0,0,coef_0Autos_1day,coef_0Autos_23day,coef_0Autos_4day +util_1Auto,1 Auto,@df.auto_ownership==1,0,coef_1Auto_1day,coef_1Auto_23day,coef_1Auto_4day +util_3plusAutos,3+ Autos,@df.auto_ownership>=3,0,coef_3plusAutos_1day,coef_3plusAutos_23day,coef_3plusAutos_4day +util_DistanceToWork,Distance to work,@df.distance_to_work,0,coef_DistanceToWork_1day,coef_DistanceToWork_23day,coef_DistanceToWork_4day +util_temp_calib,temporary calibration,1,0,coef_temp_calib_1day,coef_temp_calib_23day,coef_temp_calib_4day diff --git a/activitysim/examples/prototype_mwcog/configs/telecommute_frequency.yaml b/activitysim/examples/prototype_mwcog/configs/telecommute_frequency.yaml new file mode 100644 index 000000000..162066ef6 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/telecommute_frequency.yaml @@ -0,0 +1,9 @@ + +# borrowed from free parking model + +SPEC: telecommute_frequency.csv +COEFFICIENTS: telecommute_frequency_coeffs.csv + +#LOGIT_TYPE: NL +LOGIT_TYPE: MNL + diff --git a/activitysim/examples/prototype_mwcog/configs/telecommute_frequency_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/telecommute_frequency_coeffs.csv new file mode 100644 index 000000000..1a7acb4fc --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/telecommute_frequency_coeffs.csv @@ -0,0 +1,61 @@ +coefficient_name,value,constrain +coef_Services_1day,-1.624,F +coef_SalesOffice_1day,-0.62,F +coef_ResourceConstruct_1day,-1.57,F +coef_TransportMat_1day,-14.747,F +coef_HasChildren0to5_1day,0,F +coef_HasChildren6to12_1day,0,F +coef_OneAdultInHH_1day,0.177,F +coef_2plusAdultsInHH_1day,0,F +coef_Female_1day,0,F +coef_PartTimeWorker_1day,0,F +coef_CollegeStudent_1day,0,F +coef_PaysToPark_1day,0.457,F +coef_Income60to100k_1day,0.56,F +coef_Income100to150k_1day,0.644,F +coef_Income150kplus_1day,0.92,F +coef_0Autos_1day,0,F +coef_1Auto_1day,0,F +coef_3plusAutos_1day,0,F +coef_DistanceToWork_1day,0.016,F +coef_Services_23day,-0.651,F +coef_SalesOffice_23day,-0.738,F +coef_ResourceConstruct_23day,0,F +coef_TransportMat_23day,0,F +coef_HasChildren0to5_23day,0,F +coef_HasChildren6to12_23day,0.517,F +coef_OneAdultInHH_23day,0,F +coef_2plusAdultsInHH_23day,0,F +coef_Female_23day,0,F +coef_PartTimeWorker_23day,0.425,F +coef_CollegeStudent_23day,0.6,F +coef_PaysToPark_23day,0,F +coef_Income60to100k_23day,0.389,F +coef_Income100to150k_23day,0.193,F +coef_Income150kplus_23day,0.765,F +coef_0Autos_23day,0.407,F +coef_1Auto_23day,0,F +coef_3plusAutos_23day,-0.73,F +coef_DistanceToWork_23day,0,F +coef_Services_4day,0,F +coef_SalesOffice_4day,-0.894,F +coef_ResourceConstruct_4day,0,F +coef_TransportMat_4day,0,F +coef_HasChildren0to5_4day,-0.864,F +coef_HasChildren6to12_4day,-0.81,F +coef_OneAdultInHH_4day,-0.043,F +coef_2plusAdultsInHH_4day,0,F +coef_Female_4day,0,F +coef_PartTimeWorker_4day,1.112,F +coef_CollegeStudent_4day,0,F +coef_PaysToPark_4day,0,F +coef_Income60to100k_4day,0,F +coef_Income100to150k_4day,0,F +coef_Income150kplus_4day,0,F +coef_0Autos_4day,0,F +coef_1Auto_4day,0,F +coef_3plusAutos_4day,0,F +coef_DistanceToWork_4day,0,F +coef_temp_calib_1day,-3.464358858,F +coef_temp_calib_23day,-3.046318883,F +coef_temp_calib_4day,-3.518320974,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_departure_and_duration_alternatives.csv b/activitysim/examples/prototype_mwcog/configs/tour_departure_and_duration_alternatives.csv new file mode 100644 index 000000000..30ff417ca --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_departure_and_duration_alternatives.csv @@ -0,0 +1,1177 @@ +start,end +1,1 +1,2 +1,3 +1,4 +1,5 +1,6 +1,7 +1,8 +1,9 +1,10 +1,11 +1,12 +1,13 +1,14 +1,15 +1,16 +1,17 +1,18 +1,19 +1,20 +1,21 +1,22 +1,23 +1,24 +1,25 +1,26 +1,27 +1,28 +1,29 +1,30 +1,31 +1,32 +1,33 +1,34 +1,35 +1,36 +1,37 +1,38 +1,39 +1,40 +1,41 +1,42 +1,43 +1,44 +1,45 +1,46 +1,47 +1,48 +2,2 +2,3 +2,4 +2,5 +2,6 +2,7 +2,8 +2,9 +2,10 +2,11 +2,12 +2,13 +2,14 +2,15 +2,16 +2,17 +2,18 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+univ,NT,33,33 +#,,, +shopping,AM,9,10 +shopping,MD,13,24 +shopping,PM,25,27 +shopping,NT,33,33 +#,,, +escort,AM,9,10 +escort,MD,13,24 +escort,PM,25,27 +escort,NT,33,33 +#,,, +othmaint,AM,9,10 +othmaint,MD,13,24 +othmaint,PM,25,27 +othmaint,NT,33,33 +#,,, +othdiscr,AM,9,10 +othdiscr,MD,13,24 +othdiscr,PM,25,27 +othdiscr,NT,33,33 +#,,, +social,AM,9,10 +social,MD,13,24 +social,PM,25,27 +social,NT,33,33 +#,,, +eatout,AM,9,10 +eatout,MD,13,24 +eatout,PM,25,27 +eatout,NT,33,33 +#,,, +atwork,AM,9,10 +atwork,MD,13,24 +atwork,PM,25,27 +atwork,NT,33,33 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_mode_choice.csv b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice.csv new file mode 100644 index 000000000..678329e71 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice.csv @@ -0,0 +1,335 @@ +Label,Description,Expression,DRIVEALONE,SHARED2,SHARED3,WALK,BIKE,WALK_AB,WALK_BM,WALK_MR,WALK_CR,PNR_AB,PNR_BM,PNR_MR,PNR_CR,KNR_AB,KNR_BM,KNR_MR,KNR_CR,SCHOOLBUS,TAXI,TNC_SINGLE,TNC_SHARED +#Drive_alone_no_toll,#Drive alone no toll,,,,,,,,,,,,,,,,,,,,,, +Drive_alone_not_available_for_escort_tours,Drive alone not available for escort tours,is_escort,-999,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable,DRIVEALONE - Unavailable,sov_available == False,-999,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable_for_persons_less_than_16,DRIVEALONE - Unavailable for persons less than 16,age < 16,-999,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable_forJoint_tours,DRIVEALONE - Unavailable for joint tours,is_joint == True,-999,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable_if_didn't_drive_to_work,DRIVEALONE - Unavailable if didn't drive to work,is_atwork_subtour & ~work_tour_is_SOV,-999,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_In_vehicle_time,DRIVEALONE - In-vehicle time,@odt_skims['SOV_TIME'] + dot_skims['SOV_TIME'],coef_ivt,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Terminal_time,DRIVEALONE - Terminal time,@2 * df.terminal_time,coef_walk,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Operating_cost_,DRIVEALONE - Operating cost ,@costPerMile * (odt_skims['SOV_DIST'] + dot_skims['SOV_DIST']),coef_cost,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Parking_cost_,DRIVEALONE - Parking cost ,@df.daily_parking_cost * 1.22,coef_cost,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Total_toll_,DRIVEALONE - Total toll ,@(odt_skims['SOV_TOLL'] + dot_skims['SOV_TOLL'])*1.22,coef_cost,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Person_is_between_16_and_19_years_old,DRIVEALONE - Person is between 16 and 19 years old,@(df.age >= 16) & (df.age <= 19),coef_age1619_da,,,,,,,,,,,,,,,,,,,, +#Shared_ride_2,#Shared ride 2,,,,,,,,,,,,,,,,,,,,,, +util_SHARED2_Unavailable,SHARED2 - Unavailable,hov2_available == False,,-999,,,,,,,,,,,,,,,,,,, +util_SHARED2_Unavailable_based_on_party_size,SHARED2 - Unavailable based on party size,is_joint & (number_of_participants > 2),,-999,,,,,,,,,,,,,,,,,,, +util_SHARED2_In_vehicle_time,SHARED2 - In-vehicle time,@(odt_skims['HOV2_TIME'] + dot_skims['HOV2_TIME']),,coef_ivt,,,,,,,,,,,,,,,,,,, +util_SHARED2_Terminal_time,SHARED2 - Terminal time,@2 * df.terminal_time,,coef_walk,,,,,,,,,,,,,,,,,,, +util_SHARED2_Operating_cost,SHARED2 - Operating cost,@costPerMile * (odt_skims['HOV2_DIST'] + dot_skims['HOV2_DIST']),,coef_cost,,,,,,,,,,,,,,,,,,, +util_SHARED2_Parking_cost,SHARED2 - Parking cost,@df.daily_parking_cost / costShareSr2 * 1.22,,coef_cost,,,,,,,,,,,,,,,,,,, +util_SHARED2_Total_toll,SHARED2 - Total toll,@((odt_skims['HOV2_TOLL'] + dot_skims['HOV2_TOLL']) / costShareSr2) * 1.22,,coef_cost,,,,,,,,,,,,,,,,,,, +util_SHARED2_One_person_household,SHARED2 - One person household,@(df.hhsize == 1),,coef_hhsize1_sr,,,,,,,,,,,,,,,,,,, +util_SHARED2_Two_person_household,SHARED2 - Two person household,@(df.hhsize == 2),,coef_hhsize2_sr,,,,,,,,,,,,,,,,,,, +util_SHARED2_Person_is_16_years_old_or_older,SHARED2 - Person is 16 years old or older,@(df.age >= 16),,coef_age16p_sr,,,,,,,,,,,,,,,,,,, +#Shared_ride_3+,#Shared ride 3+,,,,,,,,,,,,,,,,,,,,,, +util_SHARED3_Unavailable,SHARED3 - Unavailable,hov3_available == False,,,-999,,,,,,,,,,,,,,,,,, +util_SHARED3_In_vehicle_time,SHARED3 - In-vehicle time,@(odt_skims['HOV3_TIME'] + dot_skims['HOV3_TIME']),,,coef_ivt,,,,,,,,,,,,,,,,,, +util_SHARED3_Terminal_time,SHARED3 - Terminal time,@2 * df.terminal_time,,,coef_walk,,,,,,,,,,,,,,,,,, +util_SHARED3_Operating_cost,SHARED3 - Operating cost,@costPerMile * (odt_skims['HOV3_DIST'] + dot_skims['HOV3_DIST']),,,coef_cost,,,,,,,,,,,,,,,,,, +util_SHARED3_Parking_cost,SHARED3 - Parking cost,@df.daily_parking_cost / costShareSr3 * 1.22,,,coef_cost,,,,,,,,,,,,,,,,,, +util_SHARED3_Total_toll,SHARED3 - Total toll,@((odt_skims['HOV3_TOLL'] + dot_skims['HOV3_TOLL']) / costShareSr3) * 1.22,,,coef_cost,,,,,,,,,,,,,,,,,, +util_SHARED3_One_person_household,SHARED3 - One person household,@(df.hhsize == 1),,,coef_hhsize1_sr,,,,,,,,,,,,,,,,,, +util_SHARED3_Two_person_household,SHARED3 - Two person household,@(df.hhsize == 2),,,coef_hhsize2_sr,,,,,,,,,,,,,,,,,, +util_SHARED3_Person_is_16_years_old_or_older,SHARED3 - Person is 16 years old or older,@(df.age >= 16),,,coef_age16p_sr,,,,,,,,,,,,,,,,,, +#util_WALK,#Walk,,,,,,,,,,,,,,,,,,,,,, +util_WALK_not_available_for_long_distances,Walk not available for long distances,@od_skims.max('DISTWALK') > 3,,,,-999,,,,,,,,,,,,,,,,, +util_WALK_Time,WALK - Time,@(od_skims['DISTWALK'] + od_skims.reverse('DISTWALK'))*60/walkSpeed,,,,coef_walk,,,,,,,,,,,,,,,,, +util_WALK_Destination_zone_densityIndex,WALK - Destination zone densityIndex,@df.density_index,,,,coef_density_walk,,,,,,,,,,,,,,,,, +util_WALK_Topology,WALK - Topology,@df.dest_topology,,,,coef_topology_walk,,,,,,,,,,,,,,,,, +#util_BIKE,#Bike,,,,,,,,,,,,,,,,,,,,,, +util_BIKE_not_available_for_long_distances,Bike not available for long distances,@od_skims.max('DISTBIKE') > 8,,,,,-999,,,,,,,,,,,,,,,, +util_BIKE_Unavailable_if_didn't_BIKE_to_work,BIKE - Unavailable if didn't bike to work,is_atwork_subtour & ~work_tour_is_bike,,,,,-999,,,,,,,,,,,,,,,, +util_BIKE_Time,BIKE - Time,@(od_skims['DISTBIKE'] + od_skims.reverse('DISTBIKE'))*60/bikeSpeed,,,,,coef_bike,,,,,,,,,,,,,,,, +util_BIKE_Destination_zone_densityIndex,BIKE - Destination zone densityIndex,@df.density_index,,,,,coef_density_bike,,,,,,,,,,,,,,,, +util_BIKE_Topology,BIKE - Topology,@df.dest_topology,,,,,coef_topology_bike,,,,,,,,,,,,,,,, +#util_WALK_to_AB,#Walk to AB,,,,,,,,,,,,,,,,,,,,,, +util_WALK_AB_Unavailable,WALK_AB - Unavailable,walk_ab_available == False,,,,,,-999,,,,,,,,,,,,,,, +util_WALK_AB_In_vehicle_time,WALK_AB - In-vehicle time,@(odt_skims['WK_AB_WK_TOTIVT'] + dot_skims['WK_AB_WK_TOTIVT']),,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_In_vehicle_time_on_XB,WALK_AB - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['WK_AB_WK_IVTXB'] + dot_skims['WK_AB_WK_IVTXB']),,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_iwait_time,WALK_AB - wait time,@(odt_skims['WK_AB_WK_IWAIT'] + dot_skims['WK_AB_WK_IWAIT']),,,,,,coef_iwait,,,,,,,,,,,,,,, +util_WALK_AB_transfer_wait_time,WALK_AB - transfer wait time,@(odt_skims['WK_AB_WK_XWAIT'] + dot_skims['WK_AB_WK_XWAIT']),,,,,,coef_xwait,,,,,,,,,,,,,,, +util_WALK_AB_number_of_transfers,WALK_AB - number of transfers,@((odt_skims['WK_AB_WK_XFERS']).clip(0) + (dot_skims['WK_AB_WK_XFERS']).clip(0)),,,,,,coef_xfers_wlktrn,,,,,,,,,,,,,,, +util_WALK_AB_Walk_time,WALK_AB - Walk time,@(odt_skims['WK_AB_WK_WACC_EGR'] + dot_skims['WK_AB_WK_WACC_EGR']),,,,,,coef_wlk_acc,,,,,,,,,,,,,,, +util_WALK_AB_Walk_other_time,WALK_AB - Walk other time,@(odt_skims['WK_AB_WK_WAUX'] + dot_skims['WK_AB_WK_WAUX']),,,,,,coef_wlk_aux,,,,,,,,,,,,,,, +util_WALK_AB_Fare,WALK_AB - Fare,@(odt_skims['WK_AB_WK_FARE'] + dot_skims['WK_AB_WK_FARE']) * 1.22,,,,,,coef_cost,,,,,,,,,,,,,,, +util_WALK_AB_Destination_zone_densityIndex,WALK_AB - Destination zone densityIndex,@df.dest_density_index,,,,,,coef_density_wlktrn,,,,,,,,,,,,,,, +util_WALK_AB_Topology,WALK_AB - Topology,@df.dest_topology,,,,,,coef_topology_wlktrn,,,,,,,,,,,,,,, +util_WALK_AB_Person_is_less_than_10_years_old,WALK_AB - Person is less than 10 years old,@(df.age <= 10),,,,,,coef_age010_wlktrn,,,,,,,,,,,,,,, +#util_WALK_to_BM,#Walk to BM,,,,,,,,,,,,,,,,,,,,,, +util_WALK_BM_Unavailable,WALK_BM - Unavailable,walk_bm_available == False,,,,,,,-999,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time,WALK_BM - In-vehicle time,@(odt_skims['WK_BM_WK_TOTIVT'] + dot_skims['WK_BM_WK_TOTIVT']),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time_on_LB,WALK_BM - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['WK_BM_WK_IVTLB'] + dot_skims['WK_BM_WK_IVTLB']),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time_on_XB,WALK_BM - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['WK_BM_WK_IVTXB'] + dot_skims['WK_BM_WK_IVTXB']),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time_on_MR,WALK_BM - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['WK_BM_WK_IVTMR'] + dot_skims['WK_BM_WK_IVTMR']),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time_on_LR,WALK_BM - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['WK_BM_WK_IVTLR'] + dot_skims['WK_BM_WK_IVTLR']),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_iwait_time,WALK_BM - Short iwait time,@(odt_skims['WK_BM_WK_IWAIT'] + dot_skims['WK_BM_WK_IWAIT']),,,,,,,coef_iwait,,,,,,,,,,,,,, +util_WALK_BM_transfer_wait_time,WALK_BM - transfer wait time,@(odt_skims['WK_BM_WK_XWAIT'] + dot_skims['WK_BM_WK_XWAIT']),,,,,,,coef_xwait,,,,,,,,,,,,,, +util_WALK_BM_number_of_transfers,WALK_BM - number of transfers,@((odt_skims['WK_BM_WK_XFERS']).clip(0) + (dot_skims['WK_BM_WK_XFERS']).clip(0)),,,,,,,coef_xfers_wlktrn,,,,,,,,,,,,,, +util_WALK_BM_Walk_time,WALK_BM - Walk time,@(odt_skims['WK_BM_WK_WACC_EGR'] + dot_skims['WK_BM_WK_WACC_EGR']),,,,,,,coef_wlk_acc,,,,,,,,,,,,,, +util_WALK_BM_Walk_other_time,WALK_BM - Walk other time,@(odt_skims['WK_BM_WK_WAUX'] + dot_skims['WK_BM_WK_WAUX']),,,,,,,coef_wlk_aux,,,,,,,,,,,,,, +util_WALK_BM_Fare,WALK_BM - Fare,@(odt_skims['WK_BM_WK_FARE'] + dot_skims['WK_BM_WK_FARE']) * 1.22,,,,,,,coef_cost,,,,,,,,,,,,,, +util_WALK_BM_Destination_zone_densityIndex,WALK_BM - Destination zone densityIndex,@df.dest_density_index,,,,,,,coef_density_wlktrn,,,,,,,,,,,,,, +util_WALK_BM_Topology,WALK_BM - Topology,@df.dest_topology,,,,,,,coef_topology_wlktrn,,,,,,,,,,,,,, +util_WALK_BM_Person_is_less_than_10_years_old,WALK_BM - Person is less than 10 years old,@(df.age <= 10),,,,,,,coef_age010_wlktrn,,,,,,,,,,,,,, +#util_WALK_to_MR,#Walk to MR,,,,,,,,,,,,,,,,,,,,,, +util_WALK_MR_Unavailable,WALK_MR - Unavailable,walk_mr_available == False,,,,,,,,-999,,,,,,,,,,,,, +util_WALK_MR_In_vehicle_time,WALK_MR - In-vehicle time,@(odt_skims['WK_MR_WK_TOTIVT'] + dot_skims['WK_MR_WK_TOTIVT']),,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_In_vehicle_time_on_MR,WALK_MR - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['WK_MR_WK_IVTMR'] + dot_skims['WK_MR_WK_IVTMR']),,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_In_vehicle_time_on_LR,WALK_MR - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['WK_MR_WK_IVTLR'] + dot_skims['WK_MR_WK_IVTLR']),,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_iwait_time,WALK_MR - iwait time,@(odt_skims['WK_MR_WK_IWAIT'] + dot_skims['WK_MR_WK_IWAIT']),,,,,,,,coef_iwait,,,,,,,,,,,,, +util_WALK_MR_transfer_wait_time,WALK_MR - transfer wait time,@(odt_skims['WK_MR_WK_XWAIT'] + dot_skims['WK_MR_WK_XWAIT']),,,,,,,,coef_xwait,,,,,,,,,,,,, +util_WALK_MR_number_of_transfers,WALK_MR - number of transfers,@((odt_skims['WK_MR_WK_XFERS']).clip(0) + (dot_skims['WK_MR_WK_XFERS']).clip(0)),,,,,,,,coef_xfers_wlktrn,,,,,,,,,,,,, +util_WALK_MR_Walk_time,WALK_MR - Walk access time,@(odt_skims['WK_MR_WK_WACC_EGR'] + dot_skims['WK_MR_WK_WACC_EGR']),,,,,,,,coef_wlk_acc,,,,,,,,,,,,, +util_WALK_MR_Walk_other_time,WALK_MR - Walk other time,@(odt_skims['WK_MR_WK_WAUX'] + dot_skims['WK_MR_WK_WAUX']),,,,,,,,coef_wlk_aux,,,,,,,,,,,,, +util_WALK_MR_Fare,WALK_MR - Fare,@(odt_skims['WK_MR_WK_FARE'] + dot_skims['WK_MR_WK_FARE']) * 1.22,,,,,,,,coef_cost,,,,,,,,,,,,, +util_WALK_MR_Destination_zone_densityIndex,WALK_MR - Destination zone densityIndex,@df.dest_density_index,,,,,,,,coef_density_wlktrn,,,,,,,,,,,,, +util_WALK_MR_Topology,WALK_MR - Topology,@df.dest_topology,,,,,,,,coef_topology_wlktrn,,,,,,,,,,,,, +util_WALK_MR_Person_is_less_than_10_years_old,WALK_MR - Person is less than 10 years old,@(df.age <= 10),,,,,,,,coef_age010_wlktrn,,,,,,,,,,,,, +#util_WALK_to_CR,#Walk to CR,,,,,,,,,,,,,,,,,,,,,, +util_WALK_CR_Unavailable,WALK_CR - Unavailable,walk_cr_available == False,,,,,,,,,-999,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time,WALK_CR - In-vehicle time,@(odt_skims['WK_CR_WK_TOTIVT'] + dot_skims['WK_CR_WK_TOTIVT']),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_CR,WALK_CR - In-vehicle time on CR,@(ivt_CR_multiplier - 1) * (odt_skims['WK_CR_WK_IVTCR'] + dot_skims['WK_CR_WK_IVTCR']),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_LB,WALK_CR - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['WK_CR_WK_IVTLB'] + dot_skims['WK_CR_WK_IVTLB']),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_XB,WALK_CR - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['WK_CR_WK_IVTXB'] + dot_skims['WK_CR_WK_IVTXB']),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_MR,WALK_CR - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['WK_CR_WK_IVTMR'] + dot_skims['WK_CR_WK_IVTMR']),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_BR,WALK_CR - In-vehicle time on BR,@(ivt_BR_multiplier - 1) * (odt_skims['WK_CR_WK_IVTBR'] + dot_skims['WK_CR_WK_IVTBR']),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_LR,WALK_CR - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['WK_CR_WK_IVTLR'] + dot_skims['WK_CR_WK_IVTLR']),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_iwait_time,WALK_CR - iwait time,@(odt_skims['WK_CR_WK_IWAIT'] + dot_skims['WK_CR_WK_IWAIT']),,,,,,,,,coef_iwait,,,,,,,,,,,, +util_WALK_CR_transfer_wait_time,WALK_CR - transfer wait time,@(odt_skims['WK_CR_WK_XWAIT'] + dot_skims['WK_CR_WK_XWAIT']),,,,,,,,,coef_xwait,,,,,,,,,,,, +util_WALK_CR_number_of_transfers,WALK_CR - number of transfers,@((odt_skims['WK_CR_WK_XFERS']).clip(0) + (dot_skims['WK_CR_WK_XFERS']).clip(0)),,,,,,,,,coef_xfers_wlktrn,,,,,,,,,,,, +util_WALK_CR_Walk_time,WALK_CR - Walk time,@(odt_skims['WK_CR_WK_WACC_EGR'] + dot_skims['WK_CR_WK_WACC_EGR']),,,,,,,,,coef_wlk_acc,,,,,,,,,,,, +util_WALK_CR_Walk_other_time,WALK_CR - Walk other time,@(odt_skims['WK_CR_WK_WAUX'] + dot_skims['WK_CR_WK_WAUX']),,,,,,,,,coef_wlk_aux,,,,,,,,,,,, +util_WALK_CR_Fare,WALK_CR - Fare,@(odt_skims['WK_CR_WK_FARE'] + dot_skims['WK_CR_WK_FARE']) * 1.22,,,,,,,,,coef_cost,,,,,,,,,,,, +util_WALK_CR_Destination_zone_densityIndex,WALK_CR - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,coef_density_wlktrn,,,,,,,,,,,, +util_WALK_CR_Topology,WALK_CR - Topology,@df.dest_topology,,,,,,,,,coef_topology_wlktrn,,,,,,,,,,,, +util_WALK_CR_Person_is_less_than_10_years_old,WALK_CR - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,coef_age010_wlktrn,,,,,,,,,,,, +#util_PNR_to_AB,#PNR to AB,,,,,,,,,,,,,,,,,,,,,, +util_PNR_AB_Unavailable,PNR_AB - Unavailable,pnr_ab_available == False,,,,,,,,,,-999,,,,,,,,,,, +util_PNR_AB_Unavailable_for_persons_less_than_16,PNR_AB - Unavailable for persons less than 16,age < 16,,,,,,,,,,-999,,,,,,,,,,, +util_PNR_AB_In_vehicle_time,PNR_AB - In-vehicle time,@(odt_skims['DR_AB_WK_TOTIVT'] + dot_skims['WK_AB_DR_TOTIVT']),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_In_vehicle_time_on_LB,PNR_AB - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['DR_AB_WK_IVTLB'] + dot_skims['WK_AB_DR_IVTLB']),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_In_vehicle_time_on_XB,PNR_AB - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['DR_AB_WK_IVTXB'] + dot_skims['WK_AB_DR_IVTXB']),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_iwait_time,PNR_AB - iwait time,@(odt_skims['DR_AB_WK_IWAIT'] + dot_skims['WK_AB_DR_IWAIT']),,,,,,,,,,coef_iwait,,,,,,,,,,, +util_PNR_AB_transfer_wait_time,PNR_AB - transfer wait time,@(odt_skims['DR_AB_WK_XWAIT'] + dot_skims['WK_AB_DR_XWAIT']),,,,,,,,,,coef_xwait,,,,,,,,,,, +util_PNR_AB_number_of_transfers,PNR_AB - number of transfers,@((odt_skims['DR_AB_WK_XFERS']).clip(0) + (dot_skims['WK_AB_DR_XFERS']).clip(0)),,,,,,,,,,coef_xfers_pnr,,,,,,,,,,, +util_PNR_AB_PNR_time,PNR_AB - PNR time,@(odt_skims['DR_AB_WK_DTIME'] + dot_skims['WK_AB_DR_DTIME']),,,,,,,,,,coef_drvacc_pnr,,,,,,,,,,, +util_PNR_AB_Walk_time,PNR_AB - Walk time,@(odt_skims['DR_AB_WK_WACC_EGR'] + dot_skims['WK_AB_DR_WACC_EGR']),,,,,,,,,,coef_wlk_acc,,,,,,,,,,, +util_PNR_AB_Walk_other_time,PNR_AB - Walk other time,@(odt_skims['DR_AB_WK_WAUX'] + dot_skims['WK_AB_DR_WAUX']),,,,,,,,,,coef_wlk_aux,,,,,,,,,,, +util_PNR_AB_Fare_and_operating_cost,PNR_AB - Fare and operating cost,@((odt_skims['DR_AB_WK_FARE'] + dot_skims['WK_AB_DR_FARE']) * 1.22 + ((odt_skims['DR_AB_WK_DDIST']+dot_skims['WK_AB_DR_DDIST']) * costPerMile)),,,,,,,,,,coef_cost,,,,,,,,,,, +util_PNR_AB_Ratio_of_PNR_access_distance_to_OD_distance,PNR_AB - Ratio of PNR access distance to OD distance,@((odt_skims['DR_AB_WK_DDIST']+ dot_skims['WK_AB_DR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,coef_drvratio_pnr,,,,,,,,,,, +util_PNR_AB_Destination_zone_densityIndex,PNR_AB - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,coef_density_pnr,,,,,,,,,,, +util_PNR_AB_Topology,PNR_AB - Topology,@df.dest_topology,,,,,,,,,,coef_topology_pnr,,,,,,,,,,, +#util_PNR_to_BM,#PNR to BM,,,,,,,,,,,,,,,,,,,,,, +util_PNR_BM_Unavailable,PNR_BM - Unavailable,pnr_bm_available == False,,,,,,,,,,,-999,,,,,,,,,, +util_PNR_BM_Unavailable_for_persons_less_than_16,PNR_BM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,-999,,,,,,,,,, +util_PNR_BM_In_vehicle_time,PNR_BM - In-vehicle time,@(odt_skims['DR_BM_WK_TOTIVT'] + dot_skims['WK_BM_DR_TOTIVT']),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_LB,PNR_BM - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['DR_BM_WK_IVTLB'] + dot_skims['WK_BM_DR_IVTLB']),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_XB,PNR_BM - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['DR_BM_WK_IVTXB'] + dot_skims['WK_BM_DR_IVTXB']),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_MR,PNR_BM - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['DR_BM_WK_IVTMR'] + dot_skims['WK_BM_DR_IVTMR']),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_LR,PNR_BM - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['DR_BM_WK_IVTLR'] + dot_skims['WK_BM_DR_IVTLR']),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_iwait_time,PNR_BM - iwait time,@(odt_skims['DR_BM_WK_IWAIT'] + dot_skims['WK_BM_DR_IWAIT']),,,,,,,,,,,coef_iwait,,,,,,,,,, +util_PNR_BM_transfer_wait_time,PNR_BM - transfer wait time,@(odt_skims['DR_BM_WK_XWAIT'] + dot_skims['WK_BM_DR_XWAIT']),,,,,,,,,,,coef_xwait,,,,,,,,,, +util_PNR_BM_number_of_transfers,PNR_BM - number of transfers,@((odt_skims['DR_BM_WK_XFERS']).clip(0) + (dot_skims['WK_BM_DR_XFERS']).clip(0)),,,,,,,,,,,coef_xfers_pnr,,,,,,,,,, +util_PNR_BM_PNR_time,PNR_BM - PNR time,@(odt_skims['DR_BM_WK_DTIME'] + dot_skims['WK_BM_DR_DTIME']),,,,,,,,,,,coef_drvacc_pnr,,,,,,,,,, +util_PNR_BM_Walk_time,PNR_BM - Walk time,@(odt_skims['DR_BM_WK_WACC_EGR'] + dot_skims['WK_BM_DR_WACC_EGR']),,,,,,,,,,,coef_wlk_acc,,,,,,,,,, +util_PNR_BM_Walk_other_time,PNR_BM - Walk other time,@(odt_skims['DR_BM_WK_WAUX'] + dot_skims['WK_BM_DR_WAUX']),,,,,,,,,,,coef_wlk_aux,,,,,,,,,, +util_PNR_BM_Fare_and_operating_cost,PNR_BM - Fare and operating cost,@((odt_skims['DR_BM_WK_FARE'] + dot_skims['WK_BM_DR_FARE']) * 1.22 + ((odt_skims['DR_BM_WK_DDIST']+dot_skims['WK_BM_DR_DDIST']) * costPerMile)),,,,,,,,,,,coef_cost,,,,,,,,,, +util_PNR_BM_Ratio_of_PNR_access_distance_to_OD_distance,PNR_BM - Ratio of PNR access distance to OD distance,@((odt_skims['DR_BM_WK_DDIST']+ dot_skims['WK_BM_DR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,,coef_drvratio_pnr,,,,,,,,,, +util_PNR_BM_Destination_zone_densityIndex,PNR_BM - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,,coef_density_pnr,,,,,,,,,, +util_PNR_BM_Topology,PNR_BM - Topology,@df.dest_topology,,,,,,,,,,,coef_topology_pnr,,,,,,,,,, +#util_PNR_to_MR,#PNR to MR,,,,,,,,,,,,,,,,,,,,,, +util_PNR_MR_Unavailable,PNR_MR - Unavailable,pnr_mr_available == False,,,,,,,,,,,,-999,,,,,,,,, +util_PNR_MR_Unavailable_for_persons_less_than_16,PNR_MR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,-999,,,,,,,,, +util_PNR_MR_In_vehicle_time,PNR_MR - In-vehicle time,@(odt_skims['DR_MR_WK_TOTIVT'] + dot_skims['WK_MR_DR_TOTIVT']),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_In_vehicle_time_on_MR,PNR_MR - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['DR_MR_WK_IVTMR'] + dot_skims['WK_MR_DR_IVTMR']),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_In_vehicle_time_on_LR,PNR_MR - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['DR_MR_WK_IVTLR'] + dot_skims['WK_MR_DR_IVTLR']),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_iwait_time,PNR_MR - iwait time,@(odt_skims['DR_MR_WK_IWAIT'] + dot_skims['WK_MR_DR_IWAIT']),,,,,,,,,,,,coef_iwait,,,,,,,,, +util_PNR_MR_transfer_wait_time,PNR_MR - transfer wait time,@(odt_skims['DR_MR_WK_XWAIT'] + dot_skims['WK_MR_DR_XWAIT']),,,,,,,,,,,,coef_xwait,,,,,,,,, +util_PNR_MR_number_of_transfers,PNR_MR - number of transfers,@((odt_skims['DR_MR_WK_XFERS']).clip(0) + (dot_skims['WK_MR_DR_XFERS']).clip(0)),,,,,,,,,,,,coef_xfers_pnr,,,,,,,,, +util_PNR_MR_PNR_time,PNR_MR - PNR time,@(odt_skims['DR_MR_WK_DTIME'] + dot_skims['WK_MR_DR_DTIME']),,,,,,,,,,,,coef_drvacc_pnr,,,,,,,,, +util_PNR_MR_Walk_time,PNR_MR - Walk time,@(odt_skims['DR_MR_WK_WACC_EGR'] + dot_skims['WK_MR_DR_WACC_EGR']),,,,,,,,,,,,coef_wlk_acc,,,,,,,,, +util_PNR_MR_Walk_other_time,PNR_MR - Walk other time,@(odt_skims['DR_MR_WK_WAUX'] + dot_skims['WK_MR_DR_WAUX']),,,,,,,,,,,,coef_wlk_aux,,,,,,,,, +util_PNR_MR_Fare_and_operating_cost,PNR_MR - Fare and operating cost,@((odt_skims['DR_MR_WK_FARE'] + dot_skims['WK_MR_DR_FARE']) * 1.22 + ((odt_skims['DR_MR_WK_DDIST']+dot_skims['WK_MR_DR_DDIST']) * costPerMile)),,,,,,,,,,,,coef_cost,,,,,,,,, +util_PNR_MR_Ratio_of_PNR_access_distance_to_OD_distance,PNR_MR - Ratio of PNR access distance to OD distance,@((odt_skims['DR_MR_WK_DDIST']+ dot_skims['WK_MR_DR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,,,coef_drvratio_pnr,,,,,,,,, +util_PNR_MR_Destination_zone_densityIndex,PNR_MR - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,,,coef_density_pnr,,,,,,,,, +util_PNR_MR_Topology,PNR_MR - Topology,@df.dest_topology,,,,,,,,,,,,coef_topology_pnr,,,,,,,,, +#util_PNR_to_CR,#PNR to CR,,,,,,,,,,,,,,,,,,,,,, +util_PNR_CR_Unavailable,PNR_CR - Unavailable,pnr_cr_available == False,,,,,,,,,,,,,-999,,,,,,,, +util_PNR_CR_Unavailable_for_persons_less_than_16,PNR_CR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,-999,,,,,,,, +util_PNR_CR_In_vehicle_time,PNR_CR - In-vehicle time,@(odt_skims['DR_CR_WK_TOTIVT'] + dot_skims['WK_CR_DR_TOTIVT']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_CR,PNR_CR - In-vehicle time on CR,@(ivt_CR_multiplier - 1) * (odt_skims['DR_CR_WK_IVTCR'] + dot_skims['WK_CR_DR_IVTCR']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_LB,PNR_CR - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['DR_CR_WK_IVTLB'] + dot_skims['WK_CR_DR_IVTLB']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_XB,PNR_CR - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['DR_CR_WK_IVTXB'] + dot_skims['WK_CR_DR_IVTXB']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_MR,PNR_CR - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['DR_CR_WK_IVTMR'] + dot_skims['WK_CR_DR_IVTMR']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_BR,PNR_CR - In-vehicle time on BR,@(ivt_BR_multiplier - 1) * (odt_skims['DR_CR_WK_IVTBR'] + dot_skims['WK_CR_DR_IVTBR']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_LR,PNR_CR - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['DR_CR_WK_IVTLR'] + dot_skims['WK_CR_DR_IVTLR']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_iwait_time,PNR_CR - iwait time,@(odt_skims['DR_CR_WK_IWAIT'] + dot_skims['WK_CR_DR_IWAIT']),,,,,,,,,,,,,coef_iwait,,,,,,,, +util_PNR_CR_transfer_wait_time,PNR_CR - transfer wait time,@(odt_skims['DR_CR_WK_XWAIT'] + dot_skims['WK_CR_DR_XWAIT']),,,,,,,,,,,,,coef_xwait,,,,,,,, +util_PNR_CR_number_of_transfers,PNR_CR - number of transfers,@((odt_skims['DR_CR_WK_XFERS']).clip(0) + (dot_skims['WK_CR_DR_XFERS']).clip(0)),,,,,,,,,,,,,coef_xfers_pnr,,,,,,,, +util_PNR_CR_PNR_time,PNR_CR - PNR time,@(odt_skims['DR_CR_WK_DTIME'] + dot_skims['WK_CR_DR_DTIME']),,,,,,,,,,,,,coef_drvacc_pnr,,,,,,,, +util_PNR_CR_Walk_time,PNR_CR - Walk time,@(odt_skims['DR_CR_WK_WACC_EGR'] + dot_skims['WK_CR_DR_WACC_EGR']),,,,,,,,,,,,,coef_wlk_acc,,,,,,,, +util_PNR_CR_Walk_other_time,PNR_CR - Walk other time,@(odt_skims['DR_CR_WK_WAUX'] + dot_skims['WK_CR_DR_WAUX']),,,,,,,,,,,,,coef_wlk_aux,,,,,,,, +util_PNR_CR_Fare_and_operating_cost,PNR_CR - Fare and operating cost,@((odt_skims['DR_CR_WK_FARE'] + dot_skims['WK_CR_DR_FARE']) * 1.22 + ((odt_skims['DR_CR_WK_DDIST']+dot_skims['WK_CR_DR_DDIST']) * costPerMile)),,,,,,,,,,,,,coef_cost,,,,,,,, +util_PNR_CR_Ratio_of_PNR_access_distance_to_OD_distance,PNR_CR - Ratio of PNR access distance to OD distance,@((odt_skims['DR_CR_WK_DDIST']+ dot_skims['WK_CR_DR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,,,,coef_drvratio_pnr,,,,,,,, +util_PNR_CR_Destination_zone_densityIndex,PNR_CR - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,,,,coef_density_pnr,,,,,,,, +util_PNR_CR_Topology,PNR_CR - Topology,@df.dest_topology,,,,,,,,,,,,,coef_topology_pnr,,,,,,,, +#util_KNR_to_AB,#KNR to AB,,,,,,,,,,,,,,,,,,,,,, +util_KNR_AB_Unavailable,KNR_AB - Unavailable,knr_ab_available == False,,,,,,,,,,,,,,-999,,,,,,, +util_KNR_AB_Unavailable_for_persons_less_than_16,KNR_AB - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,-999,,,,,,, +util_KNR_AB_In_vehicle_time,KNR_AB - In-vehicle time,@(odt_skims['KR_AB_WK_TOTIVT'] + dot_skims['WK_AB_KR_TOTIVT']),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_In_vehicle_time_on_LB,KNR_AB - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['KR_AB_WK_IVTLB'] + dot_skims['WK_AB_KR_IVTLB']),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_In_vehicle_time_on_XB,KNR_AB - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['KR_AB_WK_IVTXB'] + dot_skims['WK_AB_KR_IVTXB']),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_iwait_time,KNR_AB - iwait time,@(odt_skims['KR_AB_WK_IWAIT'] + dot_skims['WK_AB_KR_IWAIT']),,,,,,,,,,,,,,coef_iwait,,,,,,, +util_KNR_AB_transfer_wait_time,KNR_AB - transfer wait time,@(odt_skims['KR_AB_WK_XWAIT'] + dot_skims['WK_AB_KR_XWAIT']),,,,,,,,,,,,,,coef_xwait,,,,,,, +util_KNR_AB_number_of_transfers,KNR_AB - number of transfers,@((odt_skims['KR_AB_WK_XFERS']).clip(0) + (dot_skims['WK_AB_KR_XFERS']).clip(0)),,,,,,,,,,,,,,coef_xfers_knr,,,,,,, +util_KNR_AB_KNR_time,KNR_AB - KNR time,@(odt_skims['KR_AB_WK_DTIME'] + dot_skims['WK_AB_KR_DTIME']),,,,,,,,,,,,,,coef_drvacc_knr,,,,,,, +util_KNR_AB_Walk_time,KNR_AB - Walk time,@(odt_skims['KR_AB_WK_WACC_EGR'] + dot_skims['WK_AB_KR_WACC_EGR']),,,,,,,,,,,,,,coef_wlk_acc,,,,,,, +util_KNR_AB_Walk_other_time,KNR_AB - Walk other time,@(odt_skims['KR_AB_WK_WAUX'] + dot_skims['WK_AB_KR_WAUX']),,,,,,,,,,,,,,coef_wlk_aux,,,,,,, +util_KNR_AB_Fare_and_operating_cost,KNR_AB - Fare and operating cost,@((odt_skims['KR_AB_WK_FARE'] + dot_skims['WK_AB_KR_FARE']) * 1.22 + ((odt_skims['KR_AB_WK_DDIST']+dot_skims['WK_AB_KR_DDIST']) * costPerMile)),,,,,,,,,,,,,,coef_cost,,,,,,, +util_KNR_AB_Ratio_of_KNR_access_distance_to_OD_distance,KNR_AB - Ratio of KNR access distance to OD distance,@((odt_skims['KR_AB_WK_DDIST']+ dot_skims['WK_AB_KR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,,,,,coef_drvratio_knr,,,,,,, +util_KNR_AB_Destination_zone_densityIndex,KNR_AB - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,,,,,coef_density_knr,,,,,,, +util_KNR_AB_Topology,KNR_AB - Topology,@df.dest_topology,,,,,,,,,,,,,,coef_topology_knr,,,,,,, +#util_KNR_to_BM,#KNR to BM,,,,,,,,,,,,,,,,,,,,,, +util_KNR_BM_Unavailable,KNR_BM - Unavailable,knr_bm_available == False,,,,,,,,,,,,,,,-999,,,,,, +util_KNR_BM_Unavailable_for_persons_less_than_16,KNR_BM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,-999,,,,,, +util_KNR_BM_In_vehicle_time,KNR_BM - In-vehicle time,@(odt_skims['KR_BM_WK_TOTIVT'] + dot_skims['WK_BM_KR_TOTIVT']),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_LB,KNR_BM - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['KR_BM_WK_IVTLB'] + dot_skims['WK_BM_KR_IVTLB']),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_XB,KNR_BM - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['KR_BM_WK_IVTXB'] + dot_skims['WK_BM_KR_IVTXB']),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_MR,KNR_BM - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['KR_BM_WK_IVTMR'] + dot_skims['WK_BM_KR_IVTMR']),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_LR,KNR_BM - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['KR_BM_WK_IVTLR'] + dot_skims['WK_BM_KR_IVTLR']),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_iwait_time,KNR_BM - iwait time,@(odt_skims['KR_BM_WK_IWAIT'] + dot_skims['WK_BM_KR_IWAIT']),,,,,,,,,,,,,,,coef_iwait,,,,,, +util_KNR_BM_transfer_wait_time,KNR_BM - transfer wait time,@(odt_skims['KR_BM_WK_XWAIT'] + dot_skims['WK_BM_KR_XWAIT']),,,,,,,,,,,,,,,coef_xwait,,,,,, +util_KNR_BM_number_of_transfers,KNR_BM - number of transfers,@((odt_skims['KR_BM_WK_XFERS']).clip(0) + (dot_skims['WK_BM_KR_XFERS']).clip(0)),,,,,,,,,,,,,,,coef_xfers_knr,,,,,, +util_KNR_BM_KNR_time,KNR_BM - KNR time,@(odt_skims['KR_BM_WK_DTIME'] + dot_skims['WK_BM_KR_DTIME']),,,,,,,,,,,,,,,coef_drvacc_knr,,,,,, +util_KNR_BM_Walk_time,KNR_BM - Walk time,@(odt_skims['KR_BM_WK_WACC_EGR'] + dot_skims['WK_BM_KR_WACC_EGR']),,,,,,,,,,,,,,,coef_wlk_acc,,,,,, +util_KNR_BM_Walk_other_time,KNR_BM - Walk other time,@(odt_skims['KR_BM_WK_WAUX'] + dot_skims['WK_BM_KR_WAUX']),,,,,,,,,,,,,,,coef_wlk_aux,,,,,, +util_KNR_BM_Fare_and_operating_cost,KNR_BM - Fare and operating cost,@((odt_skims['KR_BM_WK_FARE'] + dot_skims['WK_BM_KR_FARE']) * 1.22 + ((odt_skims['KR_BM_WK_DDIST']+dot_skims['WK_BM_KR_DDIST']) * costPerMile)),,,,,,,,,,,,,,,coef_cost,,,,,, +util_KNR_BM_Ratio_of_KNR_access_distance_to_OD_distance,KNR_BM - Ratio of KNR access distance to OD distance,@((odt_skims['KR_BM_WK_DDIST']+ dot_skims['WK_BM_KR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,coef_drvratio_knr,,,,,, +util_KNR_BM_Destination_zone_densityIndex,KNR_BM - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,,,,,,coef_density_knr,,,,,, +util_KNR_BM_Topology,KNR_BM - Topology,@df.dest_topology,,,,,,,,,,,,,,,coef_topology_knr,,,,,, +#util_KNR_to_MR,#KNR to MR,,,,,,,,,,,,,,,,,,,,,, +util_KNR_MR_Unavailable,KNR_MR - Unavailable,knr_mr_available == False,,,,,,,,,,,,,,,,-999,,,,, +util_KNR_MR_Unavailable_for_persons_less_than_16,KNR_MR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,-999,,,,, +util_KNR_MR_In_vehicle_time,KNR_MR - In-vehicle time,@(odt_skims['KR_MR_WK_TOTIVT'] + dot_skims['WK_MR_KR_TOTIVT']),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_In_vehicle_time_on_MR,KNR_MR - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['KR_MR_WK_IVTMR'] + dot_skims['WK_MR_KR_IVTMR']),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_In_vehicle_time_on_LR,KNR_MR - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['KR_MR_WK_IVTLR'] + dot_skims['WK_MR_KR_IVTLR']),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_iwait_time,KNR_MR - iwait time,@(odt_skims['KR_MR_WK_IWAIT'] + dot_skims['WK_MR_KR_IWAIT']),,,,,,,,,,,,,,,,coef_iwait,,,,, +util_KNR_MR_transfer_wait_time,KNR_MR - transfer wait time,@(odt_skims['KR_MR_WK_XWAIT'] + dot_skims['WK_MR_KR_XWAIT']),,,,,,,,,,,,,,,,coef_xwait,,,,, +util_KNR_MR_number_of_transfers,KNR_MR - number of transfers,@((odt_skims['KR_MR_WK_XFERS']).clip(0) + (dot_skims['WK_MR_KR_XFERS']).clip(0)),,,,,,,,,,,,,,,,coef_xfers_knr,,,,, +util_KNR_MR_KNR_time,KNR_MR - KNR time,@dtim_multiplier * (odt_skims['KR_MR_WK_DTIME'] + dot_skims['WK_MR_KR_DTIME']),,,,,,,,,,,,,,,,coef_drvacc_knr,,,,, +util_KNR_MR_Walk_time,KNR_MR - Walk time,@(odt_skims['KR_MR_WK_WACC_EGR'] + dot_skims['WK_MR_KR_WACC_EGR']),,,,,,,,,,,,,,,,coef_wlk_acc,,,,, +util_KNR_MR_Walk_other_time,KNR_MR - Walk other time,@(odt_skims['KR_MR_WK_WAUX'] + dot_skims['WK_MR_KR_WAUX']),,,,,,,,,,,,,,,,coef_wlk_aux,,,,, +util_KNR_MR_Fare_and_operating_cost,KNR_MR - Fare and operating cost,@((odt_skims['KR_MR_WK_FARE'] + dot_skims['WK_MR_KR_FARE']) * 1.22 + ((odt_skims['KR_MR_WK_DDIST']+dot_skims['WK_MR_KR_DDIST']) * costPerMile)),,,,,,,,,,,,,,,,coef_cost,,,,, +util_KNR_MR_Ratio_of_KNR_access_distance_to_OD_distance,KNR_MR - Ratio of KNR access distance to OD distance,@((odt_skims['KR_MR_WK_DDIST']+ dot_skims['WK_MR_KR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,,coef_drvratio_knr,,,,, +util_KNR_MR_Destination_zone_densityIndex,KNR_MR - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,,,,,,,coef_density_knr,,,,, +util_KNR_MR_Topology,KNR_MR - Topology,@df.dest_topology,,,,,,,,,,,,,,,,coef_topology_knr,,,,, +#util_KNR_to_CR,#KNR to CR,#DR AND KR SKIMS ARE THE SAME FOR CR,,,,,,,,,,,,,,,,,,,,, +util_KNR_CR_Unavailable,KNR_CR - Unavailable,knr_cr_available == False,,,,,,,,,,,,,,,,,-999,,,, +util_KNR_CR_Unavailable_for_persons_less_than_16,KNR_CR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,-999,,,, +util_KNR_CR_In_vehicle_time,KNR_CR - In-vehicle time,@(odt_skims['KR_CR_WK_TOTIVT'] + dot_skims['WK_CR_KR_TOTIVT']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_CR,KNR_CR - In-vehicle time on CR,@(ivt_CR_multiplier - 1) * (odt_skims['KR_CR_WK_IVTCR'] + dot_skims['WK_CR_KR_IVTCR']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_LB,KNR_CR - In-vehicle time on LB,@(ivt_LB_multiplier - 1) * (odt_skims['KR_CR_WK_IVTLB'] + dot_skims['WK_CR_KR_IVTLB']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_XB,KNR_CR - In-vehicle time on XB,@(ivt_XB_multiplier - 1) * (odt_skims['KR_CR_WK_IVTXB'] + dot_skims['WK_CR_KR_IVTXB']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_MR,KNR_CR - In-vehicle time on MR,@(ivt_MR_multiplier - 1) * (odt_skims['KR_CR_WK_IVTMR'] + dot_skims['WK_CR_KR_IVTMR']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_BR,KNR_CR - In-vehicle time on BR,@(ivt_BR_multiplier - 1) * (odt_skims['KR_CR_WK_IVTBR'] + dot_skims['WK_CR_KR_IVTBR']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_LR,KNR_CR - In-vehicle time on LR,@(ivt_LR_multiplier - 1) * (odt_skims['KR_CR_WK_IVTLR'] + dot_skims['WK_CR_KR_IVTLR']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_iwait_time,KNR_CR - iwait time,@(odt_skims['KR_CR_WK_IWAIT'] + dot_skims['WK_CR_KR_IWAIT']),,,,,,,,,,,,,,,,,coef_iwait,,,, +util_KNR_CR_transfer_wait_time,KNR_CR - transfer wait time,@(odt_skims['KR_CR_WK_XWAIT'] + dot_skims['WK_CR_KR_XWAIT']),,,,,,,,,,,,,,,,,coef_xwait,,,, +util_KNR_CR_number_of_transfers,KNR_CR - number of transfers,@((odt_skims['KR_CR_WK_XFERS']).clip(0) + (dot_skims['WK_CR_KR_XFERS']).clip(0)),,,,,,,,,,,,,,,,,coef_xfers_knr,,,, +util_KNR_CR_KNR_time,KNR_CR - KNR time,@(odt_skims['KR_CR_WK_DTIME'] + dot_skims['WK_CR_KR_DTIME']),,,,,,,,,,,,,,,,,coef_drvacc_knr,,,, +util_KNR_CR_Walk_time,KNR_CR - Walk time,@(odt_skims['KR_CR_WK_WACC_EGR'] + dot_skims['WK_CR_KR_WACC_EGR']),,,,,,,,,,,,,,,,,coef_wlk_acc,,,, +util_KNR_CR_Walk_other_time,KNR_CR - Walk other time,@(odt_skims['KR_CR_WK_WAUX'] + dot_skims['WK_CR_KR_WAUX']),,,,,,,,,,,,,,,,,coef_wlk_aux,,,, +util_KNR_CR_Fare_and_operating_cost,KNR_CR - Fare and operating cost,@((odt_skims['KR_CR_WK_FARE'] + dot_skims['WK_CR_KR_FARE']) * 1.22 + ((odt_skims['KR_CR_WK_DDIST']+dot_skims['WK_CR_KR_DDIST']) * costPerMile)),,,,,,,,,,,,,,,,,coef_cost,,,, +util_KNR_CR_Ratio_of_KNR_access_distance_to_OD_distance,KNR_CR - Ratio of KNR access distance to OD distance,@((odt_skims['KR_CR_WK_DDIST']+ dot_skims['WK_CR_KR_DDIST'])/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,,,coef_drvratio_knr,,,, +util_KNR_CR_Destination_zone_densityIndex,KNR_CR - Destination zone densityIndex,@df.dest_density_index,,,,,,,,,,,,,,,,,coef_density_knr,,,, +util_KNR_CR_Topology,KNR_CR - Topology,@df.dest_topology,,,,,,,,,,,,,,,,,coef_topology_knr,,,, +#School_Bus,#School Bus,,,,,,,,,,,,,,,,,,,,,, +School_Bus_Unavailable_if_NOT_school_tour,School Bus - Unavailable if NOT school tour,~is_school,,,,,,,,,,,,,,,,,,-999,,, +School_Bus_In_vehicle_time_(HOV3+_skims)_20_mph,School Bus - In-vehicle time (HOV3+ skims) - 20 mph,@(odt_skims['HOV3_DIST'] + dot_skims['HOV3_DIST'])*3,,,,,,,,,,,,,,,,,,coef_ivt,,, +School_Bus_WALK_Time,School Bus - Walk Time,10,,,,,,,,,,,,,,,,,,coef_wlk_acc,,, +School_Bus_Wait_Time,School Bus - Wait Time,10,,,,,,,,,,,,,,,,,,coef_iwait,,, +#,Taxi,,,,,,,,,,,,,,,,,,,,,, +util_Taxi_In_vehicle_time,Taxi - In-vehicle time,@(odt_skims['HOV2_TIME'] + dot_skims['HOV2_TIME']),,,,,,,,,,,,,,,,,,,coef_ivt,, +util_Taxi_Wait_time,Taxi - Wait time,@df.totalWaitTaxi,,,,,,,,,,,,,,,,,,,coef_iwait,, +util_Taxi_Total_toll,Taxi - Total toll,@(odt_skims['HOV2_TOLL'] + dot_skims['HOV2_TOLL']) * 1.22,,,,,,,,,,,,,,,,,,,coef_cost,, +util_Taxi_Fare,Taxi - Fare,@(Taxi_baseFare * 2 + (odt_skims['HOV2_DIST'] + dot_skims['HOV2_DIST']) * Taxi_costPerMile +(odt_skims['HOV2_TIME'] + dot_skims['HOV2_TIME']) * Taxi_costPerMinute)*100,,,,,,,,,,,,,,,,,,,coef_cost,, +#,TNC Single,,,,,,,,,,,,,,,,,,,,,, +util_TNC_Single_In_vehicle_time,TNC Single - In-vehicle time,@(odt_skims['HOV2_TIME'] + dot_skims['HOV2_TIME']),,,,,,,,,,,,,,,,,,,,coef_ivt, +util_TNC_Single_Wait_time,TNC Single - Wait time,@df.totalWaitSingleTNC,,,,,,,,,,,,,,,,,,,,coef_iwait, +util_TNC_Single_Total_toll,TNC Single - Total toll,@(odt_skims['HOV2_TOLL'] + dot_skims['HOV2_TOLL']) * 1.22,,,,,,,,,,,,,,,,,,,,coef_cost, +util_TNC_Single_Cost,TNC Single - Cost,"@np.maximum(TNC_single_baseFare * 2 + (odt_skims['HOV2_DIST'] + dot_skims['HOV2_DIST']) * TNC_single_costPerMile + (odt_skims['HOV2_TIME'] + dot_skims['HOV2_TIME']) * TNC_single_costPerMinute, TNC_single_costMinimum) * 100",,,,,,,,,,,,,,,,,,,,coef_cost, +#,TNC Shared,,,,,,,,,,,,,,,,,,,,,, +util_TNC_Shared_In_vehicle_time,TNC Shared - In-vehicle time,@(odt_skims['HOV2_TIME'] + dot_skims['HOV2_TIME']) * TNC_shared_IVTFactor,,,,,,,,,,,,,,,,,,,,,coef_ivt +util_TNC_Shared_Wait_time,TNC Shared - Wait time,@df.totalWaitSharedTNC,,,,,,,,,,,,,,,,,,,,,coef_iwait +util_TNC_Shared_Total_toll,TNC Shared - Total toll,@(odt_skims['HOV2_TOLL'] + dot_skims['HOV2_TOLL']) * 1.22,,,,,,,,,,,,,,,,,,,,,coef_cost +util_TNC_Shared_Cost,TNC Shared - Cost,"@np.maximum(TNC_shared_baseFare * 2 + (odt_skims['HOV2_DIST'] + dot_skims['HOV2_DIST']) * TNC_shared_costPerMile + (odt_skims['HOV2_TIME'] + dot_skims['HOV3_TIME']) * TNC_shared_costPerMinute, TNC_shared_costMinimum) * 100",,,,,,,,,,,,,,,,,,,,,coef_cost +#indiv_tour_ASCs,#indiv tour ASCs,,,,,,,,,,,,,,,,,,,,,, +util_WALK_ASC_Zero_auto,Walk ASC - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,walk_ASC_no_auto,,,,,,,,,,,,,,,,, +util_WALK_ASC_Auto_deficient,Walk ASC - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,walk_ASC_auto_deficient,,,,,,,,,,,,,,,,, +util_WALK_ASC_Auto_sufficient,Walk ASC - Auto Sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,walk_ASC_auto_sufficient,,,,,,,,,,,,,,,,, +util_BIKE_ASC_Zero_auto,Bike ASC - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,,bike_ASC_no_auto,,,,,,,,,,,,,,,, +util_BIKE_ASC_Auto_deficient,Bike ASC - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,bike_ASC_auto_deficient,,,,,,,,,,,,,,,, +util_BIKE_ASC_Auto_sufficient,Bike ASC - Auto Sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,bike_ASC_auto_sufficient,,,,,,,,,,,,,,,, +util_Shared_ride_2_ASC_Zero_auto,Shared ride 2 ASC - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,sr2_ASC_no_auto,,,,,,,,,,,,,,,,,,, +util_Shared_ride_2_ASC_Auto_deficient,Shared ride 2 ASC - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,sr2_ASC_auto_deficient,,,,,,,,,,,,,,,,,,, +util_Shared_ride_2_ASC_Auto_sufficient,Shared ride 2 ASC - Auto Sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,sr2_ASC_auto_sufficient,,,,,,,,,,,,,,,,,,, +util_Shared_ride_3+_Zero_auto,Shared ride 3+ - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,sr3p_ASC_no_auto,,,,,,,,,,,,,,,,,, +util_Shared_ride_3+_Auto_deficient,Shared ride 3+ - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,sr3p_ASC_auto_deficient,,,,,,,,,,,,,,,,,, +util_Shared_ride_3+_Auto_sufficient,Shared ride 3+ - Auto Sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,sr3p_ASC_auto_sufficient,,,,,,,,,,,,,,,,,, +util_WALK_to_Transit_Zero_auto,Walk to Transit - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,,,walk_transit_ASC_no_auto,walk_transit_ASC_no_auto,walk_transit_ASC_no_auto,walk_transit_ASC_no_auto,,,,,,,,,,,, +util_WALK_to_Transit_Auto_deficient,Walk to Transit - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,walk_transit_ASC_auto_deficient,walk_transit_ASC_auto_deficient,walk_transit_ASC_auto_deficient,walk_transit_ASC_auto_deficient,,,,,,,,,,,, +util_WALK_to_Transit_Auto_sufficient,Walk to Transit - Auto Sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,walk_transit_ASC_auto_sufficient,walk_transit_ASC_auto_sufficient,walk_transit_ASC_auto_sufficient,walk_transit_ASC_auto_sufficient,,,,,,,,,,,, +util_PNR_to_Transit_Zero_auto,PNR to Transit - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,,,,,,,pnr_transit_ASC_no_auto,pnr_transit_ASC_no_auto,pnr_transit_ASC_no_auto,pnr_transit_ASC_no_auto,,,,,,,, +util_PNR_to_Transit_Auto_deficient,PNR to Transit - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,pnr_transit_ASC_auto_deficient,pnr_transit_ASC_auto_deficient,pnr_transit_ASC_auto_deficient,pnr_transit_ASC_auto_deficient,,,,,,,, +util_PNR_to_Transit_Auto_sufficient,PNR to Transit - Auto Sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,pnr_transit_ASC_auto_sufficient,pnr_transit_ASC_auto_sufficient,pnr_transit_ASC_auto_sufficient,pnr_transit_ASC_auto_sufficient,,,,,,,, +util_KNR_to_Transit_Zero_auto,KNR to Transit - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,,,,,,,,,,,knr_transit_ASC_no_auto,knr_transit_ASC_no_auto,knr_transit_ASC_no_auto,knr_transit_ASC_no_auto,,,, +util_KNR_to_Transit_Auto_deficient,KNR to Transit - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,knr_transit_ASC_auto_deficient,knr_transit_ASC_auto_deficient,knr_transit_ASC_auto_deficient,knr_transit_ASC_auto_deficient,,,, +util_KNR_to_Transit_Auto_sufficient,KNR to Transit - Auto Sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,knr_transit_ASC_auto_sufficient,knr_transit_ASC_auto_sufficient,knr_transit_ASC_auto_sufficient,knr_transit_ASC_auto_sufficient,,,, +util_Taxi_Zero_auto,Taxi - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,,,,,,,,,,,,,,,,taxi_ASC_no_auto,, +util_Taxi_Auto_deficient,Taxi - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,taxi_ASC_auto_deficient,, +util_Taxi_Auto_sufficient,Taxi - Auto sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,taxi_ASC_auto_sufficient,, +util_TNC_Single_Zero_auto,TNC Single - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,,,,,,,,,,,,,,,,,tnc_single_ASC_no_auto, +util_TNC_Single_Auto_deficient,TNC Single - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,tnc_single_ASC_auto_deficient, +util_TNC_Single_Auto_sufficient,TNC Single - Auto sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,tnc_single_ASC_auto_sufficient, +util_TNC_Shared_Zero_auto,TNC Shared - Zero auto,@(df.is_indiv & (df.auto_ownership == 0)),,,,,,,,,,,,,,,,,,,,,tnc_shared_ASC_no_auto +util_TNC_Shared_Auto_deficient,TNC Shared - Auto deficient,@(df.is_indiv & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,,tnc_shared_ASC_auto_deficient +util_TNC_Shared_Auto_sufficient,TNC Shared - Auto sufficient,@(df.is_indiv & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,,tnc_shared_ASC_auto_sufficient +#util_Joint_tour_ASCs,#joint tour ASCs,,,,,,,,,,,,,,,,,,,,,, +util_Joint_WALK_ASC_Zero_auto,Joint - Walk ASC - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,joint_walk_ASC_no_auto,,,,,,,,,,,,,,,,, +util_Joint_WALK_ASC_Auto_deficient,Joint - Walk ASC - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,joint_walk_ASC_auto_deficient,,,,,,,,,,,,,,,,, +util_Joint_WALK_ASC_Auto_sufficient,Joint - Walk ASC - Auto Sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,joint_walk_ASC_auto_sufficient,,,,,,,,,,,,,,,,, +util_Joint_BIKE_ASC_Zero_auto,Joint - Bike ASC - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,,joint_bike_ASC_no_auto,,,,,,,,,,,,,,,, +util_Joint_BIKE_ASC_Auto_deficient,Joint - Bike ASC - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,joint_bike_ASC_auto_deficient,,,,,,,,,,,,,,,, +util_Joint_BIKE_ASC_Auto_sufficient,Joint - Bike ASC - Auto Sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,joint_bike_ASC_auto_sufficient,,,,,,,,,,,,,,,, +util_Joint_Shared_ride_2_ASC_Zero_auto,Joint - Shared ride 2 ASC - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,joint_sr2_ASC_no_auto,,,,,,,,,,,,,,,,,,, +util_Joint_Shared_ride_2_ASC_Auto_deficient,Joint - Shared ride 2 ASC - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,joint_sr2_ASC_auto_deficient,,,,,,,,,,,,,,,,,,, +util_Joint_Shared_ride_2_ASC_Auto_sufficient,Joint - Shared ride 2 ASC - Auto Sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,joint_sr2_ASC_auto_sufficient,,,,,,,,,,,,,,,,,,, +util_Joint_Shared_ride_3+_Zero_auto,Joint - Shared ride 3+ - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,joint_sr3p_ASC_no_auto,,,,,,,,,,,,,,,,,, +util_Joint_Shared_ride_3+_Auto_deficient,Joint - Shared ride 3+ - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,joint_sr3p_ASC_auto_deficient,,,,,,,,,,,,,,,,,, +util_Joint_Shared_ride_3+_Auto_sufficient,Joint - Shared ride 3+ - Auto Sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,joint_sr3p_ASC_auto_sufficient,,,,,,,,,,,,,,,,,, +util_Joint_WALK_to_Transit_Zero_auto,Joint - Walk to Transit - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,,,joint_walk_transit_ASC_no_auto,joint_walk_transit_ASC_no_auto,joint_walk_transit_ASC_no_auto,joint_walk_transit_ASC_no_auto,,,,,,,,,,,, +util_Joint_WALK_to_Transit_Auto_deficient,Joint - Walk to Transit - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,joint_walk_transit_ASC_auto_deficient,joint_walk_transit_ASC_auto_deficient,joint_walk_transit_ASC_auto_deficient,joint_walk_transit_ASC_auto_deficient,,,,,,,,,,,, +util_Joint_WALK_to_Transit_Auto_sufficient,Joint - Walk to Transit - Auto Sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,joint_walk_transit_ASC_auto_sufficient,joint_walk_transit_ASC_auto_sufficient,joint_walk_transit_ASC_auto_sufficient,joint_walk_transit_ASC_auto_sufficient,,,,,,,,,,,, +util_Joint_PNR_to_Transit_Zero_auto,Joint - PNR to Transit - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,,,,,,,joint_pnr_transit_ASC_no_auto,joint_pnr_transit_ASC_no_auto,joint_pnr_transit_ASC_no_auto,joint_pnr_transit_ASC_no_auto,,,,,,,, +util_Joint_PNR_to_Transit_Auto_deficient,Joint - PNR to Transit - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,joint_pnr_transit_ASC_auto_deficient,joint_pnr_transit_ASC_auto_deficient,joint_pnr_transit_ASC_auto_deficient,joint_pnr_transit_ASC_auto_deficient,,,,,,,, +util_Joint_PNR_to_Transit_Auto_sufficient,Joint - PNR to Transit - Auto Sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,joint_pnr_transit_ASC_auto_sufficient,joint_pnr_transit_ASC_auto_sufficient,joint_pnr_transit_ASC_auto_sufficient,joint_pnr_transit_ASC_auto_sufficient,,,,,,,, +util_Joint_KNR_to_Transit_Zero_auto,Joint - KNR to Transit - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,,,,,,,,,,,joint_knr_transit_ASC_no_auto,joint_knr_transit_ASC_no_auto,joint_knr_transit_ASC_no_auto,joint_knr_transit_ASC_no_auto,,,, +util_Joint_KNR_to_Transit_Auto_deficient,Joint - KNR to Transit - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,joint_knr_transit_ASC_auto_deficient,joint_knr_transit_ASC_auto_deficient,joint_knr_transit_ASC_auto_deficient,joint_knr_transit_ASC_auto_deficient,,,, +util_Joint_KNR_to_Transit_Auto_sufficient,Joint - KNR to Transit - Auto Sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,joint_knr_transit_ASC_auto_sufficient,joint_knr_transit_ASC_auto_sufficient,joint_knr_transit_ASC_auto_sufficient,joint_knr_transit_ASC_auto_sufficient,,,, +util_Joint_Taxi_Zero_auto,Joint - Taxi - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,,,,,,,,,,,,,,,,joint_taxi_ASC_no_auto,, +util_Joint_Taxi_Auto_deficient,Joint - Taxi - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,joint_taxi_ASC_auto_deficient,, +util_Joint_Taxi_Auto_sufficient,Joint - Taxi - Auto sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,joint_taxi_ASC_auto_sufficient,, +util_Joint_TNC_Single_Zero_auto,Joint - TNC Single - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,,,,,,,,,,,,,,,,,joint_tnc_single_ASC_no_auto, +util_Joint_TNC_Single_Auto_deficient,Joint - TNC Single - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,joint_tnc_single_ASC_auto_deficient, +util_Joint_TNC_Single_Auto_sufficient,Joint - TNC Single - Auto sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,joint_tnc_single_ASC_auto_sufficient, +util_Joint_TNC_Shared_Zero_auto,Joint - TNC Shared - Zero auto,@(df.is_joint & (df.auto_ownership == 0)),,,,,,,,,,,,,,,,,,,,,joint_tnc_shared_ASC_no_auto +util_Joint_TNC_Shared_Auto_deficient,Joint - TNC Shared - Auto deficient,@(df.is_joint & (df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,,joint_tnc_shared_ASC_auto_deficient +util_Joint_TNC_Shared_Auto_sufficient,Joint - TNC Shared - Auto sufficient,@(df.is_joint & (df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,,,,joint_tnc_shared_ASC_auto_sufficient +util_WALK_to_Transit_dest_CBD,Walk to Transit dest CBD,@df.destination_in_cbd,,,,,,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,,,,,,,,,,,, +Drive_to_Transit_dest_CBD,Drive to Transit dest CBD,@df.destination_in_cbd,,,,,,,,,,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,,,, +Drive_to_Transit_distance_penalty,Drive to Transit - distance penalty,@drvtrn_distpen_0_multiplier * (1-od_skims['DIST']/drvtrn_distpen_max).clip(lower=0),,,,,,,,,,coef_distpen_drvtrn,coef_distpen_drvtrn,coef_distpen_drvtrn,coef_distpen_drvtrn,coef_distpen_drvtrn,coef_distpen_drvtrn,coef_distpen_drvtrn,coef_distpen_drvtrn,,,, +util_schoolbus_ASC_no_auto,School Bus No Auto ASC,@(df.auto_ownership == 0),,,,,,,,,,,,,,,,,,schoolbus_ASC_no_auto,,, +util_schoolbus_ASC_auto_deficient,School Bus Auto Deficient ASC,@((df.auto_ownership < df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,schoolbus_ASC_auto_deficient,,, +util_schoolbus_ASC_auto_sufficient,School Bus Auto Sufficient ASC,@((df.auto_ownership >= df.num_workers) & (df.auto_ownership > 0)),,,,,,,,,,,,,,,,,,schoolbus_ASC_auto_sufficient,,, +util_transit_type_ASC,Transit technology ASC,1,,,,,,,walk_BM_ASC,walk_MR_ASC,walk_CR_ASC,,PNR_BM_ASC,PNR_MR_ASC,PNR_CR_ASC,,KNR_BM_ASC,KNR_MR_ASC,KNR_CR_ASC,,,, diff --git a/activitysim/examples/prototype_mwcog/configs/tour_mode_choice.yaml b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice.yaml new file mode 100644 index 000000000..ace2fa287 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice.yaml @@ -0,0 +1,114 @@ +LOGIT_TYPE: NL +#LOGIT_TYPE: MNL + +NESTS: + name: root + coefficient: coef_nest_root + alternatives: + - name: AUTO + coefficient: coef_nest_AUTO + alternatives: + - DRIVEALONE + - SHARED2 + - SHARED3 + - name: NONMOTORIZED + coefficient: coef_nest_NONMOTORIZED + alternatives: + - WALK + - BIKE + - name: TRANSIT + coefficient: coef_nest_TRANSIT + alternatives: + - name: WALKACCESS + coefficient: coef_nest_TRANSIT_WALKACCESS + alternatives: + - WALK_AB + - WALK_BM + - WALK_MR + - WALK_CR + - name: PNRACCESS + coefficient: coef_nest_TRANSIT_PNRACCESS + alternatives: + - PNR_AB + - PNR_BM + - PNR_MR + - PNR_CR + - name: KNRACCESS + coefficient: coef_nest_TRANSIT_KNRACCESS + alternatives: + - KNR_AB + - KNR_BM + - KNR_MR + - KNR_CR + - name: SCHOOL_BUS + coefficient: coef_nest_SCHOOL_BUS + alternatives: + - SCHOOLBUS + - name: RIDEHAIL + coefficient: coef_nest_RIDEHAIL + alternatives: + - TAXI + - TNC_SINGLE + - TNC_SHARED + +SPEC: tour_mode_choice.csv +COEFFICIENTS: tour_mode_choice_coeffs.csv +COEFFICIENT_TEMPLATE: tour_mode_choice_coeffs_template.csv + +CONSTANTS: + #costPerMile: 19.26 + #costShareSr2: 1.75 + #costShareSr3: 2.50 + #waitThresh: 10.00 + walkThresh: 1.50 + shortWalk: 0.333 + longWalk: 0.667 + walkSpeed: 3.00 + bikeThresh: 6.00 + bikeSpeed: 12.00 + maxCbdAreaTypeThresh: 2 + indivTour: 1.00000 + walkThresh: 1.50 + Taxi_waitTime_mean: + 1: 5.5 + 2: 9.5 + 3: 13.3 + 4: 17.3 + 5: 26.5 + Taxi_waitTime_sd: + 1: 0 + 2: 0 + 3: 0 + 4: 0 + 5: 0 + +# so far, we can use the same spec as for non-joint tours +preprocessor: + SPEC: tour_mode_choice_annotate_choosers_preprocessor + DF: choosers + TABLES: + - land_use + - tours + +nontour_preprocessor: + SPEC: tour_mode_choice_annotate_choosers_preprocessor + DF: choosers + TABLES: + - land_use + +# to reduce memory needs filter chooser table to these fields +LOGSUM_CHOOSER_COLUMNS: + - tour_type + - hhsize + - density_index + - age + - age_16_p + - age_16_to_19 + - auto_ownership + - number_of_participants + - tour_category + - num_workers + - value_of_time + - free_parking_at_work + +MODE_CHOICE_LOGSUM_COLUMN_NAME: mode_choice_logsum diff --git a/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_annotate_choosers_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_annotate_choosers_preprocessor.csv new file mode 100644 index 000000000..cffc75890 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_annotate_choosers_preprocessor.csv @@ -0,0 +1,88 @@ +Description,Target,Expression +#,, +local,_DF_IS_TOUR,'tour_type' in df.columns +,number_of_participants,df.number_of_participants if _DF_IS_TOUR else 1 +,is_joint,(df.tour_category=='joint') if _DF_IS_TOUR else False +#,, + local,_HAVE_PARENT_TOURS,'parent_tour_id' in df.columns +,_parent_tour_mode,"reindex(tours.tour_mode, df.parent_tour_id) if _HAVE_PARENT_TOURS else ''" +,work_tour_is_drive,_parent_tour_mode.isin(['DRIVEALONE']) +,work_tour_is_bike,_parent_tour_mode=='BIKE' +,work_tour_is_SOV,_parent_tour_mode.isin(['DRIVEALONE']) +#,, +,is_mandatory,(df.tour_category=='mandatory') if 'tour_category' in df.columns else False +,is_joint,(df.tour_category=='joint') if 'tour_category' in df.columns else False +,is_indiv,~is_joint +,is_atwork_subtour,(df.tour_category=='atwork') if 'tour_category' in df.columns else False +,is_escort,(df.tour_type == 'escort') if _DF_IS_TOUR else False +,is_school,(df.tour_type=='school') & (df.is_university==False) if _DF_IS_TOUR else False +#,, +#,c_cost,(0.60 * c_ivt) / df.value_of_time +#,, +,ivot,1.0/df.value_of_time +,dest_topology,"reindex(land_use.TOPOLOGY, df[dest_col_name])" +,terminal_time,"reindex(land_use.TERMINAL, df[dest_col_name])" +,dest_density_index,"reindex(land_use.density_index, df[dest_col_name])" +# FIXME no transit subzones so all zones short walk to transit,, +,_walk_transit_origin,True +,_walk_transit_destination,True +,walk_transit_available,_walk_transit_origin & _walk_transit_destination +,pnr_transit_available,_walk_transit_destination & (df.auto_ownership > 0) +,knr_transit_available,_walk_transit_origin & _walk_transit_destination +,origin_walk_time,shortWalk*60/walkSpeed +,destination_walk_time,shortWalk*60/walkSpeed +# RIDEHAIL,, +,origin_density_measure,"(reindex(land_use.TOTPOP, df[orig_col_name]) + reindex(land_use.TOTEMP, df[orig_col_name])) / (reindex(land_use.LANDAREA*640, df[orig_col_name]) / 640)" +,dest_density_measure,"(reindex(land_use.TOTPOP, df[dest_col_name]) + reindex(land_use.TOTEMP, df[dest_col_name])) / (reindex(land_use.LANDAREA*640, df[dest_col_name]) / 640)" +,origin_density,"pd.cut(origin_density_measure, bins=[-np.inf, 500, 2000, 5000, 15000, np.inf], labels=[5, 4, 3, 2, 1]).astype(int)" +,dest_density,"pd.cut(dest_density_measure, bins=[-np.inf, 500, 2000, 5000, 15000, np.inf], labels=[5, 4, 3, 2, 1]).astype(int)" +,origin_zone_taxi_wait_time_mean,"origin_density.map({k: v for k, v in Taxi_waitTime_mean.items()})" +,origin_zone_taxi_wait_time_sd,"origin_density.map({k: v for k, v in Taxi_waitTime_sd.items()})" +,dest_zone_taxi_wait_time_mean,"dest_density.map({k: v for k, v in Taxi_waitTime_mean.items()})" +,dest_zone_taxi_wait_time_sd,"dest_density.map({k: v for k, v in Taxi_waitTime_sd.items()})" +# ,, Note that the mean and standard deviation are not the values for the distribution itself but of the underlying normal distribution it is derived from +,origTaxiWaitTime,"rng.lognormal_for_df(df, mu=origin_zone_taxi_wait_time_mean, sigma=origin_zone_taxi_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)" +,destTaxiWaitTime,"rng.lognormal_for_df(df, mu=dest_zone_taxi_wait_time_mean, sigma=dest_zone_taxi_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)" +,origin_zone_singleTNC_wait_time_mean,"origin_density.map({k: v for k, v in TNC_single_waitTime_mean.items()})" +,origin_zone_singleTNC_wait_time_sd,"origin_density.map({k: v for k, v in TNC_single_waitTime_sd.items()})" +,dest_zone_singleTNC_wait_time_mean,"dest_density.map({k: v for k, v in TNC_single_waitTime_mean.items()})" +,dest_zone_singleTNC_wait_time_sd,"dest_density.map({k: v for k, v in TNC_single_waitTime_sd.items()})" +,origSingleTNCWaitTime,"rng.lognormal_for_df(df, mu=origin_zone_singleTNC_wait_time_mean, sigma=origin_zone_singleTNC_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)" +,destSingleTNCWaitTime,"rng.lognormal_for_df(df, mu=dest_zone_singleTNC_wait_time_mean, sigma=dest_zone_singleTNC_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)" +,origin_zone_sharedTNC_wait_time_mean,"origin_density.map({k: v for k, v in TNC_shared_waitTime_mean.items()})" +,origin_zone_sharedTNC_wait_time_sd,"origin_density.map({k: v for k, v in TNC_shared_waitTime_sd.items()})" +,dest_zone_sharedTNC_wait_time_mean,"dest_density.map({k: v for k, v in TNC_shared_waitTime_mean.items()})" +,dest_zone_sharedTNC_wait_time_sd,"dest_density.map({k: v for k, v in TNC_shared_waitTime_sd.items()})" +,origSharedTNCWaitTime,"rng.lognormal_for_df(df, mu=origin_zone_sharedTNC_wait_time_mean, sigma=origin_zone_sharedTNC_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)" +,destSharedTNCWaitTime,"rng.lognormal_for_df(df, mu=dest_zone_sharedTNC_wait_time_mean, sigma=dest_zone_sharedTNC_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)" +,totalWaitTaxi,origTaxiWaitTime + destTaxiWaitTime +,totalWaitSingleTNC,origSingleTNCWaitTime + destSingleTNCWaitTime +,totalWaitSharedTNC,origSharedTNCWaitTime + destSharedTNCWaitTime +#,, +,_free_parking_available,(df.tour_type == 'work') & df.free_parking_at_work if _DF_IS_TOUR else False +,_dest_hourly_peak_parking_cost,"reindex(land_use.PRKCST, df[dest_col_name])" +,_dest_hourly_offpeak_parking_cost,"reindex(land_use.OPRKCST, df[dest_col_name])" +,_hourly_peak_parking_cost,"np.where(_free_parking_available, 0, _dest_hourly_peak_parking_cost)" +,_hourly_offpeak_parking_cost,"np.where(_free_parking_available, 0, _dest_hourly_offpeak_parking_cost)" +,daily_parking_cost,"np.where(is_mandatory, _hourly_peak_parking_cost * df.duration/2, _hourly_offpeak_parking_cost * df.duration/2)" +#,, +,distance,od_skims['DIST'] +,sov_available,(odt_skims['SOV_TIME']>0) & (dot_skims['SOV_TIME']>0) +,hov2_available,(odt_skims['HOV2_TIME'] + dot_skims['HOV2_TIME'])>0 +,hov3_available,(odt_skims['HOV3_TIME']>0) & (dot_skims['HOV3_TIME']>0) +,walk_ab_available,walk_transit_available & (odt_skims['WK_AB_WK_IVTLB']>0) & (dot_skims['WK_AB_WK_IVTLB']>0) +,walk_bm_available,walk_transit_available & (odt_skims['WK_BM_WK_IVTMR']>0) & (dot_skims['WK_BM_WK_IVTMR']>0) +,walk_mr_available,walk_transit_available & (odt_skims['WK_MR_WK_IVTMR']>0) & (dot_skims['WK_MR_WK_IVTMR']>0) +,walk_cr_available,walk_transit_available & (odt_skims['WK_CR_WK_IVTCR']>0) & (dot_skims['WK_CR_WK_IVTCR']>0) +,pnr_ab_available,pnr_transit_available & (odt_skims['DR_AB_WK_IVTLB']>0) & (dot_skims['WK_AB_DR_IVTLB']>0) +,pnr_bm_available,pnr_transit_available & (odt_skims['DR_BM_WK_IVTMR']>0) & (dot_skims['WK_BM_DR_IVTMR']>0) +,pnr_mr_available,pnr_transit_available & (odt_skims['DR_MR_WK_IVTMR']>0) & (dot_skims['WK_MR_DR_IVTMR']>0) +,pnr_cr_available,pnr_transit_available & (odt_skims['DR_CR_WK_IVTCR']>0) & (dot_skims['WK_CR_DR_IVTCR']>0) +,knr_ab_available,knr_transit_available & (odt_skims['KR_AB_WK_IVTLB']>0) & (dot_skims['WK_AB_KR_IVTLB']>0) +,knr_bm_available,knr_transit_available & (odt_skims['KR_BM_WK_IVTMR']>0) & (dot_skims['WK_BM_KR_IVTMR']>0) +,knr_mr_available,knr_transit_available & (odt_skims['KR_MR_WK_IVTMR']>0) & (dot_skims['WK_MR_KR_IVTMR']>0) +,knr_cr_available,knr_transit_available & (odt_skims['KR_CR_WK_IVTCR']>0) & (dot_skims['WK_CR_KR_IVTCR']>0) +#,, +destination in central business district,destination_in_cbd,"(reindex(land_use.AREATYPE, df[dest_col_name]) < setting('cbd_threshold')) * 1" +#,,FIXME diagnostic +#,sov_dist_rt,(odt_skims['SOV_DIST'] + dot_skims['SOV_DIST']) diff --git a/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_coeffs.csv new file mode 100644 index 000000000..17a55c327 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_coeffs.csv @@ -0,0 +1,454 @@ +coefficient_name,value,constrain +coef_ivt_work,-0.025,F +coef_cost_work,-0.000659341,F +coef_walk_work,-0.0344,F +coef_bike_work,-0.0367,F +coef_wlk_acc_work,-0.0457,F +coef_wlk_aux_work,-0.05,F +coef_drvacc_pnr_work,-0.05,F +coef_drvacc_knr_work,-0.05,F +coef_iwait_work,-0.0372,F +coef_xwait_work,-0.0382,F +coef_xfers_wlktrn_work,0.0,T +coef_xfers_pnr_work,0.0,T +coef_xfers_knr_work,0.0,T +walk_transit_CBD_ASC_work,0.479,F +drive_transit_CBD_ASC_work,1.17,F +coef_density_walk_work,0.058,F +coef_density_bike_work,0.0145,F +coef_density_wlktrn_work,0.0,T +coef_distpen_drvtrn_work,0.0,T +coef_drvratio_knr_work,0.0,T +coef_drvratio_pnr_work,0.0,T +coef_age010_wlktrn_work,0.0,T +coef_age1619_da_work,-0.205,F +coef_age16p_sr_work,-0.454,F +coef_hhsize1_sr_work,-1.5,F +coef_hhsize2_sr_work,-0.895,F +coef_topology_bike_work,0.0,T +coef_topology_knr_work,0.0,T +coef_topology_pnr_work,0.0,T +coef_topology_walk_work,0.0,T +coef_topology_wlktrn_work,0.0,T +walk_MR_ASC_work,1.01,F +walk_BM_ASC_work,0.149,F +walk_CR_ASC_work,1.2,F +PNR_MR_ASC_work,-0.8759999999999999,F +PNR_BM_ASC_work,-1.89,F +PNR_CR_ASC_work,2.08,F +KNR_MR_ASC_work,0.43,F +KNR_BM_ASC_work,0.5579999999999999,F +KNR_CR_ASC_work,-8.88,F +coef_ivt_school_univ,-0.01,T +coef_cost_school_univ,-0.001,F +coef_walk_school_univ,-0.0138,F +coef_bike_school_univ,-0.0147,F +coef_wlk_acc_school_univ,-0.0183,F +coef_wlk_aux_school_univ,-0.0183,F +coef_drvacc_pnr_school_univ,-0.0182,F +coef_drvacc_knr_school_univ,-0.0182,F +coef_iwait_school_univ,-0.0149,F +coef_xwait_school_univ,-0.0153,F +coef_xfers_wlktrn_school_univ,0.0,T +coef_xfers_pnr_school_univ,0.0,T +coef_xfers_knr_school_univ,0.0,T +walk_transit_CBD_ASC_school_univ,0.1916,F +drive_transit_CBD_ASC_school_univ,0.468,F +coef_density_walk_school_univ,0.0232,F +coef_density_bike_school_univ,0.0058,F +coef_density_wlktrn_school_univ,0.0,T +coef_distpen_drvtrn_school_univ,0.0,T +coef_drvratio_knr_school_univ,0.0,T +coef_drvratio_pnr_school_univ,0.0,T +coef_age010_wlktrn_school_univ,-0.7140000000000001,F +coef_age1619_da_school_univ,0.066,F +coef_age16p_sr_school_univ,-0.407,F +coef_hhsize1_sr_school_univ,-2.65,F +coef_hhsize2_sr_school_univ,-0.6759999999999999,F +coef_topology_bike_school_univ,0.0,T +coef_topology_knr_school_univ,0.0,T +coef_topology_pnr_school_univ,0.0,T +coef_topology_walk_school_univ,0.0,T +coef_topology_wlktrn_school_univ,0.0,T +walk_MR_ASC_school_univ,1.11,F +walk_BM_ASC_school_univ,0.537,F +walk_CR_ASC_school_univ,1.36,F +PNR_MR_ASC_school_univ,-999.0,T +PNR_BM_ASC_school_univ,-999.0,T +PNR_CR_ASC_school_univ,-999.0,T +KNR_MR_ASC_school_univ,-999.0,T +KNR_BM_ASC_school_univ,-999.0,T +KNR_CR_ASC_school_univ,-999.0,T +coef_ivt_nonmandatory,-0.0213,F +coef_cost_nonmandatory,-0.00106,F +coef_walk_nonmandatory,-0.0488,F +coef_bike_nonmandatory,-0.0522,F +coef_wlk_acc_nonmandatory,-0.0371,F +coef_wlk_aux_nonmandatory,-0.0426,T +coef_drvacc_pnr_nonmandatory,-0.0426,T +coef_drvacc_knr_nonmandatory,-0.0426,T +coef_iwait_nonmandatory,-0.03195,T +coef_xwait_nonmandatory,-0.0426,T +coef_xfers_wlktrn_nonmandatory,0.0,T +coef_xfers_pnr_nonmandatory,0.0,T +coef_xfers_knr_nonmandatory,0.0,T +walk_transit_CBD_ASC_nonmandatory,0.272,F +drive_transit_CBD_ASC_nonmandatory,0.0,F +coef_density_walk_nonmandatory,0.0579,F +coef_density_bike_nonmandatory,0.041,F +coef_density_wlktrn_nonmandatory,0.0,T +coef_distpen_drvtrn_nonmandatory,0.0,T +coef_drvratio_knr_nonmandatory,0.0,T +coef_drvratio_pnr_nonmandatory,0.0,T +coef_age010_wlktrn_nonmandatory,-1.49,F +coef_age1619_da_nonmandatory,-1.23,F +coef_age16p_sr_nonmandatory,0.79,F +coef_hhsize1_sr_nonmandatory,-1.13,F +coef_hhsize2_sr_nonmandatory,-0.757,F +coef_topology_bike_nonmandatory,0.0,T +coef_topology_knr_nonmandatory,0.0,T +coef_topology_pnr_nonmandatory,0.0,T +coef_topology_walk_nonmandatory,0.0,T +coef_topology_wlktrn_nonmandatory,0.0,T +walk_MR_ASC_nonmandatory,0.0,F +walk_BM_ASC_nonmandatory,-0.979,F +walk_CR_ASC_nonmandatory,2.01,F +PNR_MR_ASC_nonmandatory,-999.0,F +PNR_BM_ASC_nonmandatory,-999.0,F +PNR_CR_ASC_nonmandatory,-999.0,F +KNR_MR_ASC_nonmandatory,-999.0,F +KNR_BM_ASC_nonmandatory,-999.0,F +KNR_CR_ASC_nonmandatory,-999.0,F +coef_ivt_atwork,-0.0361,F +coef_cost_atwork,-0.000434,F +coef_walk_atwork,-0.0709,F +coef_bike_atwork,-0.0722,T +coef_wlk_acc_atwork,-0.0722,F +coef_wlk_aux_atwork,-0.0722,T +coef_drvacc_pnr_atwork,0.0,T +coef_drvacc_knr_atwork,0.0,F +coef_iwait_atwork,-0.1,F +coef_xwait_atwork,-0.1,T +coef_xfers_wlktrn_atwork,0.0,T +coef_xfers_pnr_atwork,0.0,T +coef_xfers_knr_atwork,0.0,T +walk_transit_CBD_ASC_atwork,0.58,F +drive_transit_CBD_ASC_atwork,0.0,T +coef_density_walk_atwork,0.0437,F +coef_density_bike_atwork,0.0,T +coef_density_wlktrn_atwork,0.0,T +coef_distpen_drvtrn_atwork,0.0,T +coef_drvratio_knr_atwork,0.0,T +coef_drvratio_pnr_atwork,0.0,T +coef_age010_wlktrn_atwork,0.0,T +coef_age1619_da_atwork,0.0,T +coef_age16p_sr_atwork,0.0,T +coef_hhsize1_sr_atwork,0.0,T +coef_hhsize2_sr_atwork,0.0,T +coef_topology_bike_atwork,0.0,T +coef_topology_knr_atwork,0.0,T +coef_topology_pnr_atwork,0.0,T +coef_topology_walk_atwork,0.0,T +coef_topology_wlktrn_atwork,0.0,T +walk_MR_ASC_atwork,1.99,F +walk_BM_ASC_atwork,-14.3,F +walk_CR_ASC_atwork,-2.63,F +PNR_MR_ASC_atwork,-999.0,T +PNR_BM_ASC_atwork,-999.0,T +PNR_CR_ASC_atwork,-999.0,T +KNR_MR_ASC_atwork,-999.0,T +KNR_BM_ASC_atwork,-999.0,T +KNR_CR_ASC_atwork,-999.0,T +coef_nest_AUTO,0.72,F +coef_nest_AUTO_DRIVEALONE,0.35,F +coef_nest_AUTO_SHAREDRIDE2,0.35,F +coef_nest_AUTO_SHAREDRIDE3,0.35,F +coef_nest_NONMOTORIZED,0.72,F +coef_nest_RIDEHAIL,0.36,F +coef_nest_root,1.0,T +coef_nest_SCHOOL_BUS,0.72,F +coef_nest_TRANSIT,0.72,F +coef_nest_TRANSIT_KNRACCESS,0.5,F +coef_nest_TRANSIT_PNRACCESS,0.5,F +coef_nest_TRANSIT_WALKACCESS,0.5,F +bike_ASC_auto_deficient_discretionary,-2.314622563152318,F +bike_ASC_auto_sufficient_discretionary,-3.16592714693174,F +bike_ASC_no_auto_discretionary,1.8206473922492574,F +joint_bike_ASC_auto_deficient_discretionary,-6.684326329341298,F +joint_bike_ASC_auto_sufficient_discretionary,-4.501341297960985,F +joint_bike_ASC_no_auto_discretionary,-8.32,F +joint_knr_transit_ASC_auto_deficient_discretionary,-18.9,F +joint_knr_transit_ASC_auto_sufficient_discretionary,-9.8,F +joint_knr_transit_ASC_no_auto_discretionary,-5.28,F +joint_pnr_transit_ASC_auto_deficient_discretionary,-8.392032157640141,F +joint_pnr_transit_ASC_auto_sufficient_discretionary,-15.7,F +joint_pnr_transit_ASC_no_auto_discretionary,0.0,F +joint_sr2_ASC_auto_deficient_discretionary,4.47397710397656,F +joint_sr2_ASC_auto_sufficient_discretionary,0.596089371356585,F +joint_sr2_ASC_no_auto_discretionary,-0.3348269658286712,F +joint_sr3p_ASC_auto_deficient_discretionary,-8.759597659763918,F +joint_sr3p_ASC_auto_sufficient_discretionary,-2.1453451696139387,F +joint_sr3p_ASC_no_auto_discretionary,25.531137193393857,F +joint_taxi_ASC_auto_deficient_discretionary,-5.899240823980289,F +joint_taxi_ASC_auto_sufficient_discretionary,-4.418718421723628,F +joint_taxi_ASC_no_auto_discretionary,-4.2064399470153795,F +joint_tnc_shared_ASC_auto_deficient_discretionary,-6.479240823980289,F +joint_tnc_shared_ASC_auto_sufficient_discretionary,-4.418718421723628,F +joint_tnc_shared_ASC_no_auto_discretionary,-4.936439947015377,F +joint_tnc_single_ASC_auto_deficient_discretionary,-7.879240823980287,F +joint_tnc_single_ASC_auto_sufficient_discretionary,-4.418718421723628,F +joint_tnc_single_ASC_no_auto_discretionary,-5.126439947015377,F +joint_walk_ASC_auto_deficient_discretionary,-2.6423977462101016,F +joint_walk_ASC_auto_sufficient_discretionary,0.27930973040681684,F +joint_walk_ASC_no_auto_discretionary,29.06807239954025,F +joint_walk_transit_ASC_auto_deficient_discretionary,-7.489016223032866,F +joint_walk_transit_ASC_auto_sufficient_discretionary,-3.5462229327295973,F +joint_walk_transit_ASC_no_auto_discretionary,27.13232401017065,F +knr_transit_ASC_auto_deficient_discretionary,-19.0,F +knr_transit_ASC_auto_sufficient_discretionary,-2.36489842946777,F +knr_transit_ASC_no_auto_discretionary,2.4500588375695913,F +pnr_transit_ASC_auto_deficient_discretionary,-18.3,F +pnr_transit_ASC_auto_sufficient_discretionary,-3.033477671851898,F +pnr_transit_ASC_no_auto_discretionary,0.0,F +schoolbus_ASC_not_school,-999.0,F +sr2_ASC_auto_deficient_discretionary,-0.9806021413713831,F +sr2_ASC_auto_sufficient_discretionary,-1.5358224919444443,F +sr2_ASC_no_auto_discretionary,1.7032603135320528,F +sr3p_ASC_auto_deficient_discretionary,-1.515123236684089,F +sr3p_ASC_auto_sufficient_discretionary,-1.6169797400620591,F +sr3p_ASC_no_auto_discretionary,1.4029597077211255,F +taxi_ASC_auto_deficient_discretionary,-1.8061232402875835,F +taxi_ASC_auto_sufficient_discretionary,-2.7196310783821733,F +taxi_ASC_no_auto_discretionary,3.366136911788236,F +tnc_shared_ASC_auto_deficient_discretionary,-2.066123240287584,F +tnc_shared_ASC_auto_sufficient_discretionary,-4.289631078382175,F +tnc_shared_ASC_no_auto_discretionary,1.7761369117882366,F +tnc_single_ASC_auto_deficient_discretionary,-0.8861232402875836,F +tnc_single_ASC_auto_sufficient_discretionary,-2.6396310783821733,F +tnc_single_ASC_no_auto_discretionary,3.696136911788236,F +walk_ASC_auto_deficient_discretionary,1.2396747160555504,F +walk_ASC_auto_sufficient_discretionary,0.14620669993715266,F +walk_ASC_no_auto_discretionary,5.430660236876429,F +walk_transit_ASC_auto_deficient_discretionary,0.09537642212091921,F +walk_transit_ASC_auto_sufficient_discretionary,-1.8612136472259984,F +walk_transit_ASC_no_auto_discretionary,5.16027718326133,F +bike_ASC_auto_deficient_maintenance,-3.377536003532798,F +bike_ASC_auto_sufficient_maintenance,-3.776552123413538,F +bike_ASC_no_auto_maintenance,2.487381459660064,F +joint_bike_ASC_auto_deficient_maintenance,-49.41432632934129,F +joint_bike_ASC_auto_sufficient_maintenance,-4.671341297960987,F +joint_bike_ASC_no_auto_maintenance,-10.6,F +joint_knr_transit_ASC_auto_deficient_maintenance,-18.9,F +joint_knr_transit_ASC_auto_sufficient_maintenance,-11.7,F +joint_knr_transit_ASC_no_auto_maintenance,-33.4,F +joint_pnr_transit_ASC_auto_deficient_maintenance,-27.492032157640157,F +joint_pnr_transit_ASC_auto_sufficient_maintenance,-14.399999999999999,F +joint_pnr_transit_ASC_no_auto_maintenance,0.0,F +joint_sr2_ASC_auto_deficient_maintenance,4.47397710397656,F +joint_sr2_ASC_auto_sufficient_maintenance,0.596089371356585,F +joint_sr2_ASC_no_auto_maintenance,-0.3348269658286712,F +joint_sr3p_ASC_auto_deficient_maintenance,-11.899597659763911,F +joint_sr3p_ASC_auto_sufficient_maintenance,-2.6353451696139376,F +joint_sr3p_ASC_no_auto_maintenance,0.7511371933938734,F +joint_taxi_ASC_auto_deficient_maintenance,-22.909240823980294,F +joint_taxi_ASC_auto_sufficient_maintenance,-4.418718421723628,F +joint_taxi_ASC_no_auto_maintenance,1.4535600529846209,F +joint_tnc_shared_ASC_auto_deficient_maintenance,-20.409240823980284,F +joint_tnc_shared_ASC_auto_sufficient_maintenance,-4.418718421723628,F +joint_tnc_shared_ASC_no_auto_maintenance,-22.046439947015372,F +joint_tnc_single_ASC_auto_deficient_maintenance,-20.30924082398029,F +joint_tnc_single_ASC_auto_sufficient_maintenance,-4.418718421723628,F +joint_tnc_single_ASC_no_auto_maintenance,-0.6764399470153786,F +joint_walk_ASC_auto_deficient_maintenance,-4.172397746210102,F +joint_walk_ASC_auto_sufficient_maintenance,-0.08069026959318316,F +joint_walk_ASC_no_auto_maintenance,5.248072399540233,F +joint_walk_transit_ASC_auto_deficient_maintenance,-22.809016223032856,F +joint_walk_transit_ASC_auto_sufficient_maintenance,-2.3262229327295967,F +joint_walk_transit_ASC_no_auto_maintenance,3.3623240101706475,F +knr_transit_ASC_auto_deficient_maintenance,-18.6,F +knr_transit_ASC_auto_sufficient_maintenance,-13.1,F +knr_transit_ASC_no_auto_maintenance,-15.7,F +pnr_transit_ASC_auto_deficient_maintenance,-15.600000000000001,F +pnr_transit_ASC_auto_sufficient_maintenance,-17.3,F +pnr_transit_ASC_no_auto_maintenance,0.0,F +sr2_ASC_auto_deficient_maintenance,-0.770836558232873,F +sr2_ASC_auto_sufficient_maintenance,-1.4126398075072164,F +sr2_ASC_no_auto_maintenance,2.8368705489342365,F +sr3p_ASC_auto_deficient_maintenance,-1.0418043251252822,F +sr3p_ASC_auto_sufficient_maintenance,-1.5096457960498852,F +sr3p_ASC_no_auto_maintenance,3.1958843831466086,F +taxi_ASC_auto_deficient_maintenance,-3.050813822837973,F +taxi_ASC_auto_sufficient_maintenance,-3.4535730013724333,F +taxi_ASC_no_auto_maintenance,4.779640150510731,F +tnc_shared_ASC_auto_deficient_maintenance,-3.960813822837972,F +tnc_shared_ASC_auto_sufficient_maintenance,-208.72357300137233,F +tnc_shared_ASC_no_auto_maintenance,1.3096401505107311,F +tnc_single_ASC_auto_deficient_maintenance,-3.6008138228379702,F +tnc_single_ASC_auto_sufficient_maintenance,-5.21357300137243,F +tnc_single_ASC_no_auto_maintenance,3.7896401505107287,F +walk_ASC_auto_deficient_maintenance,0.961103491281816,F +walk_ASC_auto_sufficient_maintenance,0.3086378353701181,F +walk_ASC_no_auto_maintenance,6.71332037504109,F +walk_transit_ASC_auto_deficient_maintenance,-0.9816456943716195,F +walk_transit_ASC_auto_sufficient_maintenance,-1.7154122348374308,F +walk_transit_ASC_no_auto_maintenance,6.493934015624426,F +bike_ASC_auto_deficient_school,-0.3587962142802607,F +bike_ASC_auto_sufficient_school,-2.2481434287968605,F +bike_ASC_no_auto_school,-6.61,F +joint_bike_ASC_auto_deficient_all,0.5839388785109728,F +joint_bike_ASC_auto_sufficient_all,2.2382650098327144,F +joint_bike_ASC_no_auto_all,0.0,F +joint_knr_transit_ASC_auto_deficient_all,28.0,F +joint_knr_transit_ASC_auto_sufficient_all,28.0,F +joint_knr_transit_ASC_no_auto_all,0.0,F +joint_pnr_transit_ASC_auto_deficient_all,14.307967842359856,F +joint_pnr_transit_ASC_auto_sufficient_all,28.0,F +joint_pnr_transit_ASC_no_auto_all,0.0,F +joint_sr2_ASC_auto_deficient_all,8.856717099261305,F +joint_sr2_ASC_auto_sufficient_all,1.866557830927722,F +joint_sr2_ASC_no_auto_all,-1.3136054748830173,F +joint_sr3p_ASC_auto_deficient_all,-12.744213154583111,F +joint_sr3p_ASC_auto_sufficient_all,1.1793670542694572,F +joint_sr3p_ASC_no_auto_all,7.188133036662488,F +joint_taxi_ASC_auto_deficient_all,-6.309240823980289,F +joint_taxi_ASC_auto_sufficient_all,-4.418718421723628,F +joint_taxi_ASC_no_auto_all,-2.946439947015379,F +joint_tnc_shared_ASC_auto_deficient_all,-6.309240823980289,F +joint_tnc_shared_ASC_auto_sufficient_all,-4.418718421723628,F +joint_tnc_shared_ASC_no_auto_all,-2.946439947015379,F +joint_tnc_single_ASC_auto_deficient_all,-6.309240823980289,F +joint_tnc_single_ASC_auto_sufficient_all,-4.418718421723628,F +joint_tnc_single_ASC_no_auto_all,-2.946439947015379,F +joint_walk_ASC_auto_deficient_all,-8.649695786770533,F +joint_walk_ASC_auto_sufficient_all,-0.846896869850848,F +joint_walk_ASC_no_auto_all,2.530309112287652,F +joint_walk_transit_ASC_auto_deficient_all,-22.25316841330574,F +joint_walk_transit_ASC_auto_sufficient_all,-9.232201799737867,F +joint_walk_transit_ASC_no_auto_all,-3.56379435293537,F +knr_transit_ASC_auto_deficient_school,-0.7771297774010263,F +knr_transit_ASC_auto_sufficient_school,-0.3479379885195866,F +knr_transit_ASC_no_auto_school,4.416351644923216,F +pnr_transit_ASC_auto_deficient_school,-17.6,F +pnr_transit_ASC_auto_sufficient_school,-3.0833071983095968,F +pnr_transit_ASC_no_auto_school,0.0,F +schoolbus_ASC_auto_deficient_school,1.4496683582704122,F +schoolbus_ASC_auto_sufficient_school,1.4373341048849948,F +schoolbus_ASC_no_auto_school,3.598171871862293,F +sr2_ASC_auto_deficient_school,1.1400834084843785,F +sr2_ASC_auto_sufficient_school,0.3723534041153868,F +sr2_ASC_no_auto_school,-4.82,F +sr3p_ASC_auto_deficient_school,1.3751525207907713,F +sr3p_ASC_auto_sufficient_school,0.807684697254822,F +sr3p_ASC_no_auto_school,0.5483992541943021,F +taxi_ASC_auto_deficient_school,-21.15823481107509,F +taxi_ASC_auto_sufficient_school,-2.4103716060177884,F +taxi_ASC_no_auto_school_univ,0.0,F +tnc_shared_ASC_auto_deficient_school,-20.25823481107509,F +tnc_shared_ASC_auto_sufficient_school,-20.760371606017802,F +tnc_shared_ASC_no_auto_school,0.8154516592775722,F +tnc_single_ASC_auto_deficient_school,-2.538234811075092,F +tnc_single_ASC_auto_sufficient_school,-3.3003716060177894,F +tnc_single_ASC_no_auto_school,0.8154516592775722,F +walk_ASC_auto_deficient_school,1.9700826773800473,F +walk_ASC_auto_sufficient_school,0.9069008474873451,F +walk_ASC_no_auto_school,4.44605462232996,F +walk_transit_ASC_auto_deficient_school,0.608197830087687,F +walk_transit_ASC_auto_sufficient_school,-0.5348068368653319,F +walk_transit_ASC_no_auto_school,4.555462342810206,F +bike_ASC_auto_deficient_univ,-2.983656896539415,F +bike_ASC_auto_sufficient_univ,-2.9847326070220013,F +bike_ASC_no_auto_univ,-0.25960529412546857,F +knr_transit_ASC_auto_deficient_univ,-2.027091996792729,F +knr_transit_ASC_auto_sufficient_univ,-3.5700988463934267,F +knr_transit_ASC_no_auto_univ,-6.0,F +pnr_transit_ASC_auto_deficient_univ,-0.624872727953999,F +pnr_transit_ASC_auto_sufficient_univ,-3.5367931821403795,F +pnr_transit_ASC_no_auto_univ,0.0,F +sr2_ASC_auto_deficient_univ,0.3770160010136651,F +sr2_ASC_auto_sufficient_univ,-0.09113888340291802,F +sr2_ASC_no_auto_univ,0.676637641704824,F +sr3p_ASC_auto_deficient_univ,-0.15358517526001764,F +sr3p_ASC_auto_sufficient_univ,-0.14430611838574922,F +sr3p_ASC_no_auto_univ,1.4803358638547641,F +taxi_ASC_auto_deficient_univ,-2.147566732660339,F +taxi_ASC_auto_sufficient_univ,-2.987735993361906,F +tnc_shared_ASC_auto_deficient_univ,-2.147566732660339,F +tnc_shared_ASC_auto_sufficient_univ,-2.987735993361906,F +tnc_shared_ASC_no_auto_univ,1.5140890468266357,F +tnc_single_ASC_auto_deficient_univ,-2.147566732660339,F +tnc_single_ASC_auto_sufficient_univ,-2.987735993361906,F +tnc_single_ASC_no_auto_univ,1.5140890468266357,F +walk_ASC_auto_deficient_univ,-1.179511441787613,F +walk_ASC_auto_sufficient_univ,-0.62287570112084,F +walk_ASC_no_auto_univ,2.339757435025446,F +walk_transit_ASC_auto_deficient_univ,-0.17454653043031698,F +walk_transit_ASC_auto_sufficient_univ,-0.9495168757760516,F +walk_transit_ASC_no_auto_univ,2.175197417493062,F +bike_ASC_auto_deficient_work,-0.3546072404991606,F +bike_ASC_auto_sufficient_work,-3.1638889609274634,F +bike_ASC_no_auto_work,2.7801931794592605,F +knr_transit_ASC_auto_deficient_work,-1.0765656262524248,F +knr_transit_ASC_auto_sufficient_work,-3.9684689024532487,F +knr_transit_ASC_no_auto_work,2.21305651338722,F +pnr_transit_ASC_auto_deficient_work,-0.09995602533313773,F +pnr_transit_ASC_auto_sufficient_work,-1.1852550721052821,F +pnr_transit_ASC_no_auto_work,0.0,F +sr2_ASC_auto_deficient_work,-0.27426164764014943,F +sr2_ASC_auto_sufficient_work,-0.4398130630584324,F +sr2_ASC_no_auto_work,0.6258725935957756,F +sr3p_ASC_auto_deficient_work,-0.9248068312058698,F +sr3p_ASC_auto_sufficient_work,-1.1074544445404517,F +sr3p_ASC_no_auto_work,0.9884803116660514,F +taxi_ASC_auto_deficient_work,-0.45047836938742336,F +taxi_ASC_auto_sufficient_work,-2.6947142945014066,F +taxi_ASC_no_auto_work,2.8060963105426344,F +tnc_shared_ASC_auto_deficient_work,-1.6704783693874226,F +tnc_shared_ASC_auto_sufficient_work,-4.384714294501407,F +tnc_shared_ASC_no_auto_work,1.8060963105426353,F +tnc_single_ASC_auto_deficient_work,-0.0904783693874232,F +tnc_single_ASC_auto_sufficient_work,-3.2747142945014067,F +tnc_single_ASC_no_auto_work,3.5060963105426355,F +walk_ASC_auto_deficient_work,2.740454435923793,F +walk_ASC_auto_sufficient_work,-0.026829625626013584,F +walk_ASC_no_auto_work,4.9093958356590734,F +walk_transit_ASC_auto_deficient_work,1.6265981598135546,F +walk_transit_ASC_auto_sufficient_work,-1.2277772965975742,F +walk_transit_ASC_no_auto_work,5.648304016804462,F +bike_ASC_auto_deficient_atwork,6.813220683803054,F +bike_ASC_auto_sufficient_atwork,-1.6328617899578455,F +bike_ASC_no_auto_atwork,-15.773940012738107,F +knr_transit_ASC_auto_deficient_atwork,-24.5,F +knr_transit_ASC_auto_sufficient_atwork,-2.19190489598871,F +knr_transit_ASC_no_auto_atwork,-48.7,F +pnr_transit_ASC_auto_deficient_atwork,-4.69,F +pnr_transit_ASC_auto_sufficient_atwork,-5.759358027052075,F +pnr_transit_ASC_no_auto_atwork,0.0,F +sr2_ASC_auto_deficient_atwork,-1.1422376987882268,F +sr2_ASC_auto_sufficient_atwork,-2.1215879415511036,F +sr2_ASC_no_auto_atwork,-18.166720634032373,F +sr3p_ASC_auto_deficient_atwork,-1.5999360630401558,F +sr3p_ASC_auto_sufficient_atwork,-2.6237767822576106,F +sr3p_ASC_no_auto_atwork,-18.663765831776058,F +taxi_ASC_auto_deficient_atwork,-0.929831757998666,F +taxi_ASC_auto_sufficient_atwork,-1.9249125548560715,F +taxi_ASC_no_auto_atwork,-16.96419195282012,F +tnc_shared_ASC_auto_deficient_atwork,-19.76983175799867,F +tnc_shared_ASC_auto_sufficient_atwork,-2.9449125548560713,F +tnc_shared_ASC_no_auto_atwork,-47.46419195282012,F +tnc_single_ASC_auto_deficient_atwork,-31.669831757998658,F +tnc_single_ASC_auto_sufficient_atwork,-3.034912554856072,F +tnc_single_ASC_no_auto_atwork,-16.46419195282012,F +walk_ASC_auto_deficient_atwork,2.6758140375284643,F +walk_ASC_auto_sufficient_atwork,0.2733957575113875,F +walk_ASC_no_auto_atwork,-11.143550534379164,F +walk_transit_ASC_auto_deficient_atwork,-0.8345491422957563,F +walk_transit_ASC_auto_sufficient_atwork,-3.6768955022907024,F +walk_transit_ASC_no_auto_atwork,-15.379013613731004,F +coef_density_knr_atwork,0.0,T +coef_density_knr_nonmandatory,0.0,T +coef_density_knr_school_univ,0.0,T +coef_density_knr_work,0.0,T +coef_density_pnr_atwork,0.0,T +coef_density_pnr_nonmandatory,0.0,T +coef_density_pnr_school_univ,0.0,T +coef_density_pnr_work,0.0,T diff --git a/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_coeffs_template.csv b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_coeffs_template.csv new file mode 100644 index 000000000..02b3d48bd --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_mode_choice_coeffs_template.csv @@ -0,0 +1,118 @@ +coefficient_name,eatout,escort,othdiscr,othmaint,school,shopping,social,univ,work,atwork +coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root,coef_nest_root +coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO,coef_nest_AUTO +coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE,coef_nest_AUTO_DRIVEALONE +coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2,coef_nest_AUTO_SHAREDRIDE2 +coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3,coef_nest_AUTO_SHAREDRIDE3 +coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED,coef_nest_NONMOTORIZED +coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT,coef_nest_TRANSIT +coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS,coef_nest_TRANSIT_WALKACCESS +coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS,coef_nest_TRANSIT_PNRACCESS +coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS,coef_nest_TRANSIT_KNRACCESS +coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS,coef_nest_SCHOOL_BUS +coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL,coef_nest_RIDEHAIL +coef_ivt,coef_ivt_nonmandatory,coef_ivt_nonmandatory,coef_ivt_nonmandatory,coef_ivt_nonmandatory,coef_ivt_school_univ,coef_ivt_nonmandatory,coef_ivt_nonmandatory,coef_ivt_school_univ,coef_ivt_work,coef_ivt_atwork +coef_cost,coef_cost_nonmandatory,coef_cost_nonmandatory,coef_cost_nonmandatory,coef_cost_nonmandatory,coef_cost_school_univ,coef_cost_nonmandatory,coef_cost_nonmandatory,coef_cost_school_univ,coef_cost_work,coef_cost_atwork +coef_walk,coef_walk_nonmandatory,coef_walk_nonmandatory,coef_walk_nonmandatory,coef_walk_nonmandatory,coef_walk_school_univ,coef_walk_nonmandatory,coef_walk_nonmandatory,coef_walk_school_univ,coef_walk_work,coef_walk_atwork +coef_wlk_acc,coef_wlk_acc_nonmandatory,coef_wlk_acc_nonmandatory,coef_wlk_acc_nonmandatory,coef_wlk_acc_nonmandatory,coef_wlk_acc_school_univ,coef_wlk_acc_nonmandatory,coef_wlk_acc_nonmandatory,coef_wlk_acc_school_univ,coef_wlk_acc_work,coef_wlk_acc_atwork +coef_wlk_aux,coef_wlk_aux_nonmandatory,coef_wlk_aux_nonmandatory,coef_wlk_aux_nonmandatory,coef_wlk_aux_nonmandatory,coef_wlk_aux_school_univ,coef_wlk_aux_nonmandatory,coef_wlk_aux_nonmandatory,coef_wlk_aux_school_univ,coef_wlk_aux_work,coef_wlk_aux_atwork +coef_bike,coef_bike_nonmandatory,coef_bike_nonmandatory,coef_bike_nonmandatory,coef_bike_nonmandatory,coef_bike_school_univ,coef_bike_nonmandatory,coef_bike_nonmandatory,coef_bike_school_univ,coef_bike_work,coef_bike_atwork +coef_iwait,coef_iwait_nonmandatory,coef_iwait_nonmandatory,coef_iwait_nonmandatory,coef_iwait_nonmandatory,coef_iwait_school_univ,coef_iwait_nonmandatory,coef_iwait_nonmandatory,coef_iwait_school_univ,coef_iwait_work,coef_iwait_atwork +coef_xwait,coef_xwait_nonmandatory,coef_xwait_nonmandatory,coef_xwait_nonmandatory,coef_xwait_nonmandatory,coef_xwait_school_univ,coef_xwait_nonmandatory,coef_xwait_nonmandatory,coef_xwait_school_univ,coef_xwait_work,coef_xwait_atwork +coef_xfers_wlktrn,coef_xfers_wlktrn_nonmandatory,coef_xfers_wlktrn_nonmandatory,coef_xfers_wlktrn_nonmandatory,coef_xfers_wlktrn_nonmandatory,coef_xfers_wlktrn_school_univ,coef_xfers_wlktrn_nonmandatory,coef_xfers_wlktrn_nonmandatory,coef_xfers_wlktrn_school_univ,coef_xfers_wlktrn_work,coef_xfers_wlktrn_atwork +coef_xfers_pnr,coef_xfers_pnr_nonmandatory,coef_xfers_pnr_nonmandatory,coef_xfers_pnr_nonmandatory,coef_xfers_pnr_nonmandatory,coef_xfers_pnr_school_univ,coef_xfers_pnr_nonmandatory,coef_xfers_pnr_nonmandatory,coef_xfers_pnr_school_univ,coef_xfers_pnr_work,coef_xfers_pnr_atwork +coef_xfers_knr,coef_xfers_knr_nonmandatory,coef_xfers_knr_nonmandatory,coef_xfers_knr_nonmandatory,coef_xfers_knr_nonmandatory,coef_xfers_knr_school_univ,coef_xfers_knr_nonmandatory,coef_xfers_knr_nonmandatory,coef_xfers_knr_school_univ,coef_xfers_knr_work,coef_xfers_knr_atwork +coef_drvacc_knr,coef_drvacc_knr_nonmandatory,coef_drvacc_knr_nonmandatory,coef_drvacc_knr_nonmandatory,coef_drvacc_knr_nonmandatory,coef_drvacc_knr_school_univ,coef_drvacc_knr_nonmandatory,coef_drvacc_knr_nonmandatory,coef_drvacc_knr_school_univ,coef_drvacc_knr_work,coef_drvacc_knr_atwork +coef_drvacc_pnr,coef_drvacc_pnr_nonmandatory,coef_drvacc_pnr_nonmandatory,coef_drvacc_pnr_nonmandatory,coef_drvacc_pnr_nonmandatory,coef_drvacc_pnr_school_univ,coef_drvacc_pnr_nonmandatory,coef_drvacc_pnr_nonmandatory,coef_drvacc_pnr_school_univ,coef_drvacc_pnr_work,coef_drvacc_pnr_atwork +coef_drvratio_pnr,coef_drvratio_pnr_nonmandatory,coef_drvratio_pnr_nonmandatory,coef_drvratio_pnr_nonmandatory,coef_drvratio_pnr_nonmandatory,coef_drvratio_pnr_school_univ,coef_drvratio_pnr_nonmandatory,coef_drvratio_pnr_nonmandatory,coef_drvratio_pnr_school_univ,coef_drvratio_pnr_work,coef_drvratio_pnr_atwork +coef_drvratio_knr,coef_drvratio_knr_nonmandatory,coef_drvratio_knr_nonmandatory,coef_drvratio_knr_nonmandatory,coef_drvratio_knr_nonmandatory,coef_drvratio_knr_school_univ,coef_drvratio_knr_nonmandatory,coef_drvratio_knr_nonmandatory,coef_drvratio_knr_school_univ,coef_drvratio_knr_work,coef_drvratio_knr_atwork +coef_distpen_drvtrn,coef_distpen_drvtrn_nonmandatory,coef_distpen_drvtrn_nonmandatory,coef_distpen_drvtrn_nonmandatory,coef_distpen_drvtrn_nonmandatory,coef_distpen_drvtrn_school_univ,coef_distpen_drvtrn_nonmandatory,coef_distpen_drvtrn_nonmandatory,coef_distpen_drvtrn_school_univ,coef_distpen_drvtrn_work,coef_distpen_drvtrn_atwork +coef_density_walk,coef_density_walk_nonmandatory,coef_density_walk_nonmandatory,coef_density_walk_nonmandatory,coef_density_walk_nonmandatory,coef_density_walk_school_univ,coef_density_walk_nonmandatory,coef_density_walk_nonmandatory,coef_density_walk_school_univ,coef_density_walk_work,coef_density_walk_atwork +coef_density_bike,coef_density_bike_nonmandatory,coef_density_bike_nonmandatory,coef_density_bike_nonmandatory,coef_density_bike_nonmandatory,coef_density_bike_school_univ,coef_density_bike_nonmandatory,coef_density_bike_nonmandatory,coef_density_bike_school_univ,coef_density_bike_work,coef_density_bike_atwork +coef_density_wlktrn,coef_density_wlktrn_nonmandatory,coef_density_wlktrn_nonmandatory,coef_density_wlktrn_nonmandatory,coef_density_wlktrn_nonmandatory,coef_density_wlktrn_school_univ,coef_density_wlktrn_nonmandatory,coef_density_wlktrn_nonmandatory,coef_density_wlktrn_school_univ,coef_density_wlktrn_work,coef_density_wlktrn_atwork +coef_density_pnr,coef_density_pnr_nonmandatory,coef_density_pnr_nonmandatory,coef_density_pnr_nonmandatory,coef_density_pnr_nonmandatory,coef_density_pnr_school_univ,coef_density_pnr_nonmandatory,coef_density_pnr_nonmandatory,coef_density_pnr_school_univ,coef_density_pnr_work,coef_density_pnr_atwork +coef_density_knr,coef_density_knr_nonmandatory,coef_density_knr_nonmandatory,coef_density_knr_nonmandatory,coef_density_knr_nonmandatory,coef_density_knr_school_univ,coef_density_knr_nonmandatory,coef_density_knr_nonmandatory,coef_density_knr_school_univ,coef_density_knr_work,coef_density_knr_atwork +coef_topology_walk,coef_topology_walk_nonmandatory,coef_topology_walk_nonmandatory,coef_topology_walk_nonmandatory,coef_topology_walk_nonmandatory,coef_topology_walk_school_univ,coef_topology_walk_nonmandatory,coef_topology_walk_nonmandatory,coef_topology_walk_school_univ,coef_topology_walk_work,coef_topology_walk_atwork +coef_topology_bike,coef_topology_bike_nonmandatory,coef_topology_bike_nonmandatory,coef_topology_bike_nonmandatory,coef_topology_bike_nonmandatory,coef_topology_bike_school_univ,coef_topology_bike_nonmandatory,coef_topology_bike_nonmandatory,coef_topology_bike_school_univ,coef_topology_bike_work,coef_topology_bike_atwork +coef_topology_wlktrn,coef_topology_wlktrn_nonmandatory,coef_topology_wlktrn_nonmandatory,coef_topology_wlktrn_nonmandatory,coef_topology_wlktrn_nonmandatory,coef_topology_wlktrn_school_univ,coef_topology_wlktrn_nonmandatory,coef_topology_wlktrn_nonmandatory,coef_topology_wlktrn_school_univ,coef_topology_wlktrn_work,coef_topology_wlktrn_atwork +coef_topology_pnr,coef_topology_pnr_nonmandatory,coef_topology_pnr_nonmandatory,coef_topology_pnr_nonmandatory,coef_topology_pnr_nonmandatory,coef_topology_pnr_school_univ,coef_topology_pnr_nonmandatory,coef_topology_pnr_nonmandatory,coef_topology_pnr_school_univ,coef_topology_pnr_work,coef_topology_pnr_atwork +coef_topology_knr,coef_topology_knr_nonmandatory,coef_topology_knr_nonmandatory,coef_topology_knr_nonmandatory,coef_topology_knr_nonmandatory,coef_topology_knr_school_univ,coef_topology_knr_nonmandatory,coef_topology_knr_nonmandatory,coef_topology_knr_school_univ,coef_topology_knr_work,coef_topology_knr_atwork +coef_age1619_da,coef_age1619_da_nonmandatory,coef_age1619_da_nonmandatory,coef_age1619_da_nonmandatory,coef_age1619_da_nonmandatory,coef_age1619_da_school_univ,coef_age1619_da_nonmandatory,coef_age1619_da_nonmandatory,coef_age1619_da_school_univ,coef_age1619_da_work,coef_age1619_da_atwork +coef_age010_wlktrn,coef_age010_wlktrn_nonmandatory,coef_age010_wlktrn_nonmandatory,coef_age010_wlktrn_nonmandatory,coef_age010_wlktrn_nonmandatory,coef_age010_wlktrn_school_univ,coef_age010_wlktrn_nonmandatory,coef_age010_wlktrn_nonmandatory,coef_age010_wlktrn_school_univ,coef_age010_wlktrn_work,coef_age010_wlktrn_atwork +coef_age16p_sr,coef_age16p_sr_nonmandatory,coef_age16p_sr_nonmandatory,coef_age16p_sr_nonmandatory,coef_age16p_sr_nonmandatory,coef_age16p_sr_school_univ,coef_age16p_sr_nonmandatory,coef_age16p_sr_nonmandatory,coef_age16p_sr_school_univ,coef_age16p_sr_work,coef_age16p_sr_atwork +coef_hhsize1_sr,coef_hhsize1_sr_nonmandatory,coef_hhsize1_sr_nonmandatory,coef_hhsize1_sr_nonmandatory,coef_hhsize1_sr_nonmandatory,coef_hhsize1_sr_school_univ,coef_hhsize1_sr_nonmandatory,coef_hhsize1_sr_nonmandatory,coef_hhsize1_sr_school_univ,coef_hhsize1_sr_work,coef_hhsize1_sr_atwork +coef_hhsize2_sr,coef_hhsize2_sr_nonmandatory,coef_hhsize2_sr_nonmandatory,coef_hhsize2_sr_nonmandatory,coef_hhsize2_sr_nonmandatory,coef_hhsize2_sr_school_univ,coef_hhsize2_sr_nonmandatory,coef_hhsize2_sr_nonmandatory,coef_hhsize2_sr_school_univ,coef_hhsize2_sr_work,coef_hhsize2_sr_atwork +walk_ASC_no_auto,walk_ASC_no_auto_discretionary,walk_ASC_no_auto_maintenance,walk_ASC_no_auto_discretionary,walk_ASC_no_auto_maintenance,walk_ASC_no_auto_school,walk_ASC_no_auto_maintenance,walk_ASC_no_auto_discretionary,walk_ASC_no_auto_univ,walk_ASC_no_auto_work,walk_ASC_no_auto_atwork +walk_ASC_auto_deficient,walk_ASC_auto_deficient_discretionary,walk_ASC_auto_deficient_maintenance,walk_ASC_auto_deficient_discretionary,walk_ASC_auto_deficient_maintenance,walk_ASC_auto_deficient_school,walk_ASC_auto_deficient_maintenance,walk_ASC_auto_deficient_discretionary,walk_ASC_auto_deficient_univ,walk_ASC_auto_deficient_work,walk_ASC_auto_deficient_atwork +walk_ASC_auto_sufficient,walk_ASC_auto_sufficient_discretionary,walk_ASC_auto_sufficient_maintenance,walk_ASC_auto_sufficient_discretionary,walk_ASC_auto_sufficient_maintenance,walk_ASC_auto_sufficient_school,walk_ASC_auto_sufficient_maintenance,walk_ASC_auto_sufficient_discretionary,walk_ASC_auto_sufficient_univ,walk_ASC_auto_sufficient_work,walk_ASC_auto_sufficient_atwork +bike_ASC_no_auto,bike_ASC_no_auto_discretionary,bike_ASC_no_auto_maintenance,bike_ASC_no_auto_discretionary,bike_ASC_no_auto_maintenance,bike_ASC_no_auto_school,bike_ASC_no_auto_maintenance,bike_ASC_no_auto_discretionary,bike_ASC_no_auto_univ,bike_ASC_no_auto_work,bike_ASC_no_auto_atwork +bike_ASC_auto_deficient,bike_ASC_auto_deficient_discretionary,bike_ASC_auto_deficient_maintenance,bike_ASC_auto_deficient_discretionary,bike_ASC_auto_deficient_maintenance,bike_ASC_auto_deficient_school,bike_ASC_auto_deficient_maintenance,bike_ASC_auto_deficient_discretionary,bike_ASC_auto_deficient_univ,bike_ASC_auto_deficient_work,bike_ASC_auto_deficient_atwork +bike_ASC_auto_sufficient,bike_ASC_auto_sufficient_discretionary,bike_ASC_auto_sufficient_maintenance,bike_ASC_auto_sufficient_discretionary,bike_ASC_auto_sufficient_maintenance,bike_ASC_auto_sufficient_school,bike_ASC_auto_sufficient_maintenance,bike_ASC_auto_sufficient_discretionary,bike_ASC_auto_sufficient_univ,bike_ASC_auto_sufficient_work,bike_ASC_auto_sufficient_atwork +sr2_ASC_no_auto,sr2_ASC_no_auto_discretionary,sr2_ASC_no_auto_maintenance,sr2_ASC_no_auto_discretionary,sr2_ASC_no_auto_maintenance,sr2_ASC_no_auto_school,sr2_ASC_no_auto_maintenance,sr2_ASC_no_auto_discretionary,sr2_ASC_no_auto_univ,sr2_ASC_no_auto_work,sr2_ASC_no_auto_atwork +sr2_ASC_auto_deficient,sr2_ASC_auto_deficient_discretionary,sr2_ASC_auto_deficient_maintenance,sr2_ASC_auto_deficient_discretionary,sr2_ASC_auto_deficient_maintenance,sr2_ASC_auto_deficient_school,sr2_ASC_auto_deficient_maintenance,sr2_ASC_auto_deficient_discretionary,sr2_ASC_auto_deficient_univ,sr2_ASC_auto_deficient_work,sr2_ASC_auto_deficient_atwork +sr2_ASC_auto_sufficient,sr2_ASC_auto_sufficient_discretionary,sr2_ASC_auto_sufficient_maintenance,sr2_ASC_auto_sufficient_discretionary,sr2_ASC_auto_sufficient_maintenance,sr2_ASC_auto_sufficient_school,sr2_ASC_auto_sufficient_maintenance,sr2_ASC_auto_sufficient_discretionary,sr2_ASC_auto_sufficient_univ,sr2_ASC_auto_sufficient_work,sr2_ASC_auto_sufficient_atwork +sr3p_ASC_no_auto,sr3p_ASC_no_auto_discretionary,sr3p_ASC_no_auto_maintenance,sr3p_ASC_no_auto_discretionary,sr3p_ASC_no_auto_maintenance,sr3p_ASC_no_auto_school,sr3p_ASC_no_auto_maintenance,sr3p_ASC_no_auto_discretionary,sr3p_ASC_no_auto_univ,sr3p_ASC_no_auto_work,sr3p_ASC_no_auto_atwork +sr3p_ASC_auto_deficient,sr3p_ASC_auto_deficient_discretionary,sr3p_ASC_auto_deficient_maintenance,sr3p_ASC_auto_deficient_discretionary,sr3p_ASC_auto_deficient_maintenance,sr3p_ASC_auto_deficient_school,sr3p_ASC_auto_deficient_maintenance,sr3p_ASC_auto_deficient_discretionary,sr3p_ASC_auto_deficient_univ,sr3p_ASC_auto_deficient_work,sr3p_ASC_auto_deficient_atwork +sr3p_ASC_auto_sufficient,sr3p_ASC_auto_sufficient_discretionary,sr3p_ASC_auto_sufficient_maintenance,sr3p_ASC_auto_sufficient_discretionary,sr3p_ASC_auto_sufficient_maintenance,sr3p_ASC_auto_sufficient_school,sr3p_ASC_auto_sufficient_maintenance,sr3p_ASC_auto_sufficient_discretionary,sr3p_ASC_auto_sufficient_univ,sr3p_ASC_auto_sufficient_work,sr3p_ASC_auto_sufficient_atwork +walk_transit_ASC_no_auto,walk_transit_ASC_no_auto_discretionary,walk_transit_ASC_no_auto_maintenance,walk_transit_ASC_no_auto_discretionary,walk_transit_ASC_no_auto_maintenance,walk_transit_ASC_no_auto_school,walk_transit_ASC_no_auto_maintenance,walk_transit_ASC_no_auto_discretionary,walk_transit_ASC_no_auto_univ,walk_transit_ASC_no_auto_work,walk_transit_ASC_no_auto_atwork +walk_transit_ASC_auto_deficient,walk_transit_ASC_auto_deficient_discretionary,walk_transit_ASC_auto_deficient_maintenance,walk_transit_ASC_auto_deficient_discretionary,walk_transit_ASC_auto_deficient_maintenance,walk_transit_ASC_auto_deficient_school,walk_transit_ASC_auto_deficient_maintenance,walk_transit_ASC_auto_deficient_discretionary,walk_transit_ASC_auto_deficient_univ,walk_transit_ASC_auto_deficient_work,walk_transit_ASC_auto_deficient_atwork +walk_transit_ASC_auto_sufficient,walk_transit_ASC_auto_sufficient_discretionary,walk_transit_ASC_auto_sufficient_maintenance,walk_transit_ASC_auto_sufficient_discretionary,walk_transit_ASC_auto_sufficient_maintenance,walk_transit_ASC_auto_sufficient_school,walk_transit_ASC_auto_sufficient_maintenance,walk_transit_ASC_auto_sufficient_discretionary,walk_transit_ASC_auto_sufficient_univ,walk_transit_ASC_auto_sufficient_work,walk_transit_ASC_auto_sufficient_atwork +pnr_transit_ASC_no_auto,pnr_transit_ASC_no_auto_discretionary,pnr_transit_ASC_no_auto_maintenance,pnr_transit_ASC_no_auto_discretionary,pnr_transit_ASC_no_auto_maintenance,pnr_transit_ASC_no_auto_school,pnr_transit_ASC_no_auto_maintenance,pnr_transit_ASC_no_auto_discretionary,pnr_transit_ASC_no_auto_univ,pnr_transit_ASC_no_auto_work,pnr_transit_ASC_no_auto_atwork +pnr_transit_ASC_auto_deficient,pnr_transit_ASC_auto_deficient_discretionary,pnr_transit_ASC_auto_deficient_maintenance,pnr_transit_ASC_auto_deficient_discretionary,pnr_transit_ASC_auto_deficient_maintenance,pnr_transit_ASC_auto_deficient_school,pnr_transit_ASC_auto_deficient_maintenance,pnr_transit_ASC_auto_deficient_discretionary,pnr_transit_ASC_auto_deficient_univ,pnr_transit_ASC_auto_deficient_work,pnr_transit_ASC_auto_deficient_atwork +pnr_transit_ASC_auto_sufficient,pnr_transit_ASC_auto_sufficient_discretionary,pnr_transit_ASC_auto_sufficient_maintenance,pnr_transit_ASC_auto_sufficient_discretionary,pnr_transit_ASC_auto_sufficient_maintenance,pnr_transit_ASC_auto_sufficient_school,pnr_transit_ASC_auto_sufficient_maintenance,pnr_transit_ASC_auto_sufficient_discretionary,pnr_transit_ASC_auto_sufficient_univ,pnr_transit_ASC_auto_sufficient_work,pnr_transit_ASC_auto_sufficient_atwork +knr_transit_ASC_no_auto,knr_transit_ASC_no_auto_discretionary,knr_transit_ASC_no_auto_maintenance,knr_transit_ASC_no_auto_discretionary,knr_transit_ASC_no_auto_maintenance,knr_transit_ASC_no_auto_school,knr_transit_ASC_no_auto_maintenance,knr_transit_ASC_no_auto_discretionary,knr_transit_ASC_no_auto_univ,knr_transit_ASC_no_auto_work,knr_transit_ASC_no_auto_atwork +knr_transit_ASC_auto_deficient,knr_transit_ASC_auto_deficient_discretionary,knr_transit_ASC_auto_deficient_maintenance,knr_transit_ASC_auto_deficient_discretionary,knr_transit_ASC_auto_deficient_maintenance,knr_transit_ASC_auto_deficient_school,knr_transit_ASC_auto_deficient_maintenance,knr_transit_ASC_auto_deficient_discretionary,knr_transit_ASC_auto_deficient_univ,knr_transit_ASC_auto_deficient_work,knr_transit_ASC_auto_deficient_atwork +knr_transit_ASC_auto_sufficient,knr_transit_ASC_auto_sufficient_discretionary,knr_transit_ASC_auto_sufficient_maintenance,knr_transit_ASC_auto_sufficient_discretionary,knr_transit_ASC_auto_sufficient_maintenance,knr_transit_ASC_auto_sufficient_school,knr_transit_ASC_auto_sufficient_maintenance,knr_transit_ASC_auto_sufficient_discretionary,knr_transit_ASC_auto_sufficient_univ,knr_transit_ASC_auto_sufficient_work,knr_transit_ASC_auto_sufficient_atwork +taxi_ASC_no_auto,taxi_ASC_no_auto_discretionary,taxi_ASC_no_auto_maintenance,taxi_ASC_no_auto_discretionary,taxi_ASC_no_auto_maintenance,taxi_ASC_no_auto_school_univ,taxi_ASC_no_auto_maintenance,taxi_ASC_no_auto_discretionary,taxi_ASC_no_auto_school_univ,taxi_ASC_no_auto_work,taxi_ASC_no_auto_atwork +taxi_ASC_auto_deficient,taxi_ASC_auto_deficient_discretionary,taxi_ASC_auto_deficient_maintenance,taxi_ASC_auto_deficient_discretionary,taxi_ASC_auto_deficient_maintenance,taxi_ASC_auto_deficient_school,taxi_ASC_auto_deficient_maintenance,taxi_ASC_auto_deficient_discretionary,taxi_ASC_auto_deficient_univ,taxi_ASC_auto_deficient_work,taxi_ASC_auto_deficient_atwork +taxi_ASC_auto_sufficient,taxi_ASC_auto_sufficient_discretionary,taxi_ASC_auto_sufficient_maintenance,taxi_ASC_auto_sufficient_discretionary,taxi_ASC_auto_sufficient_maintenance,taxi_ASC_auto_sufficient_school,taxi_ASC_auto_sufficient_maintenance,taxi_ASC_auto_sufficient_discretionary,taxi_ASC_auto_sufficient_univ,taxi_ASC_auto_sufficient_work,taxi_ASC_auto_sufficient_atwork +tnc_single_ASC_no_auto,tnc_single_ASC_no_auto_discretionary,tnc_single_ASC_no_auto_maintenance,tnc_single_ASC_no_auto_discretionary,tnc_single_ASC_no_auto_maintenance,tnc_single_ASC_no_auto_school,tnc_single_ASC_no_auto_maintenance,tnc_single_ASC_no_auto_discretionary,tnc_single_ASC_no_auto_univ,tnc_single_ASC_no_auto_work,tnc_single_ASC_no_auto_atwork +tnc_single_ASC_auto_deficient,tnc_single_ASC_auto_deficient_discretionary,tnc_single_ASC_auto_deficient_maintenance,tnc_single_ASC_auto_deficient_discretionary,tnc_single_ASC_auto_deficient_maintenance,tnc_single_ASC_auto_deficient_school,tnc_single_ASC_auto_deficient_maintenance,tnc_single_ASC_auto_deficient_discretionary,tnc_single_ASC_auto_deficient_univ,tnc_single_ASC_auto_deficient_work,tnc_single_ASC_auto_deficient_atwork +tnc_single_ASC_auto_sufficient,tnc_single_ASC_auto_sufficient_discretionary,tnc_single_ASC_auto_sufficient_maintenance,tnc_single_ASC_auto_sufficient_discretionary,tnc_single_ASC_auto_sufficient_maintenance,tnc_single_ASC_auto_sufficient_school,tnc_single_ASC_auto_sufficient_maintenance,tnc_single_ASC_auto_sufficient_discretionary,tnc_single_ASC_auto_sufficient_univ,tnc_single_ASC_auto_sufficient_work,tnc_single_ASC_auto_sufficient_atwork +tnc_shared_ASC_no_auto,tnc_shared_ASC_no_auto_discretionary,tnc_shared_ASC_no_auto_maintenance,tnc_shared_ASC_no_auto_discretionary,tnc_shared_ASC_no_auto_maintenance,tnc_shared_ASC_no_auto_school,tnc_shared_ASC_no_auto_maintenance,tnc_shared_ASC_no_auto_discretionary,tnc_shared_ASC_no_auto_univ,tnc_shared_ASC_no_auto_work,tnc_shared_ASC_no_auto_atwork +tnc_shared_ASC_auto_deficient,tnc_shared_ASC_auto_deficient_discretionary,tnc_shared_ASC_auto_deficient_maintenance,tnc_shared_ASC_auto_deficient_discretionary,tnc_shared_ASC_auto_deficient_maintenance,tnc_shared_ASC_auto_deficient_school,tnc_shared_ASC_auto_deficient_maintenance,tnc_shared_ASC_auto_deficient_discretionary,tnc_shared_ASC_auto_deficient_univ,tnc_shared_ASC_auto_deficient_work,tnc_shared_ASC_auto_deficient_atwork +tnc_shared_ASC_auto_sufficient,tnc_shared_ASC_auto_sufficient_discretionary,tnc_shared_ASC_auto_sufficient_maintenance,tnc_shared_ASC_auto_sufficient_discretionary,tnc_shared_ASC_auto_sufficient_maintenance,tnc_shared_ASC_auto_sufficient_school,tnc_shared_ASC_auto_sufficient_maintenance,tnc_shared_ASC_auto_sufficient_discretionary,tnc_shared_ASC_auto_sufficient_univ,tnc_shared_ASC_auto_sufficient_work,tnc_shared_ASC_auto_sufficient_atwork +joint_walk_ASC_no_auto,joint_walk_ASC_no_auto_discretionary,joint_walk_ASC_no_auto_maintenance,joint_walk_ASC_no_auto_discretionary,joint_walk_ASC_no_auto_maintenance,joint_walk_ASC_no_auto_all,joint_walk_ASC_no_auto_maintenance,joint_walk_ASC_no_auto_discretionary,joint_walk_ASC_no_auto_all,joint_walk_ASC_no_auto_all,joint_walk_ASC_no_auto_all +joint_walk_ASC_auto_deficient,joint_walk_ASC_auto_deficient_discretionary,joint_walk_ASC_auto_deficient_maintenance,joint_walk_ASC_auto_deficient_discretionary,joint_walk_ASC_auto_deficient_maintenance,joint_walk_ASC_auto_deficient_all,joint_walk_ASC_auto_deficient_maintenance,joint_walk_ASC_auto_deficient_discretionary,joint_walk_ASC_auto_deficient_all,joint_walk_ASC_auto_deficient_all,joint_walk_ASC_auto_deficient_all +joint_walk_ASC_auto_sufficient,joint_walk_ASC_auto_sufficient_discretionary,joint_walk_ASC_auto_sufficient_maintenance,joint_walk_ASC_auto_sufficient_discretionary,joint_walk_ASC_auto_sufficient_maintenance,joint_walk_ASC_auto_sufficient_all,joint_walk_ASC_auto_sufficient_maintenance,joint_walk_ASC_auto_sufficient_discretionary,joint_walk_ASC_auto_sufficient_all,joint_walk_ASC_auto_sufficient_all,joint_walk_ASC_auto_sufficient_all +joint_bike_ASC_no_auto,joint_bike_ASC_no_auto_discretionary,joint_bike_ASC_no_auto_maintenance,joint_bike_ASC_no_auto_discretionary,joint_bike_ASC_no_auto_maintenance,joint_bike_ASC_no_auto_all,joint_bike_ASC_no_auto_maintenance,joint_bike_ASC_no_auto_discretionary,joint_bike_ASC_no_auto_all,joint_bike_ASC_no_auto_all,joint_bike_ASC_no_auto_all +joint_bike_ASC_auto_deficient,joint_bike_ASC_auto_deficient_discretionary,joint_bike_ASC_auto_deficient_maintenance,joint_bike_ASC_auto_deficient_discretionary,joint_bike_ASC_auto_deficient_maintenance,joint_bike_ASC_auto_deficient_all,joint_bike_ASC_auto_deficient_maintenance,joint_bike_ASC_auto_deficient_discretionary,joint_bike_ASC_auto_deficient_all,joint_bike_ASC_auto_deficient_all,joint_bike_ASC_auto_deficient_all +joint_bike_ASC_auto_sufficient,joint_bike_ASC_auto_sufficient_discretionary,joint_bike_ASC_auto_sufficient_maintenance,joint_bike_ASC_auto_sufficient_discretionary,joint_bike_ASC_auto_sufficient_maintenance,joint_bike_ASC_auto_sufficient_all,joint_bike_ASC_auto_sufficient_maintenance,joint_bike_ASC_auto_sufficient_discretionary,joint_bike_ASC_auto_sufficient_all,joint_bike_ASC_auto_sufficient_all,joint_bike_ASC_auto_sufficient_all +joint_sr2_ASC_no_auto,joint_sr2_ASC_no_auto_discretionary,joint_sr2_ASC_no_auto_maintenance,joint_sr2_ASC_no_auto_discretionary,joint_sr2_ASC_no_auto_maintenance,joint_sr2_ASC_no_auto_all,joint_sr2_ASC_no_auto_maintenance,joint_sr2_ASC_no_auto_discretionary,joint_sr2_ASC_no_auto_all,joint_sr2_ASC_no_auto_all,joint_sr2_ASC_no_auto_all +joint_sr2_ASC_auto_deficient,joint_sr2_ASC_auto_deficient_discretionary,joint_sr2_ASC_auto_deficient_maintenance,joint_sr2_ASC_auto_deficient_discretionary,joint_sr2_ASC_auto_deficient_maintenance,joint_sr2_ASC_auto_deficient_all,joint_sr2_ASC_auto_deficient_maintenance,joint_sr2_ASC_auto_deficient_discretionary,joint_sr2_ASC_auto_deficient_all,joint_sr2_ASC_auto_deficient_all,joint_sr2_ASC_auto_deficient_all +joint_sr2_ASC_auto_sufficient,joint_sr2_ASC_auto_sufficient_discretionary,joint_sr2_ASC_auto_sufficient_maintenance,joint_sr2_ASC_auto_sufficient_discretionary,joint_sr2_ASC_auto_sufficient_maintenance,joint_sr2_ASC_auto_sufficient_all,joint_sr2_ASC_auto_sufficient_maintenance,joint_sr2_ASC_auto_sufficient_discretionary,joint_sr2_ASC_auto_sufficient_all,joint_sr2_ASC_auto_sufficient_all,joint_sr2_ASC_auto_sufficient_all +joint_sr3p_ASC_no_auto,joint_sr3p_ASC_no_auto_discretionary,joint_sr3p_ASC_no_auto_maintenance,joint_sr3p_ASC_no_auto_discretionary,joint_sr3p_ASC_no_auto_maintenance,joint_sr3p_ASC_no_auto_all,joint_sr3p_ASC_no_auto_maintenance,joint_sr3p_ASC_no_auto_discretionary,joint_sr3p_ASC_no_auto_all,joint_sr3p_ASC_no_auto_all,joint_sr3p_ASC_no_auto_all +joint_sr3p_ASC_auto_deficient,joint_sr3p_ASC_auto_deficient_discretionary,joint_sr3p_ASC_auto_deficient_maintenance,joint_sr3p_ASC_auto_deficient_discretionary,joint_sr3p_ASC_auto_deficient_maintenance,joint_sr3p_ASC_auto_deficient_all,joint_sr3p_ASC_auto_deficient_maintenance,joint_sr3p_ASC_auto_deficient_discretionary,joint_sr3p_ASC_auto_deficient_all,joint_sr3p_ASC_auto_deficient_all,joint_sr3p_ASC_auto_deficient_all +joint_sr3p_ASC_auto_sufficient,joint_sr3p_ASC_auto_sufficient_discretionary,joint_sr3p_ASC_auto_sufficient_maintenance,joint_sr3p_ASC_auto_sufficient_discretionary,joint_sr3p_ASC_auto_sufficient_maintenance,joint_sr3p_ASC_auto_sufficient_all,joint_sr3p_ASC_auto_sufficient_maintenance,joint_sr3p_ASC_auto_sufficient_discretionary,joint_sr3p_ASC_auto_sufficient_all,joint_sr3p_ASC_auto_sufficient_all,joint_sr3p_ASC_auto_sufficient_all +joint_walk_transit_ASC_no_auto,joint_walk_transit_ASC_no_auto_discretionary,joint_walk_transit_ASC_no_auto_maintenance,joint_walk_transit_ASC_no_auto_discretionary,joint_walk_transit_ASC_no_auto_maintenance,joint_walk_transit_ASC_no_auto_all,joint_walk_transit_ASC_no_auto_maintenance,joint_walk_transit_ASC_no_auto_discretionary,joint_walk_transit_ASC_no_auto_all,joint_walk_transit_ASC_no_auto_all,joint_walk_transit_ASC_no_auto_all +joint_walk_transit_ASC_auto_deficient,joint_walk_transit_ASC_auto_deficient_discretionary,joint_walk_transit_ASC_auto_deficient_maintenance,joint_walk_transit_ASC_auto_deficient_discretionary,joint_walk_transit_ASC_auto_deficient_maintenance,joint_walk_transit_ASC_auto_deficient_all,joint_walk_transit_ASC_auto_deficient_maintenance,joint_walk_transit_ASC_auto_deficient_discretionary,joint_walk_transit_ASC_auto_deficient_all,joint_walk_transit_ASC_auto_deficient_all,joint_walk_transit_ASC_auto_deficient_all +joint_walk_transit_ASC_auto_sufficient,joint_walk_transit_ASC_auto_sufficient_discretionary,joint_walk_transit_ASC_auto_sufficient_maintenance,joint_walk_transit_ASC_auto_sufficient_discretionary,joint_walk_transit_ASC_auto_sufficient_maintenance,joint_walk_transit_ASC_auto_sufficient_all,joint_walk_transit_ASC_auto_sufficient_maintenance,joint_walk_transit_ASC_auto_sufficient_discretionary,joint_walk_transit_ASC_auto_sufficient_all,joint_walk_transit_ASC_auto_sufficient_all,joint_walk_transit_ASC_auto_sufficient_all +joint_pnr_transit_ASC_no_auto,joint_pnr_transit_ASC_no_auto_discretionary,joint_pnr_transit_ASC_no_auto_maintenance,joint_pnr_transit_ASC_no_auto_discretionary,joint_pnr_transit_ASC_no_auto_maintenance,joint_pnr_transit_ASC_no_auto_all,joint_pnr_transit_ASC_no_auto_maintenance,joint_pnr_transit_ASC_no_auto_discretionary,joint_pnr_transit_ASC_no_auto_all,joint_pnr_transit_ASC_no_auto_all,joint_pnr_transit_ASC_no_auto_all +joint_pnr_transit_ASC_auto_deficient,joint_pnr_transit_ASC_auto_deficient_discretionary,joint_pnr_transit_ASC_auto_deficient_maintenance,joint_pnr_transit_ASC_auto_deficient_discretionary,joint_pnr_transit_ASC_auto_deficient_maintenance,joint_pnr_transit_ASC_auto_deficient_all,joint_pnr_transit_ASC_auto_deficient_maintenance,joint_pnr_transit_ASC_auto_deficient_discretionary,joint_pnr_transit_ASC_auto_deficient_all,joint_pnr_transit_ASC_auto_deficient_all,joint_pnr_transit_ASC_auto_deficient_all +joint_pnr_transit_ASC_auto_sufficient,joint_pnr_transit_ASC_auto_sufficient_discretionary,joint_pnr_transit_ASC_auto_sufficient_maintenance,joint_pnr_transit_ASC_auto_sufficient_discretionary,joint_pnr_transit_ASC_auto_sufficient_maintenance,joint_pnr_transit_ASC_auto_sufficient_all,joint_pnr_transit_ASC_auto_sufficient_maintenance,joint_pnr_transit_ASC_auto_sufficient_discretionary,joint_pnr_transit_ASC_auto_sufficient_all,joint_pnr_transit_ASC_auto_sufficient_all,joint_pnr_transit_ASC_auto_sufficient_all +joint_knr_transit_ASC_no_auto,joint_knr_transit_ASC_no_auto_discretionary,joint_knr_transit_ASC_no_auto_maintenance,joint_knr_transit_ASC_no_auto_discretionary,joint_knr_transit_ASC_no_auto_maintenance,joint_knr_transit_ASC_no_auto_all,joint_knr_transit_ASC_no_auto_maintenance,joint_knr_transit_ASC_no_auto_discretionary,joint_knr_transit_ASC_no_auto_all,joint_knr_transit_ASC_no_auto_all,joint_knr_transit_ASC_no_auto_all +joint_knr_transit_ASC_auto_deficient,joint_knr_transit_ASC_auto_deficient_discretionary,joint_knr_transit_ASC_auto_deficient_maintenance,joint_knr_transit_ASC_auto_deficient_discretionary,joint_knr_transit_ASC_auto_deficient_maintenance,joint_knr_transit_ASC_auto_deficient_all,joint_knr_transit_ASC_auto_deficient_maintenance,joint_knr_transit_ASC_auto_deficient_discretionary,joint_knr_transit_ASC_auto_deficient_all,joint_knr_transit_ASC_auto_deficient_all,joint_knr_transit_ASC_auto_deficient_all +joint_knr_transit_ASC_auto_sufficient,joint_knr_transit_ASC_auto_sufficient_discretionary,joint_knr_transit_ASC_auto_sufficient_maintenance,joint_knr_transit_ASC_auto_sufficient_discretionary,joint_knr_transit_ASC_auto_sufficient_maintenance,joint_knr_transit_ASC_auto_sufficient_all,joint_knr_transit_ASC_auto_sufficient_maintenance,joint_knr_transit_ASC_auto_sufficient_discretionary,joint_knr_transit_ASC_auto_sufficient_all,joint_knr_transit_ASC_auto_sufficient_all,joint_knr_transit_ASC_auto_sufficient_all +joint_taxi_ASC_no_auto,joint_taxi_ASC_no_auto_discretionary,joint_taxi_ASC_no_auto_maintenance,joint_taxi_ASC_no_auto_discretionary,joint_taxi_ASC_no_auto_maintenance,joint_taxi_ASC_no_auto_all,joint_taxi_ASC_no_auto_maintenance,joint_taxi_ASC_no_auto_discretionary,joint_taxi_ASC_no_auto_all,joint_taxi_ASC_no_auto_all,joint_taxi_ASC_no_auto_all +joint_taxi_ASC_auto_deficient,joint_taxi_ASC_auto_deficient_discretionary,joint_taxi_ASC_auto_deficient_maintenance,joint_taxi_ASC_auto_deficient_discretionary,joint_taxi_ASC_auto_deficient_maintenance,joint_taxi_ASC_auto_deficient_all,joint_taxi_ASC_auto_deficient_maintenance,joint_taxi_ASC_auto_deficient_discretionary,joint_taxi_ASC_auto_deficient_all,joint_taxi_ASC_auto_deficient_all,joint_taxi_ASC_auto_deficient_all +joint_taxi_ASC_auto_sufficient,joint_taxi_ASC_auto_sufficient_discretionary,joint_taxi_ASC_auto_sufficient_maintenance,joint_taxi_ASC_auto_sufficient_discretionary,joint_taxi_ASC_auto_sufficient_maintenance,joint_taxi_ASC_auto_sufficient_all,joint_taxi_ASC_auto_sufficient_maintenance,joint_taxi_ASC_auto_sufficient_discretionary,joint_taxi_ASC_auto_sufficient_all,joint_taxi_ASC_auto_sufficient_all,joint_taxi_ASC_auto_sufficient_all +joint_tnc_single_ASC_no_auto,joint_tnc_single_ASC_no_auto_discretionary,joint_tnc_single_ASC_no_auto_maintenance,joint_tnc_single_ASC_no_auto_discretionary,joint_tnc_single_ASC_no_auto_maintenance,joint_tnc_single_ASC_no_auto_all,joint_tnc_single_ASC_no_auto_maintenance,joint_tnc_single_ASC_no_auto_discretionary,joint_tnc_single_ASC_no_auto_all,joint_tnc_single_ASC_no_auto_all,joint_tnc_single_ASC_no_auto_all +joint_tnc_single_ASC_auto_deficient,joint_tnc_single_ASC_auto_deficient_discretionary,joint_tnc_single_ASC_auto_deficient_maintenance,joint_tnc_single_ASC_auto_deficient_discretionary,joint_tnc_single_ASC_auto_deficient_maintenance,joint_tnc_single_ASC_auto_deficient_all,joint_tnc_single_ASC_auto_deficient_maintenance,joint_tnc_single_ASC_auto_deficient_discretionary,joint_tnc_single_ASC_auto_deficient_all,joint_tnc_single_ASC_auto_deficient_all,joint_tnc_single_ASC_auto_deficient_all +joint_tnc_single_ASC_auto_sufficient,joint_tnc_single_ASC_auto_sufficient_discretionary,joint_tnc_single_ASC_auto_sufficient_maintenance,joint_tnc_single_ASC_auto_sufficient_discretionary,joint_tnc_single_ASC_auto_sufficient_maintenance,joint_tnc_single_ASC_auto_sufficient_all,joint_tnc_single_ASC_auto_sufficient_maintenance,joint_tnc_single_ASC_auto_sufficient_discretionary,joint_tnc_single_ASC_auto_sufficient_all,joint_tnc_single_ASC_auto_sufficient_all,joint_tnc_single_ASC_auto_sufficient_all +joint_tnc_shared_ASC_no_auto,joint_tnc_shared_ASC_no_auto_discretionary,joint_tnc_shared_ASC_no_auto_maintenance,joint_tnc_shared_ASC_no_auto_discretionary,joint_tnc_shared_ASC_no_auto_maintenance,joint_tnc_shared_ASC_no_auto_all,joint_tnc_shared_ASC_no_auto_maintenance,joint_tnc_shared_ASC_no_auto_discretionary,joint_tnc_shared_ASC_no_auto_all,joint_tnc_shared_ASC_no_auto_all,joint_tnc_shared_ASC_no_auto_all +joint_tnc_shared_ASC_auto_deficient,joint_tnc_shared_ASC_auto_deficient_discretionary,joint_tnc_shared_ASC_auto_deficient_maintenance,joint_tnc_shared_ASC_auto_deficient_discretionary,joint_tnc_shared_ASC_auto_deficient_maintenance,joint_tnc_shared_ASC_auto_deficient_all,joint_tnc_shared_ASC_auto_deficient_maintenance,joint_tnc_shared_ASC_auto_deficient_discretionary,joint_tnc_shared_ASC_auto_deficient_all,joint_tnc_shared_ASC_auto_deficient_all,joint_tnc_shared_ASC_auto_deficient_all +joint_tnc_shared_ASC_auto_sufficient,joint_tnc_shared_ASC_auto_sufficient_discretionary,joint_tnc_shared_ASC_auto_sufficient_maintenance,joint_tnc_shared_ASC_auto_sufficient_discretionary,joint_tnc_shared_ASC_auto_sufficient_maintenance,joint_tnc_shared_ASC_auto_sufficient_all,joint_tnc_shared_ASC_auto_sufficient_maintenance,joint_tnc_shared_ASC_auto_sufficient_discretionary,joint_tnc_shared_ASC_auto_sufficient_all,joint_tnc_shared_ASC_auto_sufficient_all,joint_tnc_shared_ASC_auto_sufficient_all +walk_transit_CBD_ASC,walk_transit_CBD_ASC_nonmandatory,walk_transit_CBD_ASC_nonmandatory,walk_transit_CBD_ASC_nonmandatory,walk_transit_CBD_ASC_nonmandatory,walk_transit_CBD_ASC_school_univ,walk_transit_CBD_ASC_nonmandatory,walk_transit_CBD_ASC_nonmandatory,walk_transit_CBD_ASC_school_univ,walk_transit_CBD_ASC_work,walk_transit_CBD_ASC_atwork +drive_transit_CBD_ASC,drive_transit_CBD_ASC_nonmandatory,drive_transit_CBD_ASC_nonmandatory,drive_transit_CBD_ASC_nonmandatory,drive_transit_CBD_ASC_nonmandatory,drive_transit_CBD_ASC_school_univ,drive_transit_CBD_ASC_nonmandatory,drive_transit_CBD_ASC_nonmandatory,drive_transit_CBD_ASC_school_univ,drive_transit_CBD_ASC_work,drive_transit_CBD_ASC_atwork +schoolbus_ASC_no_auto,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_no_auto_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school +schoolbus_ASC_auto_deficient,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_auto_deficient_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school +schoolbus_ASC_auto_sufficient,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_auto_sufficient_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school,schoolbus_ASC_not_school +walk_BM_ASC,walk_BM_ASC_nonmandatory,walk_BM_ASC_nonmandatory,walk_BM_ASC_nonmandatory,walk_BM_ASC_nonmandatory,walk_BM_ASC_school_univ,walk_BM_ASC_nonmandatory,walk_BM_ASC_nonmandatory,walk_BM_ASC_school_univ,walk_BM_ASC_work,walk_BM_ASC_atwork +walk_MR_ASC,walk_MR_ASC_nonmandatory,walk_MR_ASC_nonmandatory,walk_MR_ASC_nonmandatory,walk_MR_ASC_nonmandatory,walk_MR_ASC_school_univ,walk_MR_ASC_nonmandatory,walk_MR_ASC_nonmandatory,walk_MR_ASC_school_univ,walk_MR_ASC_work,walk_MR_ASC_atwork +walk_CR_ASC,walk_CR_ASC_nonmandatory,walk_CR_ASC_nonmandatory,walk_CR_ASC_nonmandatory,walk_CR_ASC_nonmandatory,walk_CR_ASC_school_univ,walk_CR_ASC_nonmandatory,walk_CR_ASC_nonmandatory,walk_CR_ASC_school_univ,walk_CR_ASC_work,walk_CR_ASC_atwork +PNR_BM_ASC,PNR_BM_ASC_nonmandatory,PNR_BM_ASC_nonmandatory,PNR_BM_ASC_nonmandatory,PNR_BM_ASC_nonmandatory,PNR_BM_ASC_school_univ,PNR_BM_ASC_nonmandatory,PNR_BM_ASC_nonmandatory,PNR_BM_ASC_school_univ,PNR_BM_ASC_work,PNR_BM_ASC_atwork +PNR_MR_ASC,PNR_MR_ASC_nonmandatory,PNR_MR_ASC_nonmandatory,PNR_MR_ASC_nonmandatory,PNR_MR_ASC_nonmandatory,PNR_MR_ASC_school_univ,PNR_MR_ASC_nonmandatory,PNR_MR_ASC_nonmandatory,PNR_MR_ASC_school_univ,PNR_MR_ASC_work,PNR_MR_ASC_atwork +PNR_CR_ASC,PNR_CR_ASC_nonmandatory,PNR_CR_ASC_nonmandatory,PNR_CR_ASC_nonmandatory,PNR_CR_ASC_nonmandatory,PNR_CR_ASC_school_univ,PNR_CR_ASC_nonmandatory,PNR_CR_ASC_nonmandatory,PNR_CR_ASC_school_univ,PNR_CR_ASC_work,PNR_CR_ASC_atwork +KNR_BM_ASC,KNR_BM_ASC_nonmandatory,KNR_BM_ASC_nonmandatory,KNR_BM_ASC_nonmandatory,KNR_BM_ASC_nonmandatory,KNR_BM_ASC_school_univ,KNR_BM_ASC_nonmandatory,KNR_BM_ASC_nonmandatory,KNR_BM_ASC_school_univ,KNR_BM_ASC_work,KNR_BM_ASC_atwork +KNR_MR_ASC,KNR_MR_ASC_nonmandatory,KNR_MR_ASC_nonmandatory,KNR_MR_ASC_nonmandatory,KNR_MR_ASC_nonmandatory,KNR_MR_ASC_school_univ,KNR_MR_ASC_nonmandatory,KNR_MR_ASC_nonmandatory,KNR_MR_ASC_school_univ,KNR_MR_ASC_work,KNR_MR_ASC_atwork +KNR_CR_ASC,KNR_CR_ASC_nonmandatory,KNR_CR_ASC_nonmandatory,KNR_CR_ASC_nonmandatory,KNR_CR_ASC_nonmandatory,KNR_CR_ASC_school_univ,KNR_CR_ASC_nonmandatory,KNR_CR_ASC_nonmandatory,KNR_CR_ASC_school_univ,KNR_CR_ASC_work,KNR_CR_ASC_atwork diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork.csv new file mode 100644 index 000000000..93d8fc472 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork.csv @@ -0,0 +1,50 @@ +Label,Description,Expression,Coefficient +util_Female_Departure_after_1230_pm_Linear,Female - Departure after 12:30 pm - Linear,"@np.where(((df.female) & (df.start>19)), (np.where((df.start<= 19), np.minimum(19 - df.start, 48), 0) + np.where((df.start > 19), np.minimum(df.start - 19, 48), 0)), 0)",coef_Female_Departure_after_1230_pm_Linear +util_Parttime_worker_Departure_after_1230_pm__Linear,Part-time worker - Departure after 12:30 pm - Linear,"@np.where(((df.ptype == 2) & (df.start>19)), (np.where((df.start<= 19), np.minimum(19 - df.start, 48), 0) + np.where((df.start > 19), np.minimum(df.start - 19, 48), 0)), 0)",coef_Parttime_worker_Departure_after_1230_pm__Linear +util_Parttime_worker_Duration_greater_than_0p5_hours_depart_and_arrive_in_the_same_period,Part-time worker - Duration greater than 0.5 hours (depart and arrive in the same period),"@np.where(((df.ptype == 2) & (df.duration>1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Parttime_worker_Duration_greater_than_0p5_hours_depart_and_arrive_in_the_same_period +util_Low_income_lt25000_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,Low income (<25000) - Duration less than 0.5 hours (depart and arrive in the same period),"@np.where(((df.is_income_less25K) & (df.duration<1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Low_income_lt25000_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period +util_Med_income_25k_to_60k_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,Med income (25k to 60k) - Duration less than 0.5 hours (depart and arrive in the same period),"@np.where(((df.is_income_25K_to_60K) & (df.duration<1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Med_income_25k_to_60k_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period +util_Med_income_25k_to_60k_Duration_greater_than_0p5_hours,Med income (25k to 60k) - Duration greater than 0.5 hours,"@np.where(((df.is_income_25K_to_60K) & (df.duration>1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Med_income_25k_to_60k_Duration_greater_than_0p5_hours +util_Medhigh_income_60k_to_120k_Duration_greater_than_0p5_hours,Med-high income (60k to 120k) - Duration greater than 0.5 hours,"@np.where(((df.is_income_60K_to_120K) & (df.duration>1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Medhigh_income_60k_to_120k_Duration_greater_than_0p5_hours +#util_Blue_collar_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,Blue collar - Duration less than 0.5 hours (depart and arrive in the same period),"@np.where(((df.work_segment == 5) & (df.duration<1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Blue_collar_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period +#util_Blue_collar_Duration_greater_than_0p5_hours,Blue collar - Duration greater than 0.5 hours,"@np.where(((df.work_segment == 5) & (df.duration>1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Blue_collar_Duration_greater_than_0p5_hours +#util_Health_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,Health - Duration less than 0.5 hours (depart and arrive in the same period),"@np.where(((df.work_segment == 3) & (df.duration<1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Health_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period +util_Distance_to_destination_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,Distance to destination - Duration less than 0.5 hours (depart and arrive in the same period),"@np.where((df.duration<1), ((np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0))) * df.od_distance, 0)",coef_Distance_to_destination_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period +util_Distance_to_destination_Duration_greater_than_0p5_hours,Distance to destination - Duration greater than 0.5 hours,"@np.where((df.duration>1), ((np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0))) * df.od_distance, 0)",coef_Distance_to_destination_Duration_greater_than_0p5_hours +util_Subtour_purpose_Business_Departure_before_1200_pm__Linear,Subtour purpose: Business - Departure before 12:00 pm - Linear,"@np.where(((df.tour_type == 'business') & (df.start<19)), (np.where((df.start<= 19), np.minimum(19 - df.start, 48), 0) + np.where((df.start > 19), np.minimum(df.start - 19, 48), 0)), 0)",coef_Subtour_purpose_Business_Departure_before_1200_pm__Linear +util_Subtour_purpose_Business_Departure_after_1230_pm_Linear,Subtour purpose: Business - Departure after 12:30 pm - Linear,"@np.where(((df.tour_type == 'business') & (df.start>19)), (np.where((df.start<= 19), np.minimum(19 - df.start, 48), 0) + np.where((df.start > 19), np.minimum(df.start - 19, 48), 0)), 0)",coef_Subtour_purpose_Business_Departure_after_1230_pm_Linear +util_Subtour_purpose_Business_Duration_greater_than_0p5_hours,Subtour purpose: Business - Duration greater than 0.5 hours,"@np.where(((df.tour_type == 'business') & (df.duration>1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Subtour_purpose_Business_Duration_greater_than_0p5_hours +util_Subtour_purpose_Eatout_Departure_before_1200_pm__Linear,Subtour purpose: Eat-out - Departure before 12:00 pm - Linear,"@np.where(((df.tour_type == 'eat') & (df.start<19)), (np.where((df.start<= 19), np.minimum(19 - df.start, 48), 0) + np.where((df.start > 19), np.minimum(df.start - 19, 48), 0)), 0)",coef_Subtour_purpose_Eatout_Departure_before_1200_pm__Linear +util_Subtour_purpose_Eatout_Departure_after_1230_pm_Linear,Subtour purpose: Eat-out - Departure after 12:30 pm - Linear,"@np.where(((df.tour_type == 'eat') & (df.start>19)), (np.where((df.start<= 19), np.minimum(19 - df.start, 48), 0) + np.where((df.start > 19), np.minimum(df.start - 19, 48), 0)), 0)",coef_Subtour_purpose_Eatout_Departure_after_1230_pm_Linear +util_Subtour_purpose_Eatout_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,Subtour purpose: Eat-out - Duration less than 0.5 hours (depart and arrive in the same period),"@np.where(((df.tour_type == 'eat') & (df.duration<1)), (np.where((df.duration <= 1), np.minimum(1 - df.duration, 47), 0) + np.where((df.duration > 1), np.minimum(df.duration - 1, 47), 0)), 0)",coef_Subtour_purpose_Eatout_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period +util__Departure_constants,# Departure constants,,coef__Departure_constants +util_Shift_for_every_30_minutes_before_1030_am_Linear,Shift for every 30 minutes before 10:30 am - Linear,"@np.where((df.start<16), (np.where((df.start< 16), np.minimum(16 - df.start, 9), 0) + np.where((df.start> 21), np.minimum(df.start - 21, 11), 0)), 0)",coef_Shift_for_every_30_minutes_before_1030_am_Linear +util_Before_1100_AM,Before 11:00 AM,@(df.start<17),coef_start_Before_1100_AM +util_1100_AM_1130_AM,11:00 AM - 11:30 AM,@(df.start==17),coef_start_1100_AM_1130_AM +util_1130_AM_1200_PM,11:30 AM - 12:00 PM,@(df.start==18),coef_start_1130_AM_1200_PM +util_1200_AM_1230_PM,12:00 AM - 12:30 PM,@(df.start==19),coef_start_1200_AM_1230_PM +util_1230_PM_0100_PM,12:30 PM - 01:00 PM,@(df.start==20),coef_start_1230_PM_0100_PM +util_After_0100_PM,After 01:00 PM,@(df.start>20),coef_start_After_0100_PM +util_Shift_for_every_30_minutes_after_130_pm_Square_Root,Shift for every 30 minutes after 1:30 pm - Square Root,"@np.where((df.start>21), ((np.where((df.start < 16), np.minimum(16 - df.start, 9), 0) + np.where((df.start > 21), np.minimum(df.start - 21, 11), 0))** 0.5), 0)",coef_Shift_for_every_30_minutes_after_130_pm_Square_Root +util__Arrival_constants,# Arrival constants,,coef__Arrival_constants +util_Shift_for_every_30_minutes_before_1130_am_Linear,Shift for every 30 minutes before 11:30 am - Linear,"@np.where((df.end<18), (np.where((df.end < 14), np.minimum(14 - df.end, 9), 0) + np.where((df.end > 24), np.minimum(df.end - 24, 10), 0)), 0)",coef_Shift_for_every_30_minutes_before_1130_am_Linear +util_Before_1200_PM,Before 12:00 PM,@(df.end<19),coef_end_Before_1200_PM +util_1200_AM_1230_PM,12:00 AM - 12:30 PM,@(df.end==19),coef_end_1200_AM_1230_PM +util_1230_PM_0100_PM,12:30 PM - 01:00 PM,@(df.end==20),coef_end_1230_PM_0100_PM +util_0100_PM_0130_PM,01:00 PM - 01:30 PM,@(df.end==21),coef_end_0100_PM_0130_PM +util_0130_PM_0200_PM,01:30 PM - 02:00 PM,@(df.end==22),coef_end_0130_PM_0200_PM +util_0200_PM_0230_PM,02:00 PM - 02:30 PM,@(df.end==23),coef_end_0200_PM_0230_PM +util_After_0230_PM,After 02:30 PM,@(df.end>23),coef_end_After_0230_PM +util_Shift_for_every_30_minutes_after_300_pm_Linear,Shift for every 30 minutes after 3:00 pm - Linear,"@np.where((df.end>24), (np.where((df.end < 14), np.minimum(14 - df.end, 9), 0) + np.where((df.end > 24), np.minimum(df.end - 24, 10), 0)), 0)",coef_Shift_for_every_30_minutes_after_300_pm_Linear +util__Duration_constants,# Duration constants,,coef__Duration_constants +util_0_hrs,0 hrs,@(df.duration==0),coef_0_hrs +util_0p5_hrs,0.5 hrs,@(df.duration==1),coef_0p5_hrs +util_1_hrs,1 hrs,@(df.duration==2),coef_1_hrs +util_1p5hrs,1.5hrs,@(df.duration==3),coef_1p5hrs +util_2_hrs,2 hrs,@(df.duration==4),coef_2_hrs +util_Longer_than_2_hrs,Longer than 2 hrs,@(df.duration>4),coef_Longer_than_2_hrs +util_Shift_for_every_30_minutes_more_than_2p5_hrs_Square_Root,Shift for every 30 minutes more than 2.5 hrs - Square Root,"@np.where((df.duration>5), ((np.where((df.duration < 0), np.minimum(0 - df.duration, 47), 0) + np.where((df.duration > 5), np.minimum(df.duration - 5, 13), 0)) ** 0.5), 0)",coef_Shift_for_every_30_minutes_more_than_2p5_hrs_Square_Root +util_Calibration_Constant_Departure_eq_18,Calibration Constant - Departure = 18,@(df.start==18),coef_Calibration_Constant_Departure_eq_18 +util_Calibration_Constant_Departure_eq_19,Calibration Constant - Departure = 19,@(df.start==19),coef_Calibration_Constant_Departure_eq_19 +util_Calibration_Constant_Arrival_eq_20,Calibration Constant - Arrival = 20,@(df.end==20),coef_Calibration_Constant_Arrival_eq_20 +util_Calibration_Constant_Arrival_eq_21,Calibration Constant - Arrival = 21,@(df.end==21),coef_Calibration_Constant_Arrival_eq_21 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork.yaml b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork.yaml new file mode 100644 index 000000000..f04f93b8e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork.yaml @@ -0,0 +1,16 @@ + +SPEC: tour_scheduling_atwork.csv +COEFFICIENTS: tour_scheduling_atwork_coeffs.csv + +preprocessor: + SPEC: tour_scheduling_atwork_preprocessor + DF: df +# TABLES: +# - land_use +# - tours + +SIMULATE_CHOOSER_COLUMNS: + - od_distance + +CONSTANTS: + time_cap: 30 \ No newline at end of file diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork_coeffs.csv new file mode 100644 index 000000000..0e7ab1acb --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork_coeffs.csv @@ -0,0 +1,47 @@ +coefficient_name,value,constrain +coef_Female_Departure_after_1230_pm_Linear,0.05574558,F +coef_Parttime_worker_Departure_after_1230_pm__Linear,0.129291333,F +coef_Parttime_worker_Duration_greater_than_0p5_hours_depart_and_arrive_in_the_same_period,0.162008704,F +coef_Low_income_lt25000_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,0.885322446,F +coef_Med_income_25k_to_60k_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,0.526935246,F +coef_Med_income_25k_to_60k_Duration_greater_than_0p5_hours,-0.081917021,F +coef_Medhigh_income_60k_to_120k_Duration_greater_than_0p5_hours,-0.068358924,F +coef_Blue_collar_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,1.191378628,F +coef_Blue_collar_Duration_greater_than_0p5_hours,0.123072852,F +coef_Health_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,0.791205377,F +coef_Distance_to_destination_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,-0.292363361,F +coef_Distance_to_destination_Duration_greater_than_0p5_hours,0.006885922,F +coef_Subtour_purpose_Business_Departure_before_1200_pm__Linear,0.268963895,F +coef_Subtour_purpose_Business_Departure_after_1230_pm_Linear,0.17631122,F +coef_Subtour_purpose_Business_Duration_greater_than_0p5_hours,0.362189199,F +coef_Subtour_purpose_Eatout_Departure_before_1200_pm__Linear,-0.250770206,F +coef_Subtour_purpose_Eatout_Departure_after_1230_pm_Linear,-0.169861029,F +coef_Subtour_purpose_Eatout_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,-0.678939929,F +coef_Shift_for_every_30_minutes_before_1030_am_Linear,-0.731880037,F +coef_start_Before_1100_AM,-2.176744062,F +coef_start_1100_AM_1130_AM,-1.190017952,F +coef_start_1130_AM_1200_PM,-0.198229872,F +coef_start_1200_AM_1230_PM,0,T +coef_start_1230_PM_0100_PM,-0.084950396,F +coef_start_After_0100_PM,-0.205562723,F +coef_Shift_for_every_30_minutes_after_130_pm_Square_Root,0.539088697,F +coef_Shift_for_every_30_minutes_before_1130_am_Linear,0.414546555,F +coef_end_Before_1200_PM,0.279351638,F +coef_end_1200_AM_1230_PM,-0.045281832,F +coef_end_1230_PM_0100_PM,0.214070736,F +coef_end_0100_PM_0130_PM,0,T +coef_end_0130_PM_0200_PM,-0.69742748,F +coef_end_0200_PM_0230_PM,-1.284283533,F +coef_end_After_0230_PM,-2.119733896,F +coef_Shift_for_every_30_minutes_after_300_pm_Linear,-0.508006414,F +coef_0_hrs,-0.969734874,F +coef_0p5_hrs,0,T +coef_1_hrs,0.177457256,F +coef_1p5hrs,-0.171124657,F +coef_2_hrs,-0.4678094,F +coef_Longer_than_2_hrs,-0.523935526,F +coef_Shift_for_every_30_minutes_more_than_2p5_hrs_Square_Root,-0.424301372,F +coef_Calibration_Constant_Departure_eq_18,-0.045958531,F +coef_Calibration_Constant_Departure_eq_19,-0.099009925,F +coef_Calibration_Constant_Arrival_eq_20,-0.0698094,F +coef_Calibration_Constant_Arrival_eq_21,-0.064355276,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork_preprocessor.csv new file mode 100644 index 000000000..26ac917ae --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_atwork_preprocessor.csv @@ -0,0 +1,3 @@ +Description,Target,Expression +#,, +local scalar distance skim,od_distance,"od_skims[('SOV_DIST', 'MD')]" diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_joint.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_joint.csv new file mode 100644 index 000000000..a9f0a5186 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_joint.csv @@ -0,0 +1,315 @@ +Label,Description,Expression,Coefficient +,,, +#ESCORT,#ESCORT,,ESCORT +util_escort_Mode_Choice_Logsum,ESCORT - Mode Choice Logsum,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort')), df.mode_choice_logsum, 0)",coef_escort_Mode_Choice_Logsum +util_escort_Distance_to_destination_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,ESCORT - Distance to destination - Duration less than 0.5 hours (depart and arrive in the same period),"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration<1)), ((df.origin_to_destination_distance) * (np.where((df.duration<=1), np.minimum(1-df.duration, 0), 0))),0)",coef_escort_Distance_to_destination_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period +util_escort_Distance_to_destination_Duration_greater_than_0p5_hours,ESCORT - Distance to destination - Duration greater than 0.5 hours,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration>1)), ((df.origin_to_destination_distance) * (np.where((df.duration>1), np.minimum(df.duration-1,47), 0))), 0)",coef_escort_Distance_to_destination_Duration_greater_than_0p5_hours +util_escort_Fulltime_worker_Departure_after_8_00_am_Linear,ESCORT - Full-time worker - Departure after 8:00 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 1) & (df.start>10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where((df.start>10), np.minimum(df.start-10,35), 0)),0)",coef_escort_Fulltime_worker_Departure_after_8_00_am_Linear +util_escort_Fulltime_worker_Departure_after_3_00_am_Linear,ESCORT - Full-time worker - Departure after 3:00 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 1) & (df.start>24)), (np.where((df.start<=24), np.minimum(24-df.start,3), 0) + np.where((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_Fulltime_worker_Departure_after_3_00_am_Linear +util_escort_Fulltime_worker_Duration_lt_0p5_hrs,ESCORT - Full-time worker - Duration < 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 1) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0)), 0)",coef_escort_Fulltime_worker_Duration_lt_0p5_hrs +util_escort_Fulltime_worker_Duration_gt_0p5_hrs,ESCORT - Full-time worker - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 1) & (df.duration>1)), (np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_Fulltime_worker_Duration_gt_0p5_hrs +util_escort_University_student_Duration_lt_0p5_hrs,ESCORT - University student - Duration < 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 3) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0)), 0)",coef_escort_University_student_Duration_lt_0p5_hrs +util_escort_Nondriving_age_student_Duration_gt_0p5_hrs,ESCORT - Non-driving age student - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & ((df.ptype == 7)|(df.ptype == 8)) & (df.duration>1)), (np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_Nondriving_age_student_Duration_gt_0p5_hrs +util_escort_Driving_age_student_Duration_lt_0p5_hrs,ESCORT - Driving age student - Duration < 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 6) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0)), 0)",coef_escort_Driving_age_student_Duration_lt_0p5_hrs +util_escort_Driving_age_student_Duration_gt_0p5_hrs,ESCORT - Driving age student - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 6) & (df.duration>1)), (np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_Driving_age_student_Duration_gt_0p5_hrs +util_escort_Preschool_kid_Duration_gt_0p5_hrs,ESCORT - Pre-school kid - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.ptype == 8) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0)), 0)",coef_escort_Preschool_kid_Duration_gt_0p5_hrs +util_escort_Medhigh_income_60k_to_120k_Duration_gt_0p5_hrs,ESCORT - Med-high income (60k to 120k) - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.is_income_60K_to_120K) & (df.duration>1)), (np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_Medhigh_income_60k_to_120k_Duration_gt_0p5_hrs +util_escort_Households_with_no_kids_Dummy_1_0_Departure_before_7_30_AM,"ESCORT - Households with no kids (Dummy- 1,0) - Departure before 7:30 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.start<10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Departure_before_7_30_AM +util_escort_Households_with_no_kids_Dummy_1_0_Departure_after_8_00_AM,"ESCORT - Households with no kids (Dummy- 1,0) - Departure after 8:00 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.start>10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Departure_after_8_00_AM +util_escort_Households_with_no_kids_Dummy_1_0_Departure_before_2_30_PM,"ESCORT - Households with no kids (Dummy- 1,0) - Departure before 2:30 PM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.start<24)), (np.where((df.start<=24), np.minimum(24-df.start,3), 0) + np.where((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Departure_before_2_30_PM +util_escort_Households_with_no_kids_Dummy_1_0_Departure_after_3_00_PM,"ESCORT - Households with no kids (Dummy- 1,0) - Departure after 3:00 PM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.start>24)), (np.where((df.start<=24), np.minimum(24-df.start,3), 0) + np.where ((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Departure_after_3_00_PM +util_escort_Households_with_no_kids_Dummy_1_0_Arrival_before_8_00_AM,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival before 8:00 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.end<11)), (np.where((df.end<=11), np.minimum(11-df.end,7), 0) + np.where((df.end>11), np.minimum(df.end-11,35), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_before_8_00_AM +util_escort_Households_with_no_kids_Dummy_1_0_Arrival_after_8_30_AM,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival after 8:30 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.end>11)), (np.where((df.end<=11), np.minimum(11-df.end,7), 0) + np.where((df.end>11), np.minimum(df.end-11,35), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_after_8_30_AM +util_escort_Households_with_no_kids_Dummy_1_0_Arrival_before_3_00_PM,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival before 3:00 PM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.end<25)), (np.where((df.end<=25), np.minimum(25-df.end,3), 0) + np.where((df.end>25), np.minimum(df.end-25,9), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_before_3_00_PM +util_escort_Households_with_no_kids_Dummy_1_0_Arrival_after_3_30_PM,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival after 3:30 PM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.num_children == 0) & (df.end>25)), (np.where((df.end<=25), np.minimum(25-df.end,3), 0) + np.where((df.end>25), np.minimum(df.end-25,9), 0)), 0)",coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_after_3_30_PM +util_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_8_00_AM,"ESCORT - Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Departure after 8:00 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.has_pre_school_child_with_mandatory > 0) & (df.start >10)), (np.where((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_8_00_AM +util_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_3_00_PM,"ESCORT - Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Departure after 3:00 PM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.has_pre_school_child_with_mandatory > 0) & (df.start>24)), (np.where((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_3_00_PM +util_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_before_8_00_AM,"ESCORT -Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival before 8:00 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.has_pre_school_child_with_mandatory > 0) & (df.end<11)), (np.where((df.end<=11), np.minimum(11-df.end,7), 0)), 0)",coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_before_8_00_AM +util_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_before_3_00_PM,"ESCORT - Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival before 3:00 PM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.has_pre_school_child_with_mandatory > 0) & (df.end<25)), (np.where((df.end<=25), np.minimum(25-df.end,3), 0)), 0)",coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_before_3_00_PM +util_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_8_00_AM,"ESCORT - Driving age School Child in HH with Mandatory tour (Dummy- 1,0) - Departure after 8:00 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.has_driving_age_child_with_mandatory > 0) & (df.start>10)), (np.where ((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_8_00_AM +util_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_after_8_30_AM,"ESCORT - Driving age School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival after 8:30 AM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.has_driving_age_child_with_mandatory > 0) & (df.end>11)), (np.where((df.end>11), np.minimum(df.end-11,35), 0)), 0)",coef_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_after_8_30_AM +util_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_after_3_30_PM,"ESCORT - Driving age School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival after 3:30 PM","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.has_driving_age_child_with_mandatory > 0) &( df.end>25)), (np.where((df.end>25), np.minimum(df.end-25,9), 0)), 0)",coef_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_after_3_30_PM +util_escort_Number_of_autos_greater_than_number_of_adults_Duration_gt_0p5_hrs,ESCORT - Number of autos greater than number of adults - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.auto_ownership > 0) & (df.auto_ownership > df.num_adults) & (df.duration>1)), (np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_Number_of_autos_greater_than_number_of_adults_Duration_gt_0p5_hrs +#FIXME_Number_of_nonescort_tours_is_not_known_until_the_nonmandatory_frequency_model_is_run,#FIXME - Number of non-escort tours is not known until the non-mandatory frequency model is run,,FIXME_Number_of_nonescort_tours_is_not_known_until_the_nonmandatory_frequency_model_is_run +#util_escort_Number_of_Individual_Tours_excluding_escorting_Duration_gt_0p5_hrs,#ESCORT - Number of Individual Tours (excluding escorting) - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type != 'escort') & (df.num_non_escort_tours > 0) & (df.duration>1)), (np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_Number_of_Individual_Tours_excluding_escorting_Duration_gt_0p5_hrs +util_escort_Number_of_joint_tours_Duration_gt_0p5_hrs,ESCORT - Number of joint tours - Duration > 0.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)) *(df.num_joint_tours), 0)",coef_escort_Number_of_joint_tours_Duration_gt_0p5_hrs +util_escort_Departure_Constant_Shift_for_every_30_minutes_before_06_30_am_Linear,ESCORT - Departure Constant: Shift for every 30 minutes before 06:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start<8)), (np.where((df.start<8), np.minimum(8-df.start,4), 0) + np.where((df.start>13), np.minimum(df.start-13,28), 0)), 0)",coef_escort_Departure_Constant_Shift_for_every_30_minutes_before_06_30_am_Linear +util_escort_Departure_Constant_Before_07_00_AM,ESCORT - Departure Constant: Before 07:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start<9)),coef_escort_Departure_Constant_Before_07_00_AM +util_escort_Departure_Constant_07_00_AM_07_30_AM,ESCORT - Departure Constant: 07:00 AM - 07:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==9)),coef_escort_Departure_Constant_07_00_AM_07_30_AM +util_escort_Departure_Constant_07_30_AM_08_00_AM,ESCORT - Departure Constant: 07:30 AM - 08:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==10)),coef_escort_Departure_Constant_07_30_AM_08_00_AM +util_escort_Departure_Constant_08_00_AM_08_30_AM,ESCORT - Departure Constant: 08:00 AM - 08:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==11)),coef_escort_Departure_Constant_08_00_AM_08_30_AM +util_escort_Departure_Constant_08_30_AM_09_00_AM,ESCORT - Departure Constant: 08:30 AM - 09:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==12)),coef_escort_Departure_Constant_08_30_AM_09_00_AM +util_escort_Departure_Constant_After_09_00_AM,ESCORT - Departure Constant: After 09:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start>12)),coef_escort_Departure_Constant_After_09_00_AM +util_escort_Departure_Constant_01_30_PM_02_00_PM,ESCORT - Departure Constant: 01:30 PM - 02:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==22)),coef_escort_Departure_Constant_01_30_PM_02_00_PM +util_escort_Departure_Constant_02_00_PM_02_30_PM,ESCORT - Departure Constant: 02:00 PM - 02:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==23)),coef_escort_Departure_Constant_02_00_PM_02_30_PM +util_escort_Departure_Constant_02_30_PM_03_00_PM,ESCORT - Departure Constant: 02:30 PM - 03:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==24)),coef_escort_Departure_Constant_02_30_PM_03_00_PM +util_escort_Departure_Constant_03_00_PM_03_30_PM,ESCORT - Departure Constant: 03:00 PM - 03:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==25)),coef_escort_Departure_Constant_03_00_PM_03_30_PM +util_escort_Departure_Constant_After_03_30_PM,ESCORT - Departure Constant: After 03:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start>25)),coef_escort_Departure_Constant_After_03_30_PM +util_escort_Departure_Constant_Shift_for_every_30_minutes_after_9_30_am_Linear,ESCORT - Departure Constant: Shift for every 30 minutes after 9:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start>13)), (np.where((df.start<8), np.minimum(8-df.start,4), 0) + (np.where((df.start>13), np.minimum(df.start-13,28), 0))), 0)",coef_escort_Departure_Constant_Shift_for_every_30_minutes_after_9_30_am_Linear +util_escort_Departure_Constant_Shift_for_every_30_minutes_after_4_00_pm_Linear,ESCORT - Departure Constant: Shift for every 30 minutes after 4:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start>26)), (np.where((df.start<0), np.minimum(0-df.start,48), 0) + np.where((df.start>26), np.minimum(df.start-26,15),0)), 0)",coef_escort_Departure_Constant_Shift_for_every_30_minutes_after_4_00_pm_Linear +util_escort_Arrival_Constant_Shift_for_every_30_minutes_before_6_30_am_Linear,ESCORT - Arrival Constant: Shift for every 30 minutes before 6:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end<8)), (np.where((df.end<8), np.minimum(8-df.end,2), 0) + np.where((df.end>13), np.minimum(df.end-13,30), 0)), 0)",coef_escort_Arrival_Constant_Shift_for_every_30_minutes_before_6_30_am_Linear +util_escort_Arrival_Constant_Before_07_00_AM,ESCORT - Arrival Constant: Before 07:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end<9)),coef_escort_Arrival_Constant_Before_07_00_AM +util_escort_Arrival_Constant_07_00_AM_07_30_AM,ESCORT - Arrival Constant: 07:00 AM - 07:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==9)),coef_escort_Arrival_Constant_07_00_AM_07_30_AM +util_escort_Arrival_Constant_07_30_AM_08_00_AM,ESCORT - Arrival Constant: 07:30 AM - 08:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==10)),coef_escort_Arrival_Constant_07_30_AM_08_00_AM +util_escort_Arrival_Constant_08_00_AM_08_30_AM,ESCORT - Arrival Constant: 08:00 AM - 08:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==11)),coef_escort_Arrival_Constant_08_00_AM_08_30_AM +util_escort_Arrival_Constant_08_30_AM_09_00_AM,ESCORT - Arrival Constant: 08:30 AM - 09:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==12)),coef_escort_Arrival_Constant_08_30_AM_09_00_AM +util_escort_Arrival_Constant_After_09_00_AM,ESCORT - Arrival Constant: After 09:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end>12)),coef_escort_Arrival_Constant_After_09_00_AM +util_escort_Arrival_Constant_02_30_PM_03_00_PM,ESCORT - Arrival Constant: 02:30 PM - 03:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==24)),coef_escort_Arrival_Constant_02_30_PM_03_00_PM +util_escort_Arrival_Constant_03_00_PM_03_30_PM,ESCORT - Arrival Constant: 03:00 PM - 03:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==25)),coef_escort_Arrival_Constant_03_00_PM_03_30_PM +util_escort_Arrival_Constant_03_30_PM_04_00_PM,ESCORT - Arrival Constant: 03:30 PM - 04:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==26)),coef_escort_Arrival_Constant_03_30_PM_04_00_PM +util_escort_Arrival_Constant_04_00_PM_04_30_PM,ESCORT - Arrival Constant: 04:00 PM - 04:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end==27)),coef_escort_Arrival_Constant_04_00_PM_04_30_PM +util_escort_Arrival_Constant_After_04_30_PM,ESCORT - Arrival Constant: After 04:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end>27)),coef_escort_Arrival_Constant_After_04_30_PM +util_escort_Arrival_Constant_Shift_for_every_30_minutes_after_9_30_am_Linear,ESCORT - Arrival Constant: Shift for every 30 minutes after 9:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end>13)), (np.where((df.end<8), np.minimum(8-df.end,2), 0) + np.where((df.end>13), np.minimum(df.end-13,30), 0)), 0)",coef_escort_Arrival_Constant_Shift_for_every_30_minutes_after_9_30_am_Linear +util_escort_Arrival_Constant_Shift_for_every_30_minutes_after_5_00_pm_Linear,ESCORT - Arrival Constant: Shift for every 30 minutes after 5:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.end>28)), (np.where((df.end<0), np.minimum(0-df.end,48), 0) + np.where((df.start>28), np.minimum(df.end-28,15), 0)), 0)",coef_escort_Arrival_Constant_Shift_for_every_30_minutes_after_5_00_pm_Linear +util_escort_Duration_Constant_0_hrs,ESCORT - Duration Constant: 0 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration==0)),coef_escort_Duration_Constant_0_hrs +util_escort_Duration_Constant_0p5_hrs,ESCORT - Duration Constant: 0.5 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration==1)),coef_escort_Duration_Constant_0p5_hrs +util_escort_Duration_Constant_1_hrs,ESCORT - Duration Constant: 1 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration==2)),coef_escort_Duration_Constant_1_hrs +util_escort_Duration_Constant_1p5hrs,ESCORT - Duration Constant: 1.5hrs,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration==3)),coef_escort_Duration_Constant_1p5hrs +util_escort_Duration_Constant_2_hrs,ESCORT - Duration Constant: 2 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration==4)),coef_escort_Duration_Constant_2_hrs +util_escort_Duration_Constant_Longer_than_2_hrs,ESCORT - Duration Constant: Longer than 2 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration>4)),coef_escort_Duration_Constant_Longer_than_2_hrs +util_escort_Calibration_Constant_Duration_eq_1,ESCORT - Calibration Constant - Duration = 1,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.duration==0)),coef_escort_Calibration_Constant_Duration_eq_1 +util_escort_Calibration_Constant_Duration_eq_2,ESCORT - Calibration Constant - Duration = 2,@(((df.tour_category == 'joint') & (df.tour_type == 'escort') & df.duration==1)),coef_escort_Calibration_Constant_Duration_eq_2 +util_escort_Calibration_Constant_Departure_eq_9,ESCORT - Calibration Constant - Departure = 9,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==9)),coef_escort_Calibration_Constant_Departure_eq_9 +util_escort_Calibration_Constant_Departure_eq_10,ESCORT - Calibration Constant - Departure = 10,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==10)),coef_escort_Calibration_Constant_Departure_eq_10 +util_escort_Calibration_Constant_Departure_eq_23,ESCORT - Calibration Constant - Departure = 23,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==23)),coef_escort_Calibration_Constant_Departure_eq_23 +util_escort_Calibration_Constant_Departure_eq_24,ESCORT - Calibration Constant - Departure = 24,@((df.tour_category == 'joint') & (df.tour_type == 'escort') & (df.start==24)),coef_escort_Calibration_Constant_Departure_eq_24 +#SHOPPING,#SHOPPING,,SHOPPING +util_shop_Joint_Shopping_tours_dummy_Departure_before_10_00_AM_Linear,SHOPPING - Joint Shopping tours dummy: Departure before 10:00 AM - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start<15)), (np.where((df.start<=15), np.minimum(15-df.start,7), 0) + np.where((df.start>15), np.minimum(df.start-15,24), 0)), 0)",coef_shop_Joint_Shopping_tours_dummy_Departure_before_10_00_AM_Linear +util_shop_Joint_Shopping_tours_dummy_Departure_after_10_30_AM_Linear,SHOPPING - Joint Shopping tours dummy: Departure after 10:30 AM - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start>15)), (np.where((df.start<=15), np.minimum(15-df.start,7), 0) + np.where((df.start>15), np.minimum(df.start-15,24), 0)), 0)",coef_shop_Joint_Shopping_tours_dummy_Departure_after_10_30_AM_Linear +util_shop_Joint_Tours_Party_Size_gt_2_Duration_lt_1p5_hrs,SHOPPING - Joint Tours Party Size > 2: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration<2) & (df.number_of_participants > 2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)), 0)",coef_shop_Joint_Tours_Party_Size_gt_2_Duration_lt_1p5_hrs +util_shop_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,SHOPPING - Joint Tours Party Size > 2: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration>2) & (df.number_of_participants > 2)), (np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shop_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr +util_shop_Joint_Tour_with_only_adults_Duration_lt_1p5_hrs,SHOPPING - Joint Tour with only adults: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration<2) & (df.composition=='adults')), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)), 0)",coef_shop_Joint_Tour_with_only_adults_Duration_lt_1p5_hrs +util_shop_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,SHOPPING - Kids in Joint Tour: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration<2) & ((df.composition=='children')|(df.composition=='mixed'))), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)), 0)",coef_shop_Kids_in_Joint_Tour_Duration_lt_1p5_hrs +util_shop_Kids_in_Joint_Tour_Duration_gt_1p5_hr,SHOPPING - Kids in Joint Tour: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration>2) & ((df.composition=='children')|(df.composition=='mixed'))), (np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shop_Kids_in_Joint_Tour_Duration_gt_1p5_hr +util_shop_Low_Income_lteq25_000_Duration_gt_1p5_hr,"SHOPPING - Low Income (<=$25,000): Duration > 1.5 hr","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.is_income_less25K) & (df.duration>3)), (np.where((df.duration>3),np.minimum(df.duration-3,27), 0)), 0)",coef_shop_Low_Income_lteq25_000_Duration_gt_1p5_hr +util_shop_Medium_Income_25_001_to_60_000_Duration_lt_1p5_hrs,"SHOPPING - Medium Income ($25,001 to $60,000): Duration < 1.5 hrs","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.is_income_25K_to_60K) & (df.duration<3)), (np.where((df.duration>3),np.minimum(df.duration-3,27), 0)), 0)",coef_shop_Medium_Income_25_001_to_60_000_Duration_lt_1p5_hrs +util_shop_MediumHigh_Income_60_001_to_120_00_Duration_gt_1p5_hr,"SHOPPING - Medium-High Income ($60,001 to $120,00): Duration > 1.5 hr","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.is_income_60K_to_120K) & (df.duration>3)), (np.where((df.duration>3), np.minimum(df.duration-3,27), 0)), 0)",coef_shop_MediumHigh_Income_60_001_to_120_00_Duration_gt_1p5_hr +util_shop_Distance_Duration_lt_1p5_hrs,SHOPPING - Distance: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)) * (df.origin_to_destination_distance), 0)",coef_shop_Distance_Duration_lt_1p5_hrs +util_shop_Distance_Duration_gt_1p5_hr,SHOPPING - Distance: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration>2)), ((np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) * (df.origin_to_destination_distance)), 0)",coef_shop_Distance_Duration_gt_1p5_hr +util_shop_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Linear,SHOPPING - Departure Constant: Shift for every 30 minutes before 08:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start<12)), (np.where((df.start<12), np.minimum(12-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)), 0)",coef_shop_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Linear +util_shop_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Square_root,SHOPPING - Departure Constant: Shift for every 30 minutes before 08:30 am - Square root,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start<12)), (np.where((df.start<12), np.minimum(12-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0))**0.5, 0)",coef_shop_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Square_root +util_shop_Departure_Constant_Before_09_00_AM,SHOPPING - Departure Constant: Before 09:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start<13)),coef_shop_Departure_Constant_Before_09_00_AM +util_shop_Departure_Constant_09_00_AM_09_30_AM,SHOPPING - Departure Constant: 09:00 AM - 09:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start==13)),coef_shop_Departure_Constant_09_00_AM_09_30_AM +util_shop_Departure_Constant_09_30_AM_10_00_AM,SHOPPING - Departure Constant: 09:30 AM - 10:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start==14)),coef_shop_Departure_Constant_09_30_AM_10_00_AM +util_shop_Departure_Constant_10_00_AM_10_30_AM,SHOPPING - Departure Constant: 10:00 AM - 10:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start==15)),coef_shop_Departure_Constant_10_00_AM_10_30_AM +util_shop_Departure_Constant_10_30_AM_11_00_AM,SHOPPING - Departure Constant: 10:30 AM - 11:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start==16)),coef_shop_Departure_Constant_10_30_AM_11_00_AM +util_shop_Departure_Constant_After_11_00_AM,SHOPPING - Departure Constant: After 11:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start>16)),coef_shop_Departure_Constant_After_11_00_AM +util_shop_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Linear,SHOPPING - Departure Constant: Shift for every 30 minutes after 11:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start>17)), (np.where((df.start<12), np.minimum(12-df.start,7),0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)), 0)",coef_shop_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Linear +util_shop_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Squared,SHOPPING - Departure Constant: Shift for every 30 minutes after 11:30 am - Squared,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.start>17)), ((np.where((df.start<12), np.minimum(12-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)) ** 2), 0)",coef_shop_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Squared +util_shop_Arrival_Constant_Shift_for_every_30_minutes_before_12_00_pm_Linear,SHOPPING - Arrival Constant: Shift for every 30 minutes before 12:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end<19)), (np.where ((df.end<19), np.minimum(19-df.end,10), 0) + np.where((df.end>38), np.minimum(df.end-38,5), 0)), 0)",coef_shop_Arrival_Constant_Shift_for_every_30_minutes_before_12_00_pm_Linear +util_shop_Arrival_Constant_Before_12_30_PM,SHOPPING - Arrival Constant: Before 12:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end<20)),coef_shop_Arrival_Constant_Before_12_30_PM +util_shop_Arrival_Constant_12_30_PM_03_00_PM,SHOPPING - Arrival Constant: 12:30 PM - 03:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & ( df.end>=20) & (df.end<=24)),coef_shop_Arrival_Constant_12_30_PM_03_00_PM +util_shop_Arrival_Constant_03_00_PM_03_30_PM,SHOPPING - Arrival Constant: 03:00 PM - 03:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end==25)),coef_shop_Arrival_Constant_03_00_PM_03_30_PM +util_shop_Arrival_Constant_03_30_PM_04_00_PM,SHOPPING - Arrival Constant: 03:30 PM - 04:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end==26)),coef_shop_Arrival_Constant_03_30_PM_04_00_PM +util_shop_Arrival_Constant_04_00_PM_04_30_PM,SHOPPING - Arrival Constant: 04:00 PM - 04:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end==27)),coef_shop_Arrival_Constant_04_00_PM_04_30_PM +util_shop_Arrival_Constant_04_30_PM_05_00_PM,SHOPPING - Arrival Constant: 04:30 PM - 05:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end==28)),coef_shop_Arrival_Constant_04_30_PM_05_00_PM +util_shop_Arrival_Constant_05_00_PM_05_30_PM,SHOPPING - Arrival Constant: 05:00 PM - 05:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end==29)),coef_shop_Arrival_Constant_05_00_PM_05_30_PM +util_shop_Arrival_Constant_05_30_PM_07_00_PM,SHOPPING - Arrival Constant: 05:30 PM - 07:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end>=30) & (df.end<=32)),coef_shop_Arrival_Constant_05_30_PM_07_00_PM +util_shop_Arrival_Constant_07_00_PM_09_30_PM,SHOPPING - Arrival Constant: 07:00 PM - 09:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end>=33) & (df.end<=37)),coef_shop_Arrival_Constant_07_00_PM_09_30_PM +util_shop_Arrival_Constant_After_09_30_PM,SHOPPING - Arrival Constant: After 09:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end>37)),coef_shop_Arrival_Constant_After_09_30_PM +util_shop_Arrival_Constant_Shift_for_every_30_minutes_after_10_00_pm_Linear,SHOPPING - Arrival Constant: Shift for every 30 minutes after 10:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.end>38)), (np.where((df.end<19), np.minimum(19-df.end,10), 0) + np.where ((df.end>38), np.minimum(df.end-38,5), 0)), 0)",coef_shop_Arrival_Constant_Shift_for_every_30_minutes_after_10_00_pm_Linear +util_shop_Duration_Constant_0_hrs,SHOPPING - Duration Constant: 0 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==0)),coef_shop_Duration_Constant_0_hrs +util_shop_Duration_Constant_0p5_hrs,SHOPPING - Duration Constant: 0.5 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==1)),coef_shop_Duration_Constant_0p5_hrs +util_shop_Duration_Constant_1_hrs,SHOPPING - Duration Constant: 1 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==2)),coef_shop_Duration_Constant_1_hrs +util_shop_Duration_Constant_1p5hrs,SHOPPING - Duration Constant: 1.5hrs,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==3)),coef_shop_Duration_Constant_1p5hrs +util_shop_Duration_Constant_2_hrs,SHOPPING - Duration Constant: 2 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==4)),coef_shop_Duration_Constant_2_hrs +util_shop_Duration_Constant_Longer_than_2_hrs,SHOPPING - Duration Constant: Longer than 2 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration>4)),coef_shop_Duration_Constant_Longer_than_2_hrs +util_shop_Duration_Constant_Duration_gt_2p5_hrs_Linear,SHOPPING - Duration Constant: Duration > 2.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration>5)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>5), np.minimum(df.duration-5,26), 0)), 0)",coef_shop_Duration_Constant_Duration_gt_2p5_hrs_Linear +util_shop_Duration_Constant_Duration_gt_2p5_hrs_Square_root,SHOPPING - Duration Constant: Duration > 2.5 hrs - Square root,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration>5)), ((np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>5), np.minimum(df.duration-5,26), 0)) ** 0.5), 0)",coef_shop_Duration_Constant_Duration_gt_2p5_hrs_Square_root +util_shop_Calibration_Constant_Duration_eq_1,SHOPPING - Calibration Constant - Duration = 1,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==0)),coef_shop_Calibration_Constant_Duration_eq_1 +util_shop_Calibration_Constant_Duration_eq_2,SHOPPING - Calibration Constant - Duration = 2,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==1)),coef_shop_Calibration_Constant_Duration_eq_2 +util_shop_Calibration_Constant_Duration_eq_3,SHOPPING - Calibration Constant - Duration = 3,@((df.tour_category == 'joint') & (df.tour_type == 'shopping') & (df.duration==2)),coef_shop_Calibration_Constant_Duration_eq_3 +#MAINTENANCE,#MAINTENANCE,,MAINTENANCE +util_maint_Joint_Maintenance_tours_dummy_Departure_before_10_00_AM_Linear,MAINTENANCE - Joint Maintenance tours dummy: Departure before 10:00 AM - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start<15)), (np.where((df.start<=15), np.minimum(15-df.start,7), 0) + np.where((df.start>15), np.minimum(df.start-15,24), 0)), 0)",coef_maint_Joint_Maintenance_tours_dummy_Departure_before_10_00_AM_Linear +util_maint_Joint_Maintenance_tours_dummy_Departure_after_10_30_AM_Linear,MAINTENANCE - Joint Maintenance tours dummy: Departure after 10:30 AM - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start>15)), (np.where((df.start<=15), np.minimum(15-df.start,7), 0) + np.where((df.start>15), np.minimum(df.start-15,24), 0)), 0)",coef_maint_Joint_Maintenance_tours_dummy_Departure_after_10_30_AM_Linear +util_maint_Joint_Tours_Party_Size_gt_2_Duration_lt_1p5_hrs,MAINTENANCE - Joint Tours Party Size > 2: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration<2) & (df.number_of_participants > 2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)), 0)",coef_maint_Joint_Tours_Party_Size_gt_2_Duration_lt_1p5_hrs +util_maint_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,MAINTENANCE - Joint Tours Party Size > 2: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration>2) & (df.number_of_participants > 2)), (np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maint_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr +util_maint_Joint_Tour_with_only_adults_Duration_lt_1p5_hrs,MAINTENANCE - Joint Tour with only adults: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration<2) & (df.composition=='adults')), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)), 0)",coef_maint_Joint_Tour_with_only_adults_Duration_lt_1p5_hrs +util_maint_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,MAINTENANCE - Kids in Joint Tour: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration<2) & ((df.composition=='children')|(df.composition=='mixed'))), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)), 0)",coef_maint_Kids_in_Joint_Tour_Duration_lt_1p5_hrs +util_maint_Kids_in_Joint_Tour_Duration_gt_1p5_hr,MAINTENANCE - Kids in Joint Tour: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration>2) & ((df.composition=='children')|(df.composition=='mixed'))), (np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maint_Kids_in_Joint_Tour_Duration_gt_1p5_hr +util_maint_Low_Income_lteq25_000_Duration_gt_1p5_hr,"MAINTENANCE - Low Income (<=$25,000): Duration > 1.5 hr","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.is_income_less25K) & (df.duration>2)), (np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maint_Low_Income_lteq25_000_Duration_gt_1p5_hr +util_maint_Medium_Income_25_001_to_60_000_Duration_lt_1p5_hrs,"MAINTENANCE - Medium Income ($25,001 to $60,000): Duration < 1.5 hrs","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.is_income_25K_to_60K) & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)), 0)",coef_maint_Medium_Income_25_001_to_60_000_Duration_lt_1p5_hrs +util_maint_Medium_Income_25_001_to_60_000_Duration_gt_1p5_hr,"MAINTENANCE - Medium Income ($25,001 to $60,000): Duration > 1.5 hr","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.is_income_25K_to_60K) & (df.duration>2)), (np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maint_Medium_Income_25_001_to_60_000_Duration_gt_1p5_hr +util_maint_MediumHigh_Income_60_001_to_120_00_Duration_gt_1p5_hr,"MAINTENANCE - Medium-High Income ($60,001 to $120,00): Duration > 1.5 hr","@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.is_income_60K_to_120K) & (df.duration>2)), (np.where((df.duration>2), np.minimum(df.duration-2,26), 0)), 0)",coef_maint_MediumHigh_Income_60_001_to_120_00_Duration_gt_1p5_hr +util_maint_Distance_Duration_lt_1p5_hrs,MAINTENANCE - Distance: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0)) *(df.origin_to_destination_distance), 0)",coef_maint_Distance_Duration_lt_1p5_hrs +util_maint_Distance_Duration_gt_1p5_hr,MAINTENANCE - Distance: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration>2)), (np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) * (df.origin_to_destination_distance), 0)",coef_maint_Distance_Duration_gt_1p5_hr +util_maint_Departure_Constant_Shift_for_every_30_minutes_before_07_30_am_Linear,MAINTENANCE - Departure Constant: Shift for every 30 minutes before 07:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start<10)), (np.where((df.start<10), np.minimum(10-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)), 0)",coef_maint_Departure_Constant_Shift_for_every_30_minutes_before_07_30_am_Linear +util_maint_Departure_Constant_Shift_for_every_30_minutes_before_07_30_am_Square_Root,MAINTENANCE - Departure Constant: Shift for every 30 minutes before 07:30 am - Square Root,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start<10)), ((np.where((df.start<10), np.minimum(10-df.start,7), 0) + (np.where((df.start>17), np.minimum(df.start-17,24), 0)))** 0.5), 0)",coef_maint_Departure_Constant_Shift_for_every_30_minutes_before_07_30_am_Square_Root +util_maint_Departure_Constant_Before_08_00_AM,MAINTENANCE - Departure Constant: Before 08:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start<11)),coef_maint_Departure_Constant_Before_08_00_AM +util_maint_Departure_Constant_08_00_AM_08_30_AM,MAINTENANCE - Departure Constant: 08:00 AM - 08:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start==11)),coef_maint_Departure_Constant_08_00_AM_08_30_AM +util_maint_Departure_Constant_08_30_AM_09_00_AM,MAINTENANCE - Departure Constant: 08:30 AM - 09:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start==12)),coef_maint_Departure_Constant_08_30_AM_09_00_AM +util_maint_Departure_Constant_09_00_AM_09_30_AM,MAINTENANCE - Departure Constant: 09:00 AM - 09:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start==13)),coef_maint_Departure_Constant_09_00_AM_09_30_AM +util_maint_Departure_Constant_09_30_AM_10_00_AM,MAINTENANCE - Departure Constant: 09:30 AM - 10:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start==14)),coef_maint_Departure_Constant_09_30_AM_10_00_AM +util_maint_Departure_Constant_10_00_AM_10_30_AM,MAINTENANCE - Departure Constant: 10:00 AM - 10:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start==15)),coef_maint_Departure_Constant_10_00_AM_10_30_AM +util_maint_Departure_Constant_10_30_AM_11_00_AM,MAINTENANCE - Departure Constant: 10:30 AM - 11:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start==16)),coef_maint_Departure_Constant_10_30_AM_11_00_AM +util_maint_Departure_Constant_After_11_00_AM,MAINTENANCE - Departure Constant: After 11:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start>16)),coef_maint_Departure_Constant_After_11_00_AM +util_maint_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Linear,MAINTENANCE - Departure Constant: Shift for every 30 minutes after 11:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start>17)), np.where((df.start<10), np.minimum(10-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0), 0)",coef_maint_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Linear +util_maint_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Squared,MAINTENANCE - Departure Constant: Shift for every 30 minutes after 11:30 am - Squared,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.start>17)), ((np.where((df.start<10), np.minimum(10-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)) ** 2), 0)",coef_maint_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Squared +util_maint_Arrival_Constant_Shift_for_every_30_minutes_before_10_00_am_Linear,MAINTENANCE - Arrival Constant: Shift for every 30 minutes before 10:00 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end<15)), (np.where((df.end<15), np.minimum(15-df.end,9), 0) + np.where((df.end>28), np.minimum(df.end-28,16), 0)), 0)",coef_maint_Arrival_Constant_Shift_for_every_30_minutes_before_10_00_am_Linear +util_maint_Arrival_Constant_Before_10_30_AM,MAINTENANCE - Arrival Constant: Before 10:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end<16)),coef_maint_Arrival_Constant_Before_10_30_AM +util_maint_Arrival_Constant_10_30_AM_11_00_AM,MAINTENANCE - Arrival Constant: 10:30 AM - 11:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end==16)),coef_maint_Arrival_Constant_10_30_AM_11_00_AM +util_maint_Arrival_Constant_11_00_AM_11_30_AM,MAINTENANCE - Arrival Constant: 11:00 AM - 11:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end==17)),coef_maint_Arrival_Constant_11_00_AM_11_30_AM +util_maint_Arrival_Constant_11_30_AM_01_30_PM,MAINTENANCE - Arrival Constant: 11:30 AM - 01:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end>=18) & (df.end<=21)),coef_maint_Arrival_Constant_11_30_AM_01_30_PM +util_maint_Arrival_Constant_01_30_PM_02_30_PM,MAINTENANCE - Arrival Constant: 01:30 PM - 02:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end>=22) & (df.end<=23)),coef_maint_Arrival_Constant_01_30_PM_02_30_PM +util_maint_Arrival_Constant_02_30_PM_04_00_PM,MAINTENANCE - Arrival Constant: 02:30 PM - 04:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end>=24) & (df.end<=26)),coef_maint_Arrival_Constant_02_30_PM_04_00_PM +util_maint_Arrival_Constant_04_00_PM_04_30_PM,MAINTENANCE - Arrival Constant: 04:00 PM - 04:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end==27)),coef_maint_Arrival_Constant_04_00_PM_04_30_PM +util_maint_Arrival_Constant_After_04_30_PM,MAINTENANCE - Arrival Constant: After 04:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end>27)),coef_maint_Arrival_Constant_After_04_30_PM +util_maint_Arrival_Constant_Shift_for_every_30_minutes_after_5_00_pm_Linear,MAINTENANCE - Arrival Constant: Shift for every 30 minutes after 5:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.end>28)), (np.where((df.end<15), np.minimum(15-df.end,9), 0) + np.where((df.end>28), np.minimum(df.end-28,16), 0)), 0)",coef_maint_Arrival_Constant_Shift_for_every_30_minutes_after_5_00_pm_Linear +util_maint_Duration_Constant_0_hrs,MAINTENANCE - Duration Constant: 0 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration==0)),coef_maint_Duration_Constant_0_hrs +util_maint_Duration_Constant_0p5_hrs,MAINTENANCE - Duration Constant: 0.5 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration==1)),coef_maint_Duration_Constant_0p5_hrs +util_maint_Duration_Constant_Longer_than_0p5_hrs,MAINTENANCE - Duration Constant: Longer than 0.5 hrs,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration>1)),coef_maint_Duration_Constant_Longer_than_0p5_hrs +util_maint_Duration_Constant_Duration_gt_1_hrs_Linear,MAINTENANCE - Duration Constant: Duration > 1 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration>2)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0)), 0)",coef_maint_Duration_Constant_Duration_gt_1_hrs_Linear +util_maint_Duration_Constant_Duration_gt_1_hrs_Square_Root,MAINTENANCE - Duration Constant: Duration > 1 hrs - Square Root,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration>2)), ((np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0))** 0.5), 0)",coef_maint_Duration_Constant_Duration_gt_1_hrs_Square_Root +util_maint_Calibration_Constant_Duration_eq_1,MAINTENANCE - Calibration Constant - Duration = 1,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration==0)),coef_maint_Calibration_Constant_Duration_eq_1 +util_maint_Calibration_Constant_Duration_eq_2,MAINTENANCE - Calibration Constant - Duration = 2,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration==1)),coef_maint_Calibration_Constant_Duration_eq_2 +util_maint_Calibration_Constant_Duration_eq_3,MAINTENANCE - Calibration Constant - Duration = 3,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration==2)),coef_maint_Calibration_Constant_Duration_eq_3 +util_maint_Calibration_Constant_Duration_eq_4,MAINTENANCE - Calibration Constant - Duration = 4,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration==3)),coef_maint_Calibration_Constant_Duration_eq_4 +util_maint_Calibration_Constant_Duration_eq_5,MAINTENANCE - Calibration Constant - Duration = 5,@((df.tour_category == 'joint') & (df.tour_type == 'othmaint') & (df.duration==4)),coef_maint_Calibration_Constant_Duration_eq_5 +#EATOUT,#EAT-OUT,,EATOUT +util_eatout_Distance_to_destination_Duration_lt_1_hrs,EAT-OUT - Distance to destination - Duration < 1 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0)) * (df.origin_to_destination_distance), 0)",coef_eatout_Distance_to_destination_Duration_lt_1_hrs +util_eatout_Distance_to_destination_Duration_gt_1_hrs,EAT-OUT - Distance to destination - Duration > 1 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration>2)), (np.where((df.duration>2), np.minimum(df.duration-2,14), 0)) *(df.origin_to_destination_distance), 0)",coef_eatout_Distance_to_destination_Duration_gt_1_hrs +util_eatout_Low_income_lt25000_Duration_lt_1_hrs,EAT-OUT - Low income (<25000) - Duration < 1 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.is_income_less25K) & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0)), 0)",coef_eatout_Low_income_lt25000_Duration_lt_1_hrs +util_eatout_Medium_25k_to_60k_Duration_lt_1_hrs,EAT-OUT - Medium (25k to 60k) - Duration < 1 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.is_income_25K_to_60K) & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0)), 0)",coef_eatout_Medium_25k_to_60k_Duration_lt_1_hrs +util_eatout_Zero_auto_HH_Duration_gt_1_hrs,EAT-OUT - Zero auto HH - Duration > 1 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.auto_ownership == 0) & (df.duration>2)), (np.where((df.duration>2), np.minimum(df.duration-2,14), 0)), 0)",coef_eatout_Zero_auto_HH_Duration_gt_1_hrs +util_eatout_Kids_in_Joint_tour_Duration_lt_1_hrs,EAT-OUT - Kids in Joint tour - Duration < 1 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration<2) & ((df.composition=='children')|(df.composition=='mixed'))), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0)), 0)",coef_eatout_Kids_in_Joint_tour_Duration_lt_1_hrs +util_eatout_Joint_Tours_Party_Size_greater_than_2_Duration_lt_1_hrs,EAT-OUT - Joint Tours Party Size greater than 2 - Duration < 1 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration<2) & (df.number_of_participants > 2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0)), 0)",coef_eatout_Joint_Tours_Party_Size_greater_than_2_Duration_lt_1_hrs +util_eatout_Departure_Constant_11_00_AM_12_00_PM,EAT-OUT - Departure Constant: 11:00 AM - 12:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start>=17) & (df.start<=18)),coef_eatout_Departure_Constant_11_00_AM_12_00_PM +util_eatout_Departure_Constant_12_00_PM_12_30_PM,EAT-OUT - Departure Constant: 12:00 PM - 12:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start==19),coef_eatout_Departure_Constant_12_00_PM_12_30_PM +util_eatout_Departure_Constant_12_30_PM_to_01_00_PM,EAT-OUT - Departure Constant: 12:30 PM to 01:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start==20),coef_eatout_Departure_Constant_12_30_PM_to_01_00_PM +util_eatout_Departure_Constant_Shift_for_every_30_minutes_before_05_00_pm_Linear,EAT-OUT - Departure Constant: Shift for every 30 minutes before 05:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start<29)), (np.where((df.start<29), np.minimum(29-df.start,20), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_eatout_Departure_Constant_Shift_for_every_30_minutes_before_05_00_pm_Linear +util_eatout_Departure_Constant_Before_05_30_PM,EAT-OUT - Departure Constant: Before 05:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start<30),coef_eatout_Departure_Constant_Before_05_30_PM +util_eatout_Departure_Constant_05_30_PM_06_00_PM,EAT-OUT - Departure Constant: 05:30 PM - 06:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start==30),coef_eatout_Departure_Constant_05_30_PM_06_00_PM +util_eatout_Departure_Constant_06_00_PM_06_30_PM,EAT-OUT - Departure Constant: 06:00 PM - 06:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start==31),coef_eatout_Departure_Constant_06_00_PM_06_30_PM +util_eatout_Departure_Constant_06_30_PM_07_00_PM,EAT-OUT - Departure Constant: 06:30 PM - 07:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start==32),coef_eatout_Departure_Constant_06_30_PM_07_00_PM +util_eatout_Departure_Constant_07_00_PM_07_30_PM,EAT-OUT - Departure Constant: 07:00 PM - 07:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start==33),coef_eatout_Departure_Constant_07_00_PM_07_30_PM +util_eatout_Departure_Constant_After_07_30_PM,EAT-OUT - Departure Constant: After 07:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start>33),coef_eatout_Departure_Constant_After_07_30_PM +util_eatout_Departure_Constant_Shift_for_every_30_minutes_after_08_00_pm_Linear,EAT-OUT - Departure Constant: Shift for every 30 minutes after 08:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start>34)), (np.where((df.start<29), np.minimum(29-df.start,20), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_eatout_Departure_Constant_Shift_for_every_30_minutes_after_08_00_pm_Linear +util_eatout_Arrival_Constant_12_30_PM_to_01_00_PM,EAT-OUT - Arrival Constant: 12:30 PM to 01:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end==20),coef_eatout_Arrival_Constant_12_30_PM_to_01_00_PM +util_eatout_Arrival_Constant_01_00_PM_to_01_30_PM,EAT-OUT - Arrival Constant: 01:00 PM to 01:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end==21),coef_eatout_Arrival_Constant_01_00_PM_to_01_30_PM +util_eatout_Arrival_Constant_01_30_PM_to_02_00_PM,EAT-OUT - Arrival Constant: 01:30 PM to 02:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end==22),coef_eatout_Arrival_Constant_01_30_PM_to_02_00_PM +util_eatout_Arrival_Constant_02_00_PM_to_02_30_PM,EAT-OUT - Arrival Constant: 02:00 PM to 02:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end==23),coef_eatout_Arrival_Constant_02_00_PM_to_02_30_PM +util_eatout_Arrival_Constant_Shift_for_every_30_minutes_before_06_30_pm_Linear,EAT-OUT - Arrival Constant: Shift for every 30 minutes before 06:30 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end<32)), (np.where((df.end<32), np.minimum(32-df.end,21), 0) + np.where((df.end>37), np.minimum(df.end-37,48), 0)), 0)",coef_eatout_Arrival_Constant_Shift_for_every_30_minutes_before_06_30_pm_Linear +util_eatout_Arrival_Constant_Before_7_00_PM,EAT-OUT - Arrival Constant: Before 7:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end<33),coef_eatout_Arrival_Constant_Before_7_00_PM +util_eatout_Arrival_Constant_7_00_PM_to_7_30_PM,EAT-OUT - Arrival Constant: 7:00 PM to 7:30 PM,@(df.tour_category == 'joint') & (df.tour_type== 'eatout') & (df.end==33),coef_eatout_Arrival_Constant_7_00_PM_to_7_30_PM +util_eatout_Arrival_Constant_7_30_PM_to_8_00_PM,EAT-OUT - Arrival Constant: 7:30 PM to 8:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end==34),coef_eatout_Arrival_Constant_7_30_PM_to_8_00_PM +util_eatout_Arrival_Constant_8_00_PM_to_8_30_PM,EAT-OUT - Arrival Constant: 8:00 PM to 8:30 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end==35),coef_eatout_Arrival_Constant_8_00_PM_to_8_30_PM +util_eatout_Arrival_Constant_8_30_PM_to_9_00_PM,EAT-OUT - Arrival Constant: 8:30 PM to 9:00 PM,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.end==36),coef_eatout_Arrival_Constant_8_30_PM_to_9_00_PM +util_eatout_Arrival_Constant_After_09_00_PM,EAT-OUT - Arrival Constant: After 09:00 PM,@(df.tour_category == 'joint') & (df.tour_type== 'eatout') & (df.end>36),coef_eatout_Arrival_Constant_After_09_00_PM +util_eatout_Arrival_Constant_Shift_for_every_30_minutes_after_09_30_pm_Linear,EAT-OUT - Arrival Constant: Shift for every 30 minutes after 09:30 pm - Linear,"@np.where(((df.tour_type== 'eatout') & (df.end>37) & (df.tour_category == 'joint')), (np.where((df.end<32), np.minimum(32-df.end,21), 0) + np.where((df.end>37), np.minimum(df.end-37,48), 0)), 0)",coef_eatout_Arrival_Constant_Shift_for_every_30_minutes_after_09_30_pm_Linear +util_eatout_Duration_Constant_Shift_for_every_30_minutes_more_than_3_hrs_Linear,EAT-OUT - Duration Constant: Shift for every 30 minutes more than 3 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration>6)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>6), np.minimum(df.duration-6,12), 0)), 0)",coef_eatout_Duration_Constant_Shift_for_every_30_minutes_more_than_3_hrs_Linear +util_eatout_Duration_Constant_0_hours,EAT-OUT - Duration Constant: 0 hours,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration==0)),coef_eatout_Duration_Constant_0_hours +util_eatout_Duration_Constant_0p5_hous,EAT-OUT - Duration Constant: 0.5 hous,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration==1)),coef_eatout_Duration_Constant_0p5_hous +util_eatout_Duration_Constant_1_hour,EAT-OUT - Duration Constant: 1 hour,@((df.tour_category == 'joint') & (df.tour_type== 'eatout') & (df.duration==2)),coef_eatout_Duration_Constant_1_hour +util_eatout_Duration_Constant_1p5_hours,EAT-OUT - Duration Constant: 1.5 hours,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration==3)),coef_eatout_Duration_Constant_1p5_hours +util_eatout_Duration_Constant_2_hours_or_more,EAT-OUT - Duration Constant: 2 hours or more,@(df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration>4),coef_eatout_Duration_Constant_2_hours_or_more +util_eatout_Duration_Constant_Shift_for_every_30_minutes_more_than_2p5_hrs_Linear,EAT-OUT - Duration Constant: Shift for every 30 minutes more than 2.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration>5)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>5), np.minimum(df.duration-5,13), 0)), 0)",coef_eatout_Duration_Constant_Shift_for_every_30_minutes_more_than_2p5_hrs_Linear +util_eatout_Calibration_Constant_Duration_eq_1,EAT-OUT - Calibration Constant - Duration = 1,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration==0)),coef_eatout_Calibration_Constant_Duration_eq_1 +util_eatout_Calibration_Constant_Duration_eq_2,EAT-OUT - Calibration Constant - Duration = 2,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration==1)),coef_eatout_Calibration_Constant_Duration_eq_2 +util_eatout_Calibration_Constant_Duration_eq_3,EAT-OUT - Calibration Constant - Duration = 3,@((df.tour_category == 'joint') & (df.tour_type== 'eatout') & (df.duration==2)),coef_eatout_Calibration_Constant_Duration_eq_3 +util_eatout_Calibration_Constant_Duration_eq_4,EAT-OUT - Calibration Constant - Duration = 4,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.duration==3)),coef_eatout_Calibration_Constant_Duration_eq_4 +util_eatout_Calibration_Constant_Departure_eq_1,EAT-OUT - Calibration Constant - Departure = 1,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start == 1)),coef_eatout_Calibration_Constant_Departure_eq_1 +util_eatout_Calibration_Constant_Departure_eq_2,EAT-OUT - Calibration Constant - Departure = 2,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start == 2)),coef_eatout_Calibration_Constant_Departure_eq_2 +util_eatout_Calibration_Constant_Departure_eq_3,EAT-OUT - Calibration Constant - Departure = 3,@((df.tour_category == 'joint') & (df.tour_type== 'eatout') & (df.start == 3)),coef_eatout_Calibration_Constant_Departure_eq_3 +util_eatout_Calibration_Constant_Departure_eq_17,EAT-OUT - Calibration Constant - Departure = 17,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start ==17)),coef_eatout_Calibration_Constant_Departure_eq_17 +util_eatout_Calibration_Constant_Departure_eq_18,EAT-OUT - Calibration Constant - Departure = 18,@((df.tour_category == 'joint') & (df.tour_type== 'eatout') & (df.start ==18)),coef_eatout_Calibration_Constant_Departure_eq_18 +util_eatout_Calibration_Constant_Departure_eq_19,EAT-OUT - Calibration Constant - Departure = 19,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start ==19)),coef_eatout_Calibration_Constant_Departure_eq_19 +util_eatout_Calibration_Constant_Departure_eq_20,EAT-OUT - Calibration Constant - Departure = 20,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start ==20)),coef_eatout_Calibration_Constant_Departure_eq_20 +util_eatout_Calibration_Constant_Departure_eq_21,EAT-OUT - Calibration Constant - Departure = 21,@((df.tour_category == 'joint') & (df.tour_type == 'eatout') & (df.start ==21)),coef_eatout_Calibration_Constant_Departure_eq_21 +#SOCIAL,#SOCIAL,,SOCIAL +util_social_Retiree_Nonworking_senior_only_HH_Duration_lt_1p5_hrs_Linear,SOCIAL - Retiree/ Non-working senior only HH: Duration < 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.retired_adults_only_hh) & (df.tour_type == 'social') & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_Retiree_Nonworking_senior_only_HH_Duration_lt_1p5_hrs_Linear +util_social_Zero_auto_households_Duration_lt_1p5_hrs_Linear,SOCIAL - Zero auto households: Duration < 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.auto_ownership == 0) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_Zero_auto_households_Duration_lt_1p5_hrs_Linear +util_social_Zero_auto_households_Duration_gt_1p5_hrs_Linear,SOCIAL - Zero auto households: Duration > 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.auto_ownership == 0) & (df.duration>3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_Zero_auto_households_Duration_gt_1p5_hrs_Linear +util_social_Number_of_auto_more_that_number_of_adults_Duration_lt_1p5_hrs_Linear,SOCIAL - Number of auto more that number of adults: Duration < 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint')&(df.tour_type == 'social') & (df.auto_ownership > 0) &(df.auto_ownership > df.num_adults) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)), 0)",coef_social_Number_of_auto_more_that_number_of_adults_Duration_lt_1p5_hrs_Linear +util_social_Number_of_auto_more_that_number_of_adults_Duration_gt_1p5_hrs_Linear,SOCIAL - Number of auto more that number of adults: Duration > 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.auto_ownership > 0) & (df.auto_ownership > df.num_adults) & (df.duration>3)), (np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_social_Number_of_auto_more_that_number_of_adults_Duration_gt_1p5_hrs_Linear +util_social_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,SOCIAL - Kids in Joint Tour: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration<3) & ((df.composition=='children')|(df.composition=='mixed'))), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)), 0)",coef_social_Kids_in_Joint_Tour_Duration_lt_1p5_hrs +util_social_Kids_in_Joint_Tour_Duration_gt_1p5_hr,SOCIAL - Kids in Joint Tour: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration>3) & ((df.composition=='children')|(df.composition=='mixed'))), (np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_social_Kids_in_Joint_Tour_Duration_gt_1p5_hr +util_social_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,SOCIAL - Joint Tours Party Size > 2: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration>3) & (df.number_of_participants > 2)), (np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr +util_social_Auto_Distance_Duration_lt_1_hrs_Linear,SOCIAL - Auto Distance: Duration < 1 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) * (df.origin_to_destination_distance)), 0) ",coef_social_Auto_Distance_Duration_lt_1_hrs_Linear +util_social_Auto_Distance_Duration_gt_1_hrs_Linear,SOCIAL - Auto Distance: Duration > 1 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration>3)), (np.where((df.duration>3), np.minimum(df.duration-3,47), 0) * (df.origin_to_destination_distance)), 0)",coef_social_Auto_Distance_Duration_gt_1_hrs_Linear +util_social_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Linear,SOCIAL - Departure Constant: Shift for every 30 minutes before 08:30 am - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start<12)), (np.where((df.start<12), np.minimum(12-df.start,48), 0) + np.where((df.start>48), np.minimum(df.start-48,48), 0)), 0)",coef_social_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Linear +util_social_Departure_Constant_Before_09_00_AM,SOCIAL - Departure Constant: Before 09:00 AM,@(df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start<13),coef_social_Departure_Constant_Before_09_00_AM +util_social_Departure_Constant_09_00_AM_to_09_30_AM,SOCIAL - Departure Constant: 09:00 AM to 09:30 AM,@(df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start==13),coef_social_Departure_Constant_09_00_AM_to_09_30_AM +util_social_Departure_Constant_Shift_for_every_30_minutes_before_05_00_pm_Linear,SOCIAL - Departure Constant: Shift for every 30 minutes before 05:00 pm - Linear,"@np.where((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start<29), (np.where((df.start<29), np.minimum(29-df.start,8), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_social_Departure_Constant_Shift_for_every_30_minutes_before_05_00_pm_Linear +util_social_Departure_Constant_Before_05_30_PM,SOCIAL - Departure Constant: Before 05:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start<30)),coef_social_Departure_Constant_Before_05_30_PM +util_social_Departure_Constant_05_30_PM_06_00_PM,SOCIAL - Departure Constant: 05:30 PM - 06:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start==30)),coef_social_Departure_Constant_05_30_PM_06_00_PM +util_social_Departure_Constant_06_00_PM_06_30_PM,SOCIAL - Departure Constant: 06:00 PM - 06:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start==31)),coef_social_Departure_Constant_06_00_PM_06_30_PM +util_social_Departure_Constant_06_30_PM_07_00_PM,SOCIAL - Departure Constant: 06:30 PM - 07:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start==32)),coef_social_Departure_Constant_06_30_PM_07_00_PM +util_social_Departure_Constant_07_00_PM_07_30_PM,SOCIAL - Departure Constant: 07:00 PM - 07:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start==33)),coef_social_Departure_Constant_07_00_PM_07_30_PM +util_social_Departure_Constant_After_07_30_PM,SOCIAL - Departure Constant: After 07:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start>33)),coef_social_Departure_Constant_After_07_30_PM +util_social_Departure_Constant_Shift_for_every_30_minutes_after_08_00_pm_Linear,SOCIAL - Departure Constant: Shift for every 30 minutes after 08:00 pm - Linear,"@np.where((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.start>34), (np.where((df.start<29), np.minimum(29-df.start,8), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_social_Departure_Constant_Shift_for_every_30_minutes_after_08_00_pm_Linear +util_social_Arrival_Constant_03_00_PM_to_03_30_PM,SOCIAL - Arrival Constant: 03:00 PM to 03:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end==25)),coef_social_Arrival_Constant_03_00_PM_to_03_30_PM +util_social_Arrival_Constant_03_30_PM_to_04_00_PM,SOCIAL - Arrival Constant: 03:30 PM to 04:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end==26)),coef_social_Arrival_Constant_03_30_PM_to_04_00_PM +util_social_Arrival_Constant_04_00_PM_to_04_30_PM,SOCIAL - Arrival Constant: 04:00 PM to 04:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end==27)),coef_social_Arrival_Constant_04_00_PM_to_04_30_PM +util_social_Arrival_Constant_05_00_PM_to_06_00_PM,SOCIAL - Arrival Constant: 05:00 PM to 06:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end>=29) & (df.end<=30)),coef_social_Arrival_Constant_05_00_PM_to_06_00_PM +util_social_Arrival_Constant_Shift_for_every_30_minutes_before_08_00_pm_Linear,SOCIAL - Arrival Constant: Shift for every 30 minutes before 08:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end<35)), (np.where((df.end<35), np.minimum(35-df.end,48), 0) + np.where((df.end>40), np.minimum(df.end-40,48), 0)), 0)",coef_social_Arrival_Constant_Shift_for_every_30_minutes_before_08_00_pm_Linear +util_social_Arrival_Constant_Before_8_30_PM,SOCIAL - Arrival Constant: Before 8:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end<36)),coef_social_Arrival_Constant_Before_8_30_PM +util_social_Arrival_Constant_8_30_PM_to_9_00_PM,SOCIAL - Arrival Constant: 8:30 PM to 9:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end==36)),coef_social_Arrival_Constant_8_30_PM_to_9_00_PM +util_social_Arrival_Constant_9_00_PM_to_9_30_PM,SOCIAL - Arrival Constant: 9:00 PM to 9:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end==37)),coef_social_Arrival_Constant_9_00_PM_to_9_30_PM +util_social_Arrival_Constant_9_30_PM_to10_00_PM,SOCIAL - Arrival Constant: 9:30 PM to10:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end==38)),coef_social_Arrival_Constant_9_30_PM_to10_00_PM +util_social_Arrival_Constant_10_00_PM_to_10_30_PM,SOCIAL - Arrival Constant: 10:00 PM to 10:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end==39)),coef_social_Arrival_Constant_10_00_PM_to_10_30_PM +util_social_Arrival_Constant_After_10_30_PM,SOCIAL - Arrival Constant: After 10:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end>39)),coef_social_Arrival_Constant_After_10_30_PM +util_social_Arrival_Constant_Shift_for_every_30_minutes_after_11_00_pm_Linear,SOCIAL - Arrival Constant: Shift for every 30 minutes after 11:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.end>40)), (np.where((df.end<35), np.minimum(35-df.end,48), 0) +np.where((df.end>40),np.minimum(df.end-40,48),0)), 0)",coef_social_Arrival_Constant_Shift_for_every_30_minutes_after_11_00_pm_Linear +util_social_Duration_Constant_Shift_for_every_30_minutes_less_than_1p5_hrs_Linear,SOCIAL - Duration Constant: Shift for every 30 minutes less than 1.5 hrs - Linear,"@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration<3)) * ((np.minimum(3-df.duration,47)*(df.duration<3)) + (np.minimum(df.duration-6,47)*(df.duration>6)))",coef_social_Duration_Constant_Shift_for_every_30_minutes_less_than_1p5_hrs_Linear +util_social_Duration_Constant_Less_than_2_hours,SOCIAL - Duration Constant: Less than 2 hours,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration<4)),coef_social_Duration_Constant_Less_than_2_hours +util_social_Duration_Constant_2_hours,SOCIAL - Duration Constant: 2 hours,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration==4)),coef_social_Duration_Constant_2_hours +util_social_Duration_Constant_2p5_hours,SOCIAL - Duration Constant: 2.5 hours,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration==5)),coef_social_Duration_Constant_2p5_hours +util_social_Duration_Constant_3_hours_or_more,SOCIAL - Duration Constant: 3 hours or more,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration>5)),coef_social_Duration_Constant_3_hours_or_more +util_social_Duration_Constant_Shift_for_every_30_minutes_more_than_3p5_hrs_Linear,SOCIAL - Duration Constant: Shift for every 30 minutes more than 3.5 hrs - Linear,"@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration>6)) * ((np.minimum(3-df.duration,47)*(df.duration<3)) + (np.minimum(df.duration-6,47)*(df.duration>6)))",coef_social_Duration_Constant_Shift_for_every_30_minutes_more_than_3p5_hrs_Linear +util_social_Calibration_Constant_Duration_eq_1,SOCIAL - Calibration Constant - Duration = 1,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==0)),coef_social_Calibration_Constant_Duration_eq_1 +util_social_Calibration_Constant_Duration_eq_2,SOCIAL - Calibration Constant - Duration = 2,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration == 1)),coef_social_Calibration_Constant_Duration_eq_2 +util_social_Calibration_Constant_Duration_eq_3,SOCIAL - Calibration Constant - Duration = 3,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==2)),coef_social_Calibration_Constant_Duration_eq_3 +util_social_Calibration_Constant_Duration_eq_4,SOCIAL - Calibration Constant - Duration = 4,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==3)),coef_social_Calibration_Constant_Duration_eq_4 +util_social_Calibration_Constant_Duration_eq_5,SOCIAL - Calibration Constant - Duration = 5,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==4)),coef_social_Calibration_Constant_Duration_eq_5 +util_social_Calibration_Constant_Duration_eq_6,SOCIAL - Calibration Constant - Duration = 6,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==5)),coef_social_Calibration_Constant_Duration_eq_6 +util_social_Calibration_Constant_Duration_eq_7,SOCIAL - Calibration Constant - Duration = 7,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==6)),coef_social_Calibration_Constant_Duration_eq_7 +util_social_Calibration_Constant_Duration_eq_8,SOCIAL - Calibration Constant - Duration = 8,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==7)),coef_social_Calibration_Constant_Duration_eq_8 +util_social_Calibration_Constant_Duration_eq_9,SOCIAL - Calibration Constant - Duration = 9,@((df.tour_category == 'joint') & (df.tour_type == 'social') & (df.duration ==8)),coef_social_Calibration_Constant_Duration_eq_9 +#DISCRETIONARY,#DISCRETIONARY,,DISCRETIONARY +util_disc_Retiree_Nonworking_senior_only_HH_Duration_lt_1p5_hrs_Linear,DISCRETIONARY - Retiree/ Non-working senior only HH: Duration < 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.retired_adults_only_hh) & (df.tour_type == 'othdiscr') & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)), 0)",coef_disc_Retiree_Nonworking_senior_only_HH_Duration_lt_1p5_hrs_Linear +util_disc_Zero_auto_households_Duration_lt_1p5_hrs_Linear,DISCRETIONARY - Zero auto households: Duration < 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.auto_ownership == 0) & (df.tour_type == 'othdiscr') & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)), 0)",coef_disc_Zero_auto_households_Duration_lt_1p5_hrs_Linear +util_disc_Zero_auto_households_Duration_gt_1p5_hrs_Linear,DISCRETIONARY - Zero auto households: Duration > 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.auto_ownership == 0) & (df.tour_type == 'othdiscr') & (df.duration>3)), (np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_disc_Zero_auto_households_Duration_gt_1p5_hrs_Linear +util_disc_Number_of_auto_more_that_number_of_adults_Duration_lt_1p5_hrs_Linear,DISCRETIONARY - Number of auto more that number of adults: Duration < 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.auto_ownership > 0) & (df.tour_type == 'othdiscr') & (df.auto_ownership > df.num_adults) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)),0)",coef_disc_Number_of_auto_more_that_number_of_adults_Duration_lt_1p5_hrs_Linear +util_disc_Number_of_auto_more_that_number_of_adults_Duration_gt_1p5_hrs_Linear,DISCRETIONARY - Number of auto more that number of adults: Duration > 1.5 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.auto_ownership > 0) &(df.tour_type == 'othdiscr')&(df.auto_ownership > df.num_adults) & (df.duration>3)), (np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_disc_Number_of_auto_more_that_number_of_adults_Duration_gt_1p5_hrs_Linear +util_disc_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,DISCRETIONARY - Kids in Joint Tour: Duration < 1.5 hrs,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration<3) & ((df.ptype == 6) | (df.ptype == 7) | (df.ptype == 8))), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)), 0)",coef_disc_Kids_in_Joint_Tour_Duration_lt_1p5_hrs +util_disc_Kids_in_Joint_Tour_Duration_gt_1p5_hr,DISCRETIONARY - Kids in Joint Tour: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration>3) & ((df.ptype == 6) | (df.ptype == 7) | (df.ptype == 8))), (np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_disc_Kids_in_Joint_Tour_Duration_gt_1p5_hr +util_disc_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,DISCRETIONARY - Joint Tours Party Size > 2: Duration > 1.5 hr,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration>3) & (df.number_of_participants > 2)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)), 0)",coef_disc_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr +util_disc_Auto_Distance_Duration_lt_1_hrs_Linear,DISCRETIONARY - Auto Distance: Duration < 1 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0)) * (df.origin_to_destination_distance), 0)",coef_disc_Auto_Distance_Duration_lt_1_hrs_Linear +util_disc_Auto_Distance_Duration_gt_1_hrs_Linear,DISCRETIONARY - Auto Distance: Duration > 1 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration>3)), (np.where((df.duration>3), np.minimum(df.duration-3,47), 0)) * (df.origin_to_destination_distance), 0)",coef_disc_Auto_Distance_Duration_gt_1_hrs_Linear +util_disc_Departure_Constant_Shift_for_every_30_minutes_before_07_30_pm_Linear,DISCRETIONARY - Departure Constant: Shift for every 30 minutes before 07:30 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start<9)), (np.where((df.start<9), np.minimum(9-df.start,48), 0) + np.where((df.start>48), np.minimum(df.start-48,48),0)), 0)",coef_disc_Departure_Constant_Shift_for_every_30_minutes_before_07_30_pm_Linear +util_disc_Departure_Constant_Before_7_30_AM_,DISCRETIONARY - Departure Constant: Before 7:30 AM ,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start<10)),coef_disc_Departure_Constant_Before_7_30_AM_ +util_disc_Departure_Constant_7_30_AM_to_8_00_AM,DISCRETIONARY - Departure Constant: 7:30 AM to 8:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==10)),coef_disc_Departure_Constant_7_30_AM_to_8_00_AM +util_disc_Departure_Constant_8_00_AM_to_8_30_AM,DISCRETIONARY - Departure Constant: 8:00 AM to 8:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==11)),coef_disc_Departure_Constant_8_00_AM_to_8_30_AM +util_disc_Departure_Constant_8_30_AM_to_9_00_AM,DISCRETIONARY - Departure Constant: 8:30 AM to 9:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==12)),coef_disc_Departure_Constant_8_30_AM_to_9_00_AM +util_disc_Departure_Constant_9_00_AM_to_9_30_AM,DISCRETIONARY - Departure Constant: 9:00 AM to 9:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==13)),coef_disc_Departure_Constant_9_00_AM_to_9_30_AM +util_disc_Departure_Constant_9_30_AM_to_10_00_AM,DISCRETIONARY - Departure Constant: 9:30 AM to 10:00 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==14)),coef_disc_Departure_Constant_9_30_AM_to_10_00_AM +util_disc_Departure_Constant_10_00_AM_to_10_30_AM,DISCRETIONARY - Departure Constant: 10:00 AM to 10:30 AM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==15)),coef_disc_Departure_Constant_10_00_AM_to_10_30_AM +util_disc_Departure_Constant_Shift_for_every_30_minutes_before_04_30_pm_Linear,DISCRETIONARY - Departure Constant: Shift for every 30 minutes before 04:30 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start<28)), (np.where((df.start<28), np.minimum(28-df.start,8),0) + np.where((df.start>33), np.minimum(df.start-33,6), 0)), 0)",coef_disc_Departure_Constant_Shift_for_every_30_minutes_before_04_30_pm_Linear +util_disc_Departure_Constant_Before_05_00_PM,DISCRETIONARY - Departure Constant: Before 05:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start<29)),coef_disc_Departure_Constant_Before_05_00_PM +util_disc_Departure_Constant_05_00_PM_05_30_PM,DISCRETIONARY - Departure Constant: 05:00 PM - 05:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==29)),coef_disc_Departure_Constant_05_00_PM_05_30_PM +util_disc_Departure_Constant_05_30_PM_06_00_PM,DISCRETIONARY - Departure Constant: 05:30 PM - 06:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==30)),coef_disc_Departure_Constant_05_30_PM_06_00_PM +util_disc_Departure_Constant_06_00_PM_06_30_PM,DISCRETIONARY - Departure Constant: 06:00 PM - 06:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==31)),coef_disc_Departure_Constant_06_00_PM_06_30_PM +util_disc_Departure_Constant_06_30_PM_07_00_PM,DISCRETIONARY - Departure Constant: 06:30 PM - 07:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==32)),coef_disc_Departure_Constant_06_30_PM_07_00_PM +util_disc_Departure_Constant_After_07_00_PM,DISCRETIONARY - Departure Constant: After 07:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start>32)),coef_disc_Departure_Constant_After_07_00_PM +util_disc_Departure_Constant_Shift_for_every_30_minutes_after_07_30_pm_Linear,DISCRETIONARY - Departure Constant: Shift for every 30 minutes after 07:30 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start>33)), (np.where((df.start<28), np.minimum(28-df.start,8), 0) + np.where((df.start>33), np.minimum(df.start-33,6), 0)), 0)",coef_disc_Departure_Constant_Shift_for_every_30_minutes_after_07_30_pm_Linear +util_disc_Arrival_Constant_Shift_for_every_30_minutes_before_06_00_pm_Linear,DISCRETIONARY - Arrival Constant: Shift for every 30 minutes before 06:00 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end<31)), (np.where((df.end<31), np.minimum(31-df.end,48), 0) + np.where((df.end>37), np.minimum(df.end-37,48), 0)), 0)",coef_disc_Arrival_Constant_Shift_for_every_30_minutes_before_06_00_pm_Linear +util_disc_Arrival_Constant_Before_6_30_PM,DISCRETIONARY - Arrival Constant: Before 6:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end<32)),coef_disc_Arrival_Constant_Before_6_30_PM +util_disc_Arrival_Constant_6_30_PM_to_7_00_PM,DISCRETIONARY - Arrival Constant: 6:30 PM to 7:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end==32)),coef_disc_Arrival_Constant_6_30_PM_to_7_00_PM +util_disc_Arrival_Constant_7_00_PM_to_7_30_PM,DISCRETIONARY - Arrival Constant: 7:00 PM to 7:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end==33)),coef_disc_Arrival_Constant_7_00_PM_to_7_30_PM +util_disc_Arrival_Constant_7_30_PM_to_8_00_PM,DISCRETIONARY - Arrival Constant: 7:30 PM to 8:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end==34)),coef_disc_Arrival_Constant_7_30_PM_to_8_00_PM +util_disc_Arrival_Constant_8_00_PM_to_8_30_PM,DISCRETIONARY - Arrival Constant: 8:00 PM to 8:30 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end==35)),coef_disc_Arrival_Constant_8_00_PM_to_8_30_PM +util_disc_Arrival_Constant_8_30_PM_to_9_00_PM,DISCRETIONARY - Arrival Constant: 8:30 PM to 9:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end==36)),coef_disc_Arrival_Constant_8_30_PM_to_9_00_PM +util_disc_Arrival_Constant_After_9_00_PM,DISCRETIONARY - Arrival Constant: After 9:00 PM,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end>36)),coef_disc_Arrival_Constant_After_9_00_PM +util_disc_Arrival_Constant_Shift_for_every_30_minutes_after_09_30_pm_Linear,DISCRETIONARY - Arrival Constant: Shift for every 30 minutes after 09:30 pm - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.end>37)), (np.where((df.end<31), np.minimum(31-df.end,48), 0) + np.where((df.end>37), np.minimum(df.end-37,48),0)), 0)",coef_disc_Arrival_Constant_Shift_for_every_30_minutes_after_09_30_pm_Linear +util_disc_Duration_Constant_0_hours,DISCRETIONARY - Duration Constant: 0 hours,@(df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration==0),coef_disc_Duration_Constant_0_hours +util_disc_Duration_Constant_0p5_hous,DISCRETIONARY - Duration Constant: 0.5 hous,@(df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration==1),coef_disc_Duration_Constant_0p5_hous +util_disc_Duration_Constant_1_hour,DISCRETIONARY - Duration Constant: 1 hour,@(df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration==2),coef_disc_Duration_Constant_1_hour +util_disc_Duration_Constant_1p5_hours,DISCRETIONARY - Duration Constant: 1.5 hours,@(df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration==3),coef_disc_Duration_Constant_1p5_hours +util_disc_Duration_Constant_2_hours,DISCRETIONARY - Duration Constant: 2 hours,@(df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration==4),coef_disc_Duration_Constant_2_hours +util_disc_Duration_Constant_2p5_hours_or_more,DISCRETIONARY - Duration Constant: 2.5 hours or more,@(df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration>4),coef_disc_Duration_Constant_2p5_hours_or_more +util_disc_Duration_Constant_Shift_for_every_30_minutes_more_than_3_hrs_Linear,DISCRETIONARY - Duration Constant: Shift for every 30 minutes more than 3 hrs - Linear,"@np.where(((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration>5)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>5), np.minimum(df.duration-5,47), 0)), 0)",coef_disc_Duration_Constant_Shift_for_every_30_minutes_more_than_3_hrs_Linear +util_disc_Calibration_Constant_Duration_eq_4,DISCRETIONARY -Calibration Constant - Duration = 4,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration==3)),coef_disc_Calibration_Constant_Duration_eq_4 +util_disc_Calibration_Constant_Duration_eq_5,DISCRETIONARY -Calibration Constant - Duration = 5,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.duration==4)),coef_disc_Calibration_Constant_Duration_eq_5 +util_disc_Calibration_Constant_Departure_eq_29,DISCRETIONARY -Calibration Constant - Departure = 29,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==29)),coef_disc_Calibration_Constant_Departure_eq_29 +util_disc_Calibration_Constant_Departure_eq_30,DISCRETIONARY -Calibration Constant - Departure = 30,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==30)),coef_disc_Calibration_Constant_Departure_eq_30 +util_disc_Calibration_Constant_Departure_eq_31,DISCRETIONARY -Calibration Constant - Departure = 31,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==31)),coef_disc_Calibration_Constant_Departure_eq_31 +util_disc_Calibration_Constant_Departure_eq_32,DISCRETIONARY -Calibration Constant - Departure = 32,@((df.tour_category == 'joint') & (df.tour_type == 'othdiscr') & (df.start==32)),coef_disc_Calibration_Constant_Departure_eq_32 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_joint_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_joint_coeffs.csv new file mode 100644 index 000000000..1717ce523 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_joint_coeffs.csv @@ -0,0 +1,307 @@ +coefficient_name,value,constrain +coef_escort_Mode_Choice_Logsum,1.173173034,F +coef_escort_Distance_to_destination_Duration_less_than_0p5_hours_depart_and_arrive_in_the_same_period,-0.335017673,F +coef_escort_Distance_to_destination_Duration_greater_than_0p5_hours,0.005298165,F +coef_escort_Fulltime_worker_Departure_after_8_00_am_Linear,-0.037980109,F +coef_escort_Fulltime_worker_Departure_after_3_00_am_Linear,0.163254125,F +coef_escort_Fulltime_worker_Duration_lt_0p5_hrs,-0.275077482,F +coef_escort_Fulltime_worker_Duration_gt_0p5_hrs,0.051530545,F +coef_escort_University_student_Duration_lt_0p5_hrs,-0.426802718,F +coef_escort_Nondriving_age_student_Duration_gt_0p5_hrs,0.240582361,F +coef_escort_Driving_age_student_Duration_lt_0p5_hrs,-0.554146191,F +coef_escort_Driving_age_student_Duration_gt_0p5_hrs,0.299387708,F +coef_escort_Preschool_kid_Duration_gt_0p5_hrs,0.195482563,F +coef_escort_Medhigh_income_60k_to_120k_Duration_gt_0p5_hrs,-0.029281467,F +coef_escort_Households_with_no_kids_Dummy_1_0_Departure_before_7_30_AM,0.589083327,F +coef_escort_Households_with_no_kids_Dummy_1_0_Departure_after_8_00_AM,0.086690827,F +coef_escort_Households_with_no_kids_Dummy_1_0_Departure_before_2_30_PM,0.477582648,F +coef_escort_Households_with_no_kids_Dummy_1_0_Departure_after_3_00_PM,-0.204065502,F +coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_before_8_00_AM,-0.360039254,F +coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_after_8_30_AM,0.091614107,F +coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_before_3_00_PM,0.432854268,F +coef_escort_Households_with_no_kids_Dummy_1_0_Arrival_after_3_30_PM,0.131037275,F +coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_8_00_AM,0.109700265,F +coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_3_00_PM,-0.224568648,F +coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_before_8_00_AM,-0.357416434,F +coef_escort_PreSchool_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_before_3_00_PM,0.629285298,F +coef_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Departure_after_8_00_AM,0.039005148,F +coef_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_after_8_30_AM,-0.06556611,F +coef_escort_Driving_age_School_Child_in_HH_with_Mandatory_tour_Dummy_1_0_Arrival_after_3_30_PM,0.117680977,F +coef_escort_Number_of_autos_greater_than_number_of_adults_Duration_gt_0p5_hrs,-0.057322708,F +coef_escort_Number_of_Individual_Tours_excluding_escorting_Duration_gt_0p5_hrs,-0.062899692,F +coef_escort_Number_of_joint_tours_Duration_gt_0p5_hrs,-0.048533895,F +coef_escort_Departure_Constant_Shift_for_every_30_minutes_before_06_30_am_Linear,-1.469240002,F +coef_escort_Departure_Constant_Before_07_00_AM,-2.070292862,F +coef_escort_Departure_Constant_07_00_AM_07_30_AM,-0.642734296,F +coef_escort_Departure_Constant_07_30_AM_08_00_AM,0,T +coef_escort_Departure_Constant_08_00_AM_08_30_AM,-0.214617667,F +coef_escort_Departure_Constant_08_30_AM_09_00_AM,-0.147266606,F +coef_escort_Departure_Constant_After_09_00_AM,-1.356686422,F +coef_escort_Departure_Constant_01_30_PM_02_00_PM,0.368092381,F +coef_escort_Departure_Constant_02_00_PM_02_30_PM,1.166803383,F +coef_escort_Departure_Constant_02_30_PM_03_00_PM,1.28466083,F +coef_escort_Departure_Constant_03_00_PM_03_30_PM,0.581891245,F +coef_escort_Departure_Constant_After_03_30_PM,0.834510243,F +coef_escort_Departure_Constant_Shift_for_every_30_minutes_after_9_30_am_Linear,0.175257649,F +coef_escort_Departure_Constant_Shift_for_every_30_minutes_after_4_00_pm_Linear,-0.019161202,F +coef_escort_Arrival_Constant_Shift_for_every_30_minutes_before_6_30_am_Linear,0.44978138,F +coef_escort_Arrival_Constant_Before_07_00_AM,0.549584585,F +coef_escort_Arrival_Constant_07_00_AM_07_30_AM,0.488181278,F +coef_escort_Arrival_Constant_07_30_AM_08_00_AM,0.236447651,F +coef_escort_Arrival_Constant_08_00_AM_08_30_AM,0,T +coef_escort_Arrival_Constant_08_30_AM_09_00_AM,-0.683756801,F +coef_escort_Arrival_Constant_After_09_00_AM,-1.428888485,F +coef_escort_Arrival_Constant_02_30_PM_03_00_PM,1.311480662,F +coef_escort_Arrival_Constant_03_00_PM_03_30_PM,1.316883154,F +coef_escort_Arrival_Constant_03_30_PM_04_00_PM,1.396838392,F +coef_escort_Arrival_Constant_04_00_PM_04_30_PM,1.03146139,F +coef_escort_Arrival_Constant_After_04_30_PM,0.907344583,F +coef_escort_Arrival_Constant_Shift_for_every_30_minutes_after_9_30_am_Linear,-0.148408887,F +coef_escort_Arrival_Constant_Shift_for_every_30_minutes_after_5_00_pm_Linear,-0.389082896,F +coef_escort_Duration_Constant_0_hrs,-0.173757322,F +coef_escort_Duration_Constant_0p5_hrs,0,T +coef_escort_Duration_Constant_1_hrs,-0.431287743,F +coef_escort_Duration_Constant_1p5hrs,-0.700473959,F +coef_escort_Duration_Constant_2_hrs,-1.071871358,F +coef_escort_Duration_Constant_Longer_than_2_hrs,-1.691098421,F +coef_escort_Calibration_Constant_Duration_eq_1,-0.047200214,F +coef_escort_Calibration_Constant_Duration_eq_2,0.035611332,F +coef_escort_Calibration_Constant_Departure_eq_9,0.106814756,F +coef_escort_Calibration_Constant_Departure_eq_10,0.215386864,F +coef_escort_Calibration_Constant_Departure_eq_23,-0.255087318,F +coef_escort_Calibration_Constant_Departure_eq_24,-0.296870428,F +coef_shop_Joint_Shopping_tours_dummy_Departure_before_10_00_AM_Linear,-0.190727375,F +coef_shop_Joint_Shopping_tours_dummy_Departure_after_10_30_AM_Linear,-0.029551313,F +coef_shop_Joint_Tours_Party_Size_gt_2_Duration_lt_1p5_hrs,-0.291965906,F +coef_shop_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,0.045755784,F +coef_shop_Joint_Tour_with_only_adults_Duration_lt_1p5_hrs,-0.571185116,F +coef_shop_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,-0.468815184,F +coef_shop_Kids_in_Joint_Tour_Duration_gt_1p5_hr,-0.047470039,F +coef_shop_Low_Income_lteq25_000_Duration_gt_1p5_hr,0.040776383,F +coef_shop_Medium_Income_25_001_to_60_000_Duration_lt_1p5_hrs,0.108462927,F +coef_shop_MediumHigh_Income_60_001_to_120_00_Duration_gt_1p5_hr,-0.037893416,F +coef_shop_Distance_Duration_lt_1p5_hrs,-0.214802537,F +coef_shop_Distance_Duration_gt_1p5_hr,0.007991656,F +coef_shop_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Linear,-0.959875456,F +coef_shop_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Square_root,1.112594898,F +coef_shop_Departure_Constant_Before_09_00_AM,-0.446394064,F +coef_shop_Departure_Constant_09_00_AM_09_30_AM,-0.021669265,F +coef_shop_Departure_Constant_09_30_AM_10_00_AM,-0.282978638,F +coef_shop_Departure_Constant_10_00_AM_10_30_AM,0,T +coef_shop_Departure_Constant_10_30_AM_11_00_AM,-0.309421311,F +coef_shop_Departure_Constant_After_11_00_AM,-0.541073357,F +coef_shop_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Linear,-0.072013428,F +coef_shop_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Squared,-0.000653398,F +coef_shop_Arrival_Constant_Shift_for_every_30_minutes_before_12_00_pm_Linear,-0.18376635,F +coef_shop_Arrival_Constant_Before_12_30_PM,-0.716195343,F +coef_shop_Arrival_Constant_12_30_PM_03_00_PM,-0.502714001,F +coef_shop_Arrival_Constant_03_00_PM_03_30_PM,-0.167868872,F +coef_shop_Arrival_Constant_03_30_PM_04_00_PM,-0.156786941,F +coef_shop_Arrival_Constant_04_00_PM_04_30_PM,0,T +coef_shop_Arrival_Constant_04_30_PM_05_00_PM,-0.057314044,F +coef_shop_Arrival_Constant_05_00_PM_05_30_PM,-0.580040851,F +coef_shop_Arrival_Constant_05_30_PM_07_00_PM,-0.32239566,F +coef_shop_Arrival_Constant_07_00_PM_09_30_PM,-0.347828147,F +coef_shop_Arrival_Constant_After_09_30_PM,-1.123574723,F +coef_shop_Arrival_Constant_Shift_for_every_30_minutes_after_10_00_pm_Linear,-0.499770654,F +coef_shop_Duration_Constant_0_hrs,-0.131743185,F +coef_shop_Duration_Constant_0p5_hrs,0.888857137,F +coef_shop_Duration_Constant_1_hrs,0,T +coef_shop_Duration_Constant_1p5hrs,-0.333413031,F +coef_shop_Duration_Constant_2_hrs,-0.850897912,F +coef_shop_Duration_Constant_Longer_than_2_hrs,-1.203783479,F +coef_shop_Duration_Constant_Duration_gt_2p5_hrs_Linear,-0.293581223,F +coef_shop_Duration_Constant_Duration_gt_2p5_hrs_Square_root,-0.215759138,F +coef_shop_Calibration_Constant_Duration_eq_1,-0.138450424,F +coef_shop_Calibration_Constant_Duration_eq_2,-0.092704403,F +coef_shop_Calibration_Constant_Duration_eq_3,-0.087738073,F +coef_maint_Joint_Maintenance_tours_dummy_Departure_before_10_00_AM_Linear,-0.139150288,F +coef_maint_Joint_Maintenance_tours_dummy_Departure_after_10_30_AM_Linear,-0.065786345,F +coef_maint_Joint_Tours_Party_Size_gt_2_Duration_lt_1p5_hrs,-0.291965906,F +coef_maint_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,0.045755784,F +coef_maint_Joint_Tour_with_only_adults_Duration_lt_1p5_hrs,-0.571185116,F +coef_maint_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,-0.468815184,F +coef_maint_Kids_in_Joint_Tour_Duration_gt_1p5_hr,-0.047470039,F +coef_maint_Low_Income_lteq25_000_Duration_gt_1p5_hr,0.040776383,F +coef_maint_Medium_Income_25_001_to_60_000_Duration_lt_1p5_hrs,0.108462927,F +coef_maint_Medium_Income_25_001_to_60_000_Duration_gt_1p5_hr,0,T +coef_maint_MediumHigh_Income_60_001_to_120_00_Duration_gt_1p5_hr,-0.037893416,F +coef_maint_Distance_Duration_lt_1p5_hrs,-0.214802537,F +coef_maint_Distance_Duration_gt_1p5_hr,0.007991656,F +coef_maint_Departure_Constant_Shift_for_every_30_minutes_before_07_30_am_Linear,-0.864112609,F +coef_maint_Departure_Constant_Shift_for_every_30_minutes_before_07_30_am_Square_Root,0.504598473,F +coef_maint_Departure_Constant_Before_08_00_AM,-0.383711788,F +coef_maint_Departure_Constant_08_00_AM_08_30_AM,-0.076771517,F +coef_maint_Departure_Constant_08_30_AM_09_00_AM,-0.169259979,F +coef_maint_Departure_Constant_09_00_AM_09_30_AM,-0.051785379,F +coef_maint_Departure_Constant_09_30_AM_10_00_AM,-0.214942451,F +coef_maint_Departure_Constant_10_00_AM_10_30_AM,0,T +coef_maint_Departure_Constant_10_30_AM_11_00_AM,-0.427568963,F +coef_maint_Departure_Constant_After_11_00_AM,-0.520863411,F +coef_maint_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Linear,0.042879095,F +coef_maint_Departure_Constant_Shift_for_every_30_minutes_after_11_30_am_Squared,-0.003157293,F +coef_maint_Arrival_Constant_Shift_for_every_30_minutes_before_10_00_am_Linear,-0.226803619,F +coef_maint_Arrival_Constant_Before_10_30_AM,-0.223212258,F +coef_maint_Arrival_Constant_10_30_AM_11_00_AM,0,T +coef_maint_Arrival_Constant_11_00_AM_11_30_AM,-0.128382637,F +coef_maint_Arrival_Constant_11_30_AM_01_30_PM,0.167977332,F +coef_maint_Arrival_Constant_01_30_PM_02_30_PM,-0.149495878,F +coef_maint_Arrival_Constant_02_30_PM_04_00_PM,0.087679934,F +coef_maint_Arrival_Constant_04_00_PM_04_30_PM,0.121707557,F +coef_maint_Arrival_Constant_After_04_30_PM,0.106745013,F +coef_maint_Arrival_Constant_Shift_for_every_30_minutes_after_5_00_pm_Linear,-0.232610927,F +coef_maint_Duration_Constant_0_hrs,-0.483549396,F +coef_maint_Duration_Constant_0p5_hrs,0,T +coef_maint_Duration_Constant_Longer_than_0p5_hrs,-1.450618319,F +coef_maint_Duration_Constant_Duration_gt_1_hrs_Linear,-0.275082922,F +coef_maint_Duration_Constant_Duration_gt_1_hrs_Square_Root,0.208434683,F +coef_maint_Calibration_Constant_Duration_eq_1,-0.124602605,F +coef_maint_Calibration_Constant_Duration_eq_2,-0.103637715,F +coef_maint_Calibration_Constant_Duration_eq_3,-0.225442145,F +coef_maint_Calibration_Constant_Duration_eq_4,-0.145273012,F +coef_maint_Calibration_Constant_Duration_eq_5,-0.019241539,F +coef_eatout_Distance_to_destination_Duration_lt_1_hrs,-0.134981987,F +coef_eatout_Distance_to_destination_Duration_gt_1_hrs,0.017860742,F +coef_eatout_Low_income_lt25000_Duration_lt_1_hrs,1.002485807,F +coef_eatout_Medium_25k_to_60k_Duration_lt_1_hrs,0.499822018,F +coef_eatout_Zero_auto_HH_Duration_gt_1_hrs,0.259409942,F +coef_eatout_Kids_in_Joint_tour_Duration_lt_1_hrs,1.785123348,F +coef_eatout_Joint_Tours_Party_Size_greater_than_2_Duration_lt_1_hrs,-1.626003709,F +coef_eatout_Departure_Constant_11_00_AM_12_00_PM,0.531539506,F +coef_eatout_Departure_Constant_12_00_PM_12_30_PM,0.673838195,F +coef_eatout_Departure_Constant_12_30_PM_to_01_00_PM,0.422292261,F +coef_eatout_Departure_Constant_Shift_for_every_30_minutes_before_05_00_pm_Linear,-0.033290717,F +coef_eatout_Departure_Constant_Before_05_30_PM,-0.561079452,F +coef_eatout_Departure_Constant_05_30_PM_06_00_PM,-0.178719161,F +coef_eatout_Departure_Constant_06_00_PM_06_30_PM,0,T +coef_eatout_Departure_Constant_06_30_PM_07_00_PM,-0.282095841,F +coef_eatout_Departure_Constant_07_00_PM_07_30_PM,-0.299748613,F +coef_eatout_Departure_Constant_After_07_30_PM,-0.845300559,F +coef_eatout_Departure_Constant_Shift_for_every_30_minutes_after_08_00_pm_Linear,-0.667843486,F +coef_eatout_Arrival_Constant_12_30_PM_to_01_00_PM,2.002032369,F +coef_eatout_Arrival_Constant_01_00_PM_to_01_30_PM,2.115334472,F +coef_eatout_Arrival_Constant_01_30_PM_to_02_00_PM,1.647879687,F +coef_eatout_Arrival_Constant_02_00_PM_to_02_30_PM,1.525310078,F +coef_eatout_Arrival_Constant_Shift_for_every_30_minutes_before_06_30_pm_Linear,-0.152980854,F +coef_eatout_Arrival_Constant_Before_7_00_PM,-0.41165142,F +coef_eatout_Arrival_Constant_7_00_PM_to_7_30_PM,-0.384557379,F +coef_eatout_Arrival_Constant_7_30_PM_to_8_00_PM,-0.044050359,F +coef_eatout_Arrival_Constant_8_00_PM_to_8_30_PM,0,T +coef_eatout_Arrival_Constant_8_30_PM_to_9_00_PM,-0.239939049,F +coef_eatout_Arrival_Constant_After_09_00_PM,-0.248639696,F +coef_eatout_Arrival_Constant_Shift_for_every_30_minutes_after_09_30_pm_Linear,-0.204771082,F +coef_eatout_Duration_Constant_Shift_for_every_30_minutes_more_than_3_hrs_Linear,-0.3357414,F +coef_eatout_Duration_Constant_0_hours,-4.268996522,F +coef_eatout_Duration_Constant_0p5_hous,-1.323297693,F +coef_eatout_Duration_Constant_1_hour,0,T +coef_eatout_Duration_Constant_1p5_hours,-0.195669185,F +coef_eatout_Duration_Constant_2_hours_or_more,-0.523723192,F +coef_eatout_Duration_Constant_Shift_for_every_30_minutes_more_than_2p5_hrs_Linear,-0.649331488,F +coef_eatout_Calibration_Constant_Duration_eq_1,-0.333697861,F +coef_eatout_Calibration_Constant_Duration_eq_2,-0.245716,F +coef_eatout_Calibration_Constant_Duration_eq_3,0.052708833,F +coef_eatout_Calibration_Constant_Duration_eq_4,0.041571499,F +coef_eatout_Calibration_Constant_Departure_eq_1,-10,F +coef_eatout_Calibration_Constant_Departure_eq_2,-10,F +coef_eatout_Calibration_Constant_Departure_eq_3,-10,F +coef_eatout_Calibration_Constant_Departure_eq_17,0.706568704,F +coef_eatout_Calibration_Constant_Departure_eq_18,0.634353544,F +coef_eatout_Calibration_Constant_Departure_eq_19,0.584387268,F +coef_eatout_Calibration_Constant_Departure_eq_20,0.469777884,F +coef_eatout_Calibration_Constant_Departure_eq_21,0.39548931,F +coef_social_Retiree_Nonworking_senior_only_HH_Duration_lt_1p5_hrs_Linear,-0.312282762,F +coef_social_Zero_auto_households_Duration_lt_1p5_hrs_Linear,-0.508439932,F +coef_social_Zero_auto_households_Duration_gt_1p5_hrs_Linear,0.074190914,F +coef_social_Number_of_auto_more_that_number_of_adults_Duration_lt_1p5_hrs_Linear,0.127185965,F +coef_social_Number_of_auto_more_that_number_of_adults_Duration_gt_1p5_hrs_Linear,0.048756122,F +coef_social_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,-0.559947083,F +coef_social_Kids_in_Joint_Tour_Duration_gt_1p5_hr,-0.115347031,F +coef_social_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,0.104494637,F +coef_social_Auto_Distance_Duration_lt_1_hrs_Linear,-0.162965435,F +coef_social_Auto_Distance_Duration_gt_1_hrs_Linear,0.006797399,F +coef_social_Departure_Constant_Shift_for_every_30_minutes_before_08_30_am_Linear,-0.529943196,F +coef_social_Departure_Constant_Before_09_00_AM,-0.198438086,F +coef_social_Departure_Constant_09_00_AM_to_09_30_AM,0.137620628,F +coef_social_Departure_Constant_Shift_for_every_30_minutes_before_05_00_pm_Linear,-0.142078961,F +coef_social_Departure_Constant_Before_05_30_PM,-0.390965052,F +coef_social_Departure_Constant_05_30_PM_06_00_PM,-0.453580491,F +coef_social_Departure_Constant_06_00_PM_06_30_PM,0,T +coef_social_Departure_Constant_06_30_PM_07_00_PM,-0.088537991,F +coef_social_Departure_Constant_07_00_PM_07_30_PM,0.052983115,F +coef_social_Departure_Constant_After_07_30_PM,-0.649629162,F +coef_social_Departure_Constant_Shift_for_every_30_minutes_after_08_00_pm_Linear,-0.09574499,F +coef_social_Arrival_Constant_03_00_PM_to_03_30_PM,0.37674882,F +coef_social_Arrival_Constant_03_30_PM_to_04_00_PM,0.583355461,F +coef_social_Arrival_Constant_04_00_PM_to_04_30_PM,0.727855233,F +coef_social_Arrival_Constant_05_00_PM_to_06_00_PM,0.249551955,F +coef_social_Arrival_Constant_Shift_for_every_30_minutes_before_08_00_pm_Linear,0.053771388,F +coef_social_Arrival_Constant_Before_8_30_PM,0.308763611,F +coef_social_Arrival_Constant_8_30_PM_to_9_00_PM,-0.208797698,F +coef_social_Arrival_Constant_9_00_PM_to_9_30_PM,-0.336319511,F +coef_social_Arrival_Constant_9_30_PM_to10_00_PM,0,T +coef_social_Arrival_Constant_10_00_PM_to_10_30_PM,-0.055707591,F +coef_social_Arrival_Constant_After_10_30_PM,-0.612356296,F +coef_social_Arrival_Constant_Shift_for_every_30_minutes_after_11_00_pm_Linear,-0.348479901,F +coef_social_Duration_Constant_Shift_for_every_30_minutes_less_than_1p5_hrs_Linear,0.619073863,F +coef_social_Duration_Constant_Less_than_2_hours,-0.584024011,F +coef_social_Duration_Constant_2_hours,-0.271552271,F +coef_social_Duration_Constant_2p5_hours,0,T +coef_social_Duration_Constant_3_hours_or_more,0.042083404,F +coef_social_Duration_Constant_Shift_for_every_30_minutes_more_than_3p5_hrs_Linear,-0.13049452,F +coef_social_Calibration_Constant_Duration_eq_1,-1.346772472,F +coef_social_Calibration_Constant_Duration_eq_2,0.377121689,F +coef_social_Calibration_Constant_Duration_eq_3,0.179818928,F +coef_social_Calibration_Constant_Duration_eq_4,-0.283418619,F +coef_social_Calibration_Constant_Duration_eq_5,-0.103541313,F +coef_social_Calibration_Constant_Duration_eq_6,-0.03704707,F +coef_social_Calibration_Constant_Duration_eq_7,-0.062437167,F +coef_social_Calibration_Constant_Duration_eq_8,0.047640282,F +coef_social_Calibration_Constant_Duration_eq_9,0.284369793,F +coef_disc_Retiree_Nonworking_senior_only_HH_Duration_lt_1p5_hrs_Linear,-0.312282762,F +coef_disc_Zero_auto_households_Duration_lt_1p5_hrs_Linear,-0.508439932,F +coef_disc_Zero_auto_households_Duration_gt_1p5_hrs_Linear,0.074190914,F +coef_disc_Number_of_auto_more_that_number_of_adults_Duration_lt_1p5_hrs_Linear,0.127185965,F +coef_disc_Number_of_auto_more_that_number_of_adults_Duration_gt_1p5_hrs_Linear,0.048756122,F +coef_disc_Kids_in_Joint_Tour_Duration_lt_1p5_hrs,-0.559947083,F +coef_disc_Kids_in_Joint_Tour_Duration_gt_1p5_hr,-0.115347031,F +coef_disc_Joint_Tours_Party_Size_gt_2_Duration_gt_1p5_hr,0.104494637,F +coef_disc_Auto_Distance_Duration_lt_1_hrs_Linear,-0.162965435,F +coef_disc_Auto_Distance_Duration_gt_1_hrs_Linear,0.006797399,F +coef_disc_Departure_Constant_Shift_for_every_30_minutes_before_07_30_pm_Linear,-0.742176805,F +coef_disc_Departure_Constant_Before_7_30_AM_,-1.323901585,F +coef_disc_Departure_Constant_7_30_AM_to_8_00_AM,-0.695441631,F +coef_disc_Departure_Constant_8_00_AM_to_8_30_AM,-0.269903336,F +coef_disc_Departure_Constant_8_30_AM_to_9_00_AM,-0.093709211,F +coef_disc_Departure_Constant_9_00_AM_to_9_30_AM,0.265634082,F +coef_disc_Departure_Constant_9_30_AM_to_10_00_AM,0.287521134,F +coef_disc_Departure_Constant_10_00_AM_to_10_30_AM,0.396547817,F +coef_disc_Departure_Constant_Shift_for_every_30_minutes_before_04_30_pm_Linear,-0.245885745,F +coef_disc_Departure_Constant_Before_05_00_PM,-1.344482349,F +coef_disc_Departure_Constant_05_00_PM_05_30_PM,-0.622632748,F +coef_disc_Departure_Constant_05_30_PM_06_00_PM,-0.456718676,F +coef_disc_Departure_Constant_06_00_PM_06_30_PM,-0.206896106,F +coef_disc_Departure_Constant_06_30_PM_07_00_PM,0,T +coef_disc_Departure_Constant_After_07_00_PM,-0.46439343,F +coef_disc_Departure_Constant_Shift_for_every_30_minutes_after_07_30_pm_Linear,-0.291998986,F +coef_disc_Arrival_Constant_Shift_for_every_30_minutes_before_06_00_pm_Linear,0.148649188,F +coef_disc_Arrival_Constant_Before_6_30_PM,0.668775963,F +coef_disc_Arrival_Constant_6_30_PM_to_7_00_PM,-0.053520826,F +coef_disc_Arrival_Constant_7_00_PM_to_7_30_PM,0.099726391,F +coef_disc_Arrival_Constant_7_30_PM_to_8_00_PM,0.063414092,F +coef_disc_Arrival_Constant_8_00_PM_to_8_30_PM,0,T +coef_disc_Arrival_Constant_8_30_PM_to_9_00_PM,-0.18610847,F +coef_disc_Arrival_Constant_After_9_00_PM,-0.423207857,F +coef_disc_Arrival_Constant_Shift_for_every_30_minutes_after_09_30_pm_Linear,-0.525545923,F +coef_disc_Duration_Constant_0_hours,-0.944257762,F +coef_disc_Duration_Constant_0p5_hous,-0.117695955,F +coef_disc_Duration_Constant_1_hour,0.438403665,F +coef_disc_Duration_Constant_1p5_hours,-0.002500048,F +coef_disc_Duration_Constant_2_hours,0,T +coef_disc_Duration_Constant_2p5_hours_or_more,0.239192556,F +coef_disc_Duration_Constant_Shift_for_every_30_minutes_more_than_3_hrs_Linear,-0.108260689,F +coef_disc_Calibration_Constant_Duration_eq_4,-0.132674257,F +coef_disc_Calibration_Constant_Duration_eq_5,-0.013371871,F +coef_disc_Calibration_Constant_Departure_eq_29,0.232927977,F +coef_disc_Calibration_Constant_Departure_eq_30,0.306104612,F +coef_disc_Calibration_Constant_Departure_eq_31,0.285520678,F +coef_disc_Calibration_Constant_Departure_eq_32,0.115886631,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_eatout.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_eatout.csv new file mode 100644 index 000000000..6c02794aa --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_eatout.csv @@ -0,0 +1,60 @@ +Label,Description,Expression,Coefficient +#EAT-OUT,#EAT-OUT,,#EAT-OUT +util_eatout_distance_to_destination_duration_less_than_1_hr,EAT-OUT - Distance to destination - Duration < 1 hr,"@np.where(((df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,14), 0)) * (df.origin_to_destination_distance), 0)",coef_eatout_distance_to_destination_duration_less_than_1_hr +util_eatout_distance_to_destination_duration_greater_than_1_hr,EAT-OUT - Distance to destination - Duration > 1 hr,"@np.where(((df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,14), 0)) *(df.origin_to_destination_distance), 0)",coef_eatout_distance_to_destination_duration_greater_than_1_hr +util_eatout_low_income_duration_less_than_1_hr,EAT-OUT - Low income (<25000) - Duration < 1 hr,"@np.where(((df.is_income_less25K) & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,14), 0)), 0)",coef_eatout_low_income_duration_less_than_1_hr +util_eatout_medium_income_duration_less_than_1_hr,EAT-OUT - Medium (25k to 60k) - Duration < 1 hr,"@np.where(((df.is_income_25K_to_60K) & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,14), 0)), 0)",coef_eatout_medium_income_duration_less_than_1_hr +util_eatout_zeroauto_HH_duration_greater_than_1_hr,EAT-OUT - Zero auto HH - Duration > 1 hrs,"@np.where(((df.auto_ownership == 0) & (df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,14), 0)), 0)",coef_eatout_zeroauto_HH_duration_greater_than_1_hr +util_eatout_university_student_departure_after_7_pm_linear,EAT-OUT - University student - Departure after 7:00 pm - Linear,"@np.where(((df.start>32) & (df.ptype == 3)), (np.where((df.start<=32), np.minimum(32-df.start,29), 0) + np.where((df.start>32), np.minimum(df.start-32,8), 0)), 0)",coef_eatout_university_student_departure_after_7_pm_linear +util_eatout_female_duration_less_than_1_hr,EAT-OUT - Female - Duration < 1 hr,"@np.where(((df.duration<2) & (df.female)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,14), 0)), 0)",coef_eatout_female_duration_less_than_1_hr +util_eatout_female_duration_greater_than_1_hr,EAT-OUT - Female - Duration > 1 hr,"@np.where(((df.duration>2) & (df.female)), (np.where((df.duration<=2), np.minimum(2-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,14), 0)), 0)",coef_eatout_female_duration_greater_than_1_hr +util_eatout_time_pressure_departure_before_6_30_pm,EAT-OUT - Time Pressure - Departure before 6:30 pm,"@np.where(((df.start<32)), (np.minimum(32-df.start,29)) * (np.log10 (30 *(tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num)))), 0)",coef_eatout_time_pressure_departure_before_6_30_pm +util_eatout_time_pressure_duration_less_than_1_hr,EAT-OUT - Time Pressure - Duration < 1 hrs,"@np.where(((df.duration<2)), np.minimum(2-df.duration,47) * (np.log10 (30 * (tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num)))), 0)",coef_eatout_time_pressure_duration_less_than_1_hr +util_eatout_departure_constant_7_30_am_to_9_am,EAT-OUT - Departure Constant: 07:30 AM - 09:00 AM,@((df.start>=10) & (df.start<=12)),coef_eatout_departure_constant_7_30_am_to_9_am +util_eatout_departure_constant_10_30_am_to_11_am,EAT-OUT - Departure Constant: 10:30 AM - 11:00 AM,@((df.start==16)),coef_eatout_departure_constant_10_30_am_to_11_am +util_eatout_departure_constant_11_am_to_11_30_am,EAT-OUT - Departure Constant: 11:00 AM - 11:30 AM,@((df.start==17)),coef_eatout_departure_constant_11_am_to_11_30_am +util_eatout_departure_constant_11_30_am_to_12_pm,EAT-OUT - Departure Constant: 11:30 AM - 12:00 PM,@((df.start==18)),coef_eatout_departure_constant_11_30_am_to_12_pm +util_eatout_departure_constant_12_pm_to_12_30_pm,EAT-OUT - Departure Constant: 12:00 PM - 12:30 PM,@((df.start==19)),coef_eatout_departure_constant_12_pm_to_12_30_pm +util_eatout_departure_constant_12_30_pm_to_1_pm,EAT-OUT - Departure Constant: 12:30 PM - 01:00 PM,@((df.start==20)),coef_eatout_departure_constant_12_30_pm_to_1_pm +util_eatout_departure_constant_1_pm_to_1_30_pm,EAT-OUT - Departure Constant: 01:00 PM - 01:30 PM,@((df.start==21)),coef_eatout_departure_constant_1_pm_to_1_30_pm +util_eatout_departure_constant_shift_for_every_30_minutes_before_5_30_pm_linear,EAT-OUT - Departure Constant: Shift for every 30 minutes before 05:30 pm - Linear,"@np.where(((df.start<31)), (np.where((df.start<30), np.minimum(30-df.start,27), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_eatout_departure_constant_shift_for_every_30_minutes_before_5_30_pm_linear +util_eatout_departure_constant_before_6_pm,EAT-OUT - Departure Constant: Before 06:00 PM,@((df.start<31)),coef_eatout_departure_constant_before_6_pm +util_eatout_departure_constant_6_pm_to_6_30_pm,EAT-OUT - Departure Constant: 06:00 PM - 06:30 PM,@((df.start==31)),coef_eatout_departure_constant_6_pm_to_6_30_pm +util_eatout_departure_constant_6_30_pm_to_7_pm,EAT-OUT - Departure Constant: 06:30 PM - 07:00 PM,@((df.start==32)),coef_eatout_departure_constant_6_30_pm_to_7_pm +util_eatout_departure_constant_7_pm_to_7_30_pm,EAT-OUT - Departure Constant: 07:00 PM - 07:30 PM,@((df.start==33)),coef_eatout_departure_constant_7_pm_to_7_30_pm +util_eatout_departure_constant_after_7_30_pm,EAT-OUT - Departure Constant: After 07:30 PM,@((df.start>33)),coef_eatout_departure_constant_after_7_30_pm +util_eatout_departure_constant_shift_for_every_30_minutes_after_8_pm_linear,EAT-OUT - Departure Constant: Shift for every 30 minutes after 08:00 pm - Linear,"@np.where(((df.start>34)), (np.where((df.start<30), np.minimum(30-df.start,27), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_eatout_departure_constant_shift_for_every_30_minutes_after_8_pm_linear +util_eatout_arrival_constant_9_30_am_to_11_am,EAT-OUT - Arrival Constant: 9:30 AM to 11:00 AM,@((df.end>=14) & (df.end<=16)),coef_eatout_arrival_constant_9_30_am_to_11_am +util_eatout_arrival_constant_12_30_pm_to_1_pm,EAT-OUT - Arrival Constant: 12:30 PM to 01:00 PM,@((df.end==20)),coef_eatout_arrival_constant_12_30_pm_to_1_pm +util_eatout_arrival_constant_1_pm_to_1_30_pm,EAT-OUT - Arrival Constant: 01:00 PM to 01:30 PM,@((df.end==21)),coef_eatout_arrival_constant_1_pm_to_1_30_pm +util_eatout_arrival_constant_1_30_pm_to_2_pm,EAT-OUT - Arrival Constant: 01:30 PM to 02:00 PM,@((df.end==22)),coef_eatout_arrival_constant_1_30_pm_to_2_pm +util_eatout_arrival_constant_2_pm_to_2_30_pm,EAT-OUT - Arrival Constant: 02:00 PM to 02:30 PM,@((df.end==23)),coef_eatout_arrival_constant_2_pm_to_2_30_pm +util_eatout_arrival_constant_2_30_pm_to_3_pm,EAT-OUT - Arrival Constant: 02:30 PM to 03:00 PM,@((df.end==24)),coef_eatout_arrival_constant_2_30_pm_to_3_pm +util_eatout_arrival_constant_shift_for_every_30_minutes_before_6_pm_linear,EAT-OUT - Arrival Constant: Shift for every 30 minutes before 06:00 pm - Linear,@((df.end<31)),coef_eatout_arrival_constant_shift_for_every_30_minutes_before_6_pm_linear +util_eatout_arrival_constant_before_6_30_pm,EAT-OUT - Arrival Constant: Before 6:30 PM,"@np.where(((df.end<32)), (np.where((df.end<31), np.minimum(31-df.end,24), 0) + np.where((df.end>37), np.minimum(df.end-37,48), 0)), 0)",coef_eatout_arrival_constant_before_6_30_pm +util_eatout_arrival_constant_6_30_pm_to_7_pm,EAT-OUT - Arrival Constant: 6:30 PM to 7:00 PM,@((df.end==32)),coef_eatout_arrival_constant_6_30_pm_to_7_pm +util_eatout_arrival_constant_7_pm_to_7_30_pm,EAT-OUT - Arrival Constant: 7:00 PM to 7:30 PM,@((df.end==33)),coef_eatout_arrival_constant_7_pm_to_7_30_pm +util_eatout_arrival_constant_7_30_pm_to_8_pm,EAT-OUT - Arrival Constant: 7:30 PM to 8:00 PM,@((df.end==34)),coef_eatout_arrival_constant_7_30_pm_to_8_pm +util_eatout_arrival_constant_8_pm_to_8_30_pm,EAT-OUT - Arrival Constant: 8:00 PM to 8:30 PM,@((df.end==35)),coef_eatout_arrival_constant_8_pm_to_8_30_pm +util_eatout_arrival_constant_8_30_pm_to_9_pm,EAT-OUT - Arrival Constant: 8:30 PM to 9:00 PM,@((df.end==36)),coef_eatout_arrival_constant_8_30_pm_to_9_pm +util_eatout_arrival_constant_after_9_pm,EAT-OUT - Arrival Constant: After 9:00 PM,@((df.tour_category != 'joint')& (df.end>36)),coef_eatout_arrival_constant_after_9_pm +util_eatout_arrival_constant_shift_for_every_30_minutes_after_9_30_pm_linear,EAT-OUT - Arrival Constant: Shift for every 30 minutes after 09:30 pm - Linear,"@np.where(((df.end>37)), (np.where((df.end<31), np.minimum(31-df.end,24), 0) + np.where((df.end>37), np.minimum(df.end-37,48), 0)), 0)",coef_eatout_arrival_constant_shift_for_every_30_minutes_after_9_30_pm_linear +util_eatout_duration_constant_0_hour,EAT-OUT - Duration Constant: 0 hour,@((df.duration==0)),coef_eatout_duration_constant_0_hour +util_eatout_duration_constant_30_minutes,EAT-OUT - Duration Constant: 0.5 hour,@((df.duration==1)),coef_eatout_duration_constant_30_minutes +util_eatout_duration_constant_1_hour,EAT-OUT - Duration Constant: 1 hour,@((df.duration==2)),coef_eatout_duration_constant_1_hour +util_eatout_duration_constant_1_hour_30_minutes,EAT-OUT - Duration Constant: 1.5 hours,@((df.duration==3)),coef_eatout_duration_constant_1_hour_30_minutes +util_eatout_duration_constant_2_hours,EAT-OUT - Duration Constant: 2 hours,@((df.tour_category != 'joint')& (df.duration==4)),coef_eatout_duration_constant_2_hours +util_eatout_duration_constant_2_hour_30_minutes_or_more,EAT-OUT - Duration Constant: 2.5 hours or more,@((df.duration>4)),coef_eatout_duration_constant_2_hour_30_minutes_or_more +util_eatout_duration_constant_shift_for_every_30_minutes_more_than_3_hrs_linear,EAT-OUT - Duration Constant: Shift for every 30 minutes more than 3 hrs - Linear,"@np.where(((df.duration>5)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>5), np.minimum(df.duration-5,11), 0)), 0)",coef_eatout_duration_constant_shift_for_every_30_minutes_more_than_3_hrs_linear +util_eatout_calibration_constant_duration_1,EAT-OUT - Calibration Constant - Duration = 1,@((df.duration==0)),coef_eatout_calibration_constant_duration_1 +util_eatout_calibration_constant_duration_2,EAT-OUT - Calibration Constant - Duration = 2,@((df.duration==1)),coef_eatout_calibration_constant_duration_2 +util_eatout_calibration_constant_duration_3,EAT-OUT - Calibration Constant - Duration = 3,@((df.duration==2)),coef_eatout_calibration_constant_duration_3 +util_eatout_calibration_constant_duration_4,EAT-OUT - Calibration Constant - Duration = 4,@((df.duration==3)),coef_eatout_calibration_constant_duration_4 +util_eatout_calibration_constant_departure_1,EAT-OUT - Calibration Constant - Departure = 1,@((df.start == 1)),coef_eatout_calibration_constant_departure_1 +util_eatout_calibration_constant_departure_2,EAT-OUT - Calibration Constant - Departure = 2,@((df.start == 2)),coef_eatout_calibration_constant_departure_2 +util_eatout_calibration_constant_departure_3,EAT-OUT - Calibration Constant - Departure = 3,@((df.start == 3)),coef_eatout_calibration_constant_departure_3 +util_eatout_calibration_constant_departure_17,EAT-OUT - Calibration Constant - Departure = 17,@((df.start ==17)),coef_eatout_calibration_constant_departure_17 +util_eatout_calibration_constant_departure_18,EAT-OUT - Calibration Constant - Departure = 18,@((df.start ==18)),coef_eatout_calibration_constant_departure_18 +util_eatout_calibration_constant_departure_19,EAT-OUT - Calibration Constant - Departure = 19,@((df.start ==19)),coef_eatout_calibration_constant_departure_19 +util_eatout_calibration_constant_departure_20,EAT-OUT - Calibration Constant - Departure = 20,@((df.start ==20)),coef_eatout_calibration_constant_departure_20 +util_eatout_calibration_constant_departure_21,EAT-OUT - Calibration Constant - Departure = 21,@((df.start ==21)),coef_eatout_calibration_constant_departure_21 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_eatout_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_eatout_coefficients.csv new file mode 100644 index 000000000..d94961976 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_eatout_coefficients.csv @@ -0,0 +1,59 @@ +coefficient_name,value,constrain +coef_eatout_distance_to_destination_duration_less_than_1_hr,-0.134981987,F +coef_eatout_distance_to_destination_duration_greater_than_1_hr,0.017860742,F +coef_eatout_low_income_duration_less_than_1_hr,1.002485807,F +coef_eatout_medium_income_duration_less_than_1_hr,0.499822018,F +coef_eatout_zeroauto_HH_duration_greater_than_1_hr,0.259409942,F +coef_eatout_university_student_departure_after_7_pm_linear,0.293827759,F +coef_eatout_female_duration_less_than_1_hr,-0.399414247,F +coef_eatout_female_duration_greater_than_1_hr,0.064593482,F +coef_eatout_time_pressure_departure_before_6_30_pm,0.083673557,F +coef_eatout_time_pressure_duration_less_than_1_hr,1.69632588,F +coef_eatout_departure_constant_7_30_am_to_9_am,1.222417262,F +coef_eatout_departure_constant_10_30_am_to_11_am,0.519559134,F +coef_eatout_departure_constant_11_am_to_11_30_am,1.191543552,F +coef_eatout_departure_constant_11_30_am_to_12_pm,1.66870995,F +coef_eatout_departure_constant_12_pm_to_12_30_pm,1.164106986,F +coef_eatout_departure_constant_12_30_pm_to_1_pm,1.057346496,F +coef_eatout_departure_constant_1_pm_to_1_30_pm,0.728959087,F +coef_eatout_departure_constant_shift_for_every_30_minutes_before_5_30_pm_linear,-0.477439748,F +coef_eatout_departure_constant_before_6_pm,-1.21554671,F +coef_eatout_departure_constant_6_pm_to_6_30_pm,-0.425984037,F +coef_eatout_departure_constant_6_30_pm_to_7_pm,0,T +coef_eatout_departure_constant_7_pm_to_7_30_pm,-0.227800647,F +coef_eatout_departure_constant_after_7_30_pm,-0.293904097,F +coef_eatout_departure_constant_shift_for_every_30_minutes_after_8_pm_linear,-0.55440861,F +coef_eatout_arrival_constant_9_30_am_to_11_am,0.486337344,F +coef_eatout_arrival_constant_12_30_pm_to_1_pm,0.629299404,F +coef_eatout_arrival_constant_1_pm_to_1_30_pm,0.938528731,F +coef_eatout_arrival_constant_1_30_pm_to_2_pm,0.584420106,F +coef_eatout_arrival_constant_2_pm_to_2_30_pm,0.842550215,F +coef_eatout_arrival_constant_2_30_pm_to_3_pm,0.298486505,F +coef_eatout_arrival_constant_shift_for_every_30_minutes_before_6_pm_linear,0.125034982,F +coef_eatout_arrival_constant_before_6_30_pm,-0.029062996,F +coef_eatout_arrival_constant_6_30_pm_to_7_pm,-0.509075598,F +coef_eatout_arrival_constant_7_pm_to_7_30_pm,-0.124885931,F +coef_eatout_arrival_constant_7_30_pm_to_8_pm,-0.605455664,F +coef_eatout_arrival_constant_8_pm_to_8_30_pm,0,T +coef_eatout_arrival_constant_8_30_pm_to_9_pm,-0.657382835,F +coef_eatout_arrival_constant_after_9_pm,-0.813629712,F +coef_eatout_arrival_constant_shift_for_every_30_minutes_after_9_30_pm_linear,-0.204722406,F +coef_eatout_duration_constant_0_hour,-11.72660422,F +coef_eatout_duration_constant_30_minutes,-5.08873115,F +coef_eatout_duration_constant_1_hour,-0.125521065,F +coef_eatout_duration_constant_1_hour_30_minutes,0,T +coef_eatout_duration_constant_2_hours,-0.124807752,F +coef_eatout_duration_constant_2_hour_30_minutes_or_more,-0.156019835,F +coef_eatout_duration_constant_shift_for_every_30_minutes_more_than_3_hrs_linear,-0.3357414,F +coef_eatout_calibration_constant_duration_1,-0.333697861,F +coef_eatout_calibration_constant_duration_2,-0.245716,F +coef_eatout_calibration_constant_duration_3,0.052708833,F +coef_eatout_calibration_constant_duration_4,0.041571499,F +coef_eatout_calibration_constant_departure_1,-10,F +coef_eatout_calibration_constant_departure_2,-10,F +coef_eatout_calibration_constant_departure_3,-10,F +coef_eatout_calibration_constant_departure_17,0.706568704,F +coef_eatout_calibration_constant_departure_18,0.634353544,F +coef_eatout_calibration_constant_departure_19,0.584387268,F +coef_eatout_calibration_constant_departure_20,0.469777884,F +coef_eatout_calibration_constant_departure_21,0.39548931,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_escort.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_escort.csv new file mode 100644 index 000000000..b07727992 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_escort.csv @@ -0,0 +1,76 @@ +Label,Description,Expression,Coefficient +# ESCORT,,, +util_escort_mode_choice_logsum,ESCORT - Mode Choice Logsum,"@np.where(df.tour_type == 'escort', df.mode_choice_logsum, 0) ",coef_escort_mode_choice_logsum +"#Note: In CTRAMP expressions, duration alternative is from 1 to 48 but in ActivitySim, it is from 0 to 47 since the duration alternative ID was calculated as (end - start). Therefore, duration in ActivitySim expression = CTRAMP duration expresssion - 1 ",,,# +util_escort_distance_to_destination_duration_less_than_30_minutes,ESCORT - Distance to destination - Duration less than 0.5 hour (depart and arrive in the same period),"@np.where(((df.duration<1)), ((df.origin_to_destination_distance) * (np.where((df.duration<=1), np.minimum(1-df.duration, 0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0))), 0)",coef_escort_distance_to_destination_duration_less_than_30_minutes +util_escort_distance_to_destination_duration_greater_than_30_minutes,ESCORT - Distance to destination - Duration greater than 0.5 hour,"@np.where(((df.duration>1)), ((df.origin_to_destination_distance) * (np.where((df.duration<=1), np.minimum(1-df.duration, 0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0))), 0)",coef_escort_distance_to_destination_duration_greater_than_30_minutes +util_escort_fulltime_worker_departure_after_8_am_linear,ESCORT - Full-time worker - Departure after 8:00 am - Linear,"@np.where(((df.ptype == 1) & (df.start>10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where((df.start>10), np.minimum(df.start-10,35), 0)),0)",coef_escort_fulltime_worker_departure_after_8_am_linear +"#Note: In CTRAMP expression file, the description below says departure is after 3 am but from the expression it seems that it would be 3 pm instead of 3 am",,, +util_escort_fulltime_worker_departure_after_3_am_linear,ESCORT - Full-time worker - Departure after 3:00 am - Linear,"@np.where(((df.ptype == 1) & (df.start>24)), (np.where((df.start<=24), np.minimum(24-df.start,3), 0) + np.where((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_fulltime_worker_departure_after_3_am_linear +util_escort_fulltime_worker_duration_less_than_30_minutes,ESCORT - Full-time worker - Duration < 0.5 hr,"@np.where(((df.ptype == 1) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_fulltime_worker_duration_less_than_30_minutes +util_escort_fulltime_worker_duration_greater_than_30_minutes,ESCORT - Full-time worker - Duration > 0.5 hr,"@np.where(((df.ptype == 1) & (df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_fulltime_worker_duration_greater_than_30_minutes +util_escort_university_student_duration_less_than_30_minutes,ESCORT - University student - Duration < 0.5 hr,"@np.where(((df.ptype == 3) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_university_student_duration_less_than_30_minutes +util_escort_non_driving_age_student_duration_greater_than_30_minutes,ESCORT - Non-driving age student - Duration > 0.5 hr,"@np.where((((df.ptype == 7)|(df.ptype == 8)) & (df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_non_driving_age_student_duration_greater_than_30_minutes +util_escort_driving_age_student_duration_less_than_30_minutes,ESCORT - Driving age student - Duration < 0.5 hr,"@np.where(((df.ptype == 6) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_driving_age_student_duration_less_than_30_minutes +util_escort_driving_age_student_duration_greater_than_30_minutes,ESCORT - Driving age student - Duration > 0.5 hr,"@np.where(((df.ptype == 6) & (df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_driving_age_student_duration_greater_than_30_minutes +"#Note: In CTRAMP expression file, description says the expression below is for duration > 0.5 hr but the expression says duration < 0.5 hr",,, +util_escort_pre_school_kid_duration_greater_than_30_minutes,ESCORT - Pre-school kid - Duration > 0.5 hr,"@np.where(((df.ptype == 8) & (df.duration<1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_pre_school_kid_duration_greater_than_30_minutes +util_escort_med_high_income_duration_greater_than_30_minutes,ESCORT - Med-high income (60k to 120k) - Duration > 0.5 hr,"@np.where(((df.is_income_60K_to_120K) & (df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_med_high_income_duration_greater_than_30_minutes +util_escort_households_with_no_kids_departure_before_7_30_am,"ESCORT - Households with no kids (Dummy- 1,0) - Departure before 7:30 AM","@np.where(((df.num_children == 0) & (df.start<10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_households_with_no_kids_departure_before_7_30_am +util_escort_households_with_no_kids_departure_after_8_00_am,"ESCORT - Households with no kids (Dummy- 1,0) - Departure after 8:00 AM","@np.where(((df.num_children == 0) & (df.start>10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_households_with_no_kids_departure_after_8_00_am +util_escort_households_with_no_kids_departure_before_2_30_pm,"ESCORT - Households with no kids (Dummy- 1,0) - Departure before 2:30 PM","@np.where(((df.num_children == 0) & (df.start<24)), (np.where((df.start<=24), np.minimum(24-df.start,3), 0) + np.where((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_households_with_no_kids_departure_before_2_30_pm +util_escort_households_with_no_kids_departure_after_3_00_pm,"ESCORT - Households with no kids (Dummy- 1,0) - Departure after 3:00 PM","@np.where(((df.num_children == 0) & (df.start>24)), (np.where((df.start<=24), np.minimum(24-df.start,3), 0) + np.where ((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_households_with_no_kids_departure_after_3_00_pm +util_escort_households_with_no_kids_arrival_before_8_am,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival before 8:00 AM","@np.where(((df.num_children == 0) & (df.end<11)), (np.where((df.end<=11), np.minimum(11-df.end,7), 0) + np.where((df.end>11), np.minimum(df.end-11,35), 0)), 0)",coef_escort_households_with_no_kids_arrival_before_8_am +util_escort_households_with_no_kids_arrival_after_8_30_am,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival after 8:30 AM","@np.where(((df.num_children == 0) & (df.end>11)), (np.where((df.end<=11), np.minimum(11-df.end,7), 0) + np.where((df.end>11), np.minimum(df.end-11,35), 0)), 0)",coef_escort_households_with_no_kids_arrival_after_8_30_am +util_escort_households_with_no_kids_arrival_before_3_pm,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival before 3:00 PM","@np.where(((df.num_children == 0) & (df.end<25)), (np.where((df.end<=25), np.minimum(25-df.end,3), 0) + np.where((df.end>25), np.minimum(df.end-25,9), 0)), 0)",coef_escort_households_with_no_kids_arrival_before_3_pm +util_escort_households_with_no_kids_arrival_after_3_30_pm,"ESCORT - Households with no kids (Dummy- 1,0) - Arrival after 3:30 PM","@np.where(((df.num_children == 0) & (df.end>25)), (np.where((df.end<=25), np.minimum(25-df.end,3), 0) + np.where((df.end>25), np.minimum(df.end-25,9), 0)), 0)",coef_escort_households_with_no_kids_arrival_after_3_30_pm +util_escort_pre_school_child_in_hh_with_mandatory_tour_departure_after_8_am,"ESCORT - Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Departure after 8:00 AM","@np.where(((df.has_pre_school_child_with_mandatory > 0) & (df.start>10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_pre_school_child_in_hh_with_mandatory_tour_departure_after_8_am +util_escort_pre_school_child_in_hh_with_mandatory_tour_departure_after_3_pm,"ESCORT - Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Departure after 3:00 PM","@np.where(((df.has_pre_school_child_with_mandatory > 0) & (df.start>24)), (np.where((df.start<=24), np.minimum(24-df.start,3), 0) + np.where((df.start>24), np.minimum(df.start-24,9), 0)), 0)",coef_escort_pre_school_child_in_hh_with_mandatory_tour_departure_after_3_pm +util_escort_pre_school_child_in_hh_with_mandatory_tour_arrival_before_8_am,"ESCORT -Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival before 8:00 AM","@np.where(((df.has_pre_school_child_with_mandatory > 0) & (df.end<11)), (np.where((df.end<=11), np.minimum(11-df.end,7), 0) + np.where((df.end>11), np.minimum(df.end-11,35), 0)), 0)",coef_escort_pre_school_child_in_hh_with_mandatory_tour_arrival_before_8_am +util_escort_pre_school_child_in_hh_with_mandatory_tour_arrival_before_3_pm,"ESCORT - Pre-School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival before 3:00 PM","@np.where(((df.has_pre_school_child_with_mandatory > 0) & (df.end<25)), (np.where((df.end<=25), np.minimum(25-df.end,3), 0) + np.where((df.end>25), np.minimum(df.end-25,9), 0)), 0)",coef_escort_pre_school_child_in_hh_with_mandatory_tour_arrival_before_3_pm +util_escort_driving_age_school_child_in_hh_with_mandatory_tour_departure_after_8_am,"ESCORT - Driving age School Child in HH with Mandatory tour (Dummy- 1,0) - Departure after 8:00 AM","@np.where(((df.has_driving_age_child_with_mandatory > 0) & (df.start>10)), (np.where((df.start<=10), np.minimum(10-df.start,7), 0) + np.where ((df.start>10), np.minimum(df.start-10,35), 0)), 0)",coef_escort_driving_age_school_child_in_hh_with_mandatory_tour_departure_after_8_am +util_escort_driving_age_school_child_in_hh_with_mandatory_tour_arrival_after_8_30_am,"ESCORT - Driving age School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival after 8:30 AM","@np.where(((df.has_driving_age_child_with_mandatory > 0) & (df.end>11)), (np.where((df.end<=11), np.minimum(11-df.end,7), 0) + np.where((df.end>11), np.minimum(df.end-11,35), 0)), 0)",coef_escort_driving_age_school_child_in_hh_with_mandatory_tour_arrival_after_8_30_am +util_escort_driving_age_school_child_in_hh_with_mandatory_tour_arrival_after_3_30_pm,"ESCORT - Driving age School Child in HH with Mandatory tour (Dummy- 1,0) - Arrival after 3:30 PM","@np.where(((df.has_driving_age_child_with_mandatory > 0) & (df.end>25)), (np.where((df.end<=25), np.minimum(25-df.end,3), 0) + np.where((df.end>25), np.minimum(df.end-25,9), 0)), 0)",coef_escort_driving_age_school_child_in_hh_with_mandatory_tour_arrival_after_3_30_pm +util_escort_number_of_autos_greater_than_number_of_adults_duration_greater_than_30_minutes,ESCORT - Number of autos greater than number of adults - Duration > 0.5 hr,"@np.where(((df.auto_ownership > 0) & (df.auto_ownership > df.num_adults) & (df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)), 0)",coef_escort_number_of_autos_greater_than_number_of_adults_duration_greater_than_30_minutes +util_escort_number_of_individual_tours_duration_greater_than_30_minutes,ESCORT -Number of Individual Tours (excluding escorting) - Duration > 0.5 hr,"@np.where(((df.num_non_escort_tours > 0) & (df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)) * (df.num_non_escort_tours), 0)",coef_escort_number_of_individual_tours_duration_greater_than_30_minutes +util_escort_number_of_joint_tours_duration_greater_than_30_minutes,ESCORT - Number of joint tours - Duration > 0.5 hr,"@np.where(((df.duration>1)), (np.where((df.duration<=1), np.minimum(1-df.duration,0), 0) + np.where((df.duration>1), np.minimum(df.duration-1,47), 0)) *(df.num_joint_tours), 0)",coef_escort_number_of_joint_tours_duration_greater_than_30_minutes +util_escort_departure_constant_shift_for_every_30_minutes_before_6_30_am_linear,ESCORT - Departure Constant: Shift for every 30 minutes before 06:30 am - Linear,"@np.where(((df.start<8)), (np.where((df.start<8), np.minimum(8-df.start,4), 0) + np.where((df.start>13), np.minimum(df.start-13,28), 0)), 0)",coef_escort_departure_constant_shift_for_every_30_minutes_before_6_30_am_linear +util_escort_departure_constant_before_7_am,ESCORT - Departure Constant: Before 07:00 AM,@((df.start<9)),coef_escort_departure_constant_before_7_am +util_escort_departure_constant_7_am_to_7_30_am,ESCORT - Departure Constant: 07:00 AM - 07:30 AM,@((df.start==9)),coef_escort_departure_constant_7_am_to_7_30_am +util_escort_departure_constant_7_30_am_to_8_am,ESCORT - Departure Constant: 07:30 AM - 08:00 AM,@((df.start==10)),coef_escort_departure_constant_7_30_am_to_8_am +util_escort_departure_constant_8_am_to_8_30_am,ESCORT - Departure Constant: 08:00 AM - 08:30 AM,@((df.start==11)),coef_escort_departure_constant_8_am_to_8_30_am +util_escort_departure_constant_8_30_am_to_9_am,ESCORT - Departure Constant: 08:30 AM - 09:00 AM,@((df.start==12)),coef_escort_departure_constant_8_30_am_to_9_am +util_escort_departure_constant_after_9_am,ESCORT - Departure Constant: After 09:00 AM,@((df.start>12)),coef_escort_departure_constant_after_9_am +util_escort_departure_constant_1_30_pm_to_2_pm,ESCORT - Departure Constant: 01:30 PM - 02:00 PM,@((df.start==22)),coef_escort_departure_constant_1_30_pm_to_2_pm +util_escort_departure_constant_2_pm_to_2_30_pm,ESCORT - Departure Constant: 02:00 PM - 02:30 PM,@((df.start==23)),coef_escort_departure_constant_2_pm_to_2_30_pm +util_escort_departure_constant_2_30_pm_to_3_pm,ESCORT - Departure Constant: 02:30 PM - 03:00 PM,@((df.start==24)),coef_escort_departure_constant_2_30_pm_to_3_pm +util_escort_departure_constant_3_pm_to_3_30_pm,ESCORT - Departure Constant: 03:00 PM - 03:30 PM,@((df.start==25)),coef_escort_departure_constant_3_pm_to_3_30_pm +util_escort_departure_constant_after_3_30_pm,ESCORT - Departure Constant: After 03:30 PM,@((df.start>25)),coef_escort_departure_constant_after_3_30_pm +util_escort_departure_constant_shift_for_every_30_minutes_after_9_30_am_linear,ESCORT - Departure Constant: Shift for every 30 minutes after 9:30 am - Linear,"@np.where(((df.start>13)), (np.where((df.start<8), np.minimum(8-df.start,4), 0) + (np.where((df.start>13), np.minimum(df.start-13,28), 0))), 0)",coef_escort_departure_constant_shift_for_every_30_minutes_after_9_30_am_linear +util_escort_departure_constant_shift_for_every_30_minutes_after_4_pm_linear,ESCORT - Departure Constant: Shift for every 30 minutes after 4:00 pm - Linear,"@np.where(((df.start>26)), (np.where((df.start<0), np.minimum(0-df.start,48), 0) + np.where((df.start>26), np.minimum(df.start-26,15),0)), 0)",coef_escort_departure_constant_shift_for_every_30_minutes_after_4_pm_linear +util_escort_arrival_constant_shift_for_every_30_minutes_before_6_30_am_linear,ESCORT - Arrival Constant: Shift for every 30 minutes before 6:30 am - Linear,"@np.where(((df.end<8)), (np.where((df.end<8), np.minimum(8-df.end,2), 0) + np.where((df.end>13), np.minimum(df.end-13,30), 0)), 0)",coef_escort_arrival_constant_shift_for_every_30_minutes_before_6_30_am_linear +util_escort_arrival_constant_before_7_am,ESCORT - Arrival Constant: Before 07:00 AM,@((df.end<9)),coef_escort_arrival_constant_before_7_am +util_escort_arrival_constant_7_am_to_7_30_am,ESCORT - Arrival Constant: 07:00 AM - 07:30 AM,@((df.end==9)),coef_escort_arrival_constant_7_am_to_7_30_am +util_escort_arrival_constant_7_30_am_to_8_am,ESCORT - Arrival Constant: 07:30 AM - 08:00 AM,@((df.end==10)),coef_escort_arrival_constant_7_30_am_to_8_am +util_escort_arrival_constant_8_am_to_8_30_am,ESCORT - Arrival Constant: 08:00 AM - 08:30 AM,@((df.end==11)),coef_escort_arrival_constant_8_am_to_8_30_am +util_escort_arrival_constant_8_30_am_to_9_am,ESCORT - Arrival Constant: 08:30 AM - 09:00 AM,@((df.end==12)),coef_escort_arrival_constant_8_30_am_to_9_am +util_escort_arrival_constant_after_9_am,ESCORT - Arrival Constant: After 09:00 AM,@((df.end>12)),coef_escort_arrival_constant_after_9_am +util_escort_arrival_constant_2_30_pm_to_3_pm,ESCORT - Arrival Constant: 02:30 PM - 03:00 PM,@((df.end==24)),coef_escort_arrival_constant_2_30_pm_to_3_pm +util_escort_arrival_constant_3_pm_to_3_30_pm,ESCORT - Arrival Constant: 03:00 PM - 03:30 PM,@((df.end==25)),coef_escort_arrival_constant_3_pm_to_3_30_pm +util_escort_arrival_constant_3_30_pm_to_4_pm,ESCORT - Arrival Constant: 03:30 PM - 04:00 PM,@((df.end==26)),coef_escort_arrival_constant_3_30_pm_to_4_pm +util_escort_arrival_constant_4_pm_to_4_30_pm,ESCORT - Arrival Constant: 04:00 PM - 04:30 PM,@((df.end==27)),coef_escort_arrival_constant_4_pm_to_4_30_pm +util_escort_arrival_constant_after_4_30_pm,ESCORT - Arrival Constant: After 04:30 PM,@((df.end>27)),coef_escort_arrival_constant_after_4_30_pm +util_escort_arrival_constant_shift_for_every_30_minutes_after_9_30_am_linear,ESCORT - Arrival Constant: Shift for every 30 minutes after 9:30 am - Linear,"@np.where(((df.end>13)), (np.where((df.end<8), np.minimum(8-df.end,2), 0) + np.where((df.end>13), np.minimum(df.end-13,30), 0)), 0)",coef_escort_arrival_constant_shift_for_every_30_minutes_after_9_30_am_linear +util_escort_arrival_constant_shift_for_every_30_minutes_after_5_pm_linear,ESCORT - Arrival Constant: Shift for every 30 minutes after 5:00 pm - Linear,"@np.where(((df.end>28)), (np.where((df.end<0), np.minimum(0-df.end,48), 0) + np.where((df.start>28), np.minimum(df.end-28,15), 0)), 0)",coef_escort_arrival_constant_shift_for_every_30_minutes_after_5_pm_linear +util_escort_duration_constant_0_hour,ESCORT - Duration Constant: 0 hr,@((df.duration==0)),coef_escort_duration_constant_0_hour +util_escort_duration_constant_30_minutes,ESCORT - Duration Constant: 0.5 hr,@((df.duration==1)),coef_escort_duration_constant_30_minutes +util_escort_duration_constant_1_hour,ESCORT - Duration Constant: 1 hr,@((df.duration==2)),coef_escort_duration_constant_1_hour +util_escort_duration_constant_1_hour_30_minutes,ESCORT - Duration Constant: 1.5hrs,@((df.duration==3)),coef_escort_duration_constant_1_hour_30_minutes +util_escort_duration_constant_2_hours,ESCORT - Duration Constant: 2 hrs,@((df.duration==4)),coef_escort_duration_constant_2_hours +util_escort_duration_constant_longer_than_2_hours,ESCORT - Duration Constant: Longer than 2 hrs,@((df.duration>4)),coef_escort_duration_constant_longer_than_2_hours +util_escort_calibration_constant_duration_1,ESCORT - Calibration Constant - Duration = 1,@((df.duration==0)),coef_escort_calibration_constant_duration_1 +util_escort_calibration_constant_duration_2,ESCORT - Calibration Constant - Duration = 2,@((df.duration==1)),coef_escort_calibration_constant_duration_2 +util_escort_calibration_constant_departure_9,ESCORT - Calibration Constant - Departure = 9,@((df.start==9)),coef_escort_calibration_constant_departure_9 +util_escort_calibration_constant_departure_10,ESCORT - Calibration Constant - Departure = 10,@((df.start==10)),coef_escort_calibration_constant_departure_10 +util_escort_calibration_constant_departure_23,ESCORT - Calibration Constant - Departure = 23,@((df.start==23)),coef_escort_calibration_constant_departure_23 +util_escort_calibration_constant_departure_24,ESCORT - Calibration Constant - Departure = 24,@((df.start==24)),coef_escort_calibration_constant_departure_24 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_escort_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_escort_coefficients.csv new file mode 100644 index 000000000..76a5b7c13 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_escort_coefficients.csv @@ -0,0 +1,72 @@ +coefficient_name,value,constrain +coef_escort_mode_choice_logsum,1.173173034,F +coef_escort_distance_to_destination_duration_less_than_30_minutes,-0.335017673,F +coef_escort_distance_to_destination_duration_greater_than_30_minutes,0.005298165,F +coef_escort_fulltime_worker_departure_after_8_am_linear,-0.037980109,F +coef_escort_fulltime_worker_departure_after_3_am_linear,0.163254125,F +coef_escort_fulltime_worker_duration_less_than_30_minutes,-0.275077482,F +coef_escort_fulltime_worker_duration_greater_than_30_minutes,0.051530545,F +coef_escort_university_student_duration_less_than_30_minutes,-0.426802718,F +coef_escort_non_driving_age_student_duration_greater_than_30_minutes,0.240582361,F +coef_escort_driving_age_student_duration_less_than_30_minutes,-0.554146191,F +coef_escort_driving_age_student_duration_greater_than_30_minutes,0.299387708,F +coef_escort_pre_school_kid_duration_greater_than_30_minutes,0.195482563,F +coef_escort_med_high_income_duration_greater_than_30_minutes,-0.029281467,F +coef_escort_households_with_no_kids_departure_before_7_30_am,0.589083327,F +coef_escort_households_with_no_kids_departure_after_8_00_am,0.086690827,F +coef_escort_households_with_no_kids_departure_before_2_30_pm,0.477582648,F +coef_escort_households_with_no_kids_departure_after_3_00_pm,-0.204065502,F +coef_escort_households_with_no_kids_arrival_before_8_am,-0.360039254,F +coef_escort_households_with_no_kids_arrival_after_8_30_am,0.091614107,F +coef_escort_households_with_no_kids_arrival_before_3_pm,0.432854268,F +coef_escort_households_with_no_kids_arrival_after_3_30_pm,0.131037275,F +coef_escort_pre_school_child_in_hh_with_mandatory_tour_departure_after_8_am,0.109700265,F +coef_escort_pre_school_child_in_hh_with_mandatory_tour_departure_after_3_pm,-0.224568648,F +coef_escort_pre_school_child_in_hh_with_mandatory_tour_arrival_before_8_am,-0.357416434,F +coef_escort_pre_school_child_in_hh_with_mandatory_tour_arrival_before_3_pm,0.629285298,F +coef_escort_driving_age_school_child_in_hh_with_mandatory_tour_departure_after_8_am,0.039005148,F +coef_escort_driving_age_school_child_in_hh_with_mandatory_tour_arrival_after_8_30_am,-0.06556611,F +coef_escort_driving_age_school_child_in_hh_with_mandatory_tour_arrival_after_3_30_pm,0.117680977,F +coef_escort_number_of_autos_greater_than_number_of_adults_duration_greater_than_30_minutes,-0.057322708,F +coef_escort_number_of_individual_tours_duration_greater_than_30_minutes,-0.062899692,F +coef_escort_number_of_joint_tours_duration_greater_than_30_minutes,-0.048533895,F +coef_escort_departure_constant_shift_for_every_30_minutes_before_6_30_am_linear,-1.469240002,F +coef_escort_departure_constant_before_7_am,-2.070292862,F +coef_escort_departure_constant_7_am_to_7_30_am,-0.642734296,F +coef_escort_departure_constant_7_30_am_to_8_am,0,T +coef_escort_departure_constant_8_am_to_8_30_am,-0.214617667,F +coef_escort_departure_constant_8_30_am_to_9_am,-0.147266606,F +coef_escort_departure_constant_after_9_am,-1.356686422,F +coef_escort_departure_constant_1_30_pm_to_2_pm,0.368092381,F +coef_escort_departure_constant_2_pm_to_2_30_pm,1.166803383,F +coef_escort_departure_constant_2_30_pm_to_3_pm,1.28466083,F +coef_escort_departure_constant_3_pm_to_3_30_pm,0.581891245,F +coef_escort_departure_constant_after_3_30_pm,0.834510243,F +coef_escort_departure_constant_shift_for_every_30_minutes_after_9_30_am_linear,0.175257649,F +coef_escort_departure_constant_shift_for_every_30_minutes_after_4_pm_linear,-0.019161202,F +coef_escort_arrival_constant_shift_for_every_30_minutes_before_6_30_am_linear,0.44978138,F +coef_escort_arrival_constant_before_7_am,0.549584585,F +coef_escort_arrival_constant_7_am_to_7_30_am,0.488181278,F +coef_escort_arrival_constant_7_30_am_to_8_am,0.236447651,F +coef_escort_arrival_constant_8_am_to_8_30_am,0,T +coef_escort_arrival_constant_8_30_am_to_9_am,-0.683756801,F +coef_escort_arrival_constant_after_9_am,-1.428888485,F +coef_escort_arrival_constant_2_30_pm_to_3_pm,1.311480662,F +coef_escort_arrival_constant_3_pm_to_3_30_pm,1.316883154,F +coef_escort_arrival_constant_3_30_pm_to_4_pm,1.396838392,F +coef_escort_arrival_constant_4_pm_to_4_30_pm,1.03146139,F +coef_escort_arrival_constant_after_4_30_pm,0.907344583,F +coef_escort_arrival_constant_shift_for_every_30_minutes_after_9_30_am_linear,-0.148408887,F +coef_escort_arrival_constant_shift_for_every_30_minutes_after_5_pm_linear,-0.389082896,F +coef_escort_duration_constant_0_hour,-0.173757322,F +coef_escort_duration_constant_30_minutes,0,T +coef_escort_duration_constant_1_hour,-0.431287743,F +coef_escort_duration_constant_1_hour_30_minutes,-0.700473959,F +coef_escort_duration_constant_2_hours,-1.071871358,F +coef_escort_duration_constant_longer_than_2_hours,-1.691098421,F +coef_escort_calibration_constant_duration_1,-0.047200214,F +coef_escort_calibration_constant_duration_2,0.035611332,F +coef_escort_calibration_constant_departure_9,0.106814756,F +coef_escort_calibration_constant_departure_10,0.215386864,F +coef_escort_calibration_constant_departure_23,-0.255087318,F +coef_escort_calibration_constant_departure_24,-0.296870428,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othdiscr.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othdiscr.csv new file mode 100644 index 000000000..69a5e039a --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othdiscr.csv @@ -0,0 +1,55 @@ +Label,Description,Expression,Coefficient +#DISCRETIONARY,#DISCRETIONARY,,#DISCRETIONARY +util_discretionary_person_less_than_18_years_old_duration_less_than_1_hr_30_minutes_linear,DISCRETIONARY - Person< 18 years old: Duration < 1.5 hrs - Linear,"@np.where(((df.duration<3) & (df.age<18)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_discretionary_person_less_than_18_years_old_duration_less_than_1_hr_30_minutes_linear +util_discretionary_person_less_than_18_years_old_duration_greater_than_1_hr_30_minutes_linear,DISCRETIONARY - Person< 18 years old: Duration > 1.5 hrs - Linear,"@np.where(((df.duration>3) & (df.age<18)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_discretionary_person_less_than_18_years_old_duration_greater_than_1_hr_30_minutes_linear +util_discretionary_non_working_senior_retiree_duration_less_than_1_hr_30_minutes_linear,DISCRETIONARY - Non-working senior/ retiree: Duration < 1.5 hrs - Linear,"@np.where(((df.duration<3) & (df.ptype == 5)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_discretionary_non_working_senior_retiree_duration_less_than_1_hr_30_minutes_linear +util_discretionary_retiree_non_working_senior_only_HH_duration_1_hr_30_minutes_linear,DISCRETIONARY - Retiree/ Non-working senior only HH: Duration < 1.5 hrs - Linear,"@np.where(((df.retired_adults_only_hh) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_discretionary_retiree_non_working_senior_only_HH_duration_1_hr_30_minutes_linear +util_discretionary_zero_auto_households_duration_less_than_1_hr_30_minutes_linear,DISCRETIONARY - Zero auto households: Duration < 1.5 hrs - Linear,"@np.where(((df.auto_ownership == 0) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_discretionary_zero_auto_households_duration_less_than_1_hr_30_minutes_linear +util_discretionary_zero_auto_households_duration_greater_than_1_hr_30_minutes_linear,DISCRETIONARY - Zero auto households: Duration > 1.5 hrs - Linear,"@np.where(((df.auto_ownership == 0) & (df.duration>3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_discretionary_zero_auto_households_duration_greater_than_1_hr_30_minutes_linear +util_discretionary_number_of_auto_more_than_number_of_adults_duration_less_than_1_hr_30_minutes_linear,DISCRETIONARY - Number of auto more that number of adults: Duration < 1.5 hrs - Linear,"@np.where(((df.auto_ownership > 0) & (df.auto_ownership > df.num_adults) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)),0)",coef_discretionary_number_of_auto_more_than_number_of_adults_duration_less_than_1_hr_30_minutes_linear +util_discretionary_number_of_auto_more_than_number_of_adults_duration_greater_than_1_hr_30_minutes_linear,DISCRETIONARY - Number of auto more that number of adults: Duration > 1.5 hrs - Linear,"@np.where(((df.auto_ownership > 0) &(df.tour_type == 'othdiscr')&(df.auto_ownership > df.num_adults) & (df.duration>3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_discretionary_number_of_auto_more_than_number_of_adults_duration_greater_than_1_hr_30_minutes_linear +"# In CTRAMP, although the description below says duration is less than 1 hr, expression is for less than 1.5 hr",,, +util_discretionary_auto_distance_duration_less_than_1_hr_linear,DISCRETIONARY - Auto Distance: Duration < 1 hr - Linear,"@np.where(((df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)) * (df.origin_to_destination_distance), 0)",coef_discretionary_auto_distance_duration_less_than_1_hr_linear +util_discretionary_auto_distance_duration_greater_than_1_hr_linear,DISCRETIONARY - Auto Distance: Duration > 1 hr - Linear,"@np.where(((df.duration>3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)) * (df.origin_to_destination_distance), 0)",coef_discretionary_auto_distance_duration_greater_than_1_hr_linear +util_discretionary_time_pressure_duration_less_than_1_hr,DISCRETIONARY - Time Pressure - Duration < 1 hr,"@np.where(((df.duration<3)), np.minimum(3-df.duration,47), 0) * (np.log10 (30 * (tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num))))",coef_discretionary_time_pressure_duration_less_than_1_hr +util_discretionary_time_pressure_duration_greater_than_1_hr,DISCRETIONARY - Time Pressure - Duration > 1 hr,"@np.where(((df.duration>3)), np.minimum(df.duration-3,47) * (np.log10 (30 * (tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num)))), 0)",coef_discretionary_time_pressure_duration_greater_than_1_hr +util_discretionary_number_of_additional_individual_social_and_dicretionary_tours_duration_less_than_1_hr,DISCRETIONARY - Number of additional individual social and dicretionary tours - Duration < 1 hr,"@np.where(((df.tour_category != 'joint')&(df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0))*(df.num_add_soc_discr_tours),0)",coef_discretionary_number_of_additional_individual_social_and_dicretionary_tours_duration_less_than_1_hr +util_discretionary_departure_constant_shift_for_every_30_minutes_before_7_30_pm_linear,DISCRETIONARY - Departure Constant: Shift for every 30 minutes before 07:30 pm - Linear,"@np.where(((df.start<9)), (np.where((df.start<9), np.minimum(9-df.start,48), 0) + np.where((df.start>48), np.minimum(df.start-48,48),0)), 0)",coef_discretionary_departure_constant_shift_for_every_30_minutes_before_7_30_pm_linear +util_discretionary_departure_constant_before_7_30_am,DISCRETIONARY - Departure Constant: Before 7:30 AM ,@((df.start<10)),coef_discretionary_departure_constant_before_7_30_am +util_discretionary_departure_constant_7_30_am_to_8_am,DISCRETIONARY - Departure Constant: 7:30 AM to 8:00 AM,@((df.start==10)),coef_discretionary_departure_constant_7_30_am_to_8_am +util_discretionary_departure_constant_8_am_to_8_30_am,DISCRETIONARY - Departure Constant: 8:00 AM to 8:30 AM,@((df.start==11)),coef_discretionary_departure_constant_8_am_to_8_30_am +util_discretionary_departure_constant_8_30_am_to_9_am,DISCRETIONARY - Departure Constant: 8:30 AM to 9:00 AM,@((df.start==12)),coef_discretionary_departure_constant_8_30_am_to_9_am +util_discretionary_departure_constant_9_am_to_9_30_am,DISCRETIONARY - Departure Constant: 9:00 AM to 9:30 AM,@((df.start==13)),coef_discretionary_departure_constant_9_am_to_9_30_am +util_discretionary_departure_constant_9_30_am_to_10_am,DISCRETIONARY - Departure Constant: 9:30 AM to 10:00 AM,@((df.start==14)),coef_discretionary_departure_constant_9_30_am_to_10_am +util_discretionary_departure_constant_10_am_to_10_30_am,DISCRETIONARY - Departure Constant: 10:00 AM to 10:30 AM,@((df.start==15)),coef_discretionary_departure_constant_10_am_to_10_30_am +util_discretionary_departure_constant_shift_for_every_30_minutes_before_4_30_pm_linear,DISCRETIONARY - Departure Constant: Shift for every 30 minutes before 04:30 pm - Linear,"@np.where(((df.start<28)), (np.where((df.start<28), np.minimum(28-df.start,8),0) + np.where((df.start>33), np.minimum(df.start-33,6), 0)), 0)",coef_discretionary_departure_constant_shift_for_every_30_minutes_before_4_30_pm_linear +util_discretionary_departure_constant_before_5_pm,DISCRETIONARY - Departure Constant: Before 05:00 PM,@((df.start<29)),coef_discretionary_departure_constant_before_5_pm +util_discretionary_departure_constant_5_pm_to_5_30_pm,DISCRETIONARY - Departure Constant: 05:00 PM - 05:30 PM,@((df.start==29)),coef_discretionary_departure_constant_5_pm_to_5_30_pm +util_discretionary_departure_constant_5_30_pm_to_6_pm,DISCRETIONARY - Departure Constant: 05:30 PM - 06:00 PM,@((df.start==30)),coef_discretionary_departure_constant_5_30_pm_to_6_pm +util_discretionary_departure_constant_6_pm_to_6_30_pm,DISCRETIONARY - Departure Constant: 06:00 PM - 06:30 PM,@((df.start==31)),coef_discretionary_departure_constant_6_pm_to_6_30_pm +util_discretionary_departure_constant_6_30_pm_to_7_pm,DISCRETIONARY - Departure Constant: 06:30 PM - 07:00 PM,@((df.start==32)),coef_discretionary_departure_constant_6_30_pm_to_7_pm +util_discretionary_departure_constant_after_7_pm,DISCRETIONARY - Departure Constant: After 07:00 PM,@((df.start>32)),coef_discretionary_departure_constant_after_7_pm +util_discretionary_departure_constant_shift_for_every_30_minutes_after_7_30_pm_linear,DISCRETIONARY - Departure Constant: Shift for every 30 minutes after 07:30 pm - Linear,"@np.where(((df.start>33)), (np.where((df.start<28), np.minimum(28-df.start,8), 0) + np.where((df.start>33), np.minimum(df.start-33,6), 0)), 0)",coef_discretionary_departure_constant_shift_for_every_30_minutes_after_7_30_pm_linear +util_discretionary_arrival_constant_shift_for_every_30_minutes_before_6_pm_linear,DISCRETIONARY - Arrival Constant: Shift for every 30 minutes before 06:00 pm - Linear,"@np.where(((df.end<31)), (np.where((df.end<31), np.minimum(31-df.end,48), 0) + np.where((df.end>37), np.minimum(df.end-37,48), 0)), 0)",coef_discretionary_arrival_constant_shift_for_every_30_minutes_before_6_pm_linear +util_discretionary_arrival_constant_before_6_30_pm,DISCRETIONARY - Arrival Constant: Before 6:30 PM,@((df.end<32)),coef_discretionary_arrival_constant_before_6_30_pm +util_discretionary_arrival_constant_6_30_pm_to_7_pm,DISCRETIONARY - Arrival Constant: 6:30 PM to 7:00 PM,@((df.end==32)),coef_discretionary_arrival_constant_6_30_pm_to_7_pm +util_discretionary_arrival_constant_7_pm_to_7_30_pm,DISCRETIONARY - Arrival Constant: 7:00 PM to 7:30 PM,@((df.end==33)),coef_discretionary_arrival_constant_7_pm_to_7_30_pm +util_discretionary_arrival_constant_7_30_pm_to_8_pm,DISCRETIONARY - Arrival Constant: 7:30 PM to 8:00 PM,@((df.end==34)),coef_discretionary_arrival_constant_7_30_pm_to_8_pm +util_discretionary_arrival_constant_8_pm_to_8_30_pm,DISCRETIONARY - Arrival Constant: 8:00 PM to 8:30 PM,@((df.end==35)),coef_discretionary_arrival_constant_8_pm_to_8_30_pm +util_discretionary_arrival_constant_8_30_pm_to_9_pm,DISCRETIONARY - Arrival Constant: 8:30 PM to 9:00 PM,@((df.end==36)),coef_discretionary_arrival_constant_8_30_pm_to_9_pm +util_discretionary_arrival_constant_after_9_pm,DISCRETIONARY - Arrival Constant: After 9:00 PM,@((df.end>36)),coef_discretionary_arrival_constant_after_9_pm +util_discretionary_arrival_constant_shift_for_every_30_minutes_after_9_30_pm_linear,DISCRETIONARY - Arrival Constant: Shift for every 30 minutes after 09:30 pm - Linear,"@np.where(((df.end>37)), (np.where((df.end<31), np.minimum(31-df.end,48), 0) + np.where((df.end>37), np.minimum(df.end-37,48),0)), 0)",coef_discretionary_arrival_constant_shift_for_every_30_minutes_after_9_30_pm_linear +util_discretionary_duration_constant_0_hour,DISCRETIONARY - Duration Constant: 0 hour,@((df.duration==0)),coef_discretionary_duration_constant_0_hour +util_discretionary_duration_constant_30_minutes,DISCRETIONARY -Duration Constant: 0.5 hour,@((df.duration==1)),coef_discretionary_duration_constant_30_minutes +util_discretionary_duration_constant_1_hour,DISCRETIONARY -Duration Constant: 1 hour,@((df.duration==2)),coef_discretionary_duration_constant_1_hour +util_discretionary_duration_constant_1_hr_30_minutes,DISCRETIONARY -Duration Constant: 1.5 hours,@((df.duration==3)),coef_discretionary_duration_constant_1_hr_30_minutes +util_discretionary_duration_constant_2_hours,DISCRETIONARY -Duration Constant: 2 hours,@((df.duration==4)),coef_discretionary_duration_constant_2_hours +util_discretionary_duration_constant_2_hr_30_minutes,DISCRETIONARY -Duration Constant: 2.5 hours,@((df.duration==5)),coef_discretionary_duration_constant_2_hr_30_minutes +util_discretionary_duration_constant_3_hours_or_more,DISCRETIONARY -Duration Constant: 3 hours or more,@((df.duration>5)),coef_discretionary_duration_constant_3_hours_or_more +util_discretionary_duration_constant_shift_for_every_30_minutes_more_than_3_hrs_linear,DISCRETIONARY -Duration Constant: Shift for every 30 minutes more than 3 hrs - Linear,"@np.where(((df.duration>6)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>6), np.minimum(df.duration-6,47), 0)), 0)",coef_discretionary_duration_constant_shift_for_every_30_minutes_more_than_3_hrs_linear +util_discretionary_calibration_constant_duration_4,DISCRETIONARY -Calibration Constant - Duration = 4,@((df.duration==3)),coef_discretionary_calibration_constant_duration_4 +util_discretionary_calibration_constant_duration_5,DISCRETIONARY -Calibration Constant - Duration = 5,@((df.duration==4)),coef_discretionary_calibration_constant_duration_5 +util_discretionary_calibration_constant_departure_29,DISCRETIONARY -Calibration Constant - Departure = 29,@((df.start==29)),coef_discretionary_calibration_constant_departure_29 +util_discretionary_calibration_constant_departure_30,DISCRETIONARY -Calibration Constant - Departure = 30,@((df.start==30)),coef_discretionary_calibration_constant_departure_30 +util_discretionary_calibration_constant_departure_31,DISCRETIONARY -Calibration Constant - Departure = 31,@((df.start==31)),coef_discretionary_calibration_constant_departure_31 +util_discretionary_calibration_constant_departure_32,DISCRETIONARY -Calibration Constant - Departure = 32,@((df.start==32)),coef_discretionary_calibration_constant_departure_32 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othdiscr_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othdiscr_coefficients.csv new file mode 100644 index 000000000..d9a4e607c --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othdiscr_coefficients.csv @@ -0,0 +1,53 @@ +coefficient_name,value,constrain +coef_discretionary_person_less_than_18_years_old_duration_less_than_1_hr_30_minutes_linear,-0.262839914,F +coef_discretionary_person_less_than_18_years_old_duration_greater_than_1_hr_30_minutes_linear,0.086919429,F +coef_discretionary_non_working_senior_retiree_duration_less_than_1_hr_30_minutes_linear,0.468354376,F +coef_discretionary_retiree_non_working_senior_only_HH_duration_1_hr_30_minutes_linear,-0.312282762,F +coef_discretionary_zero_auto_households_duration_less_than_1_hr_30_minutes_linear,-0.508439932,F +coef_discretionary_zero_auto_households_duration_greater_than_1_hr_30_minutes_linear,0.074190914,F +coef_discretionary_number_of_auto_more_than_number_of_adults_duration_less_than_1_hr_30_minutes_linear,0.127185965,F +coef_discretionary_number_of_auto_more_than_number_of_adults_duration_greater_than_1_hr_30_minutes_linear,0.048756122,F +coef_discretionary_auto_distance_duration_less_than_1_hr_linear,-0.162965435,F +coef_discretionary_auto_distance_duration_greater_than_1_hr_linear,0.006797399,F +coef_discretionary_time_pressure_duration_less_than_1_hr,-0.229264474,F +coef_discretionary_time_pressure_duration_greater_than_1_hr,0.219325112,F +coef_discretionary_number_of_additional_individual_social_and_dicretionary_tours_duration_less_than_1_hr,0.156250451,F +coef_discretionary_departure_constant_shift_for_every_30_minutes_before_7_30_pm_linear,-0.742176805,F +coef_discretionary_departure_constant_before_7_30_am,-1.323901585,F +coef_discretionary_departure_constant_7_30_am_to_8_am,-0.695441631,F +coef_discretionary_departure_constant_8_am_to_8_30_am,-0.269903336,F +coef_discretionary_departure_constant_8_30_am_to_9_am,-0.093709211,F +coef_discretionary_departure_constant_9_am_to_9_30_am,0.265634082,F +coef_discretionary_departure_constant_9_30_am_to_10_am,0.287521134,F +coef_discretionary_departure_constant_10_am_to_10_30_am,0.396547817,F +coef_discretionary_departure_constant_shift_for_every_30_minutes_before_4_30_pm_linear,-0.245885745,F +coef_discretionary_departure_constant_before_5_pm,-1.344482349,F +coef_discretionary_departure_constant_5_pm_to_5_30_pm,-0.622632748,F +coef_discretionary_departure_constant_5_30_pm_to_6_pm,-0.456718676,F +coef_discretionary_departure_constant_6_pm_to_6_30_pm,-0.206896106,F +coef_discretionary_departure_constant_6_30_pm_to_7_pm,0,T +coef_discretionary_departure_constant_after_7_pm,-0.46439343,F +coef_discretionary_departure_constant_shift_for_every_30_minutes_after_7_30_pm_linear,-0.291998986,F +coef_discretionary_arrival_constant_shift_for_every_30_minutes_before_6_pm_linear,0.148649188,F +coef_discretionary_arrival_constant_before_6_30_pm,0.668775963,F +coef_discretionary_arrival_constant_6_30_pm_to_7_pm,-0.053520826,F +coef_discretionary_arrival_constant_7_pm_to_7_30_pm,0.099726391,F +coef_discretionary_arrival_constant_7_30_pm_to_8_pm,0.063414092,F +coef_discretionary_arrival_constant_8_pm_to_8_30_pm,0,T +coef_discretionary_arrival_constant_8_30_pm_to_9_pm,-0.18610847,F +coef_discretionary_arrival_constant_after_9_pm,-0.423207857,F +coef_discretionary_arrival_constant_shift_for_every_30_minutes_after_9_30_pm_linear,-0.525545923,F +coef_discretionary_duration_constant_0_hour,0.436988282,F +coef_discretionary_duration_constant_30_minutes,1.35967577,F +coef_discretionary_duration_constant_1_hour,1.692672999,F +coef_discretionary_duration_constant_1_hr_30_minutes,1.118932964,F +coef_discretionary_duration_constant_2_hours,0.771255733,F +coef_discretionary_duration_constant_2_hr_30_minutes,0,T +coef_discretionary_duration_constant_3_hours_or_more,-0.631242175,F +coef_discretionary_duration_constant_shift_for_every_30_minutes_more_than_3_hrs_linear,-0.700935645,F +coef_discretionary_calibration_constant_duration_4,-0.132674257,F +coef_discretionary_calibration_constant_duration_5,-0.013371871,F +coef_discretionary_calibration_constant_departure_29,0.232927977,F +coef_discretionary_calibration_constant_departure_30,0.306104612,F +coef_discretionary_calibration_constant_departure_31,0.285520678,F +coef_discretionary_calibration_constant_departure_32,0.115886631,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint.csv new file mode 100644 index 000000000..04f26223e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint.csv @@ -0,0 +1,54 @@ +Label,Description,Expression,Coefficient +#MAINTENANCE,#MAINTENANCE,,#MAINTENANCE +util_maintenance_driving_age_student_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Driving age student: Duration > 1.5 hrs,"@np.where(((df.duration>2) & (df.ptype == 6)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_driving_age_student_duration_greater_than_1_hour_30_minutes +util_maintenance_full_time_worker_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Full-time worker: Duration > 1.5 hrs,"@np.where(((df.duration>2) & (df.ptype == 1)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_full_time_worker_duration_greater_than_1_hour_30_minutes +util_maintenance_non_driving_student_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Non-driving Student: Duration > 1.5 hrs,"@np.where (((df.duration>2) & ((df.ptype == 7)|(df.ptype == 8))), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_non_driving_student_duration_greater_than_1_hour_30_minutes +util_maintenance_pre_school_child_duration_less_than_1_hour_30_minutes,MAINTENANCE - Pre-school Child: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.ptype == 8)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_pre_school_child_duration_less_than_1_hour_30_minutes +util_maintenance_part_time_worker_duration_less_than_1_hour_30_minutes,MAINTENANCE - Part Time Worker: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.ptype == 2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_part_time_worker_duration_less_than_1_hour_30_minutes +util_maintenance_part_time_worker_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Part Time Worker: Duration > 1.5 hrs,"@np.where(((df.duration>2) & (df.ptype == 2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_part_time_worker_duration_greater_than_1_hour_30_minutes +util_maintenance_retired_duration_less_than_1_hour_30_minutes,MAINTENANCE - Retired: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.ptype == 1)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_retired_duration_less_than_1_hour_30_minutes +util_maintenance_retired_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Retired: Duration > 1.5 hr,"@np.where(((df.duration>2) & (df.ptype == 5)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_retired_duration_greater_than_1_hour_30_minutes +util_maintenance_university_student_duration_greater_than_1_hour_30_minutes,MAINTENANCE - University Student: Duration > 1.5 hrs,"@np.where(((df.duration>2) & (df.ptype == 3)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_university_student_duration_greater_than_1_hour_30_minutes +util_maintenance_female_duration_less_than_1_hour_30_minutes,MAINTENANCE - Female: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.female)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_female_duration_less_than_1_hour_30_minutes +util_maintenance_female_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Female: Duration > 1.5 hrs,"@np.where(((df.duration>2) & (df.female)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_female_duration_greater_than_1_hour_30_minutes +util_maintenance_low_income_duration_greater_than_1_hour_30_minutes,"MAINTENANCE - Low Income (<=$25,000): Duration > 1.5 hrs","@np.where(((df.is_income_less25K) & (df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_low_income_duration_greater_than_1_hour_30_minutes +util_maintenance_medium_income_duration_less_than_1_hour_30_minutes,"MAINTENANCE - Medium Income ($25,001 to $60,000): Duration < 1.5 hrs","@np.where(((df.is_income_25K_to_60K) & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_medium_income_duration_less_than_1_hour_30_minutes +util_maintenance_medium_income_duration_greater_than_1_hour_30_minutes,"MAINTENANCE - Medium Income ($25,001 to $60,000): Duration > 1.5 hrs","@np.where(((df.is_income_25K_to_60K) & (df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_medium_income_duration_greater_than_1_hour_30_minutes +util_maintenance_medium_high_income_duration_greater_than_1_hour_30_minutes,"MAINTENANCE - Medium-High Income ($60,001 to $120,00): Duration > 1.5 hrs","@np.where(((df.is_income_60K_to_120K) & (df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_medium_high_income_duration_greater_than_1_hour_30_minutes +util_maintenance_distance_duration_less_than_1_hour_30_minutes,MAINTENANCE - Distance: Duration < 1.5 hrs,"@np.where(((df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) *(df.origin_to_destination_distance), 0)",coef_maintenance_distance_duration_less_than_1_hour_30_minutes +util_maintenance_distance_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Distance: Duration > 1.5 hrs,"@np.where(((df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) * (df.origin_to_destination_distance), 0)",coef_maintenance_distance_duration_greater_than_1_hour_30_minutes +util_maintenance_time_pressure_duration_greater_than_1_hour_30_minutes,Time Pressure - Duration > 1.5 hrs,"@np.where(((df.duration>2)), np.minimum(df.duration-2,26) * (np.log10 (30 * (tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num)))), 0)",coef_maintenance_time_pressure_duration_greater_than_1_hour_30_minutes +util_maintenance_number_of_additional_individual_shop_and_maint_tours_duration_less_than_1_hour_30_minutes,MAINTENANCE - Number of additional individual shop and maint. tours - Duration < 1.5 hrs,"@np.where(((df.tour_category != 'joint')&(df.tour_type == 'othmaint')&(df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) * (df.num_add_shop_maint_tours), 0)",coef_maintenance_number_of_additional_individual_shop_and_maint_tours_duration_less_than_1_hour_30_minutes +util_maintenance_number_of_additional_individual_shop_and_maint_tours_duration_greater_than_1_hour_30_minutes,MAINTENANCE - Number of additional individual shop and maint. tours - Duration > 1.5 hrs,"@np.where(((df.tour_category != 'joint')&(df.tour_type == 'othmaint')&(df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) * (df.num_add_shop_maint_tours), 0)",coef_maintenance_number_of_additional_individual_shop_and_maint_tours_duration_greater_than_1_hour_30_minutes +util_maintenance_departure_constant_shift_for_every_30_minutes_before_7_30_am_linear,MAINTENANCE - Departure Constant: Shift for every 30 minutes before 07:30 am - Linear,"@np.where(((df.start<10)), (np.where((df.start<10), np.minimum(10-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)), 0)",coef_maintenance_departure_constant_shift_for_every_30_minutes_before_7_30_am_linear +util_maintenance_departure_constant_shift_for_every_30_minutes_before_7_30_am_square_root,MAINTENANCE - Departure Constant: Shift for every 30 minutes before 07:30 am - Square Root,"@np.where(((df.start<10)), ((np.where((df.start<10), np.minimum(10-df.start,7), 0) + (np.where((df.start>17), np.minimum(df.start-17,24), 0)))** 0.5), 0)",coef_maintenance_departure_constant_shift_for_every_30_minutes_before_7_30_am_square_root +util_maintenance_departure_constant_before_8_am,MAINTENANCE - Departure Constant: Before 08:00 AM,@((df.start<11)),coef_maintenance_departure_constant_before_8_am +util_maintenance_departure_constant_8_am_to_8_30_am,MAINTENANCE - Departure Constant: 08:00 AM - 08:30 AM,@((df.start==11)),coef_maintenance_departure_constant_8_am_to_8_30_am +util_maintenance_departure_constant_8_30_am_to_9_00_am,MAINTENANCE - Departure Constant: 08:30 AM - 09:00 AM,@((df.start==12)),coef_maintenance_departure_constant_8_30_am_to_9_00_am +util_maintenance_departure_constant_9_am_to_9_30_am,MAINTENANCE - Departure Constant: 09:00 AM - 09:30 AM,@((df.start==13)),coef_maintenance_departure_constant_9_am_to_9_30_am +util_maintenance_departure_constant_9_30_am_to_10_am,MAINTENANCE - Departure Constant: 09:30 AM - 10:00 AM,@((df.start==14)),coef_maintenance_departure_constant_9_30_am_to_10_am +util_maintenance_departure_constant_10_am_to_10_30_am,MAINTENANCE - Departure Constant: 10:00 AM - 10:30 AM,@((df.start==15)),coef_maintenance_departure_constant_10_am_to_10_30_am +util_maintenance_departure_constant_10_30_am_to_11_am,MAINTENANCE - Departure Constant: 10:30 AM - 11:00 AM,@((df.start==16)),coef_maintenance_departure_constant_10_30_am_to_11_am +util_maintenance_departure_constant_after_11_am,MAINTENANCE - Departure Constant: After 11:00 AM,@((df.start>16)),coef_maintenance_departure_constant_after_11_am +util_maintenance_departure_constant_shift_for_every_30_minutes_after_11_30_am_linear,MAINTENANCE - Departure Constant: Shift for every 30 minutes after 11:30 am - Linear,"@np.where(((df.start>17)), np.where((df.start<10), np.minimum(10-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0), 0)",coef_maintenance_departure_constant_shift_for_every_30_minutes_after_11_30_am_linear +util_maintenance_departure_constant_shift_for_every_30_minutes_after_11_30_am_squared,MAINTENANCE - Departure Constant: Shift for every 30 minutes after 11:30 am - Squared,"@np.where(((df.start>17)), ((np.where((df.start<10), np.minimum(10-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)) ** 2), 0)",coef_maintenance_departure_constant_shift_for_every_30_minutes_after_11_30_am_squared +util_maintenance_arrival_constant_shift_for_every_30_minutes_before_10_am_linear,MAINTENANCE - Arrival Constant: Shift for every 30 minutes before 10:00 am - Linear,"@np.where(((df.end<15)), (np.where((df.end<15), np.minimum(15-df.end,9), 0) + np.where((df.end>28), np.minimum(df.end-28,16), 0)), 0)",coef_maintenance_arrival_constant_shift_for_every_30_minutes_before_10_am_linear +util_maintenance_arrival_constant_before_10_30_am,MAINTENANCE - Arrival Constant: Before 10:30 AM,@((df.end<16)),coef_maintenance_arrival_constant_before_10_30_am +util_maintenance_arrival_constant_10_30_am_to_11_am,MAINTENANCE - Arrival Constant: 10:30 AM - 11:00 AM,@((df.end==16)),coef_maintenance_arrival_constant_10_30_am_to_11_am +util_maintenance_arrival_constant_11_am_to_11_30_am,MAINTENANCE - Arrival Constant: 11:00 AM - 11:30 AM,@((df.end==17)),coef_maintenance_arrival_constant_11_am_to_11_30_am +util_maintenance_arrival_constant_11_30_am_to_1_30_pm,MAINTENANCE - Arrival Constant: 11:30 AM - 01:30 PM,@((df.end>=18) & (df.end<=21)),coef_maintenance_arrival_constant_11_30_am_to_1_30_pm +util_maintenance_arrival_constant_1_30_pm_to_2_30_pm,MAINTENANCE - Arrival Constant: 01:30 PM - 02:30 PM,@((df.end>=22) & (df.end<=23)),coef_maintenance_arrival_constant_1_30_pm_to_2_30_pm +util_maintenance_arrival_constant_2_30_pm_to_4_pm,MAINTENANCE - Arrival Constant: 02:30 PM - 04:00 PM,@((df.end>=24) & (df.end<=26)),coef_maintenance_arrival_constant_2_30_pm_to_4_pm +util_maintenance_arrival_constant_4_pm_to_4_30_pm,MAINTENANCE - Arrival Constant: 04:00 PM - 04:30 PM,@((df.end==27)),coef_maintenance_arrival_constant_4_pm_to_4_30_pm +util_maintenance_arrival_constant_after_4_30_pm,MAINTENANCE - Arrival Constant: After 04:30 PM,@((df.end>27)),coef_maintenance_arrival_constant_after_4_30_pm +util_maintenance_arrival_constant_shift_for_every_30_minutes_after_5_pm_linear,MAINTENANCE - Arrival Constant: Shift for every 30 minutes after 5:00 pm - Linear,"@np.where(((df.end>28)), (np.where((df.end<15), np.minimum(15-df.end,9), 0) + np.where((df.end>28), np.minimum(df.end-28,16), 0)), 0)",coef_maintenance_arrival_constant_shift_for_every_30_minutes_after_5_pm_linear +util_maintenance_duration_constant_0_hr,MAINTENANCE - Duration Constant: 0 hr,@((df.duration==0)),coef_maintenance_duration_constant_0_hr +util_maintenance_duration_constant_30_minutes,MAINTENANCE - Duration Constant: 0.5 hr,@((df.duration==1)),coef_maintenance_duration_constant_30_minutes +util_maintenance_duration_constant_longer_than_30_minutes,MAINTENANCE - Duration Constant: Longer than 0.5 hr,@((df.duration>1)),coef_maintenance_duration_constant_longer_than_30_minutes +util_maintenance_duration_constant_duration_greater_than_1_hr_linear,MAINTENANCE - Duration Constant: Duration > 1 hr - Linear,"@np.where(((df.duration>2)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0)), 0)",coef_maintenance_duration_constant_duration_greater_than_1_hr_linear +util_maintenance_duration_constant_duration_greater_than_1_hr_square_root,MAINTENANCE - Duration Constant: Duration > 1 hr - Square Root,"@np.where(((df.duration>2)), ((np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0))** 0.5), 0)",coef_maintenance_duration_constant_duration_greater_than_1_hr_square_root +util_maintenance_calibration_constant_duration_1,MAINTENANCE - Calibration Constant - Duration = 1,@((df.duration==0)),coef_maintenance_calibration_constant_duration_1 +util_maintenance_calibration_constant_duration_2,MAINTENANCE - Calibration Constant - Duration = 2,@((df.duration==1)),coef_maintenance_calibration_constant_duration_2 +util_maintenance_calibration_constant_duration_3,MAINTENANCE - Calibration Constant - Duration = 3,@((df.duration==2)),coef_maintenance_calibration_constant_duration_3 +util_maintenance_calibration_constant_duration_4,MAINTENANCE - Calibration Constant - Duration = 4,@((df.duration==3)),coef_maintenance_calibration_constant_duration_4 +util_maintenance_calibration_constant_duration_5,MAINTENANCE - Calibration Constant - Duration = 5,@((df.duration==4)),coef_maintenance_calibration_constant_duration_5 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint_coefficients.csv new file mode 100644 index 000000000..991068579 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_othmaint_coefficients.csv @@ -0,0 +1,53 @@ +coefficient_name,value,constrain +coef_maintenance_driving_age_student_duration_greater_than_1_hour_30_minutes,0.122149101,F +coef_maintenance_full_time_worker_duration_greater_than_1_hour_30_minutes,-0.037886459,F +coef_maintenance_non_driving_student_duration_greater_than_1_hour_30_minutes,0.10247157,F +coef_maintenance_pre_school_child_duration_less_than_1_hour_30_minutes,-1.882944033,F +coef_maintenance_part_time_worker_duration_less_than_1_hour_30_minutes,-0.197455071,F +coef_maintenance_part_time_worker_duration_greater_than_1_hour_30_minutes,-0.045152663,F +coef_maintenance_retired_duration_less_than_1_hour_30_minutes,-0.264728908,F +coef_maintenance_retired_duration_greater_than_1_hour_30_minutes,-0.042981757,F +coef_maintenance_university_student_duration_greater_than_1_hour_30_minutes,0.045926523,F +coef_maintenance_female_duration_less_than_1_hour_30_minutes,-0.417208254,F +coef_maintenance_female_duration_greater_than_1_hour_30_minutes,0.045801918,F +coef_maintenance_low_income_duration_greater_than_1_hour_30_minutes,0.040776383,F +coef_maintenance_medium_income_duration_less_than_1_hour_30_minutes,0.108462927,F +coef_maintenance_medium_income_duration_greater_than_1_hour_30_minutes,0,T +coef_maintenance_medium_high_income_duration_greater_than_1_hour_30_minutes,-0.037893416,F +coef_maintenance_distance_duration_less_than_1_hour_30_minutes,-0.214802537,F +coef_maintenance_distance_duration_greater_than_1_hour_30_minutes,0.007991656,F +coef_maintenance_time_pressure_duration_greater_than_1_hour_30_minutes,0.013503327,F +coef_maintenance_number_of_additional_individual_shop_and_maint_tours_duration_less_than_1_hour_30_minutes,0.078844289,F +coef_maintenance_number_of_additional_individual_shop_and_maint_tours_duration_greater_than_1_hour_30_minutes,-0.115431492,F +coef_maintenance_departure_constant_shift_for_every_30_minutes_before_7_30_am_linear,-0.864112609,F +coef_maintenance_departure_constant_shift_for_every_30_minutes_before_7_30_am_square_root,0.504598473,F +coef_maintenance_departure_constant_before_8_am,-0.383711788,F +coef_maintenance_departure_constant_8_am_to_8_30_am,-0.076771517,F +coef_maintenance_departure_constant_8_30_am_to_9_00_am,-0.169259979,F +coef_maintenance_departure_constant_9_am_to_9_30_am,-0.051785379,F +coef_maintenance_departure_constant_9_30_am_to_10_am,-0.214942451,F +coef_maintenance_departure_constant_10_am_to_10_30_am,0,T +coef_maintenance_departure_constant_10_30_am_to_11_am,-0.427568963,F +coef_maintenance_departure_constant_after_11_am,-0.520863411,F +coef_maintenance_departure_constant_shift_for_every_30_minutes_after_11_30_am_linear,0.042879095,F +coef_maintenance_departure_constant_shift_for_every_30_minutes_after_11_30_am_squared,-0.003157293,F +coef_maintenance_arrival_constant_shift_for_every_30_minutes_before_10_am_linear,-0.226803619,F +coef_maintenance_arrival_constant_before_10_30_am,-0.223212258,F +coef_maintenance_arrival_constant_10_30_am_to_11_am,0,T +coef_maintenance_arrival_constant_11_am_to_11_30_am,-0.128382637,F +coef_maintenance_arrival_constant_11_30_am_to_1_30_pm,0.167977332,F +coef_maintenance_arrival_constant_1_30_pm_to_2_30_pm,-0.149495878,F +coef_maintenance_arrival_constant_2_30_pm_to_4_pm,0.087679934,F +coef_maintenance_arrival_constant_4_pm_to_4_30_pm,0.121707557,F +coef_maintenance_arrival_constant_after_4_30_pm,0.106745013,F +coef_maintenance_arrival_constant_shift_for_every_30_minutes_after_5_pm_linear,-0.232610927,F +coef_maintenance_duration_constant_0_hr,-0.483549396,F +coef_maintenance_duration_constant_30_minutes,0,T +coef_maintenance_duration_constant_longer_than_30_minutes,-1.450618319,F +coef_maintenance_duration_constant_duration_greater_than_1_hr_linear,-0.275082922,F +coef_maintenance_duration_constant_duration_greater_than_1_hr_square_root,0.208434683,F +coef_maintenance_calibration_constant_duration_1,-0.124602605,F +coef_maintenance_calibration_constant_duration_2,-0.103637715,F +coef_maintenance_calibration_constant_duration_3,-0.225442145,F +coef_maintenance_calibration_constant_duration_4,-0.145273012,F +coef_maintenance_calibration_constant_duration_5,-0.019241539,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping.csv new file mode 100644 index 000000000..11211303e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping.csv @@ -0,0 +1,54 @@ +Label,Description,Expression,Coefficient +#SHOPPING,,,#SHOPPING +util_shoppping_driving_age_student_duration_greater_than_1_hour_30_minutes,SHOPPING - Driving age student: Duration > 1.5 hrs,"@np.where(((df.duration>2) & (df.ptype == 6)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0)), 0)",coef_shoppping_driving_age_student_duration_greater_than_1_hour_30_minutes +util_shoppping_full_time_worker_duration_greater_than_1_hour_30_minutes,SHOPPING - Full-time worker: Duration > 1.5 hr,"@np.where(((df.duration>2) & (df.ptype == 1)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shoppping_full_time_worker_duration_greater_than_1_hour_30_minutes +util_shoppping_non_driving_student_duration_greater_than_1_hour_30_minutes,SHOPPING - Non-driving Student: Duration > 1.5 hrs,"@np.where(((df.duration>2) & ((df.ptype == 7)|(df.ptype == 8))), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shoppping_non_driving_student_duration_greater_than_1_hour_30_minutes +util_shoppping_pre_school_child_duration_less_than_1_hour_30_minutes,SHOPPING - Pre-school Child: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.ptype == 8)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shoppping_pre_school_child_duration_less_than_1_hour_30_minutes +util_shoppping_part_time_worker_duration_less_than_1_hour_30_minutes,SHOPPING - Part Time Worker: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.ptype == 2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shoppping_part_time_worker_duration_less_than_1_hour_30_minutes +util_shopping_part_time_worker_duration_greater_than_1_hour_30_minutes,SHOPPING - Part Time Worker: Duration > 1.5 hr,"@np.where(((df.duration>2) & (df.ptype == 2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_part_time_worker_duration_greater_than_1_hour_30_minutes +util_shopping_retired_duration_less_than_1_hour_30_minutes,SHOPPING - Retired: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.ptype == 5)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_retired_duration_less_than_1_hour_30_minutes +util_shopping_retired_duration_greater_than_1_hour_30_minutes,SHOPPING - Retired: Duration > 1.5 hr,"@np.where(((df.duration>2) & (df.ptype == 5)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_retired_duration_greater_than_1_hour_30_minutes +util_shopping_university_student_duration_greater_than_1_hour_30_minutes,SHOPPING - University Student: Duration > 1.5 hr,"@np.where(((df.duration>2) & (df.ptype == 3)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_university_student_duration_greater_than_1_hour_30_minutes +util_shopping_female_duration_less_than_1_hour_30_minutes,SHOPPING - Female: Duration < 1.5 hrs,"@np.where(((df.duration<2) & (df.female)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_female_duration_less_than_1_hour_30_minutes +util_shopping_female_duration_greater_than_1_hour_30_minutes,SHOPPING - Female: Duration > 1.5 hr,"@np.where(((df.duration>2) & (df.female)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_female_duration_greater_than_1_hour_30_minutes +util_shopping_low_income_duration_greater_than_1_hour_30_minutes,"SHOPPING - Low Income (<=$25,000): Duration > 1.5 hr","@np.where(((df.is_income_less25K) & (df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_low_income_duration_greater_than_1_hour_30_minutes +util_shopping_medium_income_duration_less_than_1_hour_30_minutes,"SHOPPING - Medium Income ($25,001 to $60,000): Duration < 1.5 hrs","@np.where(((df.is_income_25K_to_60K) & (df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_medium_income_duration_less_than_1_hour_30_minutes +util_shopping_medium_high_income_duration_greater_than_1_hour_30_minutes,"SHOPPING - Medium-High Income ($60,001 to $120,00): Duration > 1.5 hrs","@np.where(((df.is_income_60K_to_120K) & (df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2), np.minimum(df.duration-2,26), 0)), 0)",coef_shopping_medium_high_income_duration_greater_than_1_hour_30_minutes +util_shopping_distance_duration_less_than_1_hour_30_minutes,SHOPPING - Distance: Duration < 1.5 hrs,"@np.where(((df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) * (df.origin_to_destination_distance), 0)",coef_shopping_distance_duration_less_than_1_hour_30_minutes +util_shopping_distance_duration_greater_than_1_hour_30_minutes,SHOPPING - Distance: Duration > 1.5 hrs,"@np.where(((df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) * (df.origin_to_destination_distance), 0)",coef_shopping_distance_duration_greater_than_1_hour_30_minutes +util_shopping_time_pressure_duration_greater_than_1_hour_30_minutes,SHOPPING - Time Pressure - Duration > 1.5 hrs,"@np.where(((df.duration>2)), np.minimum(df.duration-2,26) *(np.log10 (30 *(tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num)))), 0)",coef_shopping_time_pressure_duration_greater_than_1_hour_30_minutes +util_shopping_number_of_additional_individual_shop_and_maint_tours_duration_less_than_1_hour_30_minutes,SHOPPING - Number of additional individual shop and maint. tours - Duration < 1.5 hrs,"@np.where(((df.duration<2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) *(df.num_add_shop_maint_tours), 0)",coef_shopping_number_of_additional_individual_shop_and_maint_tours_duration_less_than_1_hour_30_minutes +util_shopping_number_of_additional_individual_shop_and_maint_tours_duration_greater_than_1_hour_30_minutes,SHOPPING - Number of additional individual shop and maint. tours - Duration > 1.5 hrs,"@np.where(((df.tour_type == 'shopping') &(df.duration>2)), (np.where((df.duration<=2), np.minimum(2-df.duration,1), 0) + np.where((df.duration>2),np.minimum(df.duration-2,26), 0)) *(df.num_add_shop_maint_tours), 0)",coef_shopping_number_of_additional_individual_shop_and_maint_tours_duration_greater_than_1_hour_30_minutes +util_shopping_departure_constant_shift_for_every_30_minutes_before_8_30_am_linear,SHOPPING - Departure Constant: Shift for every 30 minutes before 08:30 am - Linear,"@np.where(((df.start<12)), (np.where((df.start<12), np.minimum(12-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)), 0)",coef_shopping_departure_constant_shift_for_every_30_minutes_before_8_30_am_linear +util_shopping_departure_constant_shift_for_every_30_minutes_before_8_30_am_square_root,SHOPPING - Departure Constant: Shift for every 30 minutes before 08:30 am - Square root,"@np.where(((df.start<12)), (np.where((df.start<12), np.minimum(12-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0))**0.5, 0)",coef_shopping_departure_constant_shift_for_every_30_minutes_before_8_30_am_square_root +util_shopping_departure_constant_before_9_am,SHOPPING - Departure Constant: Before 09:00 AM,@((df.start<13)),coef_shopping_departure_constant_before_9_am +util_shopping_departure_constant_9_am_to_9_30_am,SHOPPING - Departure Constant: 09:00 AM - 09:30 AM,@((df.start==13)),coef_shopping_departure_constant_9_am_to_9_30_am +util_shopping_departure_constant_9_30_am_to_10_am,SHOPPING - Departure Constant: 09:30 AM - 10:00 AM,@((df.start==14)),coef_shopping_departure_constant_9_30_am_to_10_am +util_shopping_departure_constant_10_am_to_10_30_am,SHOPPING - Departure Constant: 10:00 AM - 10:30 AM,@((df.start==15)),coef_shopping_departure_constant_10_am_to_10_30_am +util_shopping_departure_constant_10_30_am_to_11_00_am,SHOPPING - Departure Constant: 10:30 AM - 11:00 AM,@((df.start==16)),coef_shopping_departure_constant_10_30_am_to_11_00_am +util_shopping_departure_constant_after_11_am,SHOPPING - Departure Constant: After 11:00 AM,@((df.start>16)),coef_shopping_departure_constant_after_11_am +util_shopping_departure_constant_shift_for_every_30_minutes_after_11_30_am_linear,SHOPPING - Departure Constant: Shift for every 30 minutes after 11:30 am - Linear,"@np.where(((df.start>17)), (np.where((df.start<12), np.minimum(12-df.start,7),0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)), 0)",coef_shopping_departure_constant_shift_for_every_30_minutes_after_11_30_am_linear +util_shopping_departure_constant_shift_for_every_30_minutes_after_11_30_am_squared,SHOPPING - Departure Constant: Shift for every 30 minutes after 11:30 am - Squared,"@np.where(((df.start>17)), ((np.where((df.start<12), np.minimum(12-df.start,7), 0) + np.where((df.start>17), np.minimum(df.start-17,24), 0)) ** 2), 0)",coef_shopping_departure_constant_shift_for_every_30_minutes_after_11_30_am_squared +util_shopping_arrival_constant_shift_for_every_30_minutes_before_12_pm_linear,SHOPPING - Arrival Constant: Shift for every 30 minutes before 12:00 pm - Linear,"@np.where(((df.end<19)), (np.where ((df.end<19), np.minimum(19-df.end,10), 0) + np.where((df.end>38), np.minimum(df.end-38,5), 0)), 0)",coef_shopping_arrival_constant_shift_for_every_30_minutes_before_12_pm_linear +util_shopping_arrival_constant_before_12_30_pm,SHOPPING - Arrival Constant: Before 12:30 PM,@((df.end<20)),coef_shopping_arrival_constant_before_12_30_pm +util_shopping_arrival_constant_12_30_pm_to_3_pm,SHOPPING - Arrival Constant: 12:30 PM - 03:00 PM,@(( df.end>=20) & (df.end<=24)),coef_shopping_arrival_constant_12_30_pm_to_3_pm +util_shopping_arrival_constant_3_pm_to_3_30_pm,SHOPPING - Arrival Constant: 03:00 PM - 03:30 PM,@((df.end==25)),coef_shopping_arrival_constant_3_pm_to_3_30_pm +util_shopping_arrival_constant_3_30_pm_to_4_pm,SHOPPING - Arrival Constant: 03:30 PM - 04:00 PM,@((df.end==26)),coef_shopping_arrival_constant_3_30_pm_to_4_pm +util_shopping_arrival_constant_4_pm_to_4_30_pm,SHOPPING - Arrival Constant: 04:00 PM - 04:30 PM,@((df.end==27)),coef_shopping_arrival_constant_4_pm_to_4_30_pm +util_shopping_arrival_constant_4_30_pm_to_5_pm,SHOPPING - Arrival Constant: 04:30 PM - 05:00 PM,@((df.end==28)),coef_shopping_arrival_constant_4_30_pm_to_5_pm +util_shopping_arrival_constant_5_pm_to_5_30_pm,SHOPPING - Arrival Constant: 05:00 PM - 05:30 PM,@((df.end==29)),coef_shopping_arrival_constant_5_pm_to_5_30_pm +util_shopping_arrival_constant_5_30_pm_to_7_pm,SHOPPING - Arrival Constant: 05:30 PM - 07:00 PM,@((df.end>=30) & (df.end<=32)),coef_shopping_arrival_constant_5_30_pm_to_7_pm +util_shopping_arrival_constant_7_pm_to_9_30_pm,SHOPPING - Arrival Constant: 07:00 PM - 09:30 PM,@((df.end>=33) & (df.end<=37)),coef_shopping_arrival_constant_7_pm_to_9_30_pm +util_shopping_arrival_constant_after_9_30_pm,SHOPPING - Arrival Constant: After 09:30 PM,@((df.end>37)),coef_shopping_arrival_constant_after_9_30_pm +util_shopping_arrival_constant_shift_for_every_30_minutes_after_10_pm_linear,SHOPPING - Arrival Constant: Shift for every 30 minutes after 10:00 pm - Linear,"@np.where(((df.end>38)), (np.where((df.end<19), np.minimum(19-df.end,10), 0) + np.where ((df.end>38), np.minimum(df.end-38,5), 0)), 0)",coef_shopping_arrival_constant_shift_for_every_30_minutes_after_10_pm_linear +util_shopping_duration_constant_0_hr,SHOPPING - Duration Constant: 0 hr,@((df.duration==0)),coef_shopping_duration_constant_0_hr +util_shopping_duration_constant_30_minutes,SHOPPING - Duration Constant: 0.5 hr,@((df.duration==1)),coef_shopping_duration_constant_30_minutes +util_shopping_duration_constant_1_hr,SHOPPING - Duration Constant: 1 hr,@((df.duration==2)),coef_shopping_duration_constant_1_hr +util_shopping_duration_constant_1_hour_30_minutes,SHOPPING - Duration Constant: 1.5hrs,@(df.duration==3),coef_shopping_duration_constant_1_hour_30_minutes +util_shopping_duration_constant_2_hrs,SHOPPING - Duration Constant: 2 hrs,@((df.duration==4)),coef_shopping_duration_constant_2_hrs +util_shopping_duration_constant_longer_than_2_hrs,SHOPPING - Duration Constant: Longer than 2 hrs,@((df.duration>4)),coef_shopping_duration_constant_longer_than_2_hrs +util_shopping_duration_constant_duration_greater_than_2_hr_30_minutes_linear,SHOPPING - Duration Constant: Duration > 2.5 hrs - Linear,"@np.where(((df.duration>5)), (np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>5), np.minimum(df.duration-5,26), 0)), 0)",coef_shopping_duration_constant_duration_greater_than_2_hr_30_minutes_linear +util_shopping_duration_constant_duration_greater_than_2_hr_30_minutes_square_root,SHOPPING - Duration Constant: Duration > 2.5 hrs - Square root,"@np.where(((df.duration>5)), ((np.where((df.duration<0), np.minimum(0-df.duration,47), 0) + np.where((df.duration>5), np.minimum(df.duration-5,26), 0)) ** 0.5), 0)",coef_shopping_duration_constant_duration_greater_than_2_hr_30_minutes_square_root +util_shopping_calibration_constant_duration_1,SHOPPING - Calibration Constant - Duration = 1,@((df.duration==0)),coef_shopping_calibration_constant_duration_1 +util_shopping_calibration_constant_duration_2,SHOPPING - Calibration Constant - Duration = 2,@((df.duration==1)),coef_shopping_calibration_constant_duration_2 +util_shopping_calibration_constant_duration_3,SHOPPING - Calibration Constant - Duration = 3,@((df.duration==2)),coef_shopping_calibration_constant_duration_3 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping_coefficients.csv new file mode 100644 index 000000000..fac50e210 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_shopping_coefficients.csv @@ -0,0 +1,53 @@ +coefficient_name,value,constrain +coef_shoppping_driving_age_student_duration_greater_than_1_hour_30_minutes,0.122149101,F +coef_shoppping_full_time_worker_duration_greater_than_1_hour_30_minutes,-0.037886459,F +coef_shoppping_non_driving_student_duration_greater_than_1_hour_30_minutes,0.10247157,F +coef_shoppping_pre_school_child_duration_less_than_1_hour_30_minutes,-1.882944033,F +coef_shoppping_part_time_worker_duration_less_than_1_hour_30_minutes,-0.197455071,F +coef_shopping_part_time_worker_duration_greater_than_1_hour_30_minutes,-0.045152663,F +coef_shopping_retired_duration_less_than_1_hour_30_minutes,-0.264728908,F +coef_shopping_retired_duration_greater_than_1_hour_30_minutes,-0.042981757,F +coef_shopping_university_student_duration_greater_than_1_hour_30_minutes,0.045926523,F +coef_shopping_female_duration_less_than_1_hour_30_minutes,-0.417208254,F +coef_shopping_female_duration_greater_than_1_hour_30_minutes,0.045801918,F +coef_shopping_low_income_duration_greater_than_1_hour_30_minutes,0.040776383,F +coef_shopping_medium_income_duration_less_than_1_hour_30_minutes,0.108462927,F +coef_shopping_medium_high_income_duration_greater_than_1_hour_30_minutes,-0.037893416,F +coef_shopping_distance_duration_less_than_1_hour_30_minutes,-0.214802537,F +coef_shopping_distance_duration_greater_than_1_hour_30_minutes,0.007991656,F +coef_shopping_time_pressure_duration_greater_than_1_hour_30_minutes,0.013503327,F +coef_shopping_number_of_additional_individual_shop_and_maint_tours_duration_less_than_1_hour_30_minutes,0.078844289,F +coef_shopping_number_of_additional_individual_shop_and_maint_tours_duration_greater_than_1_hour_30_minutes,-0.115431492,F +coef_shopping_departure_constant_shift_for_every_30_minutes_before_8_30_am_linear,-0.959875456,F +coef_shopping_departure_constant_shift_for_every_30_minutes_before_8_30_am_square_root,1.112594898,F +coef_shopping_departure_constant_before_9_am,-0.446394064,F +coef_shopping_departure_constant_9_am_to_9_30_am,-0.021669265,F +coef_shopping_departure_constant_9_30_am_to_10_am,-0.282978638,F +coef_shopping_departure_constant_10_am_to_10_30_am,0,T +coef_shopping_departure_constant_10_30_am_to_11_00_am,-0.309421311,F +coef_shopping_departure_constant_after_11_am,-0.541073357,F +coef_shopping_departure_constant_shift_for_every_30_minutes_after_11_30_am_linear,-0.072013428,F +coef_shopping_departure_constant_shift_for_every_30_minutes_after_11_30_am_squared,-0.000653398,F +coef_shopping_arrival_constant_shift_for_every_30_minutes_before_12_pm_linear,-0.18376635,F +coef_shopping_arrival_constant_before_12_30_pm,-0.716195343,F +coef_shopping_arrival_constant_12_30_pm_to_3_pm,-0.502714001,F +coef_shopping_arrival_constant_3_pm_to_3_30_pm,-0.167868872,F +coef_shopping_arrival_constant_3_30_pm_to_4_pm,-0.156786941,F +coef_shopping_arrival_constant_4_pm_to_4_30_pm,0,T +coef_shopping_arrival_constant_4_30_pm_to_5_pm,-0.057314044,F +coef_shopping_arrival_constant_5_pm_to_5_30_pm,-0.580040851,F +coef_shopping_arrival_constant_5_30_pm_to_7_pm,-0.32239566,F +coef_shopping_arrival_constant_7_pm_to_9_30_pm,-0.347828147,F +coef_shopping_arrival_constant_after_9_30_pm,-1.123574723,F +coef_shopping_arrival_constant_shift_for_every_30_minutes_after_10_pm_linear,-0.499770654,F +coef_shopping_duration_constant_0_hr,-0.131743185,F +coef_shopping_duration_constant_30_minutes,0.888857137,F +coef_shopping_duration_constant_1_hr,0,T +coef_shopping_duration_constant_1_hour_30_minutes,-0.333413031,F +coef_shopping_duration_constant_2_hrs,-0.850897912,F +coef_shopping_duration_constant_longer_than_2_hrs,-1.203783479,F +coef_shopping_duration_constant_duration_greater_than_2_hr_30_minutes_linear,-0.293581223,F +coef_shopping_duration_constant_duration_greater_than_2_hr_30_minutes_square_root,-0.215759138,F +coef_shopping_calibration_constant_duration_1,-0.138450424,F +coef_shopping_calibration_constant_duration_2,-0.092704403,F +coef_shopping_calibration_constant_duration_3,-0.087738073,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social.csv new file mode 100644 index 000000000..174da53c8 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social.csv @@ -0,0 +1,54 @@ +Label,Description,Expression,Coefficient +#SOCIAL,#SOCIAL,,#SOCIAL +util_social_person_less_than_18_years_old_duration_less_than_1_hr_30_minutes_linear,SOCIAL - Person< 18 years old: Duration < 1.5 hrs - Linear,"@np.where(((df.duration<3) & (df.age<18)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_person_less_than_18_years_old_duration_less_than_1_hr_30_minutes_linear +util_social_person_less_than_18_years_old_duration_greater_than_1_hr_30_minutes_linear,SOCIAL - Person< 18 years old: Duration > 1.5 hrs - Linear,"@np.where(((df.duration>3) & (df.age<18)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_person_less_than_18_years_old_duration_greater_than_1_hr_30_minutes_linear +util_social_non_working_senior_or_retiree_duration_less_than_1_hr_30_minutes_linear,SOCIAL - Non-working senior/ retiree: Duration < 1.5 hrs - Linear,"@np.where(((df.duration<3) & (df.ptype == 5)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_social_non_working_senior_or_retiree_duration_less_than_1_hr_30_minutes_linear +util_social_retiree_or_non_working_senior_only_HH_duration_less_than_1_hr_30_minutes_linear,SOCIAL - Retiree/ Non-working senior only HH: Duration < 1.5 hrs - Linear,"@np.where(((df.retired_adults_only_hh) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_retiree_or_non_working_senior_only_HH_duration_less_than_1_hr_30_minutes_linear +util_social_zero_auto_households_duration_less_than_1_hr_30_minutes_linear,SOCIAL - Zero auto households: Duration < 1.5 hrs - Linear,"@np.where(((df.auto_ownership == 0) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_zero_auto_households_duration_less_than_1_hr_30_minutes_linear +util_social_zero_auto_households_duration_greater_than_1_hr_30_minutes_linear,SOCIAL - Zero auto households: Duration > 1.5 hrs - Linear,"@np.where(((df.auto_ownership == 0) & (df.duration>3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)), 0)",coef_social_zero_auto_households_duration_greater_than_1_hr_30_minutes_linear +util_social_number_of_auto_more_than_number_of_adults_duration_less_than_1_hr_30_minutes_linear,SOCIAL - Number of auto more than number of adults: Duration < 1.5 hrs - Linear,"@np.where(((df.auto_ownership > 0) &(df.auto_ownership > df.num_adults) & (df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_social_number_of_auto_more_than_number_of_adults_duration_less_than_1_hr_30_minutes_linear +util_social_number_of_auto_more_than_number_of_adults_duration_greater_than_1_hr_30_minutes_linear,SOCIAL - Number of auto more than number of adults: Duration > 1.5 hrs - Linear,"@np.where(((df.auto_ownership > 0) & (df.auto_ownership > df.num_adults) & (df.duration>3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3), np.minimum(df.duration-3,47), 0)), 0)",coef_social_number_of_auto_more_than_number_of_adults_duration_greater_than_1_hr_30_minutes_linear +"# In CTRAMP, although the description below says duration is less than 1 hr, expression is for less than 1.5 hr",,, +util_social_auto_distance_duration_less_than_1_hr_linear,SOCIAL - Auto Distance: Duration < 1 hr - Linear,"@np.where(((df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)) * (df.origin_to_destination_distance), 0)",coef_social_auto_distance_duration_less_than_1_hr_linear +util_social_auto_distance_duration_greater_than_1_hr_linear,SOCIAL - Auto Distance: Duration > 1 hr - Linear,"@np.where(((df.duration>3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)) * (df.origin_to_destination_distance), 0)",coef_social_auto_distance_duration_greater_than_1_hr_linear +util_social_time_pressure_duration_less_than_1_hr,SOCIAL - Time Pressure - Duration < 1 hr,"@np.where(((df.duration<3)), np.minimum(3-df.duration,47), 0)* (np.log10 (30 * (tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num))))",coef_social_time_pressure_duration_less_than_1_hr +util_social_time_pressure_duration_greater_than_1_hr,SOCIAL - Time Pressure - Duration > 1 hr,"@np.where(((df.duration>3)), np.minimum(df.duration-3,47), 0) * (np.log10 (30 * (tt.max_time_block_available(df.person_id)/(1.0 + df.tour_count - df.tour_num))))",coef_social_time_pressure_duration_greater_than_1_hr +util_social_number_of_additional_individual_social_and_dicretionary_tours_duration_less_than_1_hr,SOCIAL - Number of additional individual social and dicretionary tours - Duration < 1 hr,"@np.where(((df.duration<3)), (np.where((df.duration<=3), np.minimum(3-df.duration,47), 0) + np.where((df.duration>3),np.minimum(df.duration-3,47), 0)) * (df.num_add_soc_discr_tours), 0)",coef_social_number_of_additional_individual_social_and_dicretionary_tours_duration_less_than_1_hr +util_social_departure_constant_shift_for_every_30_minutes_before_8_30_am_linear,SOCIAL - Departure Constant: Shift for every 30 minutes before 08:30 am - Linear,"@((df.start<12)) * ((np.minimum(12-df.start,48)*(df.start<12)) + (np.minimum(df.start-48,48)*(df.start>48)))",coef_social_departure_constant_shift_for_every_30_minutes_before_8_30_am_linear +util_social_departure_constant_before_9_am,SOCIAL - Departure Constant: Before 09:00 AM,@(df.start<13),coef_social_departure_constant_before_9_am +util_social_departure_constant_9_am_to_9_30_am,SOCIAL - Departure Constant: 09:00 AM to 09:30 AM,@(df.start==13),coef_social_departure_constant_9_am_to_9_30_am +util_social_departure_constant_shift_for_every_30_minutes_before_5_pm_linear,SOCIAL - Departure Constant: Shift for every 30 minutes before 05:00 pm - Linear,"@np.where((df.start<29), (np.where((df.start<29), np.minimum(29-df.start,8), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_social_departure_constant_shift_for_every_30_minutes_before_5_pm_linear +util_social_departure_constant_before_5_30_pm,SOCIAL - Departure Constant: Before 05:30 PM,@((df.start<30)),coef_social_departure_constant_before_5_30_pm +util_social_departure_constant_5_30_pm_to_6_pm,SOCIAL - Departure Constant: 05:30 PM - 06:00 PM,@((df.start==30)),coef_social_departure_constant_5_30_pm_to_6_pm +util_social_departure_constant_6_pm_to_6_30_pm,SOCIAL - Departure Constant: 06:00 PM - 06:30 PM,@((df.start==31)),coef_social_departure_constant_6_pm_to_6_30_pm +util_social_departure_constant_6_30_pm_to_7_pm,SOCIAL - Departure Constant: 06:30 PM - 07:00 PM,@((df.start==32)),coef_social_departure_constant_6_30_pm_to_7_pm +util_social_departure_constant_7_pm_to_7_30_pm,SOCIAL - Departure Constant: 07:00 PM - 07:30 PM,@((df.start==33)),coef_social_departure_constant_7_pm_to_7_30_pm +util_social_departure_constant_after_7_30_pm,SOCIAL - Departure Constant: After 07:30 PM,@((df.start>33)),coef_social_departure_constant_after_7_30_pm +util_social_departure_constant_shift_for_every_30_minutes_after_8_pm_linear,SOCIAL - Departure Constant: Shift for every 30 minutes after 08:00 pm - Linear,"@np.where((df.start>34), (np.where((df.start<29), np.minimum(29-df.start,8), 0) + np.where((df.start>34), np.minimum(df.start-34,6), 0)), 0)",coef_social_departure_constant_shift_for_every_30_minutes_after_8_pm_linear +util_social_arrival_constant_3_pm_to_3_30_pm,SOCIAL - Arrival Constant: 03:00 PM to 03:30 PM,@((df.end==25)),coef_social_arrival_constant_3_pm_to_3_30_pm +util_social_arrival_constant_3_30_pm_to_4_pm,SOCIAL - Arrival Constant: 03:30 PM to 04:00 PM,@((df.end==26)),coef_social_arrival_constant_3_30_pm_to_4_pm +util_social_arrival_constant_4_pm_to_4_30_pm,SOCIAL - Arrival Constant: 04:00 PM to 04:30 PM,@((df.end==27)),coef_social_arrival_constant_4_pm_to_4_30_pm +util_social_arrival_constant_5_pm_to_6_pm,SOCIAL - Arrival Constant: 05:00 PM to 06:00 PM,@((df.end>=29) & (df.end<=30)),coef_social_arrival_constant_5_pm_to_6_pm +util_social_arrival_constant_shift_for_every_30_minutes_before_8_pm_linear,SOCIAL - Arrival Constant: Shift for every 30 minutes before 08:00 pm - Linear,"@np.where(((df.end<35)), (np.where((df.end<35), np.minimum(35-df.end,48), 0) + np.where((df.end>40), np.minimum(df.end-40,48), 0)), 0)",coef_social_arrival_constant_shift_for_every_30_minutes_before_8_pm_linear +util_social_arrival_constant_before_8_30_pm,SOCIAL - Arrival Constant: Before 8:30 PM,@((df.end<36)),coef_social_arrival_constant_before_8_30_pm +util_social_arrival_constant_8_30_pm_to_9_pm,SOCIAL - Arrival Constant: 8:30 PM to 9:00 PM,@((df.end==36)),coef_social_arrival_constant_8_30_pm_to_9_pm +util_social_arrival_constant_9_pm_to_9_30_pm,SOCIAL - Arrival Constant: 9:00 PM to 9:30 PM,@((df.end==37)),coef_social_arrival_constant_9_pm_to_9_30_pm +util_social_arrival_constant_9_30_pm_to_10_pm,SOCIAL - Arrival Constant: 9:30 PM to10:00 PM,@((df.end==38)),coef_social_arrival_constant_9_30_pm_to_10_pm +util_social_arrival_constant_10_pm_to_10_30_pm,SOCIAL - Arrival Constant: 10:00 PM to 10:30 PM,@((df.end==39)),coef_social_arrival_constant_10_pm_to_10_30_pm +util_social_arrival_constant_after_10_30_pm,SOCIAL - Arrival Constant: After 10:30 PM,@((df.end>39)),coef_social_arrival_constant_after_10_30_pm +util_social_arrival_constant_shift_for_every_30_minutes_after_11_pm_linear,SOCIAL - Arrival Constant: Shift for every 30 minutes after 11:00 pm - Linear,"@np.where(((df.end>40)), (np.where((df.end<35), np.minimum(35-df.end,48), 0) +np.where((df.end>40),np.minimum(df.end-40,48),0)), 0)",coef_social_arrival_constant_shift_for_every_30_minutes_after_11_pm_linear +util_social_duration_constant_shift_for_every_30_minutes_less_than_2_hr_30_minutes_linear,SOCIAL - Duration Constant: Shift for every 30 minutes less than 2.5 hrs - Linear,"@np.where(((df.duration<5)), (np.where((df.duration<5), np.minimum(5-df.duration,47), 0) + np.where((df.duration>7), np.minimum(df.duration-7,47), 0)), 0)",coef_social_duration_constant_shift_for_every_30_minutes_less_than_2_hr_30_minutes_linear +util_social_duration_constant_less_than_3_hours,SOCIAL - Duration Constant: Less than 3 hrs,@((df.duration<6)),coef_social_duration_constant_less_than_3_hours +util_social_duration_constant_3_hours,SOCIAL - Duration Constant: 3 hours,@((df.duration==6)),coef_social_duration_constant_3_hours +util_social_duration_constant_3_hrs_30_minutes,SOCIAL - Duration Constant: 3.5 hours,@((df.duration==7)),coef_social_duration_constant_3_hrs_30_minutes +util_social_duration_constant_4_hours_or_more,SOCIAL - Duration Constant: 4 hours or more,@((df.duration>7)),coef_social_duration_constant_4_hours_or_more +util_social_duration_constant_shift_for_every_30_minutes_more_than_4_hr_30_minutes_linear,SOCIAL - Duration Constant: Shift for every 30 minutes more than 4.5 hrs - Linear,"@np.where(((df.duration>8)), (np.where((df.duration<5), np.minimum(5-df.duration,47), 0) + np.where((df.duration>8), np.minimum(df.duration-8,47), 0)), 0)",coef_social_duration_constant_shift_for_every_30_minutes_more_than_4_hr_30_minutes_linear +util_social_calibration_constant_duration_1,SOCIAL - Calibration Constant - Duration = 1,@((df.duration ==0)),coef_social_calibration_constant_duration_1 +util_social_calibration_constant_duration_2,SOCIAL - Calibration Constant - Duration = 2,@((df.duration == 1)),coef_social_calibration_constant_duration_2 +util_social_calibration_constant_duration_3,SOCIAL - Calibration Constant - Duration = 3,@((df.duration ==2)),coef_social_calibration_constant_duration_3 +util_social_calibration_constant_duration_4,SOCIAL - Calibration Constant - Duration = 4,@((df.duration ==3)),coef_social_calibration_constant_duration_4 +util_social_calibration_constant_duration_5,SOCIAL - Calibration Constant - Duration = 5,@((df.duration ==4)),coef_social_calibration_constant_duration_5 +util_social_calibration_constant_duration_6,SOCIAL - Calibration Constant - Duration = 6,@((df.duration ==5)),coef_social_calibration_constant_duration_6 +util_social_calibration_constant_duration_7,SOCIAL - Calibration Constant - Duration = 7,@((df.duration ==6)),coef_social_calibration_constant_duration_7 +util_social_calibration_constant_duration_8,SOCIAL - Calibration Constant - Duration = 8,@((df.duration ==7)),coef_social_calibration_constant_duration_8 +util_social_calibration_constant_duration_9,SOCIAL - Calibration Constant - Duration = 9,@((df.duration ==8)),coef_social_calibration_constant_duration_9 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social_coefficients.csv new file mode 100644 index 000000000..9819e0e69 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_nonmandatory_social_coefficients.csv @@ -0,0 +1,52 @@ +coefficient_name,value,constrain +coef_social_person_less_than_18_years_old_duration_less_than_1_hr_30_minutes_linear,-0.262839914,F +coef_social_person_less_than_18_years_old_duration_greater_than_1_hr_30_minutes_linear,0.086919429,F +coef_social_non_working_senior_or_retiree_duration_less_than_1_hr_30_minutes_linear,0.468354376,F +coef_social_retiree_or_non_working_senior_only_HH_duration_less_than_1_hr_30_minutes_linear,-0.312282762,F +coef_social_zero_auto_households_duration_less_than_1_hr_30_minutes_linear,-0.508439932,F +coef_social_zero_auto_households_duration_greater_than_1_hr_30_minutes_linear,0.074190914,F +coef_social_number_of_auto_more_than_number_of_adults_duration_less_than_1_hr_30_minutes_linear,0.127185965,F +coef_social_number_of_auto_more_than_number_of_adults_duration_greater_than_1_hr_30_minutes_linear,0.048756122,F +coef_social_auto_distance_duration_less_than_1_hr_linear,-0.162965435,F +coef_social_auto_distance_duration_greater_than_1_hr_linear,0.006797399,F +coef_social_time_pressure_duration_less_than_1_hr,-0.229264474,F +coef_social_time_pressure_duration_greater_than_1_hr,0.219325112,F +coef_social_number_of_additional_individual_social_and_dicretionary_tours_duration_less_than_1_hr,0.156250451,F +coef_social_departure_constant_shift_for_every_30_minutes_before_8_30_am_linear,-0.529943196,F +coef_social_departure_constant_before_9_am,-0.198438086,F +coef_social_departure_constant_9_am_to_9_30_am,0.137620628,F +coef_social_departure_constant_shift_for_every_30_minutes_before_5_pm_linear,-0.142078961,F +coef_social_departure_constant_before_5_30_pm,-0.390965052,F +coef_social_departure_constant_5_30_pm_to_6_pm,-0.453580491,F +coef_social_departure_constant_6_pm_to_6_30_pm,0,T +coef_social_departure_constant_6_30_pm_to_7_pm,-0.088537991,F +coef_social_departure_constant_7_pm_to_7_30_pm,0.052983115,F +coef_social_departure_constant_after_7_30_pm,-0.649629162,F +coef_social_departure_constant_shift_for_every_30_minutes_after_8_pm_linear,-0.09574499,F +coef_social_arrival_constant_3_pm_to_3_30_pm,0.37674882,F +coef_social_arrival_constant_3_30_pm_to_4_pm,0.583355461,F +coef_social_arrival_constant_4_pm_to_4_30_pm,0.727855233,F +coef_social_arrival_constant_5_pm_to_6_pm,0.249551955,F +coef_social_arrival_constant_shift_for_every_30_minutes_before_8_pm_linear,0.053771388,F +coef_social_arrival_constant_before_8_30_pm,0.308763611,F +coef_social_arrival_constant_8_30_pm_to_9_pm,-0.208797698,F +coef_social_arrival_constant_9_pm_to_9_30_pm,-0.336319511,F +coef_social_arrival_constant_9_30_pm_to_10_pm,0,T +coef_social_arrival_constant_10_pm_to_10_30_pm,-0.055707591,F +coef_social_arrival_constant_after_10_30_pm,-0.612356296,F +coef_social_arrival_constant_shift_for_every_30_minutes_after_11_pm_linear,-0.348479901,F +coef_social_duration_constant_shift_for_every_30_minutes_less_than_2_hr_30_minutes_linear,0.614440191,F +coef_social_duration_constant_less_than_3_hours,0.353666691,F +coef_social_duration_constant_3_hours,0,T +coef_social_duration_constant_3_hrs_30_minutes,-0.691218836,F +coef_social_duration_constant_4_hours_or_more,-1.344375328,F +coef_social_duration_constant_shift_for_every_30_minutes_more_than_4_hr_30_minutes_linear,-0.786970714,F +coef_social_calibration_constant_duration_1,-1.346772472,F +coef_social_calibration_constant_duration_2,0.377121689,F +coef_social_calibration_constant_duration_3,0.179818928,F +coef_social_calibration_constant_duration_4,-0.283418619,F +coef_social_calibration_constant_duration_5,-0.103541313,F +coef_social_calibration_constant_duration_6,-0.03704707,F +coef_social_calibration_constant_duration_7,-0.062437167,F +coef_social_calibration_constant_duration_8,0.047640282,F +coef_social_calibration_constant_duration_9,0.284369793,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_school.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_school.csv new file mode 100644 index 000000000..434942040 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_school.csv @@ -0,0 +1,59 @@ +Label,Description,Expression,Coefficient +util_Mode_Choice_Logsum,SCHOOL - Mode Choice Logsum,mode_choice_logsum,coef_Mode_Choice_Logsum +util_Low_income_lt25000_Departure_before_730_am__Linear,SCHOOL - Low income (<25000) - Departure before 7:30 am - Linear,"@((df.is_income_less25K) & (df.start<10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Low_income_lt25000_Departure_before_730_am__Linear +util_Low_income_lt25000_Departure_after_800_am_Linear,SCHOOL - Low income (<25000) - Departure after 8:00 am - Linear,"@((df.is_income_less25K) & (df.start>10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Low_income_lt25000_Departure_after_800_am_Linear +util_Low_income_lt25000_Duration_lt_8hrs,SCHOOL - Low income (<25000) - Duration < 8hrs,"@((df.is_income_less25K) & (df.duration<8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Low_income_lt25000_Duration_lt_8hrs +util_Low_income_lt25000_Duration_gt_8hrs,SCHOOL - Low income (<25000) - Duration > 8hrs,"@((df.is_income_less25K) & (df.duration>8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Low_income_lt25000_Duration_gt_8hrs +util_Med_income_25k_to_60k_Departure_before_730_am__Linear,SCHOOL - Med income (25k to 60k) - Departure before 7:30 am - Linear,"@((df.is_income_25K_to_60K) & (df.start<10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Med_income_25k_to_60k_Departure_before_730_am__Linear +util_Age_0_to_5_yrs_Departure_Before_730_am,SCHOOL - Age 0 to 5 yrs - Departure Before 7:30 am,"@(((df.age>=0) & (df.age<=5)) & (df.start<10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Age_0_to_5_yrs_Departure_Before_730_am +util_Age_13_to_15_yrs_Departure_Before_730_am,SCHOOL - Age 13 to 15 yrs - Departure Before 7:30 am,"@(((df.age>=13) & (df.age<=15)) & (df.start<10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Age_13_to_15_yrs_Departure_Before_730_am +util_Age_13_to_15_yrs_Departure_After_800_am,SCHOOL - Age 13 to 15 yrs - Departure After 8:00 am,"@(((df.age>=13) & (df.age<=15)) & (df.start>10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Age_13_to_15_yrs_Departure_After_800_am +util_Age_16_to_17_yrs_Departure_After_800_am,SCHOOL - Age 16 to 17 yrs - Departure After 8:00 am,"@(((df.age>=16) & (df.age<=17)) & (df.start>10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Age_16_to_17_yrs_Departure_After_800_am +util_Age_0_to_5_yrs_Duration_lt_8hrs,SCHOOL - Age 0 to 5 yrs - Duration < 8hrs,"@(((df.age>0) & (df.age<=5)) & (df.duration<8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Age_0_to_5_yrs_Duration_lt_8hrs +util_Age_0_to_5_yrs_Duration_gt_8hrs,SCHOOL - Age 0 to 5 yrs - Duration > 8hrs,"@(((df.age>0) & (df.age<=5)) & (df.duration>8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Age_0_to_5_yrs_Duration_gt_8hrs +util_Age_13_to_15_yrs_Duration_lt_8hrs,SCHOOL - Age 13 to 15 yrs - Duration < 8hrs,"@(((df.age>=13) & (df.age<=15)) & (df.duration<8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Age_13_to_15_yrs_Duration_lt_8hrs +util_Age_13_to_15_yrs_Duration_gt_8hrs,SCHOOL - Age 13 to 15 yrs - Duration > 8hrs,"@(((df.age>=13) & (df.age<=15)) & (df.duration>8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Age_13_to_15_yrs_Duration_gt_8hrs +util_Age_16_to_17_yrs_Duration_gt_8hrs,SCHOOL - Age 16 to 17 yrs - Duration > 8hrs,"@(((df.age>=16) & (df.age<=17)) & (df.duration>8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Age_16_to_17_yrs_Duration_gt_8hrs +util_Time_SOV_freeflow_to_destination_Departure_before_730_am__Linear,SCHOOL - Time (SOV freeflow) to destination - Departure before 7:30 am - Linear,"@(df.start<10) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10))) * (df.roundtrip_auto_time_to_school)",coef_Time_SOV_freeflow_to_destination_Departure_before_730_am__Linear +util_Time_SOV_freeflow_to_destination_Departure_after_800_am_Linear,SCHOOL - Time (SOV freeflow) to destination - Departure after 8:00 am - Linear,"@(df.start>10) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10))) * (df.roundtrip_auto_time_to_school)",coef_Time_SOV_freeflow_to_destination_Departure_after_800_am_Linear +util_Time_SOV_freeflow_to_destination_Duration_lt_8hrs,SCHOOL - Time (SOV freeflow) to destination - Duration < 8hrs,"@(df.end<27) * ((np.minimum(27-df.end,48)*(df.end<=27)) + (np.minimum(df.end-27,48)*(df.end>27))) * (df.roundtrip_auto_time_to_school)",coef_Time_SOV_freeflow_to_destination_Duration_lt_8hrs +util_Time_SOV_freeflow_to_destination_Duration_gt_8hrs,SCHOOL - Time (SOV freeflow) to destination - Duration > 8hrs,"@(df.end>27) * ((np.minimum(27-df.end,48)*(df.end<=27)) + (np.minimum(df.end-27,48)*(df.end>27))) * (df.roundtrip_auto_time_to_school)",coef_Time_SOV_freeflow_to_destination_Duration_gt_8hrs +util_All_adults_in_the_household_are_fulltime_workers_Departure_before_730_am__Linear,SCHOOL - All adults in the household are fulltime workers - Departure before 7:30 am - Linear,"@((df.is_all_adults_full_time_workers) & (df.start<10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_All_adults_in_the_household_are_fulltime_workers_Departure_before_730_am__Linear +util_All_adults_in_the_household_are_fulltime_workers_Departure_after_800_am_Linear,SCHOOL - All adults in the household are fulltime workers - Departure after 8:00 am - Linear,"@((df.is_all_adults_full_time_workers) & (df.start>10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_All_adults_in_the_household_are_fulltime_workers_Departure_after_800_am_Linear +util_All_adults_in_the_household_are_fulltime_workers_Duration_lt_8hrs,SCHOOL - All adults in the household are fulltime workers - Duration < 8hrs,"@((df.is_all_adults_full_time_workers) & (df.end<27)) * ((np.minimum(27-df.end,48)*(df.end<=27)) + (np.minimum(df.end-27,48)*(df.end>27)))",coef_All_adults_in_the_household_are_fulltime_workers_Duration_lt_8hrs +util_All_adults_in_the_household_are_fulltime_workers_Duration_gt_8hrs,SCHOOL - All adults in the household are fulltime workers - Duration > 8hrs,"@((df.is_all_adults_full_time_workers) & (df.end>27)) * ((np.minimum(27-df.end,48)*(df.end<=27)) + (np.minimum(df.end-27,48)*(df.end>27)))",coef_All_adults_in_the_household_are_fulltime_workers_Duration_gt_8hrs +util_Subsequent_tour_is_work_tour_Duration_lt_8_hours,SCHOOL - Subsequent tour is work tour: Duration < 8 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'work')) & (df.duration<8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Subsequent_tour_is_work_tour_Duration_lt_8_hours +util_Subsequent_tour_is_work_tour_Duration_gt_8_hours,SCHOOL - Subsequent tour is work tour: Duration > 8 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'work')) & (df.duration>8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Subsequent_tour_is_work_tour_Duration_gt_8_hours +util_Subsequent_tour_is_school_tour_Departure_after_800_am,SCHOOL - Subsequent tour is school tour: Departure after 8:00 am,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'school')) & (df.start>10)) *((np.minimum(10-df.start,48)*(df.start<=10)) + (np.minimum(df.start-10,48)*(df.start>10)))",coef_Subsequent_tour_is_school_tour_Departure_after_800_am +util_Subsequent_tour_is_school_tour_Duration_lt_8_hours,SCHOOL - Subsequent tour is school tour: Duration < 8 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'school')) & (df.duration<8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Subsequent_tour_is_school_tour_Duration_lt_8_hours +util_Subsequent_tour_is_school_tour_Duration_gt_8_hours,SCHOOL - Subsequent tour is school tour: Duration > 8 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'school')) & (df.duration>8)) * ((np.minimum(8-df.duration,47)*(df.duration<=8)) + (np.minimum(df.duration-8,47)*(df.duration>8)))",coef_Subsequent_tour_is_school_tour_Duration_gt_8_hours +util_Second_tour_of_two_mandatory_tours_Duration_lt_4_hours,SCHOOL - Second tour of two mandatory tours: Duration < 4 hours,"@(((df.tour_count>1) & (df.tour_num > 1)) & (df.duration<7)) * ((np.minimum(7-df.duration,47)*(df.duration<=7)) + (np.minimum(df.duration-7,47)*(df.duration>7)))",coef_Second_tour_of_two_mandatory_tours_Duration_lt_4_hours +util_Second_tour_of_two_mandatory_tours_Duration_gt_4_hours,SCHOOL - Second tour of two mandatory tours: Duration > 4 hours,"@(((df.tour_count>1) & (df.tour_num > 1)) & (df.duration>7)) * ((np.minimum(7-df.duration,47)*(df.duration<=7)) + (np.minimum(df.duration-7,47)*(df.duration>7)))",coef_Second_tour_of_two_mandatory_tours_Duration_gt_4_hours +util_Departure_Constant_Before_0600_AM,SCHOOL - Departure Constant: Before 06:00 AM,@(df.start<7),coef_Departure_Constant_Before_0600_AM +util_Departure_Constant_0600_AM_to_0630_AM_7,SCHOOL - Departure Constant: 06:00 AM to 06:30 AM (7),@(df.start==7),coef_Departure_Constant_0600_AM_to_0630_AM_7 +util_Departure_Constant_0630_AM_to_0700_AM_8,SCHOOL - Departure Constant: 06:30 AM to 07:00 AM (8),@(df.start==8),coef_Departure_Constant_0630_AM_to_0700_AM_8 +util_Departure_Constant_0700_AM_to_0730_AM_9,SCHOOL - Departure Constant: 07:00 AM to 07:30 AM (9),@(df.start==9),coef_Departure_Constant_0700_AM_to_0730_AM_9 +util_Departure_Constant_0730_AM_to_0800_AM_10,SCHOOL - Departure Constant: 07:30 AM to 08:00 AM (10),@(df.start==10),coef_Departure_Constant_0730_AM_to_0800_AM_10 +util_Departure_Constant_After_0800_AM,SCHOOL - Departure Constant: After 08:00 AM,@(df.start>10),coef_Departure_Constant_After_0800_AM +util_Departure_Constant_Shift_for_every_30_minutes_after_830_am_Linear,SCHOOL - Departure Constant: Shift for every 30 minutes after 8:30 am - Linear,"@((df.start>11)) * ((np.minimum(7-df.start,48)*(df.start<7)) + (np.minimum(df.start-11,23)*(df.start>11)))",coef_Departure_Constant_Shift_for_every_30_minutes_after_830_am_Linear +util_Departure_Constant_Shift_for_every_30_minutes_after_830_am_Square_Root,SCHOOL - Departure Constant: Shift for every 30 minutes after 8:30 am - Square Root,"@((df.start>11)) * (((np.minimum(7-df.start,48)*(df.start<7)) + (np.minimum(df.start-11,23)*(df.start>11))) ** 0.5)",coef_Departure_Constant_Shift_for_every_30_minutes_after_830_am_Square_Root +util_Arrival_Constant_Before_0230_PM,SCHOOL - Arrival Constant: Before 02:30 PM,@(df.end<24),coef_Arrival_Constant_Before_0230_PM +util_Arrival_Constant_0230_PM_0300_PM_24_,SCHOOL - Arrival Constant: 02:30 PM - 03:00 PM (24) ,@(df.end==24),coef_Arrival_Constant_0230_PM_0300_PM_24_ +util_Arrival_Constant_0300_PM_0330_PM_25_,SCHOOL - Arrival Constant: 03:00 PM - 03:30 PM (25) ,@(df.end==25),coef_Arrival_Constant_0300_PM_0330_PM_25_ +util_Arrival_Constant_0330_PM_0400_PM_26_,SCHOOL - Arrival Constant: 03:30 PM - 04:00 PM (26) ,@(df.end==26),coef_Arrival_Constant_0330_PM_0400_PM_26_ +util_Arrival_Constant_0400_PM_0430_PM_27_,SCHOOL - Arrival Constant: 04:00 PM - 04:30 PM (27) ,@(df.end==27),coef_Arrival_Constant_0400_PM_0430_PM_27_ +util_Arrival_Constant_0430_PM_0500_PM_28_,SCHOOL - Arrival Constant: 04:30 PM - 05:00 PM (28) ,@(df.end==28),coef_Arrival_Constant_0430_PM_0500_PM_28_ +util_Arrival_Constant_0500_PM_0530_PM_29,SCHOOL - Arrival Constant: 05:00 PM - 05:30 PM (29),@(df.end==29),coef_Arrival_Constant_0500_PM_0530_PM_29 +util_Arrival_Constant_0530_PM_0600_PM_30_,SCHOOL - Arrival Constant: 05:30 PM - 06:00 PM (30) ,@(df.end==30),coef_Arrival_Constant_0530_PM_0600_PM_30_ +util_Arrival_Constant_After_0600_PM,SCHOOL - Arrival Constant: After 06:00 PM,@(df.end>30),coef_Arrival_Constant_After_0600_PM +util_Arrival_Constant_Shift_for_every_30_minutes_after_630_pm_Linear,SCHOOL - Arrival Constant: Shift for every 30 minutes after 6:30 pm - Linear,"@(df.end>31) * ((np.minimum(24-df.end,6)*(df.end<24)) + (np.minimum(df.end-31,12)*(df.end>31)))",coef_Arrival_Constant_Shift_for_every_30_minutes_after_630_pm_Linear +util_Duration_Constant_Shift_for_every_30_minutes_less_than_6p5_hrs_Linear,SCHOOL - Duration Constant: Shift for every 30 minutes less than 6.5 hrs - Linear,"@((df.duration<13)) * ((np.minimum(13-df.duration,48)*(df.duration<13)) + (np.minimum(df.duration-19,9)*(df.duration>19)))",coef_Duration_Constant_Shift_for_every_30_minutes_less_than_6p5_hrs_Linear +util_Duration_Constant_Shorter_than_7_hrs,SCHOOL - Duration Constant: Shorter than 7 hrs,@(df.duration<14),coef_Duration_Constant_Shorter_than_7_hrs +util_Duration_Constant_7_hours,SCHOOL - Duration Constant: 7 hours,@(df.duration==14),coef_Duration_Constant_7_hours +util_Duration_Constant_7p5_hours,SCHOOL - Duration Constant: 7.5 hours,@(df.duration==15),coef_Duration_Constant_7p5_hours +util_Duration_Constant_8_hours,SCHOOL - Duration Constant: 8 hours,@(df.duration==16),coef_Duration_Constant_8_hours +util_Duration_Constant_8p5_hours,SCHOOL - Duration Constant: 8.5 hours,@(df.duration==17),coef_Duration_Constant_8p5_hours +util_Duration_Constant_9_hours,SCHOOL - Duration Constant: 9 hours,@(df.duration==18),coef_Duration_Constant_9_hours +util_Duration_Constant_Longer_than_9_hrs,SCHOOL - Duration Constant: Longer than 9 hrs,@(df.duration>18),coef_Duration_Constant_Longer_than_9_hrs +util_Duration_Constant_Shift_for_every_30_minutes_more_than_9p5_hrs_Linear,SCHOOL - Duration Constant: Shift for every 30 minutes more than 9.5 hrs - Linear,"@(df.duration>19) * ((np.minimum(13-df.duration,47)*(df.duration<13)) + (np.minimum(df.duration-19,9)*(df.duration>19)))",coef_Duration_Constant_Shift_for_every_30_minutes_more_than_9p5_hrs_Linear +util_Duration_Constant_Shift_for_every_30_minutes_more_than_9p5_hrs_Squared,SCHOOL - Duration Constant: Shift for every 30 minutes more than 9.5 hrs - Squared,"@(df.duration>19) * (((np.minimum(13-df.duration,47)*(df.duration<13)) + (np.minimum(df.duration-19,9)*(df.duration>19))) ** 2)",coef_Duration_Constant_Shift_for_every_30_minutes_more_than_9p5_hrs_Squared diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_school_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_school_coeffs.csv new file mode 100644 index 000000000..589b4ce61 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_school_coeffs.csv @@ -0,0 +1,59 @@ +coefficient_name,value,constrain +coef_Mode_Choice_Logsum,0.524017431,F +coef_Low_income_lt25000_Departure_before_730_am__Linear,0.134574548,F +coef_Low_income_lt25000_Departure_after_800_am_Linear,-0.075554725,F +coef_Low_income_lt25000_Duration_lt_8hrs,-0.150039779,F +coef_Low_income_lt25000_Duration_gt_8hrs,-0.043562413,F +coef_Med_income_25k_to_60k_Departure_before_730_am__Linear,0.102594589,F +coef_Age_0_to_5_yrs_Departure_Before_730_am,-0.178916721,F +coef_Age_13_to_15_yrs_Departure_Before_730_am,-0.164708594,F +coef_Age_13_to_15_yrs_Departure_After_800_am,0.169641715,F +coef_Age_16_to_17_yrs_Departure_After_800_am,0.077527892,F +coef_Age_0_to_5_yrs_Duration_lt_8hrs,0.254486164,F +coef_Age_0_to_5_yrs_Duration_gt_8hrs,0.14409403,F +coef_Age_13_to_15_yrs_Duration_lt_8hrs,-0.211129273,F +coef_Age_13_to_15_yrs_Duration_gt_8hrs,0.102348303,F +coef_Age_16_to_17_yrs_Duration_gt_8hrs,0.1184616,F +coef_Time_SOV_freeflow_to_destination_Departure_before_730_am__Linear,0.011813391,F +coef_Time_SOV_freeflow_to_destination_Departure_after_800_am_Linear,-0.0088956,F +coef_Time_SOV_freeflow_to_destination_Duration_lt_8hrs,-0.011793416,F +coef_Time_SOV_freeflow_to_destination_Duration_gt_8hrs,0.001485453,F +coef_All_adults_in_the_household_are_fulltime_workers_Departure_before_730_am__Linear,0.1625279,F +coef_All_adults_in_the_household_are_fulltime_workers_Departure_after_800_am_Linear,-0.161840551,F +coef_All_adults_in_the_household_are_fulltime_workers_Duration_lt_8hrs,-0.233061473,F +coef_All_adults_in_the_household_are_fulltime_workers_Duration_gt_8hrs,0.08462748,F +coef_Subsequent_tour_is_work_tour_Duration_lt_8_hours,0.154332088,F +coef_Subsequent_tour_is_work_tour_Duration_gt_8_hours,-0.62871831,F +coef_Subsequent_tour_is_school_tour_Departure_after_800_am,-0.41618671,F +coef_Subsequent_tour_is_school_tour_Duration_lt_8_hours,0.261423274,F +coef_Subsequent_tour_is_school_tour_Duration_gt_8_hours,-0.263857404,F +coef_Second_tour_of_two_mandatory_tours_Duration_lt_4_hours,-0.537535787,F +coef_Second_tour_of_two_mandatory_tours_Duration_gt_4_hours,-0.545479806,F +coef_Departure_Constant_Before_0600_AM,-10.04417122,F +coef_Departure_Constant_0600_AM_to_0630_AM_7,-3.792318538,F +coef_Departure_Constant_0630_AM_to_0700_AM_8,-1.941704371,F +coef_Departure_Constant_0700_AM_to_0730_AM_9,-0.558080224,F +coef_Departure_Constant_0730_AM_to_0800_AM_10,0,T +coef_Departure_Constant_After_0800_AM,-0.280439854,F +coef_Departure_Constant_Shift_for_every_30_minutes_after_830_am_Linear,0.293697164,F +coef_Departure_Constant_Shift_for_every_30_minutes_after_830_am_Square_Root,-1.220165702,F +coef_Arrival_Constant_Before_0230_PM,0.720751128,F +coef_Arrival_Constant_0230_PM_0300_PM_24_,1.605012317,F +coef_Arrival_Constant_0300_PM_0330_PM_25_,0.463502951,F +coef_Arrival_Constant_0330_PM_0400_PM_26_,0.196107179,F +coef_Arrival_Constant_0400_PM_0430_PM_27_,0,T +coef_Arrival_Constant_0430_PM_0500_PM_28_,-0.389421484,F +coef_Arrival_Constant_0500_PM_0530_PM_29,-1.412720271,F +coef_Arrival_Constant_0530_PM_0600_PM_30_,-1.938567609,F +coef_Arrival_Constant_After_0600_PM,-2.246103785,F +coef_Arrival_Constant_Shift_for_every_30_minutes_after_630_pm_Linear,-0.552223894,F +coef_Duration_Constant_Shift_for_every_30_minutes_less_than_6p5_hrs_Linear,-0.249724903,F +coef_Duration_Constant_Shorter_than_7_hrs,-2.791243553,F +coef_Duration_Constant_7_hours,-1.679006455,F +coef_Duration_Constant_7p5_hours,-0.555288612,F +coef_Duration_Constant_8_hours,0,T +coef_Duration_Constant_8p5_hours,-0.139412248,F +coef_Duration_Constant_9_hours,-0.509620713,F +coef_Duration_Constant_Longer_than_9_hrs,-0.561449384,F +coef_Duration_Constant_Shift_for_every_30_minutes_more_than_9p5_hrs_Linear,0.379484906,F +coef_Duration_Constant_Shift_for_every_30_minutes_more_than_9p5_hrs_Squared,-0.028814477,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_university.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_university.csv new file mode 100644 index 000000000..160311a16 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_university.csv @@ -0,0 +1,42 @@ +Label,Description,Expression,Coefficient +util_Mode_Choice_Logsum,UNIVERSITY - Mode Choice Logsum,mode_choice_logsum,coef_Mode_Choice_Logsum +util_Low_income_lt25000_Departure_before_800_am_Linear,UNIVERSITY - Low income (<25000) - Departure before 8:00 am - Linear,"@((df.is_income_less25K) & (df.start<11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))",coef_Low_income_lt25000_Departure_before_800_am_Linear +util_Low_income_lt25000_Duration_lt_4hrs,UNIVERSITY - Low income (<25000) - Duration < 4hrs,"@((df.is_income_less25K) & (df.duration<8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Low_income_lt25000_Duration_lt_4hrs +util_Medium_high_income_60k_to_120k_Departure_after_830_am_Linear,UNIVERSITY - Medium high income (60k to 120k) - Departure after 8:30 am - Linear,"@((df.is_income_60K_to_120K) & (df.start>11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))",coef_Medium_high_income_60k_to_120k_Departure_after_830_am_Linear +util_Medium_high_income_60k_to_120k_Duration_gt_4hrs,UNIVERSITY - Medium high income (60k to 120k) - Duration > 4hrs,"@((df.is_income_60K_to_120K) & (df.duration>8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Medium_high_income_60k_to_120k_Duration_gt_4hrs +util_High_income_120k_plus_Departure_after_830_am_Linear,UNIVERSITY - High income (120k+) - Departure after 8:30 am - Linear,"@((df.is_income_greater120K) & (df.start>11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))",coef_High_income_120k_plus_Departure_after_830_am_Linear +util_Age_41_plus_Departure_after_830_am_Linear,UNIVERSITY - Age 41+ - Departure after 8:30 am - Linear,"@((df.age >= 41) & (df.start>11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))",coef_Age_41_plus_Departure_after_830_am_Linear +util_Age_41_plus_Durationlt_4_hrs_Linear,UNIVERSITY - Age 41+ - Duration< 4 hrs -Linear,"@((df.age >= 41) & (df.duration<8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Age_41_plus_Durationlt_4_hrs_Linear +util_Distance_to_destination_Departure_before_800_am_Linear,UNIVERSITY - Distance to destination - Departure before 8:00 am - Linear,"@((df.start<11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))*(df.distance_to_school)",coef_Distance_to_destination_Departure_before_800_am_Linear +util_Distance_to_destination_Departure_after_830_am_Linear,UNIVERSITY - Distance to destination - Departure after 8:30 am - Linear,"@((df.start>11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))*(df.distance_to_school)",coef_Distance_to_destination_Departure_after_830_am_Linear +util_Distance_to_destination_Durationlt_4_hrs_Linear,UNIVERSITY - Distance to destination - Duration< 4 hrs -Linear,"@((df.duration<8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))*(df.distance_to_school)",coef_Distance_to_destination_Durationlt_4_hrs_Linear +util_Distance_to_destination_Durationgt_4_hrs_Linear,UNIVERSITY - Distance to destination - Duration> 4 hrs- Linear,"@((df.duration>8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))*(df.distance_to_school)",coef_Distance_to_destination_Durationgt_4_hrs_Linear +util_Distance_to_destination_Durationlt_4_hrs_Square_Root,UNIVERSITY - Distance to destination - Duration< 4 hrs - Square Root,"@((df.duration<8))*(abs(((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))) ** 0.5)*(df.distance_to_school)",coef_Distance_to_destination_Durationlt_4_hrs_Square_Root +util_Subsequent_tour_is_work_tour_Departure_after_830_am,UNIVERSITY - Subsequent tour is work tour: Departure after 8:30 am,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'work')) & (df.start>11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))",coef_Subsequent_tour_is_work_tour_Departure_after_830_am +util_Subsequent_tour_is_work_tour_Duration_lt_4_hours,UNIVERSITY - Subsequent tour is work tour: Duration < 4 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'work')) & (df.duration<8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Subsequent_tour_is_work_tour_Duration_lt_4_hours +util_Subsequent_tour_is_work_tour_Duration_gt_4_hours,UNIVERSITY - Subsequent tour is work tour: Duration > 4 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'work')) & (df.duration>8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Subsequent_tour_is_work_tour_Duration_gt_4_hours +util_Subsequent_tour_is_school_tour_Departure_after_830_am,UNIVERSITY - Subsequent tour is school tour: Departure after 8:30 am,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'school')) & (df.start>11))*((np.minimum(11-df.start,8)*(df.start<=11)) + (np.minimum(df.start-11,22)*(df.start>11)))",coef_Subsequent_tour_is_school_tour_Departure_after_830_am +util_Subsequent_tour_is_school_tour_Duration_lt_4_hours,UNIVERSITY - Subsequent tour is school tour: Duration < 4 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'school')) & (df.duration<8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Subsequent_tour_is_school_tour_Duration_lt_4_hours +util_Subsequent_tour_is_school_tour_Duration_gt_4_hours,UNIVERSITY - Subsequent tour is school tour: Duration > 4 hours,"@(((df.tour_count>1) & (df.tour_num == 1) & (df.tour_type.shift(-1) == 'school')) & (df.duration>8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Subsequent_tour_is_school_tour_Duration_gt_4_hours +util_Second_tour_of_two_mandatory_tours_Duration_lt_4_hours,UNIVERSITY - Second tour of two mandatory tours: Duration < 4 hours,"@(((df.tour_count>1) & (df.tour_num > 1)) & (df.duration<8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Second_tour_of_two_mandatory_tours_Duration_lt_4_hours +util_Second_tour_of_two_mandatory_tours_Duration_gt_4_hours,UNIVERSITY - Second tour of two mandatory tours: Duration > 4 hours,"@(((df.tour_count>1) & (df.tour_num > 1)) & (df.duration>8))*((np.minimum(8-df.duration,6)*(df.duration<=8)) + (np.minimum(df.duration-8,28)*(df.duration>8)))",coef_Second_tour_of_two_mandatory_tours_Duration_gt_4_hours +util_Departure_Constant_Shift_for_every_30_minutes_before_0700_am_Linear,UNIVERSITY - Departure Constant: Shift for every 30 minutes before 07:00 am - Linear,"@((df.start<9))*((np.minimum(9-df.start,6)*(df.start<9)) + (np.minimum(df.start-13,20)*(df.start>13)))",coef_Departure_Constant_Shift_for_every_30_minutes_before_0700_am_Linear +util_Departure_Constant_Before_0730_AM,UNIVERSITY - Departure Constant: Before 07:30 AM,@(df.start<10),coef_Departure_Constant_Before_0730_AM +util_Departure_Constant_0730_AM_0800_AM,UNIVERSITY - Departure Constant: 07:30 AM - 08:00 AM,@(df.start==10),coef_Departure_Constant_0730_AM_0800_AM +util_Departure_Constant_0800_AM_0830_AM,UNIVERSITY - Departure Constant: 08:00 AM - 08:30 AM,@(df.start==11),coef_Departure_Constant_0800_AM_0830_AM +util_Departure_Constant_0830_AM_0900_AM,UNIVERSITY - Departure Constant: 08:30 AM - 09:00 AM,@(df.start==12),coef_Departure_Constant_0830_AM_0900_AM +util_Departure_Constant_After_0900_AM,UNIVERSITY - Departure Constant: After 09:00 AM,@(df.start>12),coef_Departure_Constant_After_0900_AM +util_Departure_Constant_Shift_for_every_30_minutes_after_0930_am_Square_Root,UNIVERSITY - Departure Constant: Shift for every 30 minutes after 09:30 am - Square Root,"@((df.start>13))*(((np.minimum(9-df.start,6)*(df.start<9)) + (np.minimum(df.start-13,20)*(df.start>13))) ** 0.5)",coef_Departure_Constant_Shift_for_every_30_minutes_after_0930_am_Square_Root +util_Arrival_Constant_Shift_for_every_30_minutes_before_0230_pm_Linear,UNIVERSITY - Arrival Constant: Shift for every 30 minutes before 02:30 pm - Linear,"@((df.end<24)) * ((np.minimum(24-df.end,12) * (df.end<24)) + (np.minimum(df.end-28,19) * (df.end>28)))",coef_Arrival_Constant_Shift_for_every_30_minutes_before_0230_pm_Linear +util_Arrival_Constant_Before_0300_PM,UNIVERSITY - Arrival Constant: Before 03:00 PM,@((df.end<25)),coef_Arrival_Constant_Before_0300_PM +util_Arrival_Constant_0300_PM_0330_PM,UNIVERSITY - Arrival Constant: 03:00 PM - 03:30 PM,@(df.end==25),coef_Arrival_Constant_0300_PM_0330_PM +util_Arrival_Constant_0330_PM_0400_PM,UNIVERSITY - Arrival Constant: 03:30 PM - 04:00 PM,@(df.end==26),coef_Arrival_Constant_0330_PM_0400_PM +util_Arrival_Constant_0400_PM_0430_PM,UNIVERSITY - Arrival Constant: 04:00 PM - 04:30 PM,@(df.end==27),coef_Arrival_Constant_0400_PM_0430_PM +util_Arrival_Constant_After_0430_PM,UNIVERSITY - Arrival Constant: After 04:30 PM,@(df.end>27),coef_Arrival_Constant_After_0430_PM +util_Arrival_Constant_Shift_for_every_30_minutes_after_0500_pm_Linear,UNIVERSITY - Arrival Constant: Shift for every 30 minutes after 05:00 pm - Linear,"@((df.end>28))*((np.minimum(24-df.end,12)*(df.end<24)) + (np.minimum(df.end-28,19)*(df.end>28)))",coef_Arrival_Constant_Shift_for_every_30_minutes_after_0500_pm_Linear +util_Arrival_Constant_Shift_for_every_30_minutes_after_0500_pm_Square_Root,UNIVERSITY - Arrival Constant: Shift for every 30 minutes after 05:00 pm - Square Root,"@((df.end>28)) *(((np.minimum(24-df.end,12)*(df.end<24)) + (np.minimum(df.end-28,19)*(df.end>28))) ** 0.5)",coef_Arrival_Constant_Shift_for_every_30_minutes_after_0500_pm_Square_Root +util_Duration_Constant_Shift_for_every_30_minutes_less_than_4p5_hrs_Square_Root,UNIVERSITY - Duration Constant: Shift for every 30 minutes less than 4.5 hrs - Square Root,"@((df.duration<9))*((np.minimum(9-df.duration,7)*(df.duration<9)) + (np.minimum(df.duration-11,25)*(df.duration>11)))",coef_Duration_Constant_Shift_for_every_30_minutes_less_than_4p5_hrs_Square_Root +util_Duration_Constant_4p5_hours_or_less,UNIVERSITY - Duration Constant: 4.5 hours or less,@(df.duration<10),coef_Duration_Constant_4p5_hours_or_less +util_Duration_Constant_5_hours,UNIVERSITY - Duration Constant: 5 hours,@(df.duration==10),coef_Duration_Constant_5_hours +util_Duration_Constant_5p5_hours_or_more,UNIVERSITY - Duration Constant: 5.5 hours or more,@(df.duration>10),coef_Duration_Constant_5p5_hours_or_more +util_Duration_Constant_Shift_for_every_30_minutes_more_than_5p5_hrs_Linear,UNIVERSITY - Duration Constant: Shift for every 30 minutes more than 5.5 hrs - Linear,"@((df.duration>11))*(((np.minimum(9-df.duration,7)*(df.duration<9)) + (np.minimum(df.duration-11,25)*(df.duration>11))) ** 0.5)",coef_Duration_Constant_Shift_for_every_30_minutes_more_than_5p5_hrs_Linear diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_university_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_university_coeffs.csv new file mode 100644 index 000000000..1472dfb9f --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_university_coeffs.csv @@ -0,0 +1,42 @@ +coefficient_name,value,constrain +coef_Mode_Choice_Logsum,0.384091138,F +coef_Low_income_lt25000_Departure_before_800_am_Linear,0.246389489,F +coef_Low_income_lt25000_Duration_lt_4hrs,-0.262288853,F +coef_Medium_high_income_60k_to_120k_Departure_after_830_am_Linear,-0.039079271,F +coef_Medium_high_income_60k_to_120k_Duration_gt_4hrs,-0.041536976,F +coef_High_income_120k_plus_Departure_after_830_am_Linear,-0.039306518,F +coef_Age_41_plus_Departure_after_830_am_Linear,0.055344625,F +coef_Age_41_plus_Durationlt_4_hrs_Linear,-0.152498075,F +coef_Distance_to_destination_Departure_before_800_am_Linear,0.006869786,F +coef_Distance_to_destination_Departure_after_830_am_Linear,0.003686402,F +coef_Distance_to_destination_Durationlt_4_hrs_Linear,-0.04027172,F +coef_Distance_to_destination_Durationgt_4_hrs_Linear,0.003803244,F +coef_Distance_to_destination_Durationlt_4_hrs_Square_Root,0.041070113,F +coef_Subsequent_tour_is_work_tour_Departure_after_830_am,-0.29166292,F +coef_Subsequent_tour_is_work_tour_Duration_lt_4_hours,-0.482292817,F +coef_Subsequent_tour_is_work_tour_Duration_gt_4_hours,-0.364624965,F +coef_Subsequent_tour_is_school_tour_Departure_after_830_am,-0.286206955,F +coef_Subsequent_tour_is_school_tour_Duration_lt_4_hours,0.30341795,F +coef_Subsequent_tour_is_school_tour_Duration_gt_4_hours,-0.247436221,F +coef_Second_tour_of_two_mandatory_tours_Duration_lt_4_hours,-0.211059285,F +coef_Second_tour_of_two_mandatory_tours_Duration_gt_4_hours,-0.35316727,F +coef_Departure_Constant_Shift_for_every_30_minutes_before_0700_am_Linear,-0.947594485,F +coef_Departure_Constant_Before_0730_AM,-0.296228472,F +coef_Departure_Constant_0730_AM_0800_AM,-0.650538708,F +coef_Departure_Constant_0800_AM_0830_AM,0,T +coef_Departure_Constant_0830_AM_0900_AM,-0.525569176,F +coef_Departure_Constant_After_0900_AM,-0.536008149,F +coef_Departure_Constant_Shift_for_every_30_minutes_after_0930_am_Square_Root,-0.500045988,F +coef_Arrival_Constant_Shift_for_every_30_minutes_before_0230_pm_Linear,-0.209375282,F +coef_Arrival_Constant_Before_0300_PM,-0.962572172,F +coef_Arrival_Constant_0300_PM_0330_PM,-0.627901132,F +coef_Arrival_Constant_0330_PM_0400_PM,0,T +coef_Arrival_Constant_0400_PM_0430_PM,-0.190818088,F +coef_Arrival_Constant_After_0430_PM,-0.66545038,F +coef_Arrival_Constant_Shift_for_every_30_minutes_after_0500_pm_Linear,-0.209562151,F +coef_Arrival_Constant_Shift_for_every_30_minutes_after_0500_pm_Square_Root,0.503497689,F +coef_Duration_Constant_Shift_for_every_30_minutes_less_than_4p5_hrs_Square_Root,0.225706446,F +coef_Duration_Constant_4p5_hours_or_less,0.03106769,F +coef_Duration_Constant_5_hours,0,T +coef_Duration_Constant_5p5_hours_or_more,0.343447232,F +coef_Duration_Constant_Shift_for_every_30_minutes_more_than_5p5_hrs_Linear,-0.115312573,F diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_work.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_work.csv new file mode 100644 index 000000000..e180d0c15 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_work.csv @@ -0,0 +1,100 @@ +Label,Description,Expression,Coefficient +util_Mode_Choice_Logsum,Mode Choice Logsum,mode_choice_logsum,coef_Mode_Choice_Logsum +util_Female_Departure_before_7_am,Female - Departure before 7:00 am - Linear,@((df.female) & (df.start<9)) * df.departureLinearShift1,coef_Female_Departure_before_7_am +util_Female_Arrival_after_6_pm,Female - Arrival after 6:00 pm - Linear,@((df.female) & (df.end>30)) * df.arrivalLinearShift1,coef_Female_Arrival_after_6_pm +util_Female_with_preschool_child_Departure_before_7_am,Female with preschool child - Departure before 7:00 am - Linear,@((df.female) & (df.is_pre_drive_child_in_HH) & (df.start<9)) * df.departureLinearShift1,coef_Female_with_preschool_child_Departure_before_7_am +util_Female_with_preschool_child_Departure_after_7_am,Female with preschool child - Departure after 7:30 am - Linear,@((df.female) & (df.is_pre_drive_child_in_HH) & (df.start>9)) * df.departureLinearShift1,coef_Female_with_preschool_child_Departure_after_7_am +util_Female_with_preschool_child_Arrival_after_6_pm,Female with preschool child - Arrival after 6:00 pm - Linear,@((df.female) & (df.is_pre_drive_child_in_HH) & (df.end>30)) * df.arrivalLinearShift1,coef_Female_with_preschool_child_Arrival_after_6_pm +util_Low_income_lt_25000_Departure_before_7_am,Low income (<25000) - Departure before 7:00 am - Linear,@((df.is_income_less25K) & (df.start<9)) * df.departureLinearShift1,coef_Low_income_lt_25000_Departure_before_7_am +util_Low_income_lt_25000_Departure_after_7_am,Low income (<25000) - Departure after 7:30 am - Linear,@((df.is_income_less25K) & (df.start>9)) * df.departureLinearShift1,coef_Low_income_lt_25000_Departure_after_7_am +util_Low_income_lt_25000_Arrival_after_6_pm,Low income (<25000) - Arrival after 6:00 pm - Linear,@((df.is_income_less25K) & (df.start>30)) * df.arrivalLinearShift1,coef_Low_income_lt_25000_Arrival_after_6_pm +util_Med_income_25k_to_60k_Departure_before_7_am,Med income (25k to 60k) - Departure before 7:00 am - Linear,@((df.is_income_25K_to_60K) & (df.start<9)) * df.departureLinearShift1,coef_Med_income_25k_to_60k_Departure_before_7_am +util_Med_income_25k_to_60k_Arrival_after_6_pm,Med income (25k to 60k) - Arrival after 6:00 pm - Linear,@((df.is_income_25K_to_60K) & (df.end>30)) * df.arrivalLinearShift1,coef_Med_income_25k_to_60k_Arrival_after_6_pm +util_Medhigh_income_60k_to_120k_Departure_before_7_am,Med-high income (60k to 120k) - Departure before 7:00 am - Linear,@((df.is_income_60K_to_120K) & (df.start<9)) * df.departureLinearShift1,coef_Medhigh_income_60k_to_120k_Departure_before_7_am +util_Age_16_to_18_yrs_Departure_Before_7_am,Age 16 to 18 yrs - Departure Before 7:00 am,@(((df.age>=16) & (df.age<=18)) & (df.start<9)) * df.departureLinearShift1,coef_Age_16_to_18_yrs_Departure_Before_7_am +util_Age_16_to_18_yrs_Departure_After_7_am,Age 16 to 18 yrs - Departure After 7:30 am,@(((df.age>=16) & (df.age<=18)) & (df.start>9)) * df.departureLinearShift1,coef_Age_16_to_18_yrs_Departure_After_7_am +util_Age_19_to_24_yrs_Departure_After_7_am,Age 19 to 24 yrs - Departure After 7:30 am,@(((df.age>=19) & (df.age<=24)) & (df.start>9)) * df.departureLinearShift1,coef_Age_19_to_24_yrs_Departure_After_7_am +util_Age_25_to_40_yrs_Departure_Before_7_am,Age 25 to 40 yrs - Departure Before 7:00 am,@(((df.age>=25) & (df.age<=40)) & (df.start<9)) * df.departureLinearShift1,coef_Age_25_to_40_yrs_Departure_Before_7_am +util_Age_65_plus_yrs_Departure_After_7_am,Age 65+ yrs - Departure After 7:30 am,@((df.age>=65) & (df.start>9)) * df.departureLinearShift1,coef_Age_65_plus_yrs_Departure_After_7_am +util_Age_19_to_24_yrs_Arrival_after_6_pm,Age 19 to 24 yrs - Arrival after 6:00 pm ,@(((df.age>=19) & (df.age<=24)) & (df.end>30)) * df.arrivalLinearShift1,coef_Age_19_to_24_yrs_Arrival_after_6_pm +util_Age_25_to_40_yrs_Arrival_before_5_pm,Age 25 to 40 yrs - Arrival before 5:30 pm ,@(((df.age>=25) & (df.age<=40)) & (df.end<30)) * df.arrivalLinearShift1,coef_Age_25_to_40_yrs_Arrival_before_5_pm +util_Age_56_to_64_yrs_Arrival_after_6_pm,Age 56 to 64 yrs - Arrival after 6:00 pm ,@(((df.age>=56) & (df.age<65)) & (df.end>30)) * df.arrivalLinearShift1,coef_Age_56_to_64_yrs_Arrival_after_6_pm +util_Age_65_plus_yrs_Arrival_before_5_pm,Age 65+ yrs - Arrival before 5:30 pm ,@((df.age>=65) & (df.end<30)) * df.arrivalLinearShift1,coef_Age_65_plus_yrs_Arrival_before_5_pm +util_Age_65_plus_yrs_Arrival_after_6_pm,Age 65+ yrs - Arrival after 6:00 pm ,@((df.age>=65) & (df.end>30)) * df.arrivalLinearShift1,coef_Age_65_plus_yrs_Arrival_after_6_pm +util_Zero_auto_HH_Departure_before_7_am,Zero auto HH - Departure before 7:00 am - Linear,@((df.auto_ownership == 0) & (df.start<9)) * df.departureLinearShift1,coef_Zero_auto_HH_Departure_before_7_am +util_Zero_auto_HH_Arrival_after_6_pm,Zero auto HH - Arrival after 6:00 pm - Linear,@((df.auto_ownership == 0) & (df.end>30)) * df.arrivalLinearShift1,coef_Zero_auto_HH_Arrival_after_6_pm +util_Parttime_worker_Departure_before_7_am,Part-time worker - Departure before 7:00 am - Linear,@((df.ptype==2) & (df.start<9)) * df.departureLinearShift1,coef_Parttime_worker_Departure_before_7_am +util_Parttime_worker_Departure_after_7_am,Part-time worker - Departure after 7:30 am - Linear,@((df.ptype==2) & (df.start>9)) * df.departureLinearShift1,coef_Parttime_worker_Departure_after_7_am +util_Parttime_worker_Arrival_before_5_pm,Part-time worker - Arrival before 5:30 pm - Linear,@((df.ptype==2) & (df.end<30)) * df.arrivalLinearShift1,coef_Parttime_worker_Arrival_before_5_pm +util_Parttime_worker_Arrival_after_6_pm,Part-time worker - Arrival after 6:00 pm - Linear,@((df.ptype==2) & (df.end>30)) * df.arrivalLinearShift1,coef_Parttime_worker_Arrival_after_6_pm +util_University_student_Departure_after_7_am,University student - Departure after 7:30 am - Linear,@((df.ptype==3) & (df.start>9)) * df.departureLinearShift1,coef_University_student_Departure_after_7_am +util_University_student_Arrival_before_5_pm,University student - Arrival before 5:30 pm - Linear,@((df.ptype==3) & (df.end<30)) * df.arrivalLinearShift1,coef_University_student_Arrival_before_5_pm +util_University_student_Arrival_after_6_pm,University student - Arrival after 6:00 pm - Linear,@((df.ptype==3) & (df.end>30)) * df.arrivalLinearShift1,coef_University_student_Arrival_after_6_pm +#util_Blue_collar_Departure_before_7_am,#Blue collar - Departure before 7:00 am - Linear,@((df.work_segment==5) & (df.start<9)) * df.departureLinearShift1,coef_Blue_collar_Departure_before_7_am +#util_Blue_collar_Departure_after_7_am,#Blue collar - Departure after 7:30 am - Linear,@((df.work_segment==5)& (df.start>9)) * df.departureLinearShift1,coef_Blue_collar_Departure_after_7_am +#util_Blue_collar_Arrival_before_5_pm,#Blue collar - Arrival before 5:30 pm - Linear,@((df.work_segment==5)& (df.end<30)) * df.arrivalLinearShift1,coef_Blue_collar_Arrival_before_5_pm +#util_Service_Departure_before_7_am,#Service - Departure before 7:00 am - Linear,@((df.work_segment==2) & (df.start<9)) * df.departureLinearShift1,coef_Service_Departure_before_7_am +#util_Service_Departure_after_7_am,#Service - Departure after 7:30 am - Linear,@((df.work_segment==2) & (df.start>9)) * df.departureLinearShift1,coef_Service_Departure_after_7_am +#util_Service_Arrival_before_5_pm,#Service - Arrival before 5:30 pm - Linear,@((df.work_segment==2) & (df.end<30)) * df.arrivalLinearShift1,coef_Service_Arrival_before_5_pm +#util_Health_Departure_before_7_am,#Health - Departure before 7:00 am - Linear,@((df.work_segment==3) & (df.start<9)) * df.departureLinearShift1,coef_Health_Departure_before_7_am +#util_Health_Arrival_after_6_pm,#Health - Arrival after 6:00 pm - Linear,@((df.work_segment==3) & (df.end>30)) * df.arrivalLinearShift1,coef_Health_Arrival_after_6_pm +#util_Retail_and_food_Departure_after_7_am,#Retail and food - Departure after 7:30 am - Linear,@((df.work_segment==4) & (df.start>9)) * df.departureLinearShift1,coef_Retail_and_food_Departure_after_7_am +#util_Retail_and_food_Arrival_before_5_pm,#Retail and food - Arrival before 5:30 pm - Linear,@((df.work_segment==4) & (df.end<30)) * df.arrivalLinearShift1,coef_Retail_and_food_Arrival_before_5_pm +#util_Retail_and_food_Arrival_after_6_pm,#Retail and food - Arrival after 6:00 pm - Linear,@((df.work_segment==4) & (df.end>30)) * df.arrivalLinearShift1,coef_Retail_and_food_Arrival_after_6_pm +util_Time_SOV_freeflowto_destination_Departure_before_7_am,Time (SOV freeflow) to destination - Departure before 7:00 am - Linear,@(df.start<9) * df.departureLinearShift1* (df.roundtrip_auto_time_to_work),coef_Time_SOV_freeflowto_destination_Departure_before_7_am +util_Time_SOV_freeflowto_destination_Departure_after_7_am,Time (SOV freeflow) to destination - Departure after 7:30 am - Linear,@(df.start>9) * df.departureLinearShift1 * (df.roundtrip_auto_time_to_work),coef_Time_SOV_freeflowto_destination_Departure_after_7_am +util_Time_SOV_freeflowto_destination_Arrival_before_5_pm,Time (SOV freeflow) to destination - Arrival before 5:30 pm - Linear,@(df.end<30) * df.arrivalLinearShift1 * (df.roundtrip_auto_time_to_work),coef_Time_SOV_freeflowto_destination_Arrival_before_5_pm +util_Time_SOV_freeflowto_destination_Arrival_after_6_pm,Time (SOV freeflow) to destination - Arrival after 6:00 pm - Linear,@(df.end>30) * df.arrivalLinearShift1 * (df.roundtrip_auto_time_to_work),coef_Time_SOV_freeflowto_destination_Arrival_after_6_pm +util_Presence_of_NonWorking_Adult_in_the_HH_Departure_before_7_am,Presence of Non-Working Adult in the HH - Departure before 7:00 am - Linear,@((df.is_non_worker_in_HH) & (df.start<9)) * df.departureLinearShift1,coef_Presence_of_NonWorking_Adult_in_the_HH_Departure_before_7_am +util_Presence_of_NonWorking_Adult_in_the_HH_Arrival_before_5_pm,Presence of Non-Working Adult in the HH - Arrival before 5:30 pm - Linear,@((df.is_non_worker_in_HH) & (df.end<30)) * df.arrivalLinearShift1,coef_Presence_of_NonWorking_Adult_in_the_HH_Arrival_before_5_pm +util_Presence_of_PreDriving_Age_Children_in_the_HH_Departure_before_7_am,Presence of Pre-Driving Age Children in the HH - Departure before 7:30 am - Linear,@((df.is_pre_drive_child_in_HH) & (df.start<9)) * df.departureLinearShift1,coef_Presence_of_PreDriving_Age_Children_in_the_HH_Departure_before_7_am +util_Presence_of_PreDriving_Age_Children_in_the_HH_Departure_after_8_am,Presence of Pre-Driving Age Children in the HH - Departure after 8 am - Linear,@((df.is_pre_drive_child_in_HH) & (df.start>9)) * df.departureLinearShift1,coef_Presence_of_PreDriving_Age_Children_in_the_HH_Departure_after_8_am +util_Presence_of_PreDriving_Age_Children_in_the_HH_Arrival_before_5_pm,Presence of Pre-Driving Age Children in the HH - Arrival before 5:30 pm - Linear,@((df.is_pre_drive_child_in_HH) & (df.end<30)) * df.arrivalLinearShift1,coef_Presence_of_PreDriving_Age_Children_in_the_HH_Arrival_before_5_pm +util_Presence_of_PreDriving_Age_Children_in_the_HH_Arrival_after_6_pm,Presence of Pre-Driving Age Children in the HH - Arrival after 6:00 pm - Linear,@((df.is_pre_drive_child_in_HH)& (df.end>30)) * df.arrivalLinearShift1,coef_Presence_of_PreDriving_Age_Children_in_the_HH_Arrival_after_6_pm +util_First_of_2_plus_mandatory_tour_Departure_before_7_am,First of 2+ mandatory tour - Departure before 7:00 am,@(((df.tour_count>1) & (df.tour_num == 1)) & (df.start<9)) * df.departureLinearShift1,coef_First_of_2_plus_mandatory_tour_Departure_before_7_am +util_First_of_2_plus_mandatory_tour_Departure_after_7_am,First of 2+ mandatory tour - Departure after 7:30 am,@(((df.tour_count>1) & (df.tour_num == 1)) & (df.start>9)) * df.departureLinearShift1,coef_First_of_2_plus_mandatory_tour_Departure_after_7_am +util_First_of_2_plus_mandatory_tour_Duration_lt_9p5_hours,First of 2+ mandatory tour - Duration < 9.5 hours,@(((df.tour_count>1) & (df.tour_num == 1)) & (df.duration<21)) * df.durationShift,coef_First_of_2_plus_mandatory_tour_Duration_lt_9p5_hours +util_First_of_2_plus_mandatory_tour_Duration_gt_9p5_hours,First of 2+ mandatory tour - Duration > 9.5 hours,@(((df.tour_count>1) & (df.tour_num == 1)) & (df.duration<21)) * df.durationShift,coef_First_of_2_plus_mandatory_tour_Duration_gt_9p5_hours +util_2nd_or_later_of_2_plus_mandatory_tour_Departure_before_1_pm,2nd or later of 2+ mandatory tour - Departure before 1:30 pm,@(((df.tour_count>1) & (df.tour_num > 1)) & (df.start<22)) * df.departureLinearShift1,coef_2nd_or_later_of_2_plus_mandatory_tour_Departure_before_1_pm +util_2nd_or_later_of_2_plus_mandatory_tour_Departure_after_2_pm,2nd or later of 2+ mandatory tour - Departure after 2:00 pm,@(((df.tour_count>1) & (df.tour_num > 1)) & (df.start>22)) * df.departureLinearShift1,coef_2nd_or_later_of_2_plus_mandatory_tour_Departure_after_2_pm +util_2nd_or_later_of_2_plus_mandatory_tour_Duration_lt_9p5_hours,2nd or later of 2+ mandatory tour - Duration < 9.5 hours,@(((df.tour_count>1) & (df.tour_num > 1)) & (df.duration<21)) * df.durationShift,coef_2nd_or_later_of_2_plus_mandatory_tour_Duration_lt_9p5_hours +util_2nd_or_later_of_2_plus_mandatory_tour_Duration_gt_9p5_hours,2nd or later of 2+ mandatory tour - Duration > 9.5 hours,@(((df.tour_count>1) & (df.tour_num > 1)) & (df.duration<21)) * df.durationShift,coef_2nd_or_later_of_2_plus_mandatory_tour_Duration_gt_9p5_hours +#,#Departure Constants,,coef_Departure_Constants +util_Departure_Constant_Shift_for_every_30_minutes_before_6_am,Departure Constant: Shift for every 30 minutes before 6:00 am - Linear,"@(df.start<6) * ((np.minimum(6-df.start,48)*(df.start<6)) + (np.minimum(df.start-13,21)*(df.start>13)))",coef_Departure_Constant_Shift_for_every_30_minutes_before_6_am +util_Departure_Constant_Before_06_AM,Departure Constant: Before 06:00 AM,start<7,coef_Departure_Constant_Before_06_AM +util_Departure_Constant_06_AM_06_AM_7,Departure Constant: 06:00 AM - 06:30 AM (7) ,start==7,coef_Departure_Constant_06_AM_06_AM_7 +util_Departure_Constant_06_AM_07_AM_8,Departure Constant: 06:30 AM - 07:00 AM (8) ,start==8,coef_Departure_Constant_06_AM_07_AM_8 +util_Departure_Constant_07_AM_07_AM_9,Departure Constant: 07:00 AM - 07:30 AM (9) ,start==9,coef_Departure_Constant_07_AM_07_AM_9 +util_Departure_Constant_07_AM_08_AM_10,Departure Constant: 07:30 AM - 08:00 AM (10) ,start==10,coef_Departure_Constant_07_AM_08_AM_10 +util_Departure_Constant_08_AM_08_AM_11,Departure Constant: 08:00 AM - 08:30 AM (11) ,start==11,coef_Departure_Constant_08_AM_08_AM_11 +util_Departure_Constant_08_AM_09_AM_12,Departure Constant: 08:30 AM - 09:00 AM (12) ,start==12,coef_Departure_Constant_08_AM_09_AM_12 +util_Departure_Constant_After_09_AM,Departure Constant: After 09:00 AM,start>12,coef_Departure_Constant_After_09_AM +util_Departure_Constant_Shift_for_every_30_minutes_after_9_am_Square_Root,Departure Constant: Shift for every 30 minutes after 9:30 am - Square Root,"@(df.start>13) * (((np.minimum(6-df.start,48)*(df.start<6)) + (np.minimum(df.start-13,21)*(df.start>13))) ** 0.5)",coef_Departure_Constant_Shift_for_every_30_minutes_after_9_am_Square_Root +#,#Arrival Constants,,coef_Arrival_Constants +util_Arrival_Constant_Shift_for_every_30_minutes_before_3_pm,Arrival Constant: Shift for every 30 minutes before 3:00 pm - Linear,"@(df.end<25) * ((np.minimum(25-df.end, 15)*(df.end<25))+ (np.minimum(df.end-35,11)*(df.end>35)))",coef_Arrival_Constant_Shift_for_every_30_minutes_before_3_pm +util_Arrival_Constant_Before_03_PM,Arrival Constant: Before 03:30 PM,end<26,coef_Arrival_Constant_Before_03_PM +util_Arrival_Constant_03_PM_04_PM_26,Arrival Constant: 03:30 PM - 04:00 PM (26) ,end==26,coef_Arrival_Constant_03_PM_04_PM_26 +util_Arrival_Constant_04_PM_04_PM_27,Arrival Constant: 04:00 PM - 04:30 PM (27) ,end==27,coef_Arrival_Constant_04_PM_04_PM_27 +util_Arrival_Constant_04_PM_05_PM_28,Arrival Constant: 04:30 PM - 05:00 PM (28) ,end==28,coef_Arrival_Constant_04_PM_05_PM_28 +util_Arrival_Constant_05_PM_05_PM_29,Arrival Constant: 05:00 PM - 05:30 PM (29),end==29,coef_Arrival_Constant_05_PM_05_PM_29 +util_Arrival_Constant_05_PM_06_PM_30,Arrival Constant: 05:30 PM - 06:00 PM (30) ,end==30,coef_Arrival_Constant_05_PM_06_PM_30 +util_Arrival_Constant_06_PM_06_PM_31,Arrival Constant: 06:00 PM - 06:30 PM (31) ,end==31,coef_Arrival_Constant_06_PM_06_PM_31 +util_Arrival_Constant_06_PM_7_PM_32,Arrival Constant: 06:30 PM - 7:00 PM (32) ,end==32,coef_Arrival_Constant_06_PM_7_PM_32 +util_Arrival_Constant_7_PM_7_PM_33,Arrival Constant: 7:00 PM - 7:30 PM (33) ,end==33,coef_Arrival_Constant_7_PM_7_PM_33 +util_Arrival_Constant_7_PM_8_PM_34,Arrival Constant: 7:30 PM - 8:00 PM (34) ,end==34,coef_Arrival_Constant_7_PM_8_PM_34 +util_Arrival_Constant_After_08_PM,Arrival Constant: After 08:00 PM,end>34,coef_Arrival_Constant_After_08_PM +util_Arrival_Constant_Shift_for_every_30_minutes_after_6_pm_Square_root,Arrival Constant: Shift for every 30 minutes after 6:30 pm - Square root,"@(df.end>35) * (((np.minimum(25-df.end, 15)*(df.end<25))+ (np.minimum(df.end-35,11)*(df.end>35))) ** 0.5)",coef_Arrival_Constant_Shift_for_every_30_minutes_after_6_pm_Square_root +#,#Duration Constants,,coef_Duration_Constants +util_Duration_Constant_Shift_for_every_30_minutes_less_than_8p5_hrs,Duration Constant: Shift for every 30 minutes less than 8.5 hrs - Linear,"@(df.duration<16) * ((np.minimum(16-df.duration,47)*(df.duration<16)) + (np.minimum(df.duration-25,10)*(df.duration>25)))",coef_Duration_Constant_Shift_for_every_30_minutes_less_than_8p5_hrs +util_Duration_Constant_Shorter_than_8p5_hrs,Duration Constant: Shorter than 8.5 hrs,duration<17,coef_Duration_Constant_Shorter_than_8p5_hrs +util_Duration_Constant_8p5_hours,Duration Constant: 8.5 hours,duration==17,coef_Duration_Constant_8p5_hours +util_Duration_Constant_9_hours,Duration Constant: 9 hours,duration==18,coef_Duration_Constant_9_hours +util_Duration_Constant_9p5_hours,Duration Constant: 9.5 hours,duration==19,coef_Duration_Constant_9p5_hours +util_Duration_Constant_10_hours,Duration Constant: 10 hours,duration==20,coef_Duration_Constant_10_hours +util_Duration_Constant_10p5_hours,Duration Constant: 10.5 hours,duration==21,coef_Duration_Constant_10p5_hours +util_Duration_Constant_11_hours,Duration Constant: 11 hours,duration==22,coef_Duration_Constant_11_hours +util_Duration_Constant_11p5_hours,Duration Constant: 11.5 hours,duration==23,coef_Duration_Constant_11p5_hours +util_Duration_Constant_12_hours,Duration Constant: 12 hours,duration==24,coef_Duration_Constant_12_hours +util_Duration_Constant_Longer_than_12_hrs,Duration Constant: Longer than 12 hrs,duration>24,coef_Duration_Constant_Longer_than_12_hrs +util_Duration_Constant_Shift_for_every_30_minutes_more_than_10_hrs,Duration Constant: Shift for every 30 minutes more than 10 hrs - Linear,"@(df.duration>25) * ((np.minimum(16-df.duration,47)*(df.duration<16)) + (np.minimum(df.duration-25,10)*(df.duration>25)))",coef_Duration_Constant_Shift_for_every_30_minutes_more_than_10_hrs +util_Calibration_constant_Duration_0,Calibration constant: Duration = 0,duration == 0,coef_Calibration_constant_Duration_0 diff --git a/activitysim/examples/prototype_mwcog/configs/tour_scheduling_work_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_work_coeffs.csv new file mode 100644 index 000000000..19a85e817 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/tour_scheduling_work_coeffs.csv @@ -0,0 +1,97 @@ +coefficient_name,value,constrain +coef_Mode_Choice_Logsum,0.2279,T +coef_Female_Departure_before_7_am,-0.12935306,F +coef_Female_Arrival_after_6_pm,-0.041312616,F +coef_Female_with_preschool_child_Departure_before_7_am,-0.129130464,F +coef_Female_with_preschool_child_Departure_after_7_am,-0.031947595,F +coef_Female_with_preschool_child_Arrival_after_6_pm,-0.048859218,F +coef_Low_income_lt_25000_Departure_before_7_am,0.232768373,F +coef_Low_income_lt_25000_Departure_after_7_am,0.014908169,F +coef_Low_income_lt_25000_Arrival_after_6_pm,0.039105101,F +coef_Med_income_25k_to_60k_Departure_before_7_am,0.123945957,F +coef_Med_income_25k_to_60k_Arrival_after_6_pm,0.020965221,F +coef_Medhigh_income_60k_to_120k_Departure_before_7_am,0.09890939,F +coef_Age_16_to_18_yrs_Departure_Before_7_am,-0.459593556,F +coef_Age_16_to_18_yrs_Departure_After_7_am,0.060951693,F +coef_Age_19_to_24_yrs_Departure_After_7_am,0.031477187,F +coef_Age_25_to_40_yrs_Departure_Before_7_am,-0.11723451,F +coef_Age_65_plus_yrs_Departure_After_7_am,0.051923956,F +coef_Age_19_to_24_yrs_Arrival_after_6_pm,0.032734453,F +coef_Age_25_to_40_yrs_Arrival_before_5_pm,-0.027623617,F +coef_Age_56_to_64_yrs_Arrival_after_6_pm,-0.049130187,F +coef_Age_65_plus_yrs_Arrival_before_5_pm,0.056774635,F +coef_Age_65_plus_yrs_Arrival_after_6_pm,-0.077532684,F +coef_Zero_auto_HH_Departure_before_7_am,0.396983749,F +coef_Zero_auto_HH_Arrival_after_6_pm,0.050665232,F +coef_Parttime_worker_Departure_before_7_am,-0.264760988,F +coef_Parttime_worker_Departure_after_7_am,0.126626287,F +coef_Parttime_worker_Arrival_before_5_pm,0.175158545,F +coef_Parttime_worker_Arrival_after_6_pm,-0.054124518,F +coef_University_student_Departure_after_7_am,0.024758204,F +coef_University_student_Arrival_before_5_pm,0.035389739,F +coef_University_student_Arrival_after_6_pm,0.06173996,F +coef_Blue_collar_Departure_before_7_am,0.327242475,F +coef_Blue_collar_Departure_after_7_am,0.047214248,F +coef_Blue_collar_Arrival_before_5_pm,0.04197056,F +coef_Service_Departure_before_7_am,0.117783508,F +coef_Service_Departure_after_7_am,0.081611629,F +coef_Service_Arrival_before_5_pm,0,T +coef_Health_Departure_before_7_am,0.135275931,F +coef_Health_Arrival_after_6_pm,0.062010123,F +coef_Retail_and_food_Departure_after_7_am,0.076302969,F +coef_Retail_and_food_Arrival_before_5_pm,0.052905387,F +coef_Retail_and_food_Arrival_after_6_pm,0.027069194,F +coef_Time_SOV_freeflowto_destination_Departure_before_7_am,0.011511462,F +coef_Time_SOV_freeflowto_destination_Departure_after_7_am,-0.003821379,F +coef_Time_SOV_freeflowto_destination_Arrival_before_5_pm,-0.00549578,F +coef_Time_SOV_freeflowto_destination_Arrival_after_6_pm,0.002253695,F +coef_Presence_of_NonWorking_Adult_in_the_HH_Departure_before_7_am,0.069957209,F +coef_Presence_of_NonWorking_Adult_in_the_HH_Arrival_before_5_pm,-0.019807228,F +coef_Presence_of_PreDriving_Age_Children_in_the_HH_Departure_before_7_am,-0.084564489,F +coef_Presence_of_PreDriving_Age_Children_in_the_HH_Departure_after_8_am,-0.023894467,F +coef_Presence_of_PreDriving_Age_Children_in_the_HH_Arrival_before_5_pm,0.018983499,F +coef_Presence_of_PreDriving_Age_Children_in_the_HH_Arrival_after_6_pm,-0.032091123,F +coef_First_of_2_plus_mandatory_tour_Departure_before_7_am,0.145890035,F +coef_First_of_2_plus_mandatory_tour_Departure_after_7_am,-0.214531877,F +coef_First_of_2_plus_mandatory_tour_Duration_lt_9p5_hours,0.3069241,F +coef_First_of_2_plus_mandatory_tour_Duration_gt_9p5_hours,-0.526297898,F +coef_2nd_or_later_of_2_plus_mandatory_tour_Departure_before_1_pm,-0.221304523,F +coef_2nd_or_later_of_2_plus_mandatory_tour_Departure_after_2_pm,-0.176348812,F +coef_2nd_or_later_of_2_plus_mandatory_tour_Duration_lt_9p5_hours,0.064893097,F +coef_2nd_or_later_of_2_plus_mandatory_tour_Duration_gt_9p5_hours,-0.656942049,F +coef_Departure_Constant_Shift_for_every_30_minutes_before_6_am,-1.151564775,F +coef_Departure_Constant_Before_06_AM,-2.197677208,F +coef_Departure_Constant_06_AM_06_AM_7,-1.314098638,F +coef_Departure_Constant_06_AM_07_AM_8,-0.558766028,F +coef_Departure_Constant_07_AM_07_AM_9,0,T +coef_Departure_Constant_07_AM_08_AM_10,-0.036957515,F +coef_Departure_Constant_08_AM_08_AM_11,-0.285560423,F +coef_Departure_Constant_08_AM_09_AM_12,-0.555478447,F +coef_Departure_Constant_After_09_AM,-0.865125273,F +coef_Departure_Constant_Shift_for_every_30_minutes_after_9_am_Square_Root,-0.435746145,F +coef_Arrival_Constant_Shift_for_every_30_minutes_before_3_pm,-0.191607342,F +coef_Arrival_Constant_Before_03_PM,-0.289333093,F +coef_Arrival_Constant_03_PM_04_PM_26,-0.273555837,F +coef_Arrival_Constant_04_PM_04_PM_27,-0.142653706,F +coef_Arrival_Constant_04_PM_05_PM_28,-0.124814807,F +coef_Arrival_Constant_05_PM_05_PM_29,0.004265544,F +coef_Arrival_Constant_05_PM_06_PM_30,0,T +coef_Arrival_Constant_06_PM_06_PM_31,-0.060515031,F +coef_Arrival_Constant_06_PM_7_PM_32,-0.236621114,F +coef_Arrival_Constant_7_PM_7_PM_33,-0.577646614,F +coef_Arrival_Constant_7_PM_8_PM_34,-0.815994515,F +coef_Arrival_Constant_After_08_PM,-0.854151925,F +coef_Arrival_Constant_Shift_for_every_30_minutes_after_6_pm_Square_root,-0.469720787,F +coef_Duration_Constant_Shift_for_every_30_minutes_less_than_8p5_hrs,-0.074266981,F +coef_Duration_Constant_Shorter_than_8p5_hrs,-0.748584335,F +coef_Duration_Constant_8p5_hours,-0.654814097,F +coef_Duration_Constant_9_hours,-0.372064236,F +coef_Duration_Constant_9p5_hours,-0.144226124,F +coef_Duration_Constant_10_hours,0.013153356,F +coef_Duration_Constant_10p5_hours,0,T +coef_Duration_Constant_11_hours,-0.115847245,F +coef_Duration_Constant_11p5_hours,-0.288506368,F +coef_Duration_Constant_12_hours,-0.524241874,F +coef_Duration_Constant_Longer_than_12_hrs,-0.598634071,F +coef_Duration_Constant_Shift_for_every_30_minutes_more_than_10_hrs,-0.293607565,F +coef_Calibration_constant_Duration_0,-10,F diff --git a/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.csv b/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.csv new file mode 100644 index 000000000..9f0f2f0f5 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.csv @@ -0,0 +1,21 @@ +Label,Description,Expression,no_pass,pass +util_ft,Full-time worker,@df.pemploy==PEMPLOY_FULL,0,coef_ft_pass +util_pt,Part-time worker,@df.pemploy==PEMPLOY_PART,0,coef_pt_pass +util_un,University/College,@df.ptype==PTYPE_SCHOOL,0,coef_un_pass +util_nw,Non-working adult,@df.ptype==PTYPE_NONWORK,0,coef_nw_pass +util_rt,Retired,@df.ptype==PTYPE_RETIRED,0,coef_rt_pass +util_inc1,0-$9k,"@df.income.between(0, 9000)",0,coef_inc1_pass +util_inc2,$10-$24k,"@df.income.between(10000, 24000)",0,coef_inc2_pass +util_inc3,$25-$34k,"@df.income.between(25000,34000)",0,coef_inc3_pass +util_inc4,$35-$49k,"@df.income.between(35000,49000)",0,coef_inc4_pass +util_inc10,$250k+,@df.income >= 250000,0,coef_inc10_pass +#util_na20,NAICS 20 (mining/utilities/construct),@df.industry_naics=='20',0,coef_na20_pas +#util_na30,NAICS 30 (manufacturing,@df.industry_naics=='30',0,coef_na30_pas +#util_na50,NAICS 50 (Info/Fin/insur/real estate/prof/sci/tech/manage/admin),@df.industry_naics=='50',0,coef_na50_pas +#util_na70,NAICS 70 (Entertain/accom),@df.industry_naics=='70',0,coef_na70_pas +#util_na80,NAICS 80 (Other services),@df.industry_naics=='80',0,coef_na80_pas +#util_publ,NAICS 90 (Public admin),@df.industry_naics=='90',0,coef_publ_pas +#approximate measure for the time being,,,, +util_wrkamt,Auto minus transit time (work),@df.work_auto_savings * -1,0,coef_wrkamt_pas +util_subs,Subsidy offered,@df.transit_pass_subsidy,0,coef_subs_pas +utils_pass_asc,Constant,1,0,coef_pass_asc diff --git a/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.yaml b/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.yaml new file mode 100644 index 000000000..5cb754b4a --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership.yaml @@ -0,0 +1,7 @@ + +SPEC: transit_pass_ownership.csv +COEFFICIENTS: transit_pass_ownership_coeffs.csv + +#LOGIT_TYPE: NL +LOGIT_TYPE: MNL + diff --git a/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership_coeffs.csv new file mode 100644 index 000000000..aa756b4c0 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/transit_pass_ownership_coeffs.csv @@ -0,0 +1,20 @@ +coefficient_name,coefficient_name,value,constrain +coef_ft_pass,Full-time worker,2.034739841,F +coef_pt_pass,Part-time worker,1.934451611,F +coef_un_pass,University/College,2.38777737,F +coef_nw_pass,Non-working adult,1.520740664,F +coef_rt_pass,Retired,1.963879497,F +coef_inc1_pass,0-$9k,0.609753946,F +coef_inc2_pass,$10-$24k,0.421989203,F +coef_inc3_pass,$25-$34k,0.2119704,F +coef_inc4_pass,$35-$49k,0.139201682,F +coef_inc10_pass,$250k+,-0.169998314,F +coef_wrkamt_pas,Auto minus transit time (work),0.001934995,F +coef_na20_pas,NAICS 20 (mining/utilities/construct),-0.324742563,F +coef_na30_pas,NAICS 30 (manufacturing),-0.473249951,F +coef_na50_pas,NAICS 50 (Info/Fin/insur/real estate/prof/sci/tech/manage/admin),0.2731,F +coef_na70_pas,NAICS 70 (Entertain/accom),0.219432837,F +coef_na80_pas,NAICS 80 (Other services),-0.585251651,F +coef_publ_pas,NAICS 90 (Public admin),0.30410587,F +coef_subs_pas,Subsidy offered,1.967569275,F +coef_pass_asc,Constant,-3.932862618,F diff --git a/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.csv b/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.csv new file mode 100644 index 000000000..1a3d6a2aa --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.csv @@ -0,0 +1,12 @@ +Label,Description,Expression,no_subsidy,subsidy +util_ft,Full-time worker,@df.pemploy==PEMPLOY_FULL,0,coef_ft +util_pt,Part-time worker,@df.pemploy==PEMPLOY_PART,0,coef_pt +util_un,University/College,@df.ptype==PTYPE_SCHOOL,0,coef_un +#util_na70,NAICS 70 (Entertain/accom),@df.industry_naics=='70',0,coef_na70 +#util_na80,NAICS 80 (Other services),@df.industry_naics=='80',0,coef_na80 +#util_publ,NAICS 90 (Public admin),@df.industry_naics=='90',0,coef_publ +#approximate measure for the time being,,,, +util_tr_hh_emp,Household transit accessibility,@df.trOpRetail,0,coef_tr_hh_emp +#approximate measure for the time being,,,, +util_pkcost,Daily parking cost (dollars),@df.PRKCST+df.OPRKCST,0,coef_pkcost +utils_sub_asc,Constant,1,0,coef_sub_asc diff --git a/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.yaml b/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.yaml new file mode 100644 index 000000000..5f5244134 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy.yaml @@ -0,0 +1,7 @@ + +SPEC: transit_pass_subsidy.csv +COEFFICIENTS: transit_pass_subsidy_coeffs.csv + +#LOGIT_TYPE: NL +LOGIT_TYPE: MNL + diff --git a/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy_coeffs.csv new file mode 100644 index 000000000..8e4b511e0 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/transit_pass_subsidy_coeffs.csv @@ -0,0 +1,10 @@ +coefficient_name,coefficient_name,value,constrain +coef_ft,Full-time worker,1.882665664,F +coef_pt,Part-time worker,1.360746182,F +coef_un,University/College,2.026985147,F +coef_na70,NAICS 70 (Entertain/accom),-0.659568416,F +coef_na80,NAICS 80 (Other services),-0.352588858,F +coef_publ,NAICS 90 (Public admin),0.864991571,F +coef_tr_hh_emp,Transit accessibility to households,0.049608562,F +coef_pkcost,Daily parking cost (dollars),0.060145818,F +coef_sub_asc,Constant,-5.138015944,F diff --git a/activitysim/examples/prototype_mwcog/configs/trip_destination.csv b/activitysim/examples/prototype_mwcog/configs/trip_destination.csv new file mode 100644 index 000000000..3f950aa96 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_destination.csv @@ -0,0 +1,17 @@ +Label,Description,Expression,work,univ,school,escort,shopping,eatout,othmaint,social,othdiscr,atwork +util_size_term,size term,"@np.log1p(size_terms.get(df.dest_taz, df.purpose))",coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one +util_no_attractions,no attractions,"@size_terms.get(df.dest_taz, df.purpose) == 0",coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable +#util_stop_zone_CDB_are_type,#stop zone CBD area type,"@reindex(land_use.area_type, df.dest_taz) < setting('cbd_threshold')",,,,,,,,,, +util_distance_inbound,distance (calibration adjustment individual - inbound),@(~df.is_joint & ~df.outbound) * (od_skims['DIST'] + dp_skims['DIST']),coef_util_distance_work_outbound,coef_util_distance_univ,coef_util_distance_school,coef_util_distance_escort,coef_util_distance_shopping,coef_util_distance_eatout,coef_util_distance_othmaint,coef_util_distance_social,coef_util_distance_othdiscr,coef_util_distance_atwork +util_distance_outbound,distance (calibration adjustment individual - outbound),@(~df.is_joint & df.outbound) * (od_skims['DIST'] + dp_skims['DIST']),coef_util_distance_work_inbound,coef_util_distance_univ,coef_util_distance_school,coef_util_distance_escort,coef_util_distance_shopping,coef_util_distance_eatout,coef_util_distance_othmaint,coef_util_distance_social,coef_util_distance_othdiscr,coef_util_distance_atwork +util_distance_joint,distance (calibration adjustment joint),@df.is_joint * (od_skims['DIST'] + dp_skims['DIST']),,,,coef_distance_joint,coef_distance_joint,coef_distance_joint,coef_distance_joint,coef_distance_joint,coef_distance_joint, +util_prox_home_outbound,stop proximity to home (outbound),@df.outbound * od_skims['DIST'],coef_prox_home_outbound_work,,,,,,,,, +util_prox_home_inbound,stop proximity to home (inbound),@~df.outbound * dp_skims['DIST'],coef_prox_home_inbound_work,,,,,,,,, +util_prox_dest_outbound,stop proximity to main destination (outbound),@df.outbound * dp_skims['DIST'],coef_prox_dest_outbound_work,,,,,,,,, +util_prox_dest_inbound,stop proximity to main destination (inbound),@~df.outbound * od_skims['DIST'],0,,,,,,,,, +#,,,,,,,,,,,, +util_sample_of_alternatives_correction_factor,Sample of alternatives correction factor,"@np.minimum(np.log(df.pick_count/df.prob), 60)",coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one,coef_one +util_mode_choice_logsum_os,Mode choice logsum from origin to stop,od_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum +util_stop_not_accessible_by_this_tour_mode,Can't access stop zone by this tour mode,(od_logsum < -100),coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable +util_mode_choice_logsum_sd,Mode choice logsum from stop to destination,dp_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum,coef_mode_choice_logsum +util_dest_not_accessible_by_this_tour_mode,Can't access destination zone by this tour mode,(dp_logsum < -100),coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable diff --git a/activitysim/examples/prototype_mwcog/configs/trip_destination.yaml b/activitysim/examples/prototype_mwcog/configs/trip_destination.yaml new file mode 100644 index 000000000..8bac788cc --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_destination.yaml @@ -0,0 +1,44 @@ +SAMPLE_SPEC: trip_destination_sample.csv +SPEC: trip_destination.csv +COEFFICIENTS: trip_destination_coefficients.csv + +SAMPLE_SIZE: 30 + +DESTINATION_SAMPLE_SPEC: trip_destination_sample.csv +DESTINATION_SPEC: trip_destination.csv + +LOGSUM_SETTINGS: trip_mode_choice.yaml + +# optional (comment out if not desired) +DEST_CHOICE_LOGSUM_COLUMN_NAME: destination_logsum + +# comment out DEST_CHOICE_LOGSUM_COLUMN_NAME if saved alt logsum table +DEST_CHOICE_SAMPLE_TABLE_NAME: trip_destination_sample + +# model-specific logsum-related settings +TRIP_ORIGIN: origin +ALT_DEST_COL_NAME: dest_taz +PRIMARY_DEST: destination + +# tour_mode is already in trips table, so we don't need it from tours +# (it is assigned in trip_destination_annotate_trips_preprocessor ) +REDUNDANT_TOURS_MERGED_CHOOSER_COLUMNS: + - tour_mode + +CONSTANTS: + max_walk_distance: 3 + max_bike_distance: 8 + +preprocessor: + SPEC: trip_destination_annotate_trips_preprocessor + DF: trips + TABLES: + - tours + - persons + +# drop failed trips and cleanup failed trip leg_mates for consistency +# (i.e. adjust trip_count, trip_num, first for missing failed trips) +CLEANUP: False + +# this setting is used by testing code to force failed trip_destination +# fail_some_trips_for_testing: False diff --git a/activitysim/examples/prototype_mwcog/configs/trip_destination_annotate_trips_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/trip_destination_annotate_trips_preprocessor.csv new file mode 100644 index 000000000..0217a6855 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_destination_annotate_trips_preprocessor.csv @@ -0,0 +1,9 @@ +Description,Target,Expression +#,, +,tour_mode,"reindex(tours.tour_mode, df.tour_id)" +,_tod,"np.where(df.outbound,reindex_i(tours.start, df.tour_id),reindex_i(tours.end, df.tour_id))" +,trip_period,network_los.skim_time_period_label(_tod) +,is_joint,"reindex(tours.tour_category, df.tour_id)=='joint'" +#,,not needed as school is not chosen as an intermediate trip destination +#,_grade_school,"(df.primary_purpose == 'school') & reindex(persons.is_gradeschool, df.person_id)" +#,size_segment,"df.primary_purpose.where(df.primary_purpose != 'school', np.where(_grade_school,'gradeschool', 'highschool'))" diff --git a/activitysim/examples/prototype_mwcog/configs/trip_destination_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/trip_destination_coefficients.csv new file mode 100644 index 000000000..db732ac07 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_destination_coefficients.csv @@ -0,0 +1,19 @@ +coefficient_name,value,constrain +coef_unavailable,-999,T +coef_one,1,T +coef_mode_choice_logsum,1.821,F +coef_distance_joint,-0.1238,F +coef_util_distance_work_outbound,-0.049725916,F +coef_util_distance_work_inbound,0.147813279,F +coef_util_distance_univ,-0.0613,F +coef_util_distance_school,-0.1056,F +coef_util_distance_escort,-0.1491,F +coef_util_distance_shopping,-0.1192,F +coef_util_distance_eatout,-0.1029,F +coef_util_distance_othmaint,-0.205,F +coef_util_distance_social,-0.1329,F +coef_util_distance_othdiscr,-0.146172224,F +coef_util_distance_atwork,-0.167334597,F +coef_prox_home_outbound_work,-0.38,F +coef_prox_home_inbound_work,-0.15,F +coef_prox_dest_outbound_work,-0.26,F diff --git a/activitysim/examples/prototype_mwcog/configs/trip_destination_sample.csv b/activitysim/examples/prototype_mwcog/configs/trip_destination_sample.csv new file mode 100644 index 000000000..6a0a53480 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_destination_sample.csv @@ -0,0 +1,18 @@ +Description,Expression,work,univ,school,escort,shopping,eatout,othmaint,social,othdiscr,atwork +,_od_DIST@od_skims['DIST'],1,1,1,1,1,1,1,1,1,1 +,_dp_DIST@dp_skims['DIST'],1,1,1,1,1,1,1,1,1,1 +Not available if walk tour not within walking distance,@(df.tour_mode=='WALK') & (od_skims['DISTWALK'] > max_walk_distance),-999,-999,-999,-999,-999,-999,-999,-999,-999,-999 +Not available if walk tour not within walking distance,@(df.tour_mode=='WALK') & (dp_skims['DISTWALK'] > max_walk_distance),-999,-999,-999,-999,-999,-999,-999,-999,-999,-999 +Not available if bike tour not within biking distance,@(df.tour_mode=='BIKE') & (od_skims['DISTBIKE'] > max_bike_distance),-999,-999,-999,-999,-999,-999,-999,-999,-999,-999 +Not available if bike tour not within biking distance,@(df.tour_mode=='BIKE') & (dp_skims['DISTBIKE'] > max_bike_distance),-999,-999,-999,-999,-999,-999,-999,-999,-999,-999 +#If transit tour is not in walk sub-zone it must be walkable,,,,,,,,,,, +size term,"@np.log1p(size_terms.get(df.dest_taz, df.purpose))",1,1,1,1,1,1,1,1,1,1 +no attractions,"@size_terms.get(df.dest_taz, df.purpose) == 0",-999,-999,-999,-999,-999,-999,-999,-999,-999,-999 +#stop zone CBD area type,"@reindex(land_use.AreaType, df.dest_taz) < setting('cbd_threshold')",,,,,,,,,, +distance (calibration adjustment individual - inbound),@(~df.is_joint & ~df.outbound) * (_od_DIST + _dp_DIST),-0.049725916,-0.0613,-0.1056,-0.1491,-0.1192,-0.1029,-0.0962,-0.1329,-0.126172224,-0.122334597 +distance (calibration adjustment individual - outbound),@(~df.is_joint & df.outbound) * (_od_DIST + _dp_DIST),0.147813279,-0.0613,-0.1056,-0.1491,-0.1192,-0.1029,-0.0962,-0.1329,-0.126172224,-0.122334597 +distance (calibration adjustment joint),@df.is_joint * (_od_DIST + _dp_DIST),0,0,0,-0.1238,-0.1238,-0.1238,-0.1238,-0.1238,-0.123801985,0 +stop proximity to home (outbound),@df.outbound * _od_DIST,-0.38,0,0,0,0,0,0,0,0,0 +stop proximity to home (inbound),@~df.outbound * _od_DIST,-0.15,0,0,0,0,0,0,0,0,0 +stop proximity to main destination (outbound),@df.outbound * _dp_DIST,-0.26,,,,,,,,, +stop proximity to main destination (inbound),@~df.outbound * _od_DIST,0,,,,,,,,, diff --git a/activitysim/examples/prototype_mwcog/configs/trip_mode_choice.csv b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice.csv new file mode 100644 index 000000000..fa8def35f --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice.csv @@ -0,0 +1,455 @@ +Label,Description,Expression,DRIVEALONE,SHARED2,SHARED3,WALK,BIKE,WALK_AB,WALK_BM,WALK_MR,WALK_CR,PNR_AB,PNR_BM,PNR_MR,PNR_CR,KNR_AB,KNR_BM,KNR_MR,KNR_CR,SCHOOLBUS,TAXI,TNC_SINGLE,TNC_SHARED +#Drive_alone_no_toll,#Drive alone no toll,,,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable,DRIVEALONE - Unavailable,sov_available == False,coef_unavailable,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable_for_persons_less_than_16,DRIVEALONE - Unavailable for persons less than 16,age < 16,coef_unavailable,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable_for_joint_tours,DRIVEALONE - Unavailable for joint tours,is_joint == True,coef_unavailable,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Unavailable_if_didn't_drive_to_work,DRIVEALONE - Unavailable if didn't drive to work,is_atwork_subtour & ~work_tour_is_SOV,coef_unavailable,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_In_vehicle_time,DRIVEALONE - In-vehicle time,@odt_skims['SOV_TIME'],coef_ivt,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Terminal_time,DRIVEALONE - Terminal time,@coef_walktimeshort_multiplier * df.total_terminal_time,coef_ivt,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Operating_cost_,DRIVEALONE - Operating cost ,@ivt_cost_multiplier * df.ivot * costPerMile * odt_skims['SOV_DIST'],coef_ivt,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Parking_cost_,DRIVEALONE - Parking cost ,@ivt_cost_multiplier * df.ivot * df.total_parking_cost,coef_ivt,,,,,,,,,,,,,,,,,,,, +util_DRIVEALONE_Person_is_between_16_and_19_years_old,DRIVEALONE - Person is between 16 and 19 years old,@c_age1619_da * ((df.age >= 16) & (df.age <= 19)),coef_age1619_da,,,,,,,,,,,,,,,,,,,, +#Shared_ride_2,#Shared ride 2,,,,,,,,,,,,,,,,,,,,,, +util_SHARED2_Unavailable,SHARED2 - Unavailable,hov2_available == False,,coef_unavailable,,,,,,,,,,,,,,,,,,, +util_SHARED2_Unavailable_based_on_party_size,SHARED2 - Unavailable based on party size,is_joint & (number_of_participants > 2),,coef_unavailable,,,,,,,,,,,,,,,,,,, +util_SHARED2_In_vehicle_time,SHARED2 - In-vehicle time,@odt_skims['HOV2_TIME'],,coef_ivt,,,,,,,,,,,,,,,,,,, +util_SHARED2_Terminal_time,SHARED2 - Terminal time,@coef_walktimeshort_multiplier * df.total_terminal_time,,coef_ivt,,,,,,,,,,,,,,,,,,, +util_SHARED2_Operating_cost,SHARED2 - Operating cost,@ivt_cost_multiplier * df.ivot * costPerMile * odt_skims['HOV2_DIST'],,coef_ivt,,,,,,,,,,,,,,,,,,, +util_SHARED2_Parking_cost,SHARED2 - Parking cost,@ivt_cost_multiplier * df.ivot * df.total_parking_cost / costShareSr2,,coef_ivt,,,,,,,,,,,,,,,,,,, +util_SHARED2_One_person_household,SHARED2 - One person household,@(df.hhsize == 1),,coef_hhsize1_sr,,,,,,,,,,,,,,,,,,, +util_SHARED2_Two_person_household,SHARED2 - Two person household,@(df.hhsize == 2),,coef_hhsize2_sr,,,,,,,,,,,,,,,,,,, +util_SHARED2_Person_is_16_years_old_or_older,SHARED2 - Person is 16 years old or older,@(df.age >= 16),,coef_age1619_da,,,,,,,,,,,,,,,,,,, +#Shared_ride_3+,#Shared ride 3+,,,,,,,,,,,,,,,,,,,,,, +util_SHARED3_Unavailable,SHARED3 - Unavailable,hov3_available == False,,,coef_unavailable,,,,,,,,,,,,,,,,,, +util_SHARED3_Unavailable_based_joint_tour_mode,SHARED3 - Unavailable based joint tour mode,@df.is_joint & df.i_tour_mode.isin(I_SR2_MODES),,,coef_unavailable,,,,,,,,,,,,,,,,,, +util_SHARED3_Unavailable_if_tour_mode_is_shared_2,SHARED3 - Unavailable if tour mode is shared 2,@df.i_tour_mode.isin(I_SR2_MODES),,,coef_unavailable,,,,,,,,,,,,,,,,,, +util_SHARED3_In_vehicle_time,SHARED3 - In-vehicle time,@odt_skims['HOV3_TIME'],,,coef_ivt,,,,,,,,,,,,,,,,,, +util_SHARED3_Terminal_time,SHARED3 - Terminal time,@coef_walktimeshort_multiplier * df.total_terminal_time,,,coef_ivt,,,,,,,,,,,,,,,,,, +util_SHARED3_Operating_cost,SHARED3 - Operating cost,@ivt_cost_multiplier * df.ivot * costPerMile * odt_skims['HOV3_DIST'],,,coef_ivt,,,,,,,,,,,,,,,,,, +util_SHARED3_Parking_cost,SHARED3 - Parking cost,@ivt_cost_multiplier * df.ivot * df.total_parking_cost / costShareSr3,,,coef_ivt,,,,,,,,,,,,,,,,,, +util_SHARED3_One_person_household,SHARED3 - One person household,@(df.hhsize == 1),,,coef_hhsize1_sr,,,,,,,,,,,,,,,,,, +util_SHARED3_Two_person_household,SHARED3 - Two person household,@(df.hhsize == 2),,,coef_hhsize2_sr,,,,,,,,,,,,,,,,,, +util_SHARED3_Person_is_16_years_old_or_older,SHARED3 - Person is 16 years old or older,@(df.age >= 16),,,coef_age16p_sr,,,,,,,,,,,,,,,,,, +#Walk,#Walk,,,,,,,,,,,,,,,,,,,,,, +util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@coef_walktimeshort_multiplier * od_skims['DISTWALK'].clip(upper=walkThresh) * 60/walkSpeed,,,,coef_ivt,,,,,,,,,,,,,,,,, +util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * (od_skims['DISTWALK'] - walkThresh).clip(lower=0) * 60/walkSpeed,,,,coef_ivt,,,,,,,,,,,,,,,,, +util_WALK_Destination_zone_densityIndex,WALK - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,coef_ivt,,,,,,,,,,,,,,,,, +util_WALK_Topology,WALK - Topology,@topology_walk_multiplier * df.trip_topology,,,,coef_ivt,,,,,,,,,,,,,,,,, +#Bike,#Bike,,,,,,,,,,,,,,,,,,,,,, +util_BIKE_Unavailable_if_tour_mode_is_not_bike,BIKE - Unavailable if tour mode is not bike,~tour_mode_is_bike,,,,,coef_unavailable,,,,,,,,,,,,,,,, +util_BIKE_Unavailable_if_didn't_bike_to_work,BIKE - Unavailable if didn't bike to work,is_atwork_subtour & ~work_tour_is_bike,,,,,coef_unavailable,,,,,,,,,,,,,,,, +util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@coef_biketimeshort_multiplier * od_skims['DISTBIKE'].clip(upper=bikeThresh)*60/bikeSpeed,,,,,coef_ivt,,,,,,,,,,,,,,,, +util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@biketimelong_multiplier * (od_skims['DISTBIKE']-bikeThresh).clip(lower=0)*60/bikeSpeed,,,,,coef_ivt,,,,,,,,,,,,,,,, +util_BIKE_Destination_zone_densityIndex,BIKE - Destination zone densityIndex,@density_index_multiplier*df.density_index,,,,,coef_ivt,,,,,,,,,,,,,,,, +util_BIKE_Topology,BIKE - Topology,@topology_bike_multiplier * df.trip_topology,,,,,coef_ivt,,,,,,,,,,,,,,,, +#Walk_to_AB,#Walk to AB,,,,,,,,,,,,,,,,,,,,,, +util_WALK_AB_Unavailable,WALK_AB - Unavailable,walk_ab_available == False,,,,,,coef_unavailable,,,,,,,,,,,,,,, +util_WALK_AB_In_vehicle_time,WALK_AB - In-vehicle time,@odt_skims['WK_AB_WK_TOTIVT'],,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_In_vehicle_time_on_XB,WALK_AB - In-vehicle time on XB,@(coef_ivt_xb_multiplier - 1) * odt_skims['WK_AB_WK_IVTXB'],,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Short_iwait_time,WALK_AB - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WK_AB_WK_IWAIT']).clip(upper=waitThresh),,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Long_iwait_time,WALK_AB - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WK_AB_WK_IWAIT']-waitThresh).clip(0),,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_transfer_wait_time,WALK_AB - transfer wait time,@coef_xwait_multiplier * odt_skims['WK_AB_WK_XWAIT'],,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_number_of_transfers,WALK_AB - number of transfers,@xfers_wlk_multiplier * (odt_skims['WK_AB_WK_XFERS']).clip(0),,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Walk_access_time,WALK_AB - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Walk_egress_time,WALK_AB - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Walk_other_time,WALK_AB - Walk other time,@coef_waux_multiplier * odt_skims['WK_AB_WK_WAUX'],,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Fare,WALK_AB - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WK_AB_WK_FARE'],,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Destination_zone_densityIndex,WALK_AB - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Topology,WALK_AB - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,coef_ivt,,,,,,,,,,,,,,, +util_WALK_AB_Person_is_less_than_10_years_old,WALK_AB - Person is less than 10 years old,@(df.age <= 10),,,,,,coef_age010_trn,,,,,,,,,,,,,,, +#Walk_to_BM,#Walk to BM,,,,,,,,,,,,,,,,,,,,,, +util_WALK_BM_Unavailable,WALK_BM - Unavailable,walk_bm_available == False,,,,,,,coef_unavailable,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time,WALK_BM - In-vehicle time,@odt_skims['WK_BM_WK_TOTIVT'],,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time_on_XB,WALK_BM - In-vehicle time on XB,@(coef_ivt_xb_multiplier - 1) * odt_skims['WK_BM_WK_IVTXB'],,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time_on_MR,WALK_BM - In-vehicle time on MR,@(coef_ivt_mr_multiplier - 1) * odt_skims['WK_BM_WK_IVTMR'],,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_In_vehicle_time_on_LR,WALK_BM - In-vehicle time on LR,@(coef_ivt_lr_multiplier - 1) * odt_skims['WK_BM_WK_IVTLR'],,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Short_iwait_time,WALK_BM - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WK_BM_WK_IWAIT']).clip(upper=waitThresh),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Long_iwait_time,WALK_BM - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WK_BM_WK_IWAIT']-waitThresh).clip(0),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_transfer_wait_time,WALK_BM - transfer wait time,@coef_xwait_multiplier * odt_skims['WK_BM_WK_XWAIT'],,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_number_of_transfers,WALK_BM - number of transfers,@xfers_wlk_multiplier * (odt_skims['WK_BM_WK_XFERS']).clip(0),,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Walk_access_time,WALK_BM - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Walk_egress_time,WALK_BM - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Walk_otherLight_rail/Ferry_time,WALK_BM - Walk otherLight rail/Ferry time,@coef_waux_multiplier * odt_skims['WK_BM_WK_WAUX'],,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Fare,WALK_BM - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WK_BM_WK_FARE'],,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Destination_zone_densityIndex,WALK_BM - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Topology,WALK_BM - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,coef_ivt,,,,,,,,,,,,,, +util_WALK_BM_Person_is_less_than_10_years_old,WALK_BM - Person is less than 10 years old,@(df.age <= 10),,,,,,,coef_age010_trn,,,,,,,,,,,,,, +#Walk_to_MR,#Walk to MR,,,,,,,,,,,,,,,,,,,,,, +util_WALK_MR_Unavailable,WALK_MR - Unavailable,walk_mr_available == False,,,,,,,,coef_unavailable,,,,,,,,,,,,, +util_WALK_MR_In_vehicle_time,WALK_MR - In-vehicle time,@odt_skims['WK_MR_WK_TOTIVT'],,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_In_vehicle_time_on_MR,WALK_MR - In-vehicle time on MR,@(coef_ivt_mr_multiplier - 1) * odt_skims['WK_MR_WK_IVTMR'],,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_In_vehicle_time_on_LR,WALK_MR - In-vehicle time on LR,@(coef_ivt_lr_multiplier - 1) * odt_skims['WK_MR_WK_IVTLR'],,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Short_iwait_time,WALK_MR - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WK_MR_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Long_iwait_time,WALK_MR - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WK_MR_WK_IWAIT']-waitThresh).clip(0),,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_transfer_wait_time,WALK_MR - transfer wait time,@coef_xwait_multiplier * odt_skims['WK_MR_WK_XWAIT'],,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_number_of_transfers,WALK_MR - number of transfers,@xfers_wlk_multiplier * (odt_skims['WK_MR_WK_XFERS']).clip(0),,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Walk_access_time,WALK_MR - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Walk_egress_time,WALK_MR - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Walk_other_time,WALK_MR - Walk other time,@coef_waux_multiplier * odt_skims['WK_MR_WK_WAUX'],,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Fare,WALK_MR - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WK_MR_WK_FARE'],,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Destination_zone_densityIndex,WALK_MR - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Topology,WALK_MR - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,coef_ivt,,,,,,,,,,,,, +util_WALK_MR_Person_is_less_than_10_years_old,WALK_MR - Person is less than 10 years old,@(df.age <= 10),,,,,,,,coef_age010_trn,,,,,,,,,,,,, +#Walk_to_CR,#Walk to CR,,,,,,,,,,,,,,,,,,,,,, +util_WALK_CR_Unavailable,WALK_CR - Unavailable,walk_cr_available == False,,,,,,,,,coef_unavailable,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time,WALK_CR - In-vehicle time,@odt_skims['WK_CR_WK_TOTIVT'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_XB,WALK_CR - In-vehicle time on XB,@(coef_ivt_xb_multiplier - 1) * odt_skims['WK_CR_WK_IVTXB'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_MR,WALK_CR - In-vehicle time on MR,@(coef_ivt_mr_multiplier - 1) * odt_skims['WK_CR_WK_IVTMR'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_BR,WALK_CR - In-vehicle time on BR,@(coef_ivt_br_multiplier - 1) * odt_skims['WK_CR_WK_IVTBR'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_LR,WALK_CR - In-vehicle time on LR,@(coef_ivt_lr_multiplier - 1) * odt_skims['WK_CR_WK_IVTLR'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_In_vehicle_time_on_CR,WALK_CR - In-vehicle time on CR,@(coef_ivt_cr_multiplier - 1) * odt_skims['WK_CR_WK_IVTCR'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Short_iwait_time,WALK_CR - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WK_CR_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Long_iwait_time,WALK_CR - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WK_CR_WK_IWAIT']-waitThresh).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_transfer_wait_time,WALK_CR - transfer wait time,@coef_xwait_multiplier * odt_skims['WK_CR_WK_XWAIT'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_number_of_transfers,WALK_CR - number of transfers,@xfers_wlk_multiplier * (odt_skims['WK_CR_WK_XFERS']).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Walk_access_time,WALK_CR - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Walk_egress_time,WALK_CR - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Walk_other_time,WALK_CR - Walk other time,@coef_waux_multiplier * odt_skims['WK_CR_WK_WAUX'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Fare,WALK_CR - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WK_CR_WK_FARE'],,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Destination_zone_densityIndex,WALK_CR - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Topology,WALK_CR - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,coef_ivt,,,,,,,,,,,, +util_WALK_CR_Person_is_less_than_10_years_old,WALK_CR - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,coef_age010_trn,,,,,,,,,,,, +#PNR_to_AB,#PNR to AB,,,,,,,,,,,,,,,,,,,,,, +util_PNR_AB_Unavailable_for_zero_auto_households,PNR_AB - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,coef_unavailable,,,,,,,,,,, +util_PNR_AB_Unavailable_for_persons_less_than_16,PNR_AB - Unavailable for persons less than 16,age < 16,,,,,,,,,,coef_unavailable,,,,,,,,,,, +util_PNR_AB_Destination_zone_densityIndex,PNR_AB - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_Topology,PNR_AB - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_Person_is_less_than_10_years_old,PNR_AB - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Unavailable,PNR_AB outbound - Unavailable,outbound & ~pnr_ab_available_outbound,,,,,,,,,,coef_unavailable,,,,,,,,,,, +util_PNR_AB_outbound_In_vehicle_time,PNR_AB outbound - In-vehicle time,@df.outbound * odt_skims['DR_AB_WK_TOTIVT'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_In_vehicle_time_on_XB,PNR_AB outbound - In-vehicle time on XB,@df.outbound * (coef_ivt_xb_multiplier - 1) * odt_skims['DR_AB_WK_IVTXB'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Short_iwait_time,PNR_AB outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DR_AB_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Long_iwait_time,PNR_AB outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DR_AB_WK_IWAIT']-waitThresh).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_transfer_wait_time,PNR_AB outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DR_AB_WK_XWAIT'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_number_of_transfers,PNR_AB outbound - number of transfers,@df.outbound * xfers_wlk_multiplier * (odt_skims['DR_AB_WK_XFERS']).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Drive_time,PNR_AB outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DR_AB_WK_DTIME'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Walk_egress_time,PNR_AB outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Walk_other_time,PNR_AB outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DR_AB_WK_WAUX'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Fare_and_operating_cost,PNR_AB outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DR_AB_WK_FARE'] + costPerMile*odt_skims['DR_AB_WK_DDIST']),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_outbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_AB outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DR_AB_WK_DDIST'])/ (od_skims['DIST']),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Unavailable,PNR_AB inbound - Unavailable,inbound & ~pnr_ab_available_inbound,,,,,,,,,,coef_unavailable,,,,,,,,,,, +util_PNR_AB_inbound_In_vehicle_time,PNR_AB inbound - In-vehicle time,@df.inbound * odt_skims['WK_AB_DR_TOTIVT'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Short_iwait_time,PNR_AB inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_AB_DR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Long_iwait_time,PNR_AB inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_AB_DR_IWAIT']-waitThresh).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_transfer_wait_time,PNR_AB inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_AB_DR_XWAIT'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_number_of_transfers,PNR_AB inbound - number of transfers,@df.inbound * xfers_wlk_multiplier * (odt_skims['WK_AB_DR_XFERS']).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Drive_time,PNR_AB inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_AB_DR_DTIME'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Walk_access_time,PNR_AB inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Walk_other_time,PNR_AB inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_AB_DR_WAUX'],,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Fare_and_operating_cost,PNR_AB inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_AB_DR_FARE'] + costPerMile*odt_skims['WK_AB_DR_DDIST']),,,,,,,,,,coef_ivt,,,,,,,,,,, +util_PNR_AB_inbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_AB inbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['WK_AB_DR_DDIST'])/ (od_skims['DIST']),,,,,,,,,,coef_ivt,,,,,,,,,,, +#Drive_to_BM,#Drive to BM,,,,,,,,,,,,,,,,,,,,,, +util_PNR_BM_Unavailable_for_zero_auto_households,PNR_BM - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,coef_unavailable,,,,,,,,,, +util_PNR_BM_Unavailable_for_persons_less_than_16,PNR_BM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,coef_unavailable,,,,,,,,,, +util_PNR_BM__Destination_zone_densityIndex,PNR_BM - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM__Topology,PNR_BM - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM__Person_is_less_than_10_years_old,PNR_BM - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Unavailable,PNR_BM outbound - Unavailable,outbound & ~pnr_bm_available_outbound,,,,,,,,,,,coef_unavailable,,,,,,,,,, +util_PNR_BM_outbound_In_vehicle_time,PNR_BM outbound - In-vehicle time,@df.outbound * odt_skims['DR_BM_WK_TOTIVT'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_XB,PNR_BM - In-vehicle time on XB,@df.outbound * (coef_ivt_xb_multiplier - 1) * odt_skims['DR_BM_WK_IVTXB'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_MR,PNR_BM - In-vehicle time on MR,@df.outbound * (coef_ivt_mr_multiplier - 1) * odt_skims['DR_BM_WK_IVTMR'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_LR,PNR_BM - In-vehicle time on LR,@df.outbound * (coef_ivt_lr_multiplier - 1) * odt_skims['DR_BM_WK_IVTLR'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Short_iwait_time,PNR_BM outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DR_BM_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Long_iwait_time,PNR_BM outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DR_BM_WK_IWAIT']-waitThresh).clip(0) ,,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_transfer_wait_time,PNR_BM outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DR_BM_WK_XWAIT'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_number_of_transfers,PNR_BM outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DR_BM_WK_XFERS']).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Drive_time,PNR_BM outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DR_BM_WK_DTIME'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Walk_egress_time,PNR_BM outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Walk_other_time,PNR_BM outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DR_BM_WK_WAUX'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Fare_and_operating_cost,PNR_BM outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DR_BM_WK_FARE'] + costPerMile * odt_skims['DR_BM_WK_DDIST']),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_outbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_BM outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DR_BM_WK_DDIST']) / od_skims['DIST'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Unavailable,PNR_BM inbound - Unavailable,inbound & ~pnr_bm_available_inbound,,,,,,,,,,,coef_unavailable,,,,,,,,,, +util_PNR_BM_inbound_In_vehicle_time,PNR_BM inbound - In-vehicle time,@df.inbound * odt_skims['WK_BM_DR_TOTIVT'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_XB,PNR_BM - In-vehicle time on XB,@df.inbound * (coef_ivt_xb_multiplier - 1) * odt_skims['WK_BM_DR_IVTXB'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_MR,PNR_BM - In-vehicle time on MR,@df.inbound * (coef_ivt_mr_multiplier - 1) * odt_skims['WK_BM_DR_IVTMR'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_In_vehicle_time_on_LR,PNR_BM - In-vehicle time on LR,@df.inbound * (coef_ivt_lr_multiplier - 1) * odt_skims['WK_BM_DR_IVTLR'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Short_iwait_time,PNR_BM inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_BM_DR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Long_iwait_time,PNR_BM inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_BM_DR_IWAIT']-waitThresh).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_transfer_wait_time,PNR_BM inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_BM_DR_XWAIT'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_number_of_transfers,PNR_BM inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WK_BM_DR_XFERS']).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Drive_time,PNR_BM inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_BM_DR_DTIME'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Walk_access_time,PNR_BM inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Walk_other_time,PNR_BM inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_BM_DR_WAUX'],,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Fare_and_operating_cost,PNR_BM inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_BM_DR_FARE'] + costPerMile * odt_skims['WK_BM_DR_DDIST']),,,,,,,,,,,coef_ivt,,,,,,,,,, +util_PNR_BM_inbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_BM inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WK_BM_DR_DDIST'])/ od_skims['DIST'],,,,,,,,,,,coef_ivt,,,,,,,,,, +#PNR_to_MR,#PNR to MR,,,,,,,,,,,,,,,,,,,,,, +util_PNR_MR_Unavailable_for_zero_auto_households,PNR_MR - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,coef_unavailable,,,,,,,,, +util_PNR_MR_Unavailable_for_persons_less_than_16,PNR_MR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,coef_unavailable,,,,,,,,, +util_PNR_MR_Destination_zone_densityIndex,PNR_MR - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_Topology,PNR_MR - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_Person_is_less_than_10_years_old,PNR_MR - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Unavailable,PNR_MR outbound - Unavailable,outbound & ~pnr_mr_available_outbound,,,,,,,,,,,,coef_unavailable,,,,,,,,, +util_PNR_MR_outbound_In_vehicle_time,PNR_MR outbound - In-vehicle time,@df.outbound * odt_skims['DR_MR_WK_TOTIVT'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_In_vehicle_time_on_MR,PNR_MR - In-vehicle time on MR,@df.outbound * (coef_ivt_mr_multiplier - 1) * odt_skims['DR_MR_WK_IVTMR'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_In_vehicle_time_on_LR,PNR_MR - In-vehicle time on LR,@df.outbound * (coef_ivt_lr_multiplier - 1) * odt_skims['DR_MR_WK_IVTLR'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Short_iwait_time,PNR_MR outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DR_MR_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Long_iwait_time,PNR_MR outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DR_MR_WK_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_transfer_wait_time,PNR_MR outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DR_MR_WK_XWAIT'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_number_of_transfers,PNR_MR outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DR_MR_WK_XFERS']).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Drive_time,PNR_MR outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DR_MR_WK_DTIME'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Walk_egress_ime,PNR_MR outbound - Walk egress ime,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Walk_other_time,PNR_MR outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DR_MR_WK_WAUX'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Fare_and_operating_cost,PNR_MR outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DR_MR_WK_FARE'] + costPerMile * odt_skims['DR_MR_WK_DDIST']),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_outbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_MR outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DR_MR_WK_DDIST']) / od_skims['DIST'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Unavailable,PNR_MR inbound - Unavailable,inbound & ~pnr_mr_available_inbound,,,,,,,,,,,,coef_unavailable,,,,,,,,, +util_PNR_MR_inbound_In_vehicle_time,PNR_MR inbound - In-vehicle time,@df.inbound * odt_skims['WK_MR_DR_TOTIVT'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_In_vehicle_time_on_MR,PNR_MR - In-vehicle time on MR,@df.inbound * (coef_ivt_mr_multiplier - 1) * odt_skims['WK_MR_DR_IVTMR'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_In_vehicle_time_on_LR,PNR_MR - In-vehicle time on LR,@df.inbound * (coef_ivt_lr_multiplier - 1) * odt_skims['WK_MR_DR_IVTLR'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Short_iwait_time,PNR_MR inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_MR_DR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Long_iwait_time,PNR_MR inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_MR_DR_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_transfer_wait_time,PNR_MR inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_MR_DR_XWAIT'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_number_of_transfers,PNR_MR inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WK_MR_DR_XFERS']).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Drive_time,PNR_MR inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_MR_DR_DTIME'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Walk_access_time,PNR_MR inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Walk_other_time,PNR_MR inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_MR_DR_WAUX'],,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Fare_and_operating_cost,PNR_MR inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_MR_DR_FARE'] + costPerMile * odt_skims['WK_MR_DR_DDIST']),,,,,,,,,,,,coef_ivt,,,,,,,,, +util_PNR_MR_inbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_MR inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WK_MR_DR_DDIST']) / od_skims['DIST'],,,,,,,,,,,,coef_ivt,,,,,,,,, +#PNR_to_CR,#PNR to CR,,,,,,,,,,,,,,,,,,,,,, +util_PNR_CR_Unavailable_for_zero_auto_households,PNR_CR - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,coef_unavailable,,,,,,,, +util_PNR_CR_Unavailable_for_persons_less_than_16,PNR_CR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,coef_unavailable,,,,,,,, +util_PNR_CR_Destination_zone_densityIndex,PNR_CR - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_Topology,PNR_CR - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_Person_is_less_than_10_years_old,PNR_CR - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Unavailable,PNR_CR outbound - Unavailable,outbound & ~pnr_cr_available_outbound,,,,,,,,,,,,,coef_unavailable,,,,,,,, +util_PNR_CR_outbound_In_vehicle_time,PNR_CR outbound - In-vehicle time,@df.outbound * odt_skims['DR_CR_WK_TOTIVT'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_XB,PNR_CR - In-vehicle time on XB,@df.outbound * (coef_ivt_xb_multiplier - 1) * odt_skims['DR_CR_WK_IVTXB'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_MR,PNR_CR - In-vehicle time on MR,@df.outbound * (coef_ivt_mr_multiplier - 1) * odt_skims['DR_CR_WK_IVTMR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_BR,PNR_CR - In-vehicle time on BR,@df.outbound * (coef_ivt_br_multiplier - 1) * odt_skims['DR_CR_WK_IVTBR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_CR,PNR_CR - In-vehicle time on CR,@df.outbound * (coef_ivt_cr_multiplier - 1) * odt_skims['DR_CR_WK_IVTCR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_LR,PNR_CR - In-vehicle time on LR,@df.outbound * (coef_ivt_lr_multiplier - 1) * odt_skims['DR_CR_WK_IVTLR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Short_iwait_time,PNR_CR outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DR_CR_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Long_iwait_time,PNR_CR outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DR_CR_WK_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_transfer_wait_time,PNR_CR outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DR_CR_WK_XWAIT'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_number_of_transfers,PNR_CR outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DR_CR_WK_XFERS']).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Drive_time,PNR_CR outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DR_CR_WK_DTIME'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Walk_egress_ime,PNR_CR outbound - Walk egress ime,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Walk_other_time,PNR_CR outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DR_CR_WK_WAUX'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Fare_and_operating_cost,PNR_CR outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DR_CR_WK_FARE'] + costPerMile * odt_skims['DR_CR_WK_DDIST']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_outbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_CR outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DR_CR_WK_DDIST']) / od_skims['DIST'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Unavailable,PNR_CR inbound - Unavailable,inbound & ~pnr_cr_available_inbound,,,,,,,,,,,,,coef_unavailable,,,,,,,, +util_PNR_CR_inbound_In_vehicle_time,PNR_CR inbound - In-vehicle time,@df.inbound * odt_skims['WK_CR_DR_TOTIVT'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_XB,PNR_CR - In-vehicle time on XB,@df.inbound * (coef_ivt_xb_multiplier - 1) * odt_skims['WK_CR_DR_IVTXB'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_MR,PNR_CR - In-vehicle time on MR,@df.inbound * (coef_ivt_mr_multiplier - 1) * odt_skims['WK_CR_DR_IVTMR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_BR,PNR_CR - In-vehicle time on BR,@df.inbound * (coef_ivt_br_multiplier - 1) * odt_skims['WK_CR_DR_IVTBR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_CR,PNR_CR - In-vehicle time on CR,@df.inbound * (coef_ivt_cr_multiplier - 1) * odt_skims['WK_CR_DR_IVTCR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_In_vehicle_time_on_LR,PNR_CR - In-vehicle time on LR,@df.inbound * (coef_ivt_lr_multiplier - 1) * odt_skims['WK_CR_DR_IVTLR'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Short_iwait_time,PNR_CR inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_CR_DR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Long_iwait_time,PNR_CR inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_CR_DR_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_transfer_wait_time,PNR_CR inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_CR_DR_XWAIT'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_number_of_transfers,PNR_CR inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WK_CR_DR_XFERS']).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Drive_time,PNR_CR inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_CR_DR_DTIME'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Walk_access_time,PNR_CR inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Walk_other_time,PNR_CR inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_CR_DR_WAUX'],,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Fare_and_operating_cost,PNR_CR inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_CR_DR_FARE'] + costPerMile * odt_skims['WK_CR_DR_DDIST']),,,,,,,,,,,,,coef_ivt,,,,,,,, +util_PNR_CR_inbound_Ratio_of_drive_access_distance_to_OD_distance,PNR_CR inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WK_CR_DR_DDIST']) / od_skims['DIST'],,,,,,,,,,,,,coef_ivt,,,,,,,, +#KNR_to_AB,#KNR to AB,,,,,,,,,,,,,,,,,,,,,, +util_KNR_AB_Unavailable_for_persons_less_than_16,KNR_AB - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,coef_unavailable,,,,,,, +util_KNR_AB_Destination_zone_densityIndex,KNR_AB - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_Topology,KNR_AB - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_Person_is_less_than_10_years_old,KNR_AB - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Unavailable,KNR_AB outbound - Unavailable,outbound & ~knr_ab_available_outbound,,,,,,,,,,,,,,coef_unavailable,,,,,,, +util_KNR_AB_outbound_In_vehicle_time,KNR_AB outbound - In-vehicle time,@df.outbound * odt_skims['KR_AB_WK_TOTIVT'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_In_vehicle_time_on_XB,KNR_AB outbound - In-vehicle time on XB,@df.outbound * (coef_ivt_xb_multiplier - 1) * odt_skims['KR_AB_WK_IVTXB'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Short_iwait_time,KNR_AB outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['KR_AB_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Long_iwait_time,KNR_AB outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['KR_AB_WK_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_transfer_wait_time,KNR_AB outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['KR_AB_WK_XWAIT'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_number_of_transfers,KNR_AB outbound - number of transfers,@df.outbound * xfers_wlk_multiplier * (odt_skims['KR_AB_WK_XFERS']).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Drive_time,KNR_AB outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['KR_AB_WK_DTIME'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Walk_egress_time,KNR_AB outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Walk_other_time,KNR_AB outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['KR_AB_WK_WAUX'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Fare_and_operating_cost,KNR_AB outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['KR_AB_WK_FARE'] + costPerMile*odt_skims['KR_AB_WK_DDIST']),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_outbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_AB outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['KR_AB_WK_DDIST'])/ (od_skims['DIST']),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Unavailable,KNR_AB inbound - Unavailable,inbound & ~knr_ab_available_inbound,,,,,,,,,,,,,,coef_unavailable,,,,,,, +util_KNR_AB_inbound_In_vehicle_time,KNR_AB inbound - In-vehicle time,@df.inbound * odt_skims['WK_AB_KR_TOTIVT'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Short_iwait_time,KNR_AB inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_AB_KR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Long_iwait_time,KNR_AB inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_AB_KR_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_transfer_wait_time,KNR_AB inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_AB_KR_XWAIT'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_number_of_transfers,KNR_AB inbound - number of transfers,@df.inbound * xfers_wlk_multiplier * (odt_skims['WK_AB_KR_XFERS']).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Drive_time,KNR_AB inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_AB_KR_DTIME'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Walk_access_time,KNR_AB inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Walk_other_time,KNR_AB inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_AB_KR_WAUX'],,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Fare_and_operating_cost,KNR_AB inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_AB_KR_FARE'] + costPerMile*odt_skims['WK_AB_KR_DDIST']),,,,,,,,,,,,,,coef_ivt,,,,,,, +util_KNR_AB_inbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_AB inbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['WK_AB_KR_DDIST'])/ (od_skims['DIST']),,,,,,,,,,,,,,coef_ivt,,,,,,, +#Drive_to_BM,#Drive to BM,,,,,,,,,,,,,,,,,,,,,, +util_KNR_BM_Unavailable_for_persons_less_than_16,KNR_BM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,coef_unavailable,,,,,, +util_KNR_BM__Destination_zone_densityIndex,KNR_BM - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM__Topology,KNR_BM - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM__Person_is_less_than_10_years_old,KNR_BM - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Unavailable,KNR_BM outbound - Unavailable,outbound & ~knr_bm_available_outbound,,,,,,,,,,,,,,,coef_unavailable,,,,,, +util_KNR_BM_outbound_In_vehicle_time,KNR_BM outbound - In-vehicle time,@df.outbound * odt_skims['KR_BM_WK_TOTIVT'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_XB,KNR_BM - In-vehicle time on XB,@df.outbound * (coef_ivt_xb_multiplier - 1) * odt_skims['KR_BM_WK_IVTXB'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_MR,KNR_BM - In-vehicle time on MR,@df.outbound * (coef_ivt_mr_multiplier - 1) * odt_skims['KR_BM_WK_IVTMR'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_LR,KNR_BM - In-vehicle time on LR,@df.outbound * (coef_ivt_lr_multiplier - 1) * odt_skims['KR_BM_WK_IVTLR'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Short_iwait_time,KNR_BM outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['KR_BM_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Long_iwait_time,KNR_BM outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['KR_BM_WK_IWAIT']-waitThresh).clip(0) ,,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_transfer_wait_time,KNR_BM outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['KR_BM_WK_XWAIT'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_number_of_transfers,KNR_BM outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['KR_BM_WK_XFERS']).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Drive_time,KNR_BM outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['KR_BM_WK_DTIME'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Walk_egress_time,KNR_BM outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Walk_other_time,KNR_BM outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['KR_BM_WK_WAUX'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Fare_and_operating_cost,KNR_BM outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['KR_BM_WK_FARE'] + costPerMile * odt_skims['KR_BM_WK_DDIST']),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_outbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_BM outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['KR_BM_WK_DDIST']) / od_skims['DIST'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Unavailable,KNR_BM inbound - Unavailable,inbound & ~knr_bm_available_inbound,,,,,,,,,,,,,,,coef_unavailable,,,,,, +util_KNR_BM_inbound_In_vehicle_time,KNR_BM inbound - In-vehicle time,@df.inbound * odt_skims['WK_BM_KR_TOTIVT'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_XB,KNR_BM - In-vehicle time on XB,@df.inbound * (coef_ivt_xb_multiplier - 1) * odt_skims['WK_BM_KR_IVTXB'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_MR,KNR_BM - In-vehicle time on MR,@df.inbound * (coef_ivt_mr_multiplier - 1) * odt_skims['WK_BM_KR_IVTMR'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_In_vehicle_time_on_LR,KNR_BM - In-vehicle time on LR,@df.inbound * (coef_ivt_lr_multiplier - 1) * odt_skims['WK_BM_KR_IVTLR'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Short_iwait_time,KNR_BM inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_BM_KR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Long_iwait_time,KNR_BM inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_BM_KR_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_transfer_wait_time,KNR_BM inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_BM_KR_XWAIT'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_number_of_transfers,KNR_BM inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WK_BM_KR_XFERS']).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Drive_time,KNR_BM inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_BM_KR_DTIME'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Walk_access_time,KNR_BM inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Walk_other_time,KNR_BM inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_BM_KR_WAUX'],,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Fare_and_operating_cost,KNR_BM inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_BM_KR_FARE'] + costPerMile * odt_skims['WK_BM_KR_DDIST']),,,,,,,,,,,,,,,coef_ivt,,,,,, +util_KNR_BM_inbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_BM inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WK_BM_KR_DDIST'])/ od_skims['DIST'],,,,,,,,,,,,,,,coef_ivt,,,,,, +#KNR_to_MR,#KNR to MR,,,,,,,,,,,,,,,,,,,,,, +util_KNR_MR_Unavailable_for_persons_less_than_16,KNR_MR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,coef_unavailable,,,,, +util_KNR_MR_Destination_zone_densityIndex,KNR_MR - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_Topology,KNR_MR - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_Person_is_less_than_10_years_old,KNR_MR - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Unavailable,KNR_MR outbound - Unavailable,outbound & ~knr_mr_available_outbound,,,,,,,,,,,,,,,,coef_unavailable,,,,, +util_KNR_MR_outbound_In_vehicle_time,KNR_MR outbound - In-vehicle time,@df.outbound * odt_skims['KR_MR_WK_TOTIVT'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_In_vehicle_time_on_MR,KNR_MR - In-vehicle time on MR,@df.outbound * (coef_ivt_mr_multiplier - 1) * odt_skims['KR_MR_WK_IVTMR'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_In_vehicle_time_on_LR,KNR_MR - In-vehicle time on LR,@df.outbound * (coef_ivt_lr_multiplier - 1) * odt_skims['KR_MR_WK_IVTLR'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Short_iwait_time,KNR_MR outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['KR_MR_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Long_iwait_time,KNR_MR outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['KR_MR_WK_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_transfer_wait_time,KNR_MR outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['KR_MR_WK_XWAIT'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_number_of_transfers,KNR_MR outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['KR_MR_WK_XFERS']).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Drive_time,KNR_MR outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['KR_MR_WK_DTIME'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Walk_egress_ime,KNR_MR outbound - Walk egress ime,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Walk_other_time,KNR_MR outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['KR_MR_WK_WAUX'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Fare_and_operating_cost,KNR_MR outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['KR_MR_WK_FARE'] + costPerMile * odt_skims['KR_MR_WK_DDIST']),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_outbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_MR outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['KR_MR_WK_DDIST']) / od_skims['DIST'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Unavailable,KNR_MR inbound - Unavailable,inbound & ~knr_mr_available_inbound,,,,,,,,,,,,,,,,coef_unavailable,,,,, +util_KNR_MR_inbound_In_vehicle_time,KNR_MR inbound - In-vehicle time,@df.inbound * odt_skims['WK_MR_KR_TOTIVT'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_In_vehicle_time_on_MR,KNR_MR - In-vehicle time on MR,@df.inbound * (coef_ivt_mr_multiplier - 1) * odt_skims['WK_MR_KR_IVTMR'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_In_vehicle_time_on_LR,KNR_MR - In-vehicle time on LR,@df.inbound * (coef_ivt_lr_multiplier - 1) * odt_skims['WK_MR_KR_IVTLR'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Short_iwait_time,KNR_MR inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_MR_KR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Long_iwait_time,KNR_MR inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_MR_KR_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_transfer_wait_time,KNR_MR inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_MR_KR_XWAIT'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_number_of_transfers,KNR_MR inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WK_MR_KR_XFERS']).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Drive_time,KNR_MR inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_MR_KR_DTIME'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Walk_access_time,KNR_MR inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Walk_other_time,KNR_MR inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_MR_KR_WAUX'],,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Fare_and_operating_cost,KNR_MR inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_MR_KR_FARE'] + costPerMile * odt_skims['WK_MR_KR_DDIST']),,,,,,,,,,,,,,,,coef_ivt,,,,, +util_KNR_MR_inbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_MR inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WK_MR_KR_DDIST']) / od_skims['DIST'],,,,,,,,,,,,,,,,coef_ivt,,,,, +#KNR_to_CR,#KNR to CR,,,,,,,,,,,,,,,,,,,,,, +util_KNR_CR_Unavailable_for_persons_less_than_16,KNR_CR - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,coef_unavailable,,,, +util_KNR_CR_Destination_zone_densityIndex,KNR_CR - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_Topology,KNR_CR - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_Person_is_less_than_10_years_old,KNR_CR - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Unavailable,KNR_CR outbound - Unavailable,outbound & ~knr_cr_available_outbound,,,,,,,,,,,,,,,,,coef_unavailable,,,, +util_KNR_CR_outbound_In_vehicle_time,KNR_CR outbound - In-vehicle time,@df.outbound * odt_skims['DR_CR_WK_TOTIVT'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_XB,KNR_CR - In-vehicle time on XB,@df.outbound * (coef_ivt_xb_multiplier - 1) * odt_skims['DR_CR_WK_IVTXB'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_MR,KNR_CR - In-vehicle time on MR,@df.outbound * (coef_ivt_mr_multiplier - 1) * odt_skims['DR_CR_WK_IVTMR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_BR,KNR_CR - In-vehicle time on BR,@df.outbound * (coef_ivt_br_multiplier - 1) * odt_skims['DR_CR_WK_IVTBR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_LR,KNR_CR - In-vehicle time on LR,@df.outbound * (coef_ivt_lr_multiplier - 1) * odt_skims['DR_CR_WK_IVTLR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_CR,KNR_CR - In-vehicle time on CR,@df.outbound * (coef_ivt_cr_multiplier - 1) * odt_skims['DR_CR_WK_IVTCR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Short_iwait_time,KNR_CR outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DR_CR_WK_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Long_iwait_time,KNR_CR outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DR_CR_WK_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_transfer_wait_time,KNR_CR outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DR_CR_WK_XWAIT'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_number_of_transfers,KNR_CR outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DR_CR_WK_XFERS']).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Drive_time,KNR_CR outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DR_CR_WK_DTIME'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Walk_egress_ime,KNR_CR outbound - Walk egress ime,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Walk_other_time,KNR_CR outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DR_CR_WK_WAUX'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Fare_and_operating_cost,KNR_CR outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DR_CR_WK_FARE'] + costPerMile * odt_skims['DR_CR_WK_DDIST']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_outbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_CR outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DR_CR_WK_DDIST']) / od_skims['DIST'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Unavailable,KNR_CR inbound - Unavailable,inbound & ~knr_cr_available_inbound,,,,,,,,,,,,,,,,,coef_unavailable,,,, +util_KNR_CR_inbound_In_vehicle_time,KNR_CR inbound - In-vehicle time,@df.inbound * odt_skims['WK_CR_DR_TOTIVT'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_XB,KNR_CR - In-vehicle time on XB,@df.inbound * (coef_ivt_xb_multiplier - 1) * odt_skims['WK_CR_DR_IVTXB'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_CR,KNR_CR - In-vehicle time on CR,@df.inbound * (coef_ivt_mr_multiplier - 1) * odt_skims['WK_CR_DR_IVTCR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_BR,KNR_CR - In-vehicle time on BR,@df.inbound * (coef_ivt_br_multiplier - 1) * odt_skims['WK_CR_DR_IVTBR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_LR,KNR_CR - In-vehicle time on LR,@df.inbound * (coef_ivt_lr_multiplier - 1) * odt_skims['WK_CR_DR_IVTLR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_In_vehicle_time_on_CR,KNR_CR - In-vehicle time on CR,@df.inbound * (coef_ivt_cr_multiplier - 1) * odt_skims['WK_CR_DR_IVTCR'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Short_iwait_time,KNR_CR inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WK_CR_DR_IWAIT']).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Long_iwait_time,KNR_CR inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WK_CR_DR_IWAIT']-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_transfer_wait_time,KNR_CR inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WK_CR_DR_XWAIT'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_number_of_transfers,KNR_CR inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WK_CR_DR_XFERS']).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Drive_time,KNR_CR inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WK_CR_DR_DTIME'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Walk_access_time,KNR_CR inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Walk_other_time,KNR_CR inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WK_CR_DR_WAUX'],,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Fare_and_operating_cost,KNR_CR inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WK_CR_DR_FARE'] + costPerMile * odt_skims['WK_CR_DR_DDIST']),,,,,,,,,,,,,,,,,coef_ivt,,,, +util_KNR_CR_inbound_Ratio_of_drive_access_distance_to_OD_distance,KNR_CR inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WK_CR_DR_DDIST']) / od_skims['DIST'],,,,,,,,,,,,,,,,,coef_ivt,,,, +#Taxi,#Taxi,,,,,,,,,,,,,,,,,,,,,, +util_Taxi_In_vehicle_time,Taxi - In-vehicle time,@odt_skims['HOV2_TIME'],,,,,,,,,,,,,,,,,,,coef_ivt,, +util_Taxi_Wait_time,Taxi - Wait time,@1.5 * df.origTaxiWaitTime,,,,,,,,,,,,,,,,,,,coef_ivt,, +#Taxi_Tolls,#Taxi - Tolls,@ivt_cost_multiplier * df.ivot * odt_skims['HOV2_VTOLL'],,,,,,,,,,,,,,,,,,,coef_ivt,, +#Taxi_Bridge_toll,#Taxi - Bridge toll,@ivt_cost_multiplier * df.ivot * odt_skims['HOV2_BTOLL'],,,,,,,,,,,,,,,,,,,coef_ivt,, +util_Taxi_Fare,Taxi - Fare,@ivt_cost_multiplier * df.ivot * (Taxi_baseFare + odt_skims['HOV2_DIST'] * Taxi_costPerMile + odt_skims['HOV2_TIME'] * Taxi_costPerMinute)*100,,,,,,,,,,,,,,,,,,,coef_ivt,, +#TNC_Single,#TNC Single,,,,,,,,,,,,,,,,,,,,,, +util_TNC_Single_In_vehicle_time,TNC Single - In-vehicle time,@odt_skims['HOV2_TIME'] ,,,,,,,,,,,,,,,,,,,,coef_ivt, +util_TNC_Single_Wait_time,TNC Single - Wait time,@1.5 * df.origSingleTNCWaitTime,,,,,,,,,,,,,,,,,,,,coef_ivt, +#TNC_Single_Tolls,#TNC Single - Tolls,@ivt_cost_multiplier * df.ivot * odt_skims['HOV2_VTOLL'],,,,,,,,,,,,,,,,,,,,coef_ivt, +#TNC_Single_Bridge_toll,#TNC Single - Bridge toll,@ivt_cost_multiplier * df.ivot * (odt_skims['HOV2_BTOLL'] + dot_skims['HOV2_BTOLL']),,,,,,,,,,,,,,,,,,,,coef_ivt, +util_TNC_Single_Cost,TNC Single - Cost,"@ivt_cost_multiplier * df.ivot * np.maximum(TNC_single_baseFare + odt_skims['HOV2_DIST'] * TNC_single_costPerMile + odt_skims['HOV2_TIME'] * TNC_single_costPerMinute, TNC_single_costMinimum) * 100",,,,,,,,,,,,,,,,,,,,coef_ivt, +#TNC_Shared,#TNC Shared,,,,,,,,,,,,,,,,,,,,,, +util_TNC_Shared_In_vehicle_time,TNC Shared - In-vehicle time,@odt_skims['HOV2_TIME'] * TNC_shared_IVTFactor,,,,,,,,,,,,,,,,,,,,,coef_ivt +util_TNC_Shared_Wait_time,TNC Shared - Wait time,@1.5 * df.origSharedTNCWaitTime,,,,,,,,,,,,,,,,,,,,,coef_ivt +#TNC_Shared_Tolls,#TNC Shared - Tolls,@ivt_cost_multiplier * df.ivot * odt_skims['HOV2_VTOLL'],,,,,,,,,,,,,,,,,,,,,coef_ivt +#TNC_Shared_Bridge_toll,#TNC Shared - Bridge toll,@ivt_cost_multiplier * df.ivot * (odt_skims['HOV2_BTOLL'] + dot_skims['HOV2_BTOLL']),,,,,,,,,,,,,,,,,,,,,coef_ivt +util_TNC_Shared_Cost,TNC Shared - Cost,"@ivt_cost_multiplier * df.ivot * np.maximum(TNC_shared_baseFare + odt_skims['HOV2_DIST'] * TNC_shared_costPerMile + odt_skims['HOV2_TIME']* TNC_shared_costPerMinute, TNC_shared_costMinimum) * 100",,,,,,,,,,,,,,,,,,,,,coef_ivt +#,#,,,,,,,,,,,,,,,,,,,,,, +util_Auto_tour_mode_availability,Auto tour mode availability,tour_mode_is_auto,,,,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,,, +util_SOV_tour_mode_availability,SOV tour mode availability,tour_mode_is_SOV,,coef_unavailable,coef_unavailable,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable +util_sr2_tour_mode_availability,SR2 tour mode availability,tour_mode_is_sr2,,,coef_unavailable,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable +util_sr3p_tour_mode_availability,SR3+ tour mode availability,tour_mode_is_sr3p,,,,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable +util_Walk_tour_mode_availability,Walk tour mode availability,tour_mode_is_walk,coef_unavailable,coef_unavailable,coef_unavailable,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable +util_Bike_tour_mode_availability,Bike tour mode availability,tour_mode_is_bike,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable +util_Walk_to_Transit_tour_mode_availability,Walk to Transit tour mode availability,tour_mode_is_walk_transit,coef_unavailable,,,,coef_unavailable,,,,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,,, +util_Drive_to_Transit_tour_mode_availability,Drive to Transit tour mode availability,tour_mode_is_drive_transit,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,,,,,,,,,coef_unavailable,,, +util_School_bus_tour_mode_availability,School bus tour mode availability,tour_mode_is_school_bus,coef_unavailable,,,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,,coef_unavailable,coef_unavailable,coef_unavailable +util_Ride_Hail_tour_mode_availability,Ride Hail tour mode availability,tour_mode_is_ride_hail,coef_unavailable,,,,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,coef_unavailable,,, +#indiv_tour_ASCs,#indiv tour ASCs,,,,,,,,,,,,,,,,,,,,,, +util_Drive_Alone_tour_mode_ASC_shared_ride_2,Drive Alone tour mode ASC -- shared ride 2,@(df.is_indiv & df.i_tour_mode.isin(I_SOV_MODES)),,sov_ASC_sr2,,,,,,,,,,,,,,,,,,, +util_Drive_Alone_tour_mode_ASC_shared_ride_3+,Drive Alone tour mode ASC -- shared ride 3+,@(df.is_indiv & df.i_tour_mode.isin(I_SOV_MODES)),,,sov_ASC_sr3p,,,,,,,,,,,,,,,,,, +util_Drive_Alone_tour_mode_ASC_walk,Drive Alone tour mode ASC -- walk,@(df.is_indiv & df.i_tour_mode.isin(I_SOV_MODES)),,,,sov_ASC_walk,,,,,,,,,,,,,,,,, +util_Drive_Alone_tour_mode_ASC_ride_hail,Drive Alone tour mode ASC -- ride hail,@(df.is_indiv & df.i_tour_mode.isin(I_SOV_MODES)),,,,,,,,,,,,,,,,,,,sov_ASC_rh,sov_ASC_rh,sov_ASC_rh +util_Shared_Ride_2_tour_mode_ASC_drive_alone,Shared Ride 2 tour mode ASC -- drive alone,@(df.is_indiv & df.i_tour_mode.isin(I_SR2_MODES)),sr2_ASC_sov,,,,,,,,,,,,,,,,,,,, +util_Shared_Ride_2_tour_mode_ASC_walk,Shared Ride 2 tour mode ASC -- walk,@(df.is_indiv & df.i_tour_mode.isin(I_SR2_MODES)),,,,sr2_ASC_walk,,,,,,,,,,,,,,,,, +util_Shared_Ride_2_tour_mode_ASC_ride_hail,Shared Ride 2 tour mode ASC -- ride hail,@(df.is_indiv & df.i_tour_mode.isin(I_SR2_MODES)),,,,,,,,,,,,,,,,,,,sr2_ASC_rh,sr2_ASC_rh,sr2_ASC_rh +util_Shared_Ride_3+_tour_mode_ASC_drive_alone,Shared Ride 3+ tour mode ASC -- drive alone,@(df.is_indiv & df.i_tour_mode.isin(I_SR3P_MODES)),sr3p_ASC_sr2,,,,,,,,,,,,,,,,,,,, +util_Shared_Ride_3+_tour_mode_ASC_shared_ride_2,Shared Ride 3+ tour mode ASC -- shared ride 2,@(df.is_indiv & df.i_tour_mode.isin(I_SR3P_MODES)),,sr3p_ASC_sr2,,,,,,,,,,,,,,,,,,, +util_Shared_Ride_3+_tour_mode_ASC_walk,Shared Ride 3+ tour mode ASC -- walk,@(df.is_indiv & df.i_tour_mode.isin(I_SR3P_MODES)),,,,sr3p_ASC_walk,,,,,,,,,,,,,,,,, +util_Shared_Ride_3+_tour_mode_ASC_ride_hail,Shared Ride 3+ tour mode ASC -- ride hail,@(df.is_indiv & df.i_tour_mode.isin(I_SR3P_MODES)),,,,,,,,,,,,,,,,,,,sr3p_ASC_rh,sr3p_ASC_rh,sr3p_ASC_rh +util_Walk_tour_mode_ASC_ride_hail,Walk tour mode ASC -- ride hail,@df.is_indiv & (df.i_tour_mode == I_WALK_MODE),,,,,,,,,,,,,,,,,,,walk_ASC_rh,walk_ASC_rh,walk_ASC_rh +util_Bike_tour_mode_ASC_walk,Bike tour mode ASC -- walk,@df.is_indiv & (df.i_tour_mode == I_BIKE_MODE),,,,bike_ASC_walk,,,,,,,,,,,,,,,,, +util_Bike_tour_mode_ASC_ride_hail,Bike tour mode ASC -- ride hail,@df.is_indiv & (df.i_tour_mode == I_BIKE_MODE),,,,,,,,,,,,,,,,,,,bike_ASC_rh,bike_ASC_rh,bike_ASC_rh +util_Walk_transit_tour_mode_ASC_shared_ride_2,Walk-transit tour mode ASC -- shared ride 2,@(df.is_indiv & df.i_tour_mode.isin(I_WALK_TRANSIT_MODES)),,walk_transit_ASC_sr2,,,,,,,,,,,,,,,,,,, +util_Walk_transit_tour_mode_ASC_shared_ride_3+,Walk-transit tour mode ASC -- shared ride 3+,@(df.is_indiv & df.i_tour_mode.isin(I_WALK_TRANSIT_MODES)),,,walk_transit_ASC_sr3p,,,,,,,,,,,,,,,,,, +util_Walk_transit_tour_mode_ASC_walk,Walk-transit tour mode ASC -- walk,@(df.is_indiv & df.i_tour_mode.isin(I_WALK_TRANSIT_MODES)),,,,walk_transit_ASC_walk,,,,,,,,,,,,,,,,, +util_Walk_transit_tour_mode_ASC_ride_hail,Walk-transit tour mode ASC -- ride hail,@(df.is_indiv & df.tour_mode_is_walk_transit),,,,,,,,,,,,,,,,,,,walk_transit_ASC_rh,walk_transit_ASC_rh,walk_transit_ASC_rh +util_Drive_to_Transit_tour_mode_ASC_ride_hail,Drive to Transit tour mode ASC -- ride hail,@(df.is_indiv & df.tour_mode_is_drive_transit),,,,,,,,,,,,,,,,,,,drive_transit_ASC_rh,drive_transit_ASC_rh,drive_transit_ASC_rh +util_Ride_Hail_tour_mode_ASC_ride_hail,Ride Hail tour mode ASC -- ride hail,@(df.is_indiv & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,ride_hail_ASC_taxi,, +util_Ride_Hail_tour_mode_ASC_ride_hail,Ride Hail tour mode ASC -- ride hail,@(df.is_indiv & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,ride_hail_ASC_tnc_single, +util_Ride_Hail_tour_mode_ASC_ride_hail,Ride Hail tour mode ASC -- ride hail,@(df.is_indiv & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,,ride_hail_ASC_tnc_shared +util_joint_auto_tour_mode_ASC_shared_ride_2,joint - auto tour mode ASC -- shared ride 2,@(df.is_joint & df.i_tour_mode.isin(I_AUTO_MODES)),,joint_auto_ASC_sr2,,,,,,,,,,,,,,,,,,, +util_joint_auto_tour_mode_ASC_shared_ride_3+,joint - auto tour mode ASC -- shared ride 3+,@(df.is_joint & df.i_tour_mode.isin(I_AUTO_MODES)),,,joint_auto_ASC_sr3p,,,,,,,,,,,,,,,,,, +util_joint_auto_tour_mode_ASC_walk,joint - auto tour mode ASC -- walk,@(df.is_joint & df.i_tour_mode.isin(I_AUTO_MODES)),,,,joint_auto_ASC_walk,,,,,,,,,,,,,,,,, +util_joint_auto_tour_mode_ASC_ride_hail,joint - auto tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_AUTO_MODES)),,,,,,,,,,,,,,,,,,,joint_auto_ASC_rh,joint_auto_ASC_rh,joint_auto_ASC_rh +util_joint_Bike_tour_mode_ASC_walk,joint - Bike tour mode ASC -- walk,@df.is_joint & (df.i_tour_mode == I_BIKE_MODE),,,,joint_bike_ASC_walk,,,,,,,,,,,,,,,,, +util_joint_Bike_tour_mode_ASC_ride_hail,joint - Bike tour mode ASC -- ride hail,@df.is_joint & (df.i_tour_mode == I_BIKE_MODE),,,,,,,,,,,,,,,,,,,joint_bike_ASC_rh,joint_bike_ASC_rh,joint_bike_ASC_rh +util_joint_Walk_transit_tour_mode_ASC_shared_ride_2,joint - Walk-transit tour mode ASC -- shared ride 2,@(df.is_joint & df.i_tour_mode.isin(I_WALK_TRANSIT_MODES)),,joint_walk_transit_ASC_sr2,,,,,,,,,,,,,,,,,,, +util_joint_Walk_transit_tour_mode_ASC_shared_ride_3+,joint - Walk-transit tour mode ASC -- shared ride 3+,@(df.is_joint & df.i_tour_mode.isin(I_WALK_TRANSIT_MODES)),,,joint_walk_transit_ASC_sr3p,,,,,,,,,,,,,,,,,, +util_joint_Walk_transit_tour_mode_ASC_walk,joint - Walk-transit tour mode ASC -- walk,@(df.is_joint & df.i_tour_mode.isin(I_WALK_TRANSIT_MODES)),,,,joint_walk_transit_ASC_walk,,,,,,,,,,,,,,,,, +util_joint_Walk_to_Transit_tour_mode_ASC_ride_hail,joint - Walk to Transit tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_WALK_TRANSIT_MODES)),,,,,,,,,,,,,,,,,,,joint_walk_transit_ASC_rh,joint_walk_transit_ASC_rh,joint_walk_transit_ASC_rh +util_joint_Drive_to_Transit_tour_mode_ASC_ride_hail,joint - Drive to Transit tour mode ASC -- ride hail,@(df.is_joint & df.tour_mode_is_drive_transit),,,,,,,,,,,,,,,,,,,joint_drive_transit_ASC_rh,joint_drive_transit_ASC_rh,joint_drive_transit_ASC_rh +util_joint_Ride_Hail_tour_mode_ASC_ride_hail,joint - Ride Hail tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,joint_ride_hail_ASC_taxi,, +util_joint_Ride_Hail_tour_mode_ASC_ride_hail,joint - Ride Hail tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,joint_ride_hail_ASC_tnc_single, +util_joint_Ride_Hail_tour_mode_ASC_ride_hail,joint - Ride Hail tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,,joint_ride_hail_ASC_tnc_shared +#,#,,,,,,,,,,,,,,,,,,,,,, +util_Walk_not_available_for_long_distances,Walk not available for long distances,@df.tour_mode_is_walk & (od_skims['DISTWALK'] > 3),,,,coef_unavailable,,,,,,,,,,,,,,,,, +util_Bike_not_available_for_long_distances,Bike not available for long distances,@df.tour_mode_is_walk & (od_skims['DISTBIKE'] > 8),,,,,coef_unavailable,,,,,,,,,,,,,,,, +#School_Bus,#School Bus,,,,,,,,,,,,,,,,,,,,,, +util_School_Bus_Unavailable_if_primary_purpose_NOT_school,School Bus Unavailable if primary purpose NOT school,~is_school,,,,,,,,,,,,,,,,,,coef_unavailable,,, +util_School_Bus_Unavailable_Tour_Mode_SOV,School Bus Unavailable - Tour Mode = SOV,tour_mode_is_SOV,,,,,,,,,,,,,,,,,,coef_unavailable,,, +util_School_Bus_Unavailable_Tour_Mode_Transit,School Bus Unavailable - Tour Mode = Transit,tour_mode_is_drive_transit,,,,,,,,,,,,,,,,,,coef_unavailable,,, +util_School_Bus_In_vehicle_time_(20_miles_per_hour),School Bus - In-vehicle time (20 miles per hour),@odt_skims['HOV3_DIST']*3,,,,,,,,,,,,,,,,,,1,,, +util_School_Bus_Walk_Time,School Bus - Walk Time,@coef_wacc_multiplier*10,,,,,,,,,,,,,,,,,,1,,, +util_School_Bus_Wait_Time,School Bus - Wait Time,@coef_short_iwait_multiplier*10,,,,,,,,,,,,,,,,,,1,,, +util_School_Bus_tour_mode_ASC_shared_ride_2,School Bus tour mode ASC -- shared ride 2,@df.i_tour_mode.isin(I_SCHOOLBUS_MODE),,schoolbus_ASC_sr2,,,,,,,,,,,,,,,,,,, +util_School_Bus_tour_mode_ASC_shared_ride_3+,School Bus tour mode ASC -- shared ride 3+,@df.i_tour_mode.isin(I_SCHOOLBUS_MODE),,,schoolbus_ASC_sr3p,,,,,,,,,,,,,,,,,, +util_School_Bus_tour_mode_ASC_walk,School Bus tour mode ASC -- walk,@df.i_tour_mode.isin(I_SCHOOLBUS_MODE),,,,schoolbus_ASC_walk,,,,,,,,,,,,,,,,, +util_School_Bus_tour_mode_ASC_ride_hail,School Bus tour mode ASC -- ride hail,@df.i_tour_mode.isin(I_SCHOOLBUS_MODE),,,,,,,,,,,,,,,,,,,schoolbus_ASC_rh,schoolbus_ASC_rh,schoolbus_ASC_rh +util_Origin_density_index,Origin density index,@(origin_density_applied*df.origin_density_index).clip(origin_density_index_max) if origin_density_applied else 0,,,,,,,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,,,,,coef_ivt,coef_ivt +util_TNC_shared_adjustment,TNC shared adjustment,@adjust_tnc_shared,,,,,,,,,,,,,,,,,,,,,coef_ivt diff --git a/activitysim/examples/prototype_mwcog/configs/trip_mode_choice.yaml b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice.yaml new file mode 100644 index 000000000..79a06b74d --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice.yaml @@ -0,0 +1,148 @@ +# trip_mode_choice.yaml + +SPEC: trip_mode_choice.csv +COEFFICIENTS: trip_mode_choice_coefficients.csv +COEFFICIENT_TEMPLATE: trip_mode_choice_coefficients_template.csv + +LOGIT_TYPE: NL + +NESTS: + name: root + coefficient: 1.00 + alternatives: + - name: AUTO + coefficient: 0.72 + alternatives: + - DRIVEALONE + - SHARED2 + - SHARED3 + - name: NONMOTORIZED + coefficient: 0.72 + alternatives: + - WALK + - BIKE + - name: TRANSIT + coefficient: 0.72 + alternatives: + - name: WALKACCESS + coefficient: 0.5 + alternatives: + - WALK_AB + - WALK_BM + - WALK_MR + - WALK_CR + - name: PNRACCESS + coefficient: 0.5 + alternatives: + - PNR_AB + - PNR_BM + - PNR_MR + - PNR_CR + - name: KNRACCESS + coefficient: 0.5 + alternatives: + - KNR_AB + - KNR_BM + - KNR_MR + - KNR_CR + - name: SCHOOL_BUS + coefficient: 0.72 + alternatives: + - SCHOOLBUS + - name: RIDEHAIL + coefficient: 0.36 + alternatives: + - TAXI + - TNC_SINGLE + - TNC_SHARED + +CONSTANTS: + orig_col_name: origin + dest_col_name: destination + walkThresh: 1.00 + walktimelong_multiplier: 5 + biketimelong_multiplier: 5 + xfers_wlk_multiplier: 5 + xfers_drv_multiplier: 15 + density_index_multiplier: -5 + I_MODE_MAP: + DRIVEALONE: 1 + SHARED2: 2 + SHARED3: 3 + WALK: 4 + BIKE: 5 + WALK_AB: 6 + WALK_BM: 7 + WALK_MR: 8 + WALK_CR: 9 + PNR_AB: 10 + PNR_BM: 11 + PNR_MR: 12 + PNR_CR: 13 + KNR_AB: 14 + KNR_BM: 15 + KNR_MR: 16 + KNR_CR: 17 + SCHOOLBUS: 18 + TAXI: 19 + TNC_SINGLE: 20 + TNC_SHARED: 21 + I_SOV_MODES: [1] + I_SR2_MODES: [2] + I_SR3P_MODES: [3] + I_AUTO_MODES: [1, 2, 3] + I_WALK_MODE: 4 + I_BIKE_MODE: 5 + I_WALK_TRANSIT_MODES: [6,7,8,9] + I_DRIVE_TRANSIT_MODES: [10,11,12,13,14,15,16,17] + I_PNR_TRANSIT_MODES: [10,11,12,13] + I_KNR_TRANSIT_MODES: [14,15,16,17] + I_AB_MODES: [6,10,14] + I_BM_MODES: [7,11,15] + I_MR_MODES: [8,12,16] + I_CR_MODES: [9,13,17] + I_SCHOOLBUS_MODE: [18] + I_RIDE_HAIL_MODES: [19, 20, 21] + Taxi_waitTime_mean: + 1: 5.5 + 2: 9.5 + 3: 13.3 + 4: 17.3 + 5: 26.5 + Taxi_waitTime_sd: + 1: 0 + 2: 0 + 3: 0 + 4: 0 + 5: 0 + + +# so far, we can use the same spec as for non-joint tours +preprocessor: + SPEC: trip_mode_choice_annotate_trips_preprocessor + DF: df + TABLES: + - land_use + - tours + +# - SPEC: trip_mode_choice_annotate_trips_preprocessor2 +# DF: df +# TABLES: +# - land_use + +# to reduce memory needs filter chooser table to these fields +TOURS_MERGED_CHOOSER_COLUMNS: + - hhsize + - age + - auto_ownership + - number_of_participants + - tour_category + - parent_tour_id + - tour_mode + - duration + - value_of_time + - tour_type + - free_parking_at_work + + +MODE_CHOICE_LOGSUM_COLUMN_NAME: mode_choice_logsum diff --git a/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_annotate_trips_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_annotate_trips_preprocessor.csv new file mode 100644 index 000000000..33d0c0de9 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_annotate_trips_preprocessor.csv @@ -0,0 +1,101 @@ +Description,Target,Expression, +,is_joint,(df.number_of_participants > 1), +,is_indiv,(df.number_of_participants == 1), +,is_atwork_subtour,~df.parent_tour_id.isnull(), +,is_school,"(df.primary_purpose=='school') & (df.purpose.isin(['school', 'Home']))", +,c_cost,(0.60 * coef_ivt) / df.value_of_time, +,ivot,1.0 / df.value_of_time, +#,,, +#atwork subtours,,, +#FIXME tripModeChoice uec wrongly conflates these with tour_mode_is_bike?,,, +,parent_tour_mode,"reindex(tours.tour_mode, df.parent_tour_id).fillna('')", +,work_tour_is_SOV,parent_tour_mode.isin(['DRIVEALONE']), +,work_tour_is_bike,parent_tour_mode=='BIKE', +#,,, +,i_tour_mode,df.tour_mode.map(I_MODE_MAP), +,tour_mode_is_SOV,i_tour_mode.isin(I_SOV_MODES), +,tour_mode_is_sr2,i_tour_mode.isin(I_SR2_MODES), +,tour_mode_is_sr3p,i_tour_mode.isin(I_SR3P_MODES), +,tour_mode_is_auto,i_tour_mode.isin(I_AUTO_MODES), +,tour_mode_is_walk,i_tour_mode.isin([I_WALK_MODE]), +,tour_mode_is_bike,i_tour_mode.isin([I_BIKE_MODE]), +,tour_mode_is_walk_transit,i_tour_mode.isin(I_WALK_TRANSIT_MODES), +,tour_mode_is_drive_transit,i_tour_mode.isin(I_DRIVE_TRANSIT_MODES), +,tour_mode_not_drive_transit,~tour_mode_is_drive_transit, +,tour_mode_is_pnr_transit,i_tour_mode.isin(I_PNR_TRANSIT_MODES), +,tour_mode_is_knr_transit,i_tour_mode.isin(I_KNR_TRANSIT_MODES), +,tour_mode_is_ab,i_tour_mode.isin(I_AB_MODES), +,tour_mode_is_bm,i_tour_mode.isin(I_BM_MODES), +,tour_mode_is_mr,i_tour_mode.isin(I_MR_MODES), +,tour_mode_is_cr,i_tour_mode.isin(I_CR_MODES), +,tour_mode_is_school_bus,i_tour_mode.isin(I_SCHOOLBUS_MODE), +,tour_mode_is_ride_hail,i_tour_mode.isin(I_RIDE_HAIL_MODES), +#,,, +,inbound,~df.outbound, +,first_trip,df.trip_num == 1, +,last_trip,df.trip_num == df.trip_count, +origin terminal time not counted at home,_origin_terminal_time,"np.where(df.outbound & first_trip, 0, reindex(land_use.TERMINAL, df[ORIGIN]))", +dest terminal time not counted at home,_dest_terminal_time,"np.where(inbound & last_trip, 0, reindex(land_use.TERMINAL, df[DESTINATION]))", +,total_terminal_time,_origin_terminal_time + _dest_terminal_time, +#,,, +,free_parking_available,(df.tour_type == 'work') & df.free_parking_at_work, +,dest_hourly_peak_parking_cost,"reindex(land_use.PRKCST, df[DESTINATION])", +,origin_hourly_peak_parking_cost,"reindex(land_use.PRKCST, df[ORIGIN])", +,origin_duration,"np.where(first_trip, np.where(inbound,df.duration/2 * ~free_parking_available,0), 1)", +,dest_duration,"np.where(last_trip, np.where(inbound, df.duration/2 * ~free_parking_available, 0), 1)", +,origin_parking_cost,origin_duration*origin_hourly_peak_parking_cost, +,dest_parking_cost,dest_duration*dest_hourly_peak_parking_cost, +,total_parking_cost,(origin_parking_cost + dest_parking_cost) / 2.0, +,trip_topology,"np.where(df.outbound, reindex(land_use.TOPOLOGY, df[DESTINATION]), reindex(land_use.TOPOLOGY, df[ORIGIN]))", +,density_index,"np.where(df.outbound, reindex(land_use.density_index, df[DESTINATION]), reindex(land_use.density_index, df[ORIGIN]))", +,origin_density_index,"np.where(df.outbound, reindex(land_use.density_index, df[ORIGIN]), reindex(land_use.density_index, df[DESTINATION]))", +# FIXME no transit subzones so all zones short walk to transit,,, +,_walk_transit_origin,True, +,_walk_transit_destination,True, +,walk_transit_available,_walk_transit_origin & _walk_transit_destination & (tour_mode_not_drive_transit), +,pnr_transit_available,tour_mode_is_pnr_transit, +,knr_transit_available,tour_mode_is_knr_transit, +,origin_walk_time,shortWalk*60/walkSpeed, +,destination_walk_time,shortWalk*60/walkSpeed, +# RIDEHAIL,,, +,origin_density_measure,"(reindex(land_use.TOTPOP, df[orig_col_name]) + reindex(land_use.TOTEMP, df[orig_col_name])) / (reindex(land_use.LANDAREA*640, df[orig_col_name]) / 640)", +,origin_density,"pd.cut(origin_density_measure, bins=[-np.inf, 500, 2000, 5000, 15000, np.inf], labels=[5, 4, 3, 2, 1]).astype(int)", +,origin_zone_taxi_wait_time_mean,"origin_density.map({k: v for k, v in Taxi_waitTime_mean.items()})", +,origin_zone_taxi_wait_time_sd,"origin_density.map({k: v for k, v in Taxi_waitTime_sd.items()})", +# ,, Note that the mean and standard deviation are not the values for the distribution itself, but of the underlying normal distribution it is derived from +,origTaxiWaitTime,"rng.lognormal_for_df(df, mu=origin_zone_taxi_wait_time_mean, sigma=origin_zone_taxi_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)", +,origin_zone_singleTNC_wait_time_mean,"origin_density.map({k: v for k, v in TNC_single_waitTime_mean.items()})", +,origin_zone_singleTNC_wait_time_sd,"origin_density.map({k: v for k, v in TNC_single_waitTime_sd.items()})", +,origSingleTNCWaitTime,"rng.lognormal_for_df(df, mu=origin_zone_singleTNC_wait_time_mean, sigma=origin_zone_singleTNC_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)", +,origin_zone_sharedTNC_wait_time_mean,"origin_density.map({k: v for k, v in TNC_shared_waitTime_mean.items()})", +,origin_zone_sharedTNC_wait_time_sd,"origin_density.map({k: v for k, v in TNC_shared_waitTime_sd.items()})", +,origSharedTNCWaitTime,"rng.lognormal_for_df(df, mu=origin_zone_sharedTNC_wait_time_mean, sigma=origin_zone_sharedTNC_wait_time_sd, broadcast=True, scale=True).clip(min_waitTime, max_waitTime)", +#,,, +,sov_available,(odt_skims['SOV_TIME']>0) & tour_mode_not_drive_transit, +,hov2_available,(odt_skims['HOV2_TIME']>0) & tour_mode_not_drive_transit, +,hov3_available,(odt_skims['HOV3_TIME']>0) & tour_mode_not_drive_transit, +,walk_ab_available,walk_transit_available & (odt_skims['WK_AB_WK_IVTLB']>0) & tour_mode_is_ab, +,walk_bm_available,walk_transit_available & (odt_skims['WK_BM_WK_IVTMR']>0) & tour_mode_is_bm, +,walk_mr_available,walk_transit_available & (odt_skims['WK_MR_WK_IVTMR']>0) & tour_mode_is_mr, +,walk_cr_available,walk_transit_available & (odt_skims['WK_CR_WK_IVTCR']>0) & tour_mode_is_cr, +,pnr_ab_available_outbound,pnr_transit_available & df.outbound & (odt_skims['DR_AB_WK_IVTLB']>0) & tour_mode_is_ab, +,pnr_ab_available_inbound,pnr_transit_available & ~df.outbound & (odt_skims['WK_AB_DR_IVTLB']>0) & tour_mode_is_ab, +,pnr_bm_available_outbound,pnr_transit_available & df.outbound & (odt_skims['DR_BM_WK_IVTMR']>0) & tour_mode_is_bm, +,pnr_bm_available_inbound,pnr_transit_available & ~df.outbound & (odt_skims['WK_BM_DR_IVTMR']>0) & tour_mode_is_bm, +,pnr_mr_available_outbound,pnr_transit_available & df.outbound & (odt_skims['DR_MR_WK_IVTMR']>0) & tour_mode_is_mr, +,pnr_mr_available_inbound,pnr_transit_available & ~df.outbound & (odt_skims['WK_MR_DR_IVTMR']>0) & tour_mode_is_mr, +,pnr_cr_available_outbound,pnr_transit_available & df.outbound & (odt_skims['DR_CR_WK_IVTCR']>0) & tour_mode_is_cr, +,pnr_cr_available_inbound,pnr_transit_available & ~df.outbound & (odt_skims['WK_CR_DR_IVTCR']>0) & tour_mode_is_cr, +,knr_ab_available_outbound,knr_transit_available & df.outbound & (odt_skims['KR_AB_WK_IVTLB']>0) & tour_mode_is_ab, +,knr_ab_available_inbound,knr_transit_available & ~df.outbound & (odt_skims['WK_AB_KR_IVTLB']>0) & tour_mode_is_ab, +,knr_bm_available_outbound,knr_transit_available & df.outbound & (odt_skims['KR_BM_WK_IVTMR']>0) & tour_mode_is_bm, +,knr_bm_available_inbound,knr_transit_available & ~df.outbound & (odt_skims['WK_BM_KR_IVTMR']>0) & tour_mode_is_bm, +,knr_mr_available_outbound,knr_transit_available & df.outbound & (odt_skims['KR_MR_WK_IVTMR']>0) & tour_mode_is_mr, +,knr_mr_available_inbound,knr_transit_available & ~df.outbound & (odt_skims['WK_MR_KR_IVTMR']>0) & tour_mode_is_mr, +,knr_cr_available_outbound,knr_transit_available & df.outbound & (odt_skims['KR_CR_WK_IVTCR']>0) & tour_mode_is_cr, +,knr_cr_available_inbound,knr_transit_available & ~df.outbound & (odt_skims['WK_CR_KR_IVTCR']>0) & tour_mode_is_cr, +#,od_dist_walk,od_skims['DISTWALK'], +#,do_dist_walk,od_skims.reverse('DISTWALK'), +#,max_dist_walk,od_skims.max('DISTWALK'), +#,dist_bike,od_skims['DISTBIKE'], +#,dist_only,od_skims['DIST'], diff --git a/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients.csv b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients.csv new file mode 100644 index 000000000..911b55be3 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients.csv @@ -0,0 +1,557 @@ +coefficient_name,value,constrain +coef_unavailable,-999.0,T +coef_one,1.0,T +coef_nest_root,1.0,T +coef_nest_AUTO,0.72,T +coef_nest_NONMOTORIZED,0.72,T +coef_nest_TRANSIT,0.72,T +coef_nest_WALKACCESS,0.5,T +coef_nest_PNRACCESS,0.5,T +coef_nest_KNRACCESS,0.5,T +coef_nest_RIDEHAIL,0.36,T +#,, +coef_ivt_othmaint_social,-0.02,F +coef_ivt_work,-0.02,F +coef_ivt_univ_school,-0.03,F +coef_ivt_escort_shopping_eatout_othdiscr_atwork,-0.03,F +#,, +coef_age1619_da,0.0,F +coef_age010_trn,0.0,F +coef_age16p_sr,0.0,F +coef_hhsize1_sr,-0.73,F +coef_hhsize2_sr,0.0,F +coef_walktimeshort_atwork,1.35,F +coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,2.0,T +coef_biketimeshort_atwork,2.7,F +coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,4.0,T +coef_dtim_atwork,1.35,F +coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,2.0,T +coef_ivt_xb_multiplier,1.0,T +coef_ivt_mr_multiplier,0.9,T +coef_ivt_br_multiplier,0.9,T +coef_ivt_lr_multiplier,0.8,T +coef_ivt_cr_multiplier,0.7,T +coef_long_iwait_atwork,0.67,F +coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,1.0,T +coef_short_iwait_atwork,1.35,F +coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,2.0,T +coef_wacc_atwork,1.35,F +coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,2.0,T +coef_waux_atwork,1.35,F +coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,2.0,T +coef_wegr_atwork,1.35,F +coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,2.0,T +coef_xwait_atwork,1.35,F +coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,2.0,T +#,, +coef_bike_ASC_walk_atwork,-5.05, +coef_bike_ASC_walk_eatout,-3.7, +coef_bike_ASC_walk_escort,-15.52, +coef_bike_ASC_walk_othdiscr,-2.36, +coef_bike_ASC_walk_othmaint,-2.57, +coef_bike_ASC_walk_school,-3.24, +coef_bike_ASC_walk_shopping,-3.02, +coef_bike_ASC_walk_social,-14.24, +coef_bike_ASC_walk_univ,-2.49, +coef_bike_ASC_walk_work,-2.83, +coef_bike_ASC_rh_atwork,-7.0, +coef_bike_ASC_rh_eatout,-7.0, +coef_bike_ASC_rh_escort,-7.0, +coef_bike_ASC_rh_othdiscr,-7.0, +coef_bike_ASC_rh_othmaint,-7.0, +coef_bike_ASC_rh_parking,-7.0, +coef_bike_ASC_rh_school,-7.0, +coef_bike_ASC_rh_shopping,-7.0, +coef_bike_ASC_rh_social,-7.0, +coef_bike_ASC_rh_univ,-7.0, +coef_bike_ASC_rh_work,-7.0, +coef_joint_bike_ASC_walk_atwork,0.0, +coef_joint_bike_ASC_walk_eatout,-3.0, +coef_joint_bike_ASC_walk_escort,-3.0, +coef_joint_bike_ASC_walk_othdiscr,-3.0, +coef_joint_bike_ASC_walk_othmaint,-3.0, +coef_joint_bike_ASC_walk_school,0.0, +coef_joint_bike_ASC_walk_shopping,-3.0, +coef_joint_bike_ASC_walk_social,-3.0, +coef_joint_bike_ASC_walk_univ,0.0, +coef_joint_bike_ASC_walk_work,0.0, +coef_joint_bike_ASC_rh_atwork,0.0, +coef_joint_bike_ASC_rh_eatout,-12.31, +coef_joint_bike_ASC_rh_escort,0.0, +coef_joint_bike_ASC_rh_othdiscr,-12.31, +coef_joint_bike_ASC_rh_othmaint,-12.31, +coef_joint_bike_ASC_rh_parking,0.0, +coef_joint_bike_ASC_rh_school,0.0, +coef_joint_bike_ASC_rh_shopping,-12.31, +coef_joint_bike_ASC_rh_social,-12.31, +coef_joint_bike_ASC_rh_univ,0.0, +coef_joint_bike_ASC_rh_work,0.0, +coef_joint_auto_ASC_sr2_atwork,0.0, +coef_joint_auto_ASC_sr2_eatout,-0.0634, +coef_joint_auto_ASC_sr2_escort,0.0, +coef_joint_auto_ASC_sr2_othdiscr,-0.0634, +coef_joint_auto_ASC_sr2_othmaint,-0.0634, +coef_joint_auto_ASC_sr2_school,0.0, +coef_joint_auto_ASC_sr2_shopping,0.5875, +coef_joint_auto_ASC_sr2_social,-0.0634, +coef_joint_auto_ASC_sr2_univ,0.0, +coef_joint_auto_ASC_sr2_work,0.0, +coef_joint_auto_ASC_sr3p_atwork,0.0, +coef_joint_auto_ASC_sr3p_eatout,-0.1625, +coef_joint_auto_ASC_sr3p_escort,0.0, +coef_joint_auto_ASC_sr3p_othdiscr,-0.1625, +coef_joint_auto_ASC_sr3p_othmaint,-0.1625, +coef_joint_auto_ASC_sr3p_school,0.0, +coef_joint_auto_ASC_sr3p_shopping,-19.0454, +coef_joint_auto_ASC_sr3p_social,-0.1625, +coef_joint_auto_ASC_sr3p_univ,0.0, +coef_joint_auto_ASC_sr3p_work,0.0, +coef_joint_auto_ASC_walk_atwork,0.0, +coef_joint_auto_ASC_walk_eatout,-0.7144, +coef_joint_auto_ASC_walk_escort,0.0, +coef_joint_auto_ASC_walk_othdiscr,-0.7144, +coef_joint_auto_ASC_walk_othmaint,-0.7144, +coef_joint_auto_ASC_walk_school,0.0, +coef_joint_auto_ASC_walk_shopping,-23.4688, +coef_joint_auto_ASC_walk_social,-0.7144, +coef_joint_auto_ASC_walk_univ,0.0, +coef_joint_auto_ASC_walk_work,0.0, +coef_joint_auto_ASC_rh_atwork,0.0, +coef_joint_auto_ASC_rh_eatout,-7.0, +coef_joint_auto_ASC_rh_escort,0.0, +coef_joint_auto_ASC_rh_othdiscr,-7.0, +coef_joint_auto_ASC_rh_othmaint,-7.0, +coef_joint_auto_ASC_rh_school,0.0, +coef_joint_auto_ASC_rh_shopping,-7.0, +coef_joint_auto_ASC_rh_social,-7.0, +coef_joint_auto_ASC_rh_univ,0.0, +coef_joint_auto_ASC_rh_work,0.0, +coef_joint_walk_transit_ASC_sr2_atwork,0.07382298328759998, +coef_joint_walk_transit_ASC_sr2_eatout,-2.31, +coef_joint_walk_transit_ASC_sr2_escort,-2.2361770167123995, +coef_joint_walk_transit_ASC_sr2_othdiscr,-2.2361770167123995, +coef_joint_walk_transit_ASC_sr2_othmaint,-2.2361770167123995, +coef_joint_walk_transit_ASC_sr2_school,0.07382298328759998, +coef_joint_walk_transit_ASC_sr2_shopping,-2.2361770167123995, +coef_joint_walk_transit_ASC_sr2_social,-2.31, +coef_joint_walk_transit_ASC_sr2_univ,0.07382298328759998, +coef_joint_walk_transit_ASC_sr2_work,0.07382298328759998, +coef_joint_walk_transit_ASC_sr3p_atwork,-10.0, +coef_joint_walk_transit_ASC_sr3p_eatout,-3.88, +coef_joint_walk_transit_ASC_sr3p_escort,-13.88, +coef_joint_walk_transit_ASC_sr3p_othdiscr,-13.88, +coef_joint_walk_transit_ASC_sr3p_othmaint,-13.88, +coef_joint_walk_transit_ASC_sr3p_school,-10.0, +coef_joint_walk_transit_ASC_sr3p_shopping,-13.88, +coef_joint_walk_transit_ASC_sr3p_social,-3.88, +coef_joint_walk_transit_ASC_sr3p_univ,-10.0, +coef_joint_walk_transit_ASC_sr3p_work,-10.0, +coef_joint_walk_transit_ASC_walk_atwork,-0.5954623418574255, +coef_joint_walk_transit_ASC_walk_eatout,1.58, +coef_joint_walk_transit_ASC_walk_escort,0.9845376581425747, +coef_joint_walk_transit_ASC_walk_othdiscr,0.9845376581425747, +coef_joint_walk_transit_ASC_walk_othmaint,0.9845376581425747, +coef_joint_walk_transit_ASC_walk_school,-0.5954623418574255, +coef_joint_walk_transit_ASC_walk_shopping,0.9845376581425747, +coef_joint_walk_transit_ASC_walk_social,1.58, +coef_joint_walk_transit_ASC_walk_univ,-0.5954623418574255, +coef_joint_walk_transit_ASC_walk_work,-0.5954623418574255, +coef_joint_walk_transit_ASC_rh_atwork,0.0, +coef_joint_walk_transit_ASC_rh_eatout,1.23, +coef_joint_walk_transit_ASC_rh_escort,0.0, +coef_joint_walk_transit_ASC_rh_othdiscr,1.23, +coef_joint_walk_transit_ASC_rh_othmaint,1.23, +coef_joint_walk_transit_ASC_rh_parking,0.0, +coef_joint_walk_transit_ASC_rh_school,0.0, +coef_joint_walk_transit_ASC_rh_shopping,1.23, +coef_joint_walk_transit_ASC_rh_social,1.23, +coef_joint_walk_transit_ASC_rh_univ,0.0, +coef_joint_walk_transit_ASC_rh_work,0.0, +coef_joint_drive_transit_ASC_rh_atwork,0.0, +coef_joint_drive_transit_ASC_rh_eatout,4.61, +coef_joint_drive_transit_ASC_rh_escort,0.0, +coef_joint_drive_transit_ASC_rh_othdiscr,4.61, +coef_joint_drive_transit_ASC_rh_othmaint,4.61, +coef_joint_drive_transit_ASC_rh_parking,0.0, +coef_joint_drive_transit_ASC_rh_school,0.0, +coef_joint_drive_transit_ASC_rh_shopping,4.61, +coef_joint_drive_transit_ASC_rh_social,4.61, +coef_joint_drive_transit_ASC_rh_univ,0.0, +coef_joint_drive_transit_ASC_rh_work,0.0, +coef_schoolbus_ASC_sr2_atwork,0.0, +coef_schoolbus_ASC_sr2_eatout,0.0, +coef_schoolbus_ASC_sr2_escort,0.0, +coef_schoolbus_ASC_sr2_othdiscr,0.0, +coef_schoolbus_ASC_sr2_othmaint,0.0, +coef_schoolbus_ASC_sr2_school,-6.566636768886607, +coef_schoolbus_ASC_sr2_shopping,0.0, +coef_schoolbus_ASC_sr2_social,0.0, +coef_schoolbus_ASC_sr2_univ,0.0, +coef_schoolbus_ASC_sr2_work,0.0, +coef_schoolbus_ASC_sr3p_atwork,0.0, +coef_schoolbus_ASC_sr3p_eatout,0.0, +coef_schoolbus_ASC_sr3p_escort,0.0, +coef_schoolbus_ASC_sr3p_othdiscr,0.0, +coef_schoolbus_ASC_sr3p_othmaint,0.0, +coef_schoolbus_ASC_sr3p_school,-6.52605763616968, +coef_schoolbus_ASC_sr3p_shopping,0.0, +coef_schoolbus_ASC_sr3p_social,0.0, +coef_schoolbus_ASC_sr3p_univ,0.0, +coef_schoolbus_ASC_sr3p_work,0.0, +coef_schoolbus_ASC_walk_atwork,0.0, +coef_schoolbus_ASC_walk_eatout,0.0, +coef_schoolbus_ASC_walk_escort,0.0, +coef_schoolbus_ASC_walk_othdiscr,0.0, +coef_schoolbus_ASC_walk_othmaint,0.0, +coef_schoolbus_ASC_walk_school,-6.382554226620955, +coef_schoolbus_ASC_walk_shopping,0.0, +coef_schoolbus_ASC_walk_social,0.0, +coef_schoolbus_ASC_walk_univ,0.0, +coef_schoolbus_ASC_walk_work,0.0, +coef_schoolbus_ASC_rh_atwork,0.0, +coef_schoolbus_ASC_rh_othdisc,0.0, +coef_schoolbus_ASC_rh_social,0.0, +coef_schoolbus_ASC_rh_othmaint,0.0, +coef_schoolbus_ASC_rh_eatout,0.0, +coef_schoolbus_ASC_rh_shopping,0.0, +coef_schoolbus_ASC_rh_escort,-2.28, +coef_schoolbus_ASC_rh_school,-5.0, +coef_schoolbus_ASC_rh_univ,0.0, +coef_schoolbus_ASC_rh_work,0.0, +coef_sov_ASC_sr2_atwork,-999.0, +coef_sov_ASC_sr2_eatout,-999.0, +coef_sov_ASC_sr2_escort,0.0, +coef_sov_ASC_sr2_othdiscr,-999.0, +coef_sov_ASC_sr2_othmaint,-999.0, +coef_sov_ASC_sr2_parking,-999.0, +coef_sov_ASC_sr2_school,-999.0, +coef_sov_ASC_sr2_shopping,-999.0, +coef_sov_ASC_sr2_social,-999.0, +coef_sov_ASC_sr2_univ,-999.0, +coef_sov_ASC_sr2_work,-999.0, +coef_sov_ASC_sr3p_atwork,-999.0, +coef_sov_ASC_sr3p_eatout,-999.0, +coef_sov_ASC_sr3p_escort,0.0, +coef_sov_ASC_sr3p_othdiscr,-999.0, +coef_sov_ASC_sr3p_othmaint,-999.0, +coef_sov_ASC_sr3p_school,-999.0, +coef_sov_ASC_sr3p_shopping,-999.0, +coef_sov_ASC_sr3p_social,-999.0, +coef_sov_ASC_sr3p_univ,-999.0, +coef_sov_ASC_sr3p_work,-999.0, +coef_sov_ASC_walk_atwork,-13.03, +coef_sov_ASC_walk_eatout,-11.13, +coef_sov_ASC_walk_escort,-10.41, +coef_sov_ASC_walk_othdiscr,-11.34, +coef_sov_ASC_walk_othmaint,-11.71, +coef_sov_ASC_walk_school,-11.0, +coef_sov_ASC_walk_shopping,-11.88, +coef_sov_ASC_walk_social,-11.59, +coef_sov_ASC_walk_univ,-10.33, +coef_sov_ASC_walk_work,-11.58, +coef_sov_ASC_rh_atwork,-7.0, +coef_sov_ASC_rh_eatout,0.0, +coef_sov_ASC_rh_escort,0.0, +coef_sov_ASC_rh_othdiscr,0.0, +coef_sov_ASC_rh_othmaint,0.0, +coef_sov_ASC_rh_parking,-6.65, +coef_sov_ASC_rh_school,-5.65, +coef_sov_ASC_rh_shopping,0.0, +coef_sov_ASC_rh_social,0.0, +coef_sov_ASC_rh_univ,-6.65, +coef_sov_ASC_rh_work,-7.0, +coef_sr2_ASC_sov_atwork,-0.4988466896476158, +coef_sr2_ASC_sov_eatout,-0.5234703277804155, +coef_sr2_ASC_sov_escort,-0.2175035032905785, +coef_sr2_ASC_sov_othdiscr,-0.5234703277804155, +coef_sr2_ASC_sov_othmaint,-0.2175035032905785, +coef_sr2_ASC_sov_school,0.41591282919463496, +coef_sr2_ASC_sov_shopping,-0.2175035032905785, +coef_sr2_ASC_sov_social,-0.5234703277804155, +coef_sr2_ASC_sov_univ,-0.903569738115396, +coef_sr2_ASC_sov_work,-0.010011487339503113, +coef_sr2_ASC_walk_atwork,-14.4, +coef_sr2_ASC_walk_eatout,-10.74, +coef_sr2_ASC_walk_escort,-13.470000000000002, +coef_sr2_ASC_walk_othdiscr,-10.690000000000001, +coef_sr2_ASC_walk_othmaint,-12.01, +coef_sr2_ASC_walk_school,-10.17, +coef_sr2_ASC_walk_shopping,-11.529999999999998, +coef_sr2_ASC_walk_social,-11.46, +coef_sr2_ASC_walk_univ,-9.83, +coef_sr2_ASC_walk_work,-10.41, +coef_sr2_ASC_rh_atwork,-7.0, +coef_sr2_ASC_rh_eatout,-7.0, +coef_sr2_ASC_rh_escort,-7.0, +coef_sr2_ASC_rh_othdiscr,-7.0, +coef_sr2_ASC_rh_othmaint,-7.0, +coef_sr2_ASC_rh_parking,-6.69, +coef_sr2_ASC_rh_school,-7.0, +coef_sr2_ASC_rh_shopping,-7.0, +coef_sr2_ASC_rh_social,-7.0, +coef_sr2_ASC_rh_univ,-6.69, +coef_sr2_ASC_rh_work,-7.0, +coef_sr3p_ASC_sov_atwork,5.062326073251256, +coef_sr3p_ASC_sov_eatout,-3.523217533958665, +coef_sr3p_ASC_sov_escort,-2.789912846672032, +coef_sr3p_ASC_sov_othdiscr,-3.523217533958665, +coef_sr3p_ASC_sov_othmaint,-2.789912846672032, +coef_sr3p_ASC_sov_school,-5.4040260311378185, +coef_sr3p_ASC_sov_shopping,-2.789912846672032, +coef_sr3p_ASC_sov_social,-3.523217533958665, +coef_sr3p_ASC_sov_univ,-3.0858954190275263, +coef_sr3p_ASC_sov_work,3.5876358231539403, +coef_sr3p_ASC_sr2_atwork,-2.080782638559888, +coef_sr3p_ASC_sr2_eatout,-0.9552465068907723, +coef_sr3p_ASC_sr2_escort,-0.6779703783939575, +coef_sr3p_ASC_sr2_othdiscr,-1.2452465068907723, +coef_sr3p_ASC_sr2_othmaint,-0.6979703783939575, +coef_sr3p_ASC_sr2_school,-0.9203689858027605, +coef_sr3p_ASC_sr2_shopping,-0.48797037839395746, +coef_sr3p_ASC_sr2_social,-0.7952465068907724, +coef_sr3p_ASC_sr2_univ,-0.8035918988403229, +coef_sr3p_ASC_sr2_work,-1.0138507099494185, +coef_sr3p_ASC_walk_atwork,-13.89, +coef_sr3p_ASC_walk_eatout,-10.15, +coef_sr3p_ASC_walk_escort,-12.36, +coef_sr3p_ASC_walk_othdiscr,-10.629999999999999, +coef_sr3p_ASC_walk_othmaint,-11.31, +coef_sr3p_ASC_walk_school,-10.71, +coef_sr3p_ASC_walk_shopping,-11.86, +coef_sr3p_ASC_walk_social,-10.42, +coef_sr3p_ASC_walk_univ,-9.98, +coef_sr3p_ASC_walk_work,-10.73, +coef_sr3p_ASC_rh_atwork,-6.03, +coef_sr3p_ASC_rh_eatout,-7.0, +coef_sr3p_ASC_rh_escort,-7.0, +coef_sr3p_ASC_rh_othdiscr,-7.0, +coef_sr3p_ASC_rh_othmaint,-7.0, +coef_sr3p_ASC_rh_parking,-7.0, +coef_sr3p_ASC_rh_school,-6.67, +coef_sr3p_ASC_rh_shopping,-7.0, +coef_sr3p_ASC_rh_social,-7.0, +coef_sr3p_ASC_rh_univ,-7.0, +coef_sr3p_ASC_rh_work,-7.0, +coef_walk_transit_ASC_sr2_atwork,-8.0, +coef_walk_transit_ASC_sr2_eatout,-4.752656534154784, +coef_walk_transit_ASC_sr2_escort,-3.9281485359445245, +coef_walk_transit_ASC_sr2_othdiscr,-4.752656534154784, +coef_walk_transit_ASC_sr2_othmaint,-3.9281485359445245, +coef_walk_transit_ASC_sr2_school,-4.309709722353679, +coef_walk_transit_ASC_sr2_shopping,-3.9281485359445245, +coef_walk_transit_ASC_sr2_social,-4.752656534154784, +coef_walk_transit_ASC_sr2_univ,-2.8854208118015596, +coef_walk_transit_ASC_sr2_work,-2.8452845589061027, +coef_walk_transit_ASC_sr3p_atwork,-6.0203237313838125, +coef_walk_transit_ASC_sr3p_eatout,-5.245523142380726, +coef_walk_transit_ASC_sr3p_escort,-5.42458388014317, +coef_walk_transit_ASC_sr3p_othdiscr,-5.245523142380726, +coef_walk_transit_ASC_sr3p_othmaint,-5.42458388014317, +coef_walk_transit_ASC_sr3p_school,-4.383484815493833, +coef_walk_transit_ASC_sr3p_shopping,-5.42458388014317, +coef_walk_transit_ASC_sr3p_social,-5.245523142380726, +coef_walk_transit_ASC_sr3p_univ,-3.739727312222718, +coef_walk_transit_ASC_sr3p_work,-3.9742145708402035, +coef_walk_transit_ASC_walk_atwork,-1.9069314763883787, +coef_walk_transit_ASC_walk_eatout,-0.7312960561330122, +coef_walk_transit_ASC_walk_escort,-0.7607352842053103, +coef_walk_transit_ASC_walk_othdiscr,-0.7312960561330122, +coef_walk_transit_ASC_walk_othmaint,-0.7607352842053103, +coef_walk_transit_ASC_walk_school,-1.5841513183326301, +coef_walk_transit_ASC_walk_shopping,-0.7607352842053103, +coef_walk_transit_ASC_walk_social,-0.7312960561330122, +coef_walk_transit_ASC_walk_univ,-1.6281172172805785, +coef_walk_transit_ASC_walk_work,0.45108415805734536, +coef_walk_transit_ASC_rh_atwork,-3.85, +coef_walk_transit_ASC_rh_eatout,-4.75, +coef_walk_transit_ASC_rh_escort,-3.11, +coef_walk_transit_ASC_rh_othdiscr,-4.75, +coef_walk_transit_ASC_rh_othmaint,-3.11, +coef_walk_transit_ASC_rh_parking,-4.27, +coef_walk_transit_ASC_rh_school,-7.0, +coef_walk_transit_ASC_rh_shopping,-3.11, +coef_walk_transit_ASC_rh_social,-4.75, +coef_walk_transit_ASC_rh_univ,-4.27, +coef_walk_transit_ASC_rh_work,-3.74, +coef_drive_transit_ASC_rh_atwork,-6.95, +coef_drive_transit_ASC_rh_eatout,3.57, +coef_drive_transit_ASC_rh_escort,0.69, +coef_drive_transit_ASC_rh_othdiscr,-1.5, +coef_drive_transit_ASC_rh_othmaint,0.69, +coef_drive_transit_ASC_rh_parking,-0.63, +coef_drive_transit_ASC_rh_school,-3.0, +coef_drive_transit_ASC_rh_shopping,0.69, +coef_drive_transit_ASC_rh_social,3.57, +coef_drive_transit_ASC_rh_univ,-0.63, +coef_drive_transit_ASC_rh_work,-2.5, +coef_joint_walk_ASC_rh_atwork,0.0, +coef_joint_walk_ASC_rh_eatout,-3.04, +coef_joint_walk_ASC_rh_escort,0.0, +coef_joint_walk_ASC_rh_othdiscr,-3.04, +coef_joint_walk_ASC_rh_othmaint,-3.04, +coef_joint_walk_ASC_rh_parking,0.0, +coef_joint_walk_ASC_rh_school,0.0, +coef_joint_walk_ASC_rh_shopping,-3.04, +coef_joint_walk_ASC_rh_social,-3.04, +coef_joint_walk_ASC_rh_univ,0.0, +coef_joint_walk_ASC_rh_work,0.0, +coef_walk_ASC_rh_atwork,-7.0, +coef_walk_ASC_rh_eatout,-7.0, +coef_walk_ASC_rh_escort,-7.0, +coef_walk_ASC_rh_othdiscr,-7.0, +coef_walk_ASC_rh_othmaint,-7.0, +coef_walk_ASC_rh_parking,-7.0, +coef_walk_ASC_rh_school,-7.0, +coef_walk_ASC_rh_shopping,-7.0, +coef_walk_ASC_rh_social,-7.0, +coef_walk_ASC_rh_univ,-7.0, +coef_walk_ASC_rh_work,-7.0, +coef_auto_ASC_rh_atwork,0.0, +coef_auto_ASC_rh_eatout,-7.0, +coef_auto_ASC_rh_escort,0.0, +coef_auto_ASC_rh_othdiscr,-7.0, +coef_auto_ASC_rh_othmaint,-7.0, +coef_auto_ASC_rh_parking,0.0, +coef_auto_ASC_rh_school,0.0, +coef_auto_ASC_rh_shopping,-7.0, +coef_auto_ASC_rh_social,-7.0, +coef_auto_ASC_rh_univ,0.0, +coef_auto_ASC_rh_work,0.0, +coef_ride_hail_ASC_sr2_atwork,-12.601900928873786, +coef_ride_hail_ASC_sr2_eatout,-7.803202757204481, +coef_ride_hail_ASC_sr2_escort,-27.83017990291652, +coef_ride_hail_ASC_sr2_othdiscr,-7.803202757204481, +coef_ride_hail_ASC_sr2_othmaint,-27.83017990291652, +coef_ride_hail_ASC_sr2_parking,-2.58, +coef_ride_hail_ASC_sr2_school,-2.243298293783643, +coef_ride_hail_ASC_sr2_shopping,-27.83017990291652, +coef_ride_hail_ASC_sr2_social,-7.803202757204481, +coef_ride_hail_ASC_sr2_univ,-5.853905893273362, +coef_ride_hail_ASC_sr2_work,-8.006853817327343, +coef_ride_hail_ASC_sr3p_atwork,-17.0, +coef_ride_hail_ASC_sr3p_eatout,-15.049601054356177, +coef_ride_hail_ASC_sr3p_escort,-25.255147299828984, +coef_ride_hail_ASC_sr3p_othdiscr,-15.049601054356177, +coef_ride_hail_ASC_sr3p_othmaint,-25.255147299828984, +coef_ride_hail_ASC_sr3p_parking,-3.19, +coef_ride_hail_ASC_sr3p_school,-3.5983406573577765, +coef_ride_hail_ASC_sr3p_shopping,-25.255147299828984, +coef_ride_hail_ASC_sr3p_social,-15.049601054356177, +coef_ride_hail_ASC_sr3p_univ,-16.405932727661213, +coef_ride_hail_ASC_sr3p_work,-15.300582211216001, +coef_ride_hail_ASC_walk_atwork,-2.7032741603658432, +coef_ride_hail_ASC_walk_eatout,1.8707796557281626, +coef_ride_hail_ASC_walk_escort,-5.845814638712761, +coef_ride_hail_ASC_walk_othdiscr,1.8707796557281626, +coef_ride_hail_ASC_walk_othmaint,-5.845814638712761, +coef_ride_hail_ASC_walk_parking,-10.85, +coef_ride_hail_ASC_walk_school,-11.24, +coef_ride_hail_ASC_walk_shopping,-5.845814638712761, +coef_ride_hail_ASC_walk_social,1.8707796557281626, +coef_ride_hail_ASC_walk_univ,-8.315651083482015, +coef_ride_hail_ASC_walk_work,11.274653599340692, +coef_ride_hail_ASC_walk_transit_atwork,-7.0, +coef_ride_hail_ASC_walk_transit_eatout,-7.0, +coef_ride_hail_ASC_walk_transit_escort,-7.0, +coef_ride_hail_ASC_walk_transit_othdiscr,-7.0, +coef_ride_hail_ASC_walk_transit_othmaint,-7.0, +coef_ride_hail_ASC_walk_transit_parking,-7.0, +coef_ride_hail_ASC_walk_transit_school,-7.0, +coef_ride_hail_ASC_walk_transit_shopping,-7.0, +coef_ride_hail_ASC_walk_transit_social,-7.0, +coef_ride_hail_ASC_walk_transit_univ,-7.0, +coef_ride_hail_ASC_walk_transit_work,-10.87, +coef_ride_hail_ASC_taxi_atwork,6.801151893636805, +coef_ride_hail_ASC_taxi_eatout,5.016880709175902, +coef_ride_hail_ASC_taxi_escort,5.749519895198072, +coef_ride_hail_ASC_taxi_othdiscr,5.016880709175902, +coef_ride_hail_ASC_taxi_othmaint,5.749519895198072, +coef_ride_hail_ASC_taxi_parking,-1.6, +coef_ride_hail_ASC_taxi_school,4.537307920198721, +coef_ride_hail_ASC_taxi_shopping,5.749519895198072, +coef_ride_hail_ASC_taxi_social,5.016880709175902, +coef_ride_hail_ASC_taxi_univ,6.276571222444565, +coef_ride_hail_ASC_taxi_work,6.743937159221356, +coef_ride_hail_ASC_tnc_single_atwork,5.437200737804858, +coef_ride_hail_ASC_tnc_single_eatout,6.242409580427641, +coef_ride_hail_ASC_tnc_single_escort,6.411533193972196, +coef_ride_hail_ASC_tnc_single_othdiscr,6.242409580427641, +coef_ride_hail_ASC_tnc_single_othmaint,6.411533193972196, +coef_ride_hail_ASC_tnc_single_parking,0.11, +coef_ride_hail_ASC_tnc_single_school,3.8633980460214343, +coef_ride_hail_ASC_tnc_single_shopping,6.411533193972196, +coef_ride_hail_ASC_tnc_single_social,6.242409580427641, +coef_ride_hail_ASC_tnc_single_univ,5.529890080456208, +coef_ride_hail_ASC_tnc_single_work,8.561417006634297, +coef_ride_hail_ASC_tnc_shared,0.0, +coef_joint_ride_hail_ASC_sr2_atwork,1.3253957469297355, +coef_joint_ride_hail_ASC_sr2_eatout,-3.3, +coef_joint_ride_hail_ASC_sr2_escort,2.245395746929735, +coef_joint_ride_hail_ASC_sr2_othdiscr,2.2853957469297352, +coef_joint_ride_hail_ASC_sr2_othmaint,2.245395746929735, +coef_joint_ride_hail_ASC_sr2_parking,-2.58, +coef_joint_ride_hail_ASC_sr2_school,2.5253957469297355, +coef_joint_ride_hail_ASC_sr2_shopping,2.245395746929735, +coef_joint_ride_hail_ASC_sr2_social,-3.3, +coef_joint_ride_hail_ASC_sr2_univ,3.005395746929736, +coef_joint_ride_hail_ASC_sr2_work,1.6753957469297354, +coef_joint_ride_hail_ASC_sr3p_atwork,-25.65862562346605, +coef_joint_ride_hail_ASC_sr3p_eatout,-4.06, +coef_joint_ride_hail_ASC_sr3p_escort,-25.65862562346605, +coef_joint_ride_hail_ASC_sr3p_othdiscr,-22.71862562346605, +coef_joint_ride_hail_ASC_sr3p_othmaint,-25.65862562346605, +coef_joint_ride_hail_ASC_sr3p_parking,-3.19, +coef_joint_ride_hail_ASC_sr3p_school,-22.748625623466047, +coef_joint_ride_hail_ASC_sr3p_shopping,-25.65862562346605, +coef_joint_ride_hail_ASC_sr3p_social,-4.06, +coef_joint_ride_hail_ASC_sr3p_univ,-21.848625623466056, +coef_joint_ride_hail_ASC_sr3p_work,-29.528625623466056, +coef_joint_ride_hail_ASC_walk_atwork,3.820817277110533, +coef_joint_ride_hail_ASC_walk_eatout,-1.33, +coef_joint_ride_hail_ASC_walk_escort,-1.4991827228894663, +coef_joint_ride_hail_ASC_walk_othdiscr,4.170817277110533, +coef_joint_ride_hail_ASC_walk_othmaint,-1.4991827228894663, +coef_joint_ride_hail_ASC_walk_parking,-10.85, +coef_joint_ride_hail_ASC_walk_school,4.260817277110533, +coef_joint_ride_hail_ASC_walk_shopping,-1.4991827228894663, +coef_joint_ride_hail_ASC_walk_social,-1.33, +coef_joint_ride_hail_ASC_walk_univ,-5.34918272288947, +coef_joint_ride_hail_ASC_walk_work,7.000817277110533, +coef_joint_ride_hail_ASC_walk_transit_atwork,-7.0, +coef_joint_ride_hail_ASC_walk_transit_eatout,-7.0, +coef_joint_ride_hail_ASC_walk_transit_escort,-7.0, +coef_joint_ride_hail_ASC_walk_transit_othdiscr,-7.0, +coef_joint_ride_hail_ASC_walk_transit_othmaint,-7.0, +coef_joint_ride_hail_ASC_walk_transit_parking,-7.0, +coef_joint_ride_hail_ASC_walk_transit_school,-7.0, +coef_joint_ride_hail_ASC_walk_transit_shopping,-7.0, +coef_joint_ride_hail_ASC_walk_transit_social,-7.0, +coef_joint_ride_hail_ASC_walk_transit_univ,-7.0, +coef_joint_ride_hail_ASC_walk_transit_work,-10.87, +coef_joint_ride_hail_ASC_taxi_atwork,8.803997422549498, +coef_joint_ride_hail_ASC_taxi_eatout,-7.0, +coef_joint_ride_hail_ASC_taxi_escort,8.803997422549498, +coef_joint_ride_hail_ASC_taxi_othdiscr,1.8039974225494988, +coef_joint_ride_hail_ASC_taxi_othmaint,1.8039974225494988, +coef_joint_ride_hail_ASC_taxi_parking,0.0, +coef_joint_ride_hail_ASC_taxi_school,8.803997422549498, +coef_joint_ride_hail_ASC_taxi_shopping,1.8039974225494988, +coef_joint_ride_hail_ASC_taxi_social,-7.0, +coef_joint_ride_hail_ASC_taxi_univ,8.803997422549498, +coef_joint_ride_hail_ASC_taxi_work,8.803997422549498, +coef_joint_ride_hail_ASC_tnc_single_atwork,5.793160946034619, +coef_joint_ride_hail_ASC_tnc_single_eatout,-4.73, +coef_joint_ride_hail_ASC_tnc_single_escort,5.793160946034619, +coef_joint_ride_hail_ASC_tnc_single_othdiscr,1.0631609460346199, +coef_joint_ride_hail_ASC_tnc_single_othmaint,1.0631609460346199, +coef_joint_ride_hail_ASC_tnc_single_parking,0.0, +coef_joint_ride_hail_ASC_tnc_single_school,5.793160946034619, +coef_joint_ride_hail_ASC_tnc_single_shopping,1.0631609460346199, +coef_joint_ride_hail_ASC_tnc_single_social,-4.73, +coef_joint_ride_hail_ASC_tnc_single_univ,5.793160946034619, +coef_joint_ride_hail_ASC_tnc_single_work,5.793160946034619, +coef_joint_ride_hail_ASC_tnc_shared,0.0, +walk_express_penalty,10.0,T +adjust_tnc_shared,30.0,T +coef_origin_density_applied_work_univ_school,0.0,T +coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork,1.0,T diff --git a/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients_template.csv b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients_template.csv new file mode 100644 index 000000000..61acc0f61 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_mode_choice_coefficients_template.csv @@ -0,0 +1,88 @@ +coefficient_name,work,univ,school,escort,shopping,eatout,othmaint,social,othdiscr,atwork +#same for all segments,,,,,,,,,, +coef_unavailable,,,,,,,,,, +coef_one,,,,,,,,,, +coef_nest_root,,,,,,,,,, +coef_nest_AUTO,,,,,,,,,, +coef_nest_NONMOTORIZED,,,,,,,,,, +coef_nest_TRANSIT,,,,,,,,,, +coef_nest_WALKACCESS,,,,,,,,,, +coef_nest_PNRACCESS,,,,,,,,,, +coef_nest_KNRACCESS,,,,,,,,,, +coef_nest_RIDEHAIL,,,,,,,,,, +#,,,,,,,,,, +coef_ivt,coef_ivt_work,coef_ivt_univ_school,coef_ivt_univ_school,coef_ivt_escort_shopping_eatout_othdiscr_atwork,coef_ivt_escort_shopping_eatout_othdiscr_atwork,coef_ivt_escort_shopping_eatout_othdiscr_atwork,coef_ivt_othmaint_social,coef_ivt_othmaint_social,coef_ivt_escort_shopping_eatout_othdiscr_atwork,coef_ivt_escort_shopping_eatout_othdiscr_atwork +coef_age1619_da,,,,,,,,,, +coef_age010_trn,,,,,,,,,, +coef_age16p_sr,,,,,,,,,, +coef_hhsize1_sr,,,,,,,,,, +coef_hhsize2_sr,,,,,,,,,, +#multipliers that differ by purpose and were apparently estimated only for atwork,,,,,,,,,, +coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier,coef_ivt_xb_multiplier +coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier,coef_ivt_mr_multiplier +coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier,coef_ivt_br_multiplier +coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier,coef_ivt_lr_multiplier +coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier,coef_ivt_cr_multiplier +coef_short_iwait_multiplier,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_short_iwait_atwork +coef_long_iwait_multiplier,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_long_iwait_atwork +coef_wacc_multiplier,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wacc_atwork +coef_wegr_multiplier,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_wegr_atwork +coef_waux_multiplier,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_waux_atwork +coef_dtim_multiplier,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_dtim_atwork +coef_xwait_multiplier,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_xwait_atwork +coef_walktimeshort_multiplier,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_walktimeshort_atwork +coef_biketimeshort_multiplier,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_work_univ_school_escort_shopping_eatout_othmaint_social_othdiscr,coef_biketimeshort_atwork +#ASCs,,,,,,,,,, +sov_ASC_sr2,coef_sov_ASC_sr2_work,coef_sov_ASC_sr2_univ,coef_sov_ASC_sr2_school,coef_sov_ASC_sr2_escort,coef_sov_ASC_sr2_shopping,coef_sov_ASC_sr2_eatout,coef_sov_ASC_sr2_othmaint,coef_sov_ASC_sr2_social,coef_sov_ASC_sr2_othdiscr,coef_sov_ASC_sr2_atwork +sov_ASC_sr3p,coef_sov_ASC_sr3p_work,coef_sov_ASC_sr3p_univ,coef_sov_ASC_sr3p_school,coef_sov_ASC_sr3p_escort,coef_sov_ASC_sr3p_shopping,coef_sov_ASC_sr3p_eatout,coef_sov_ASC_sr3p_othmaint,coef_sov_ASC_sr3p_social,coef_sov_ASC_sr3p_othdiscr,coef_sov_ASC_sr3p_atwork +sov_ASC_walk,coef_sov_ASC_walk_work,coef_sov_ASC_walk_univ,coef_sov_ASC_walk_school,coef_sov_ASC_walk_escort,coef_sov_ASC_walk_shopping,coef_sov_ASC_walk_eatout,coef_sov_ASC_walk_othmaint,coef_sov_ASC_walk_social,coef_sov_ASC_walk_othdiscr,coef_sov_ASC_walk_atwork +sov_ASC_rh,coef_sov_ASC_rh_work,coef_sov_ASC_rh_univ,coef_sov_ASC_rh_school,coef_sov_ASC_rh_escort,coef_sov_ASC_rh_shopping,coef_sov_ASC_rh_eatout,coef_sov_ASC_rh_othmaint,coef_sov_ASC_rh_social,coef_sov_ASC_rh_othdiscr,coef_sov_ASC_rh_atwork +sr2_ASC_sov,coef_sr2_ASC_sov_work,coef_sr2_ASC_sov_univ,coef_sr2_ASC_sov_school,coef_sr2_ASC_sov_escort,coef_sr2_ASC_sov_shopping,coef_sr2_ASC_sov_eatout,coef_sr2_ASC_sov_othmaint,coef_sr2_ASC_sov_social,coef_sr2_ASC_sov_othdiscr,coef_sr2_ASC_sov_atwork +sr2_ASC_walk,coef_sr2_ASC_walk_work,coef_sr2_ASC_walk_univ,coef_sr2_ASC_walk_school,coef_sr2_ASC_walk_escort,coef_sr2_ASC_walk_shopping,coef_sr2_ASC_walk_eatout,coef_sr2_ASC_walk_othmaint,coef_sr2_ASC_walk_social,coef_sr2_ASC_walk_othdiscr,coef_sr2_ASC_walk_atwork +sr2_ASC_rh,coef_sr2_ASC_rh_work,coef_sr2_ASC_rh_univ,coef_sr2_ASC_rh_school,coef_sr2_ASC_rh_escort,coef_sr2_ASC_rh_shopping,coef_sr2_ASC_rh_eatout,coef_sr2_ASC_rh_othmaint,coef_sr2_ASC_rh_social,coef_sr2_ASC_rh_othdiscr,coef_sr2_ASC_rh_atwork +sr3p_ASC_sov,coef_sr3p_ASC_sov_work,coef_sr3p_ASC_sov_univ,coef_sr3p_ASC_sov_school,coef_sr3p_ASC_sov_escort,coef_sr3p_ASC_sov_shopping,coef_sr3p_ASC_sov_eatout,coef_sr3p_ASC_sov_othmaint,coef_sr3p_ASC_sov_social,coef_sr3p_ASC_sov_othdiscr,coef_sr3p_ASC_sov_atwork +sr3p_ASC_sr2,coef_sr3p_ASC_sr2_work,coef_sr3p_ASC_sr2_univ,coef_sr3p_ASC_sr2_school,coef_sr3p_ASC_sr2_escort,coef_sr3p_ASC_sr2_shopping,coef_sr3p_ASC_sr2_eatout,coef_sr3p_ASC_sr2_othmaint,coef_sr3p_ASC_sr2_social,coef_sr3p_ASC_sr2_othdiscr,coef_sr3p_ASC_sr2_atwork +sr3p_ASC_walk,coef_sr3p_ASC_walk_work,coef_sr3p_ASC_walk_univ,coef_sr3p_ASC_walk_school,coef_sr3p_ASC_walk_escort,coef_sr3p_ASC_walk_shopping,coef_sr3p_ASC_walk_eatout,coef_sr3p_ASC_walk_othmaint,coef_sr3p_ASC_walk_social,coef_sr3p_ASC_walk_othdiscr,coef_sr3p_ASC_walk_atwork +sr3p_ASC_rh,coef_sr3p_ASC_rh_work,coef_sr3p_ASC_rh_univ,coef_sr3p_ASC_rh_school,coef_sr3p_ASC_rh_escort,coef_sr3p_ASC_rh_shopping,coef_sr3p_ASC_rh_eatout,coef_sr3p_ASC_rh_othmaint,coef_sr3p_ASC_rh_social,coef_sr3p_ASC_rh_othdiscr,coef_sr3p_ASC_rh_atwork +walk_ASC_rh,coef_walk_ASC_rh_work,coef_walk_ASC_rh_univ,coef_walk_ASC_rh_school,coef_walk_ASC_rh_escort,coef_walk_ASC_rh_shopping,coef_walk_ASC_rh_eatout,coef_walk_ASC_rh_othmaint,coef_walk_ASC_rh_social,coef_walk_ASC_rh_othdiscr,coef_walk_ASC_rh_atwork +bike_ASC_walk,coef_bike_ASC_walk_work,coef_bike_ASC_walk_univ,coef_bike_ASC_walk_school,coef_bike_ASC_walk_escort,coef_bike_ASC_walk_shopping,coef_bike_ASC_walk_eatout,coef_bike_ASC_walk_othmaint,coef_bike_ASC_walk_social,coef_bike_ASC_walk_othdiscr,coef_bike_ASC_walk_atwork +bike_ASC_rh,coef_bike_ASC_rh_work,coef_bike_ASC_rh_univ,coef_bike_ASC_rh_school,coef_bike_ASC_rh_escort,coef_bike_ASC_rh_shopping,coef_bike_ASC_rh_eatout,coef_bike_ASC_rh_othmaint,coef_bike_ASC_rh_social,coef_bike_ASC_rh_othdiscr,coef_bike_ASC_rh_atwork +walk_transit_ASC_sr2,coef_walk_transit_ASC_sr2_work,coef_walk_transit_ASC_sr2_univ,coef_walk_transit_ASC_sr2_school,coef_walk_transit_ASC_sr2_escort,coef_walk_transit_ASC_sr2_shopping,coef_walk_transit_ASC_sr2_eatout,coef_walk_transit_ASC_sr2_othmaint,coef_walk_transit_ASC_sr2_social,coef_walk_transit_ASC_sr2_othdiscr,coef_walk_transit_ASC_sr2_atwork +walk_transit_ASC_sr3p,coef_walk_transit_ASC_sr3p_work,coef_walk_transit_ASC_sr3p_univ,coef_walk_transit_ASC_sr3p_school,coef_walk_transit_ASC_sr3p_escort,coef_walk_transit_ASC_sr3p_shopping,coef_walk_transit_ASC_sr3p_eatout,coef_walk_transit_ASC_sr3p_othmaint,coef_walk_transit_ASC_sr3p_social,coef_walk_transit_ASC_sr3p_othdiscr,coef_walk_transit_ASC_sr3p_atwork +walk_transit_ASC_walk,coef_walk_transit_ASC_walk_work,coef_walk_transit_ASC_walk_univ,coef_walk_transit_ASC_walk_school,coef_walk_transit_ASC_walk_escort,coef_walk_transit_ASC_walk_shopping,coef_walk_transit_ASC_walk_eatout,coef_walk_transit_ASC_walk_othmaint,coef_walk_transit_ASC_walk_social,coef_walk_transit_ASC_walk_othdiscr,coef_walk_transit_ASC_walk_atwork +walk_transit_ASC_rh,coef_walk_transit_ASC_rh_work,coef_walk_transit_ASC_rh_univ,coef_walk_transit_ASC_rh_school,coef_walk_transit_ASC_rh_escort,coef_walk_transit_ASC_rh_shopping,coef_walk_transit_ASC_rh_eatout,coef_walk_transit_ASC_rh_othmaint,coef_walk_transit_ASC_rh_social,coef_walk_transit_ASC_rh_othdiscr,coef_walk_transit_ASC_rh_atwork +schoolbus_ASC_sr2,coef_schoolbus_ASC_sr2_work,coef_schoolbus_ASC_sr2_univ,coef_schoolbus_ASC_sr2_school,coef_schoolbus_ASC_sr2_escort,coef_schoolbus_ASC_sr2_shopping,coef_schoolbus_ASC_sr2_eatout,coef_schoolbus_ASC_sr2_othmaint,coef_schoolbus_ASC_sr2_social,coef_schoolbus_ASC_sr2_othdiscr,coef_schoolbus_ASC_sr2_atwork +schoolbus_ASC_sr3p,coef_schoolbus_ASC_sr3p_work,coef_schoolbus_ASC_sr3p_univ,coef_schoolbus_ASC_sr3p_school,coef_schoolbus_ASC_sr3p_escort,coef_schoolbus_ASC_sr3p_shopping,coef_schoolbus_ASC_sr3p_eatout,coef_schoolbus_ASC_sr3p_othmaint,coef_schoolbus_ASC_sr3p_social,coef_schoolbus_ASC_sr3p_othdiscr,coef_schoolbus_ASC_sr3p_atwork +schoolbus_ASC_walk,coef_schoolbus_ASC_walk_work,coef_schoolbus_ASC_walk_univ,coef_schoolbus_ASC_walk_school,coef_schoolbus_ASC_walk_escort,coef_schoolbus_ASC_walk_shopping,coef_schoolbus_ASC_walk_eatout,coef_schoolbus_ASC_walk_othmaint,coef_schoolbus_ASC_walk_social,coef_schoolbus_ASC_walk_othdiscr,coef_schoolbus_ASC_walk_atwork +schoolbus_ASC_rh,coef_schoolbus_ASC_rh_work,coef_schoolbus_ASC_rh_univ,coef_schoolbus_ASC_rh_school,coef_schoolbus_ASC_rh_escort,coef_schoolbus_ASC_rh_shopping,coef_schoolbus_ASC_rh_eatout,coef_schoolbus_ASC_rh_othmaint,coef_schoolbus_ASC_rh_social,coef_schoolbus_ASC_rh_othdisc,coef_schoolbus_ASC_rh_atwork +#,,,,,,,,,, +drive_transit_ASC_rh,coef_drive_transit_ASC_rh_work,coef_drive_transit_ASC_rh_univ,coef_drive_transit_ASC_rh_school,coef_drive_transit_ASC_rh_escort,coef_drive_transit_ASC_rh_shopping,coef_drive_transit_ASC_rh_eatout,coef_drive_transit_ASC_rh_othmaint,coef_drive_transit_ASC_rh_social,coef_drive_transit_ASC_rh_othdiscr,coef_drive_transit_ASC_rh_atwork +ride_hail_ASC_sr2,coef_ride_hail_ASC_sr2_work,coef_ride_hail_ASC_sr2_univ,coef_ride_hail_ASC_sr2_school,coef_ride_hail_ASC_sr2_escort,coef_ride_hail_ASC_sr2_shopping,coef_ride_hail_ASC_sr2_eatout,coef_ride_hail_ASC_sr2_othmaint,coef_ride_hail_ASC_sr2_social,coef_ride_hail_ASC_sr2_othdiscr,coef_ride_hail_ASC_sr2_atwork +ride_hail_ASC_sr3p,coef_ride_hail_ASC_sr3p_work,coef_ride_hail_ASC_sr3p_univ,coef_ride_hail_ASC_sr3p_school,coef_ride_hail_ASC_sr3p_escort,coef_ride_hail_ASC_sr3p_shopping,coef_ride_hail_ASC_sr3p_eatout,coef_ride_hail_ASC_sr3p_othmaint,coef_ride_hail_ASC_sr3p_social,coef_ride_hail_ASC_sr3p_othdiscr,coef_ride_hail_ASC_sr3p_atwork +ride_hail_ASC_walk,coef_ride_hail_ASC_walk_work,coef_ride_hail_ASC_walk_univ,coef_ride_hail_ASC_walk_school,coef_ride_hail_ASC_walk_escort,coef_ride_hail_ASC_walk_shopping,coef_ride_hail_ASC_walk_eatout,coef_ride_hail_ASC_walk_othmaint,coef_ride_hail_ASC_walk_social,coef_ride_hail_ASC_walk_othdiscr,coef_ride_hail_ASC_walk_atwork +ride_hail_ASC_walk_transit,coef_ride_hail_ASC_walk_transit_work,coef_ride_hail_ASC_walk_transit_univ,coef_ride_hail_ASC_walk_transit_school,coef_ride_hail_ASC_walk_transit_escort,coef_ride_hail_ASC_walk_transit_shopping,coef_ride_hail_ASC_walk_transit_eatout,coef_ride_hail_ASC_walk_transit_othmaint,coef_ride_hail_ASC_walk_transit_social,coef_ride_hail_ASC_walk_transit_othdiscr,coef_ride_hail_ASC_walk_transit_atwork +ride_hail_ASC_taxi,coef_ride_hail_ASC_taxi_work,coef_ride_hail_ASC_taxi_univ,coef_ride_hail_ASC_taxi_school,coef_ride_hail_ASC_taxi_escort,coef_ride_hail_ASC_taxi_shopping,coef_ride_hail_ASC_taxi_eatout,coef_ride_hail_ASC_taxi_othmaint,coef_ride_hail_ASC_taxi_social,coef_ride_hail_ASC_taxi_othdiscr,coef_ride_hail_ASC_taxi_atwork +ride_hail_ASC_tnc_single,coef_ride_hail_ASC_tnc_single_work,coef_ride_hail_ASC_tnc_single_univ,coef_ride_hail_ASC_tnc_single_school,coef_ride_hail_ASC_tnc_single_escort,coef_ride_hail_ASC_tnc_single_shopping,coef_ride_hail_ASC_tnc_single_eatout,coef_ride_hail_ASC_tnc_single_othmaint,coef_ride_hail_ASC_tnc_single_social,coef_ride_hail_ASC_tnc_single_othdiscr,coef_ride_hail_ASC_tnc_single_atwork +ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared,coef_ride_hail_ASC_tnc_shared +joint_auto_ASC_sr2,coef_joint_auto_ASC_sr2_work,coef_joint_auto_ASC_sr2_univ,coef_joint_auto_ASC_sr2_school,coef_joint_auto_ASC_sr2_escort,coef_joint_auto_ASC_sr2_shopping,coef_joint_auto_ASC_sr2_eatout,coef_joint_auto_ASC_sr2_othmaint,coef_joint_auto_ASC_sr2_social,coef_joint_auto_ASC_sr2_othdiscr,coef_joint_auto_ASC_sr2_atwork +joint_auto_ASC_sr3p,coef_joint_auto_ASC_sr3p_work,coef_joint_auto_ASC_sr3p_univ,coef_joint_auto_ASC_sr3p_school,coef_joint_auto_ASC_sr3p_escort,coef_joint_auto_ASC_sr3p_shopping,coef_joint_auto_ASC_sr3p_eatout,coef_joint_auto_ASC_sr3p_othmaint,coef_joint_auto_ASC_sr3p_social,coef_joint_auto_ASC_sr3p_othdiscr,coef_joint_auto_ASC_sr3p_atwork +joint_auto_ASC_walk,coef_joint_auto_ASC_walk_work,coef_joint_auto_ASC_walk_univ,coef_joint_auto_ASC_walk_school,coef_joint_auto_ASC_walk_escort,coef_joint_auto_ASC_walk_shopping,coef_joint_auto_ASC_walk_eatout,coef_joint_auto_ASC_walk_othmaint,coef_joint_auto_ASC_walk_social,coef_joint_auto_ASC_walk_othdiscr,coef_joint_auto_ASC_walk_atwork +joint_auto_ASC_rh,coef_joint_auto_ASC_rh_work,coef_joint_auto_ASC_rh_univ,coef_joint_auto_ASC_rh_school,coef_joint_auto_ASC_rh_escort,coef_joint_auto_ASC_rh_shopping,coef_joint_auto_ASC_rh_eatout,coef_joint_auto_ASC_rh_othmaint,coef_joint_auto_ASC_rh_social,coef_joint_auto_ASC_rh_othdiscr,coef_joint_auto_ASC_rh_atwork +joint_walk_ASC_rh,coef_joint_walk_ASC_rh_work,coef_joint_walk_ASC_rh_univ,coef_joint_walk_ASC_rh_school,coef_joint_walk_ASC_rh_escort,coef_joint_walk_ASC_rh_shopping,coef_joint_walk_ASC_rh_eatout,coef_joint_walk_ASC_rh_othmaint,coef_joint_walk_ASC_rh_social,coef_joint_walk_ASC_rh_othdiscr,coef_joint_walk_ASC_rh_atwork +joint_bike_ASC_walk,coef_joint_bike_ASC_walk_work,coef_joint_bike_ASC_walk_univ,coef_joint_bike_ASC_walk_school,coef_joint_bike_ASC_walk_escort,coef_joint_bike_ASC_walk_shopping,coef_joint_bike_ASC_walk_eatout,coef_joint_bike_ASC_walk_othmaint,coef_joint_bike_ASC_walk_social,coef_joint_bike_ASC_walk_othdiscr,coef_joint_bike_ASC_walk_atwork +joint_bike_ASC_rh,coef_joint_bike_ASC_rh_work,coef_joint_bike_ASC_rh_univ,coef_joint_bike_ASC_rh_school,coef_joint_bike_ASC_rh_escort,coef_joint_bike_ASC_rh_shopping,coef_joint_bike_ASC_rh_eatout,coef_joint_bike_ASC_rh_othmaint,coef_joint_bike_ASC_rh_social,coef_joint_bike_ASC_rh_othdiscr,coef_joint_bike_ASC_rh_atwork +joint_walk_transit_ASC_sr2,coef_joint_walk_transit_ASC_sr2_work,coef_joint_walk_transit_ASC_sr2_univ,coef_joint_walk_transit_ASC_sr2_school,coef_joint_walk_transit_ASC_sr2_escort,coef_joint_walk_transit_ASC_sr2_shopping,coef_joint_walk_transit_ASC_sr2_eatout,coef_joint_walk_transit_ASC_sr2_othmaint,coef_joint_walk_transit_ASC_sr2_social,coef_joint_walk_transit_ASC_sr2_othdiscr,coef_joint_walk_transit_ASC_sr2_atwork +joint_walk_transit_ASC_sr3p,coef_joint_walk_transit_ASC_sr3p_work,coef_joint_walk_transit_ASC_sr3p_univ,coef_joint_walk_transit_ASC_sr3p_school,coef_joint_walk_transit_ASC_sr3p_escort,coef_joint_walk_transit_ASC_sr3p_shopping,coef_joint_walk_transit_ASC_sr3p_eatout,coef_joint_walk_transit_ASC_sr3p_othmaint,coef_joint_walk_transit_ASC_sr3p_social,coef_joint_walk_transit_ASC_sr3p_othdiscr,coef_joint_walk_transit_ASC_sr3p_atwork +joint_walk_transit_ASC_walk,coef_joint_walk_transit_ASC_walk_work,coef_joint_walk_transit_ASC_walk_univ,coef_joint_walk_transit_ASC_walk_school,coef_joint_walk_transit_ASC_walk_escort,coef_joint_walk_transit_ASC_walk_shopping,coef_joint_walk_transit_ASC_walk_eatout,coef_joint_walk_transit_ASC_walk_othmaint,coef_joint_walk_transit_ASC_walk_social,coef_joint_walk_transit_ASC_walk_othdiscr,coef_joint_walk_transit_ASC_walk_atwork +joint_walk_transit_ASC_rh,coef_joint_walk_transit_ASC_rh_work,coef_joint_walk_transit_ASC_rh_univ,coef_joint_walk_transit_ASC_rh_school,coef_joint_walk_transit_ASC_rh_escort,coef_joint_walk_transit_ASC_rh_shopping,coef_joint_walk_transit_ASC_rh_eatout,coef_joint_walk_transit_ASC_rh_othmaint,coef_joint_walk_transit_ASC_rh_social,coef_joint_walk_transit_ASC_rh_othdiscr,coef_joint_walk_transit_ASC_rh_atwork +joint_drive_transit_ASC_rh,coef_joint_drive_transit_ASC_rh_work,coef_joint_drive_transit_ASC_rh_univ,coef_joint_drive_transit_ASC_rh_school,coef_joint_drive_transit_ASC_rh_escort,coef_joint_drive_transit_ASC_rh_shopping,coef_joint_drive_transit_ASC_rh_eatout,coef_joint_drive_transit_ASC_rh_othmaint,coef_joint_drive_transit_ASC_rh_social,coef_joint_drive_transit_ASC_rh_othdiscr,coef_joint_drive_transit_ASC_rh_atwork +joint_ride_hail_ASC_sr2,coef_joint_ride_hail_ASC_sr2_work,coef_joint_ride_hail_ASC_sr2_univ,coef_joint_ride_hail_ASC_sr2_school,coef_joint_ride_hail_ASC_sr2_escort,coef_joint_ride_hail_ASC_sr2_shopping,coef_joint_ride_hail_ASC_sr2_eatout,coef_joint_ride_hail_ASC_sr2_othmaint,coef_joint_ride_hail_ASC_sr2_social,coef_joint_ride_hail_ASC_sr2_othdiscr,coef_joint_ride_hail_ASC_sr2_atwork +joint_ride_hail_ASC_sr3p,coef_joint_ride_hail_ASC_sr3p_work,coef_joint_ride_hail_ASC_sr3p_univ,coef_joint_ride_hail_ASC_sr3p_school,coef_joint_ride_hail_ASC_sr3p_escort,coef_joint_ride_hail_ASC_sr3p_shopping,coef_joint_ride_hail_ASC_sr3p_eatout,coef_joint_ride_hail_ASC_sr3p_othmaint,coef_joint_ride_hail_ASC_sr3p_social,coef_joint_ride_hail_ASC_sr3p_othdiscr,coef_joint_ride_hail_ASC_sr3p_atwork +joint_ride_hail_ASC_walk,coef_joint_ride_hail_ASC_walk_work,coef_joint_ride_hail_ASC_walk_univ,coef_joint_ride_hail_ASC_walk_school,coef_joint_ride_hail_ASC_walk_escort,coef_joint_ride_hail_ASC_walk_shopping,coef_joint_ride_hail_ASC_walk_eatout,coef_joint_ride_hail_ASC_walk_othmaint,coef_joint_ride_hail_ASC_walk_social,coef_joint_ride_hail_ASC_walk_othdiscr,coef_joint_ride_hail_ASC_walk_atwork +joint_ride_hail_ASC_walk_transit,coef_joint_ride_hail_ASC_walk_transit_work,coef_joint_ride_hail_ASC_walk_transit_univ,coef_joint_ride_hail_ASC_walk_transit_school,coef_joint_ride_hail_ASC_walk_transit_escort,coef_joint_ride_hail_ASC_walk_transit_shopping,coef_joint_ride_hail_ASC_walk_transit_eatout,coef_joint_ride_hail_ASC_walk_transit_othmaint,coef_joint_ride_hail_ASC_walk_transit_social,coef_joint_ride_hail_ASC_walk_transit_othdiscr,coef_joint_ride_hail_ASC_walk_transit_atwork +joint_ride_hail_ASC_taxi,coef_joint_ride_hail_ASC_taxi_work,coef_joint_ride_hail_ASC_taxi_univ,coef_joint_ride_hail_ASC_taxi_school,coef_joint_ride_hail_ASC_taxi_escort,coef_joint_ride_hail_ASC_taxi_shopping,coef_joint_ride_hail_ASC_taxi_eatout,coef_joint_ride_hail_ASC_taxi_othmaint,coef_joint_ride_hail_ASC_taxi_social,coef_joint_ride_hail_ASC_taxi_othdiscr,coef_joint_ride_hail_ASC_taxi_atwork +joint_ride_hail_ASC_tnc_single,coef_joint_ride_hail_ASC_tnc_single_work,coef_joint_ride_hail_ASC_tnc_single_univ,coef_joint_ride_hail_ASC_tnc_single_school,coef_joint_ride_hail_ASC_tnc_single_escort,coef_joint_ride_hail_ASC_tnc_single_shopping,coef_joint_ride_hail_ASC_tnc_single_eatout,coef_joint_ride_hail_ASC_tnc_single_othmaint,coef_joint_ride_hail_ASC_tnc_single_social,coef_joint_ride_hail_ASC_tnc_single_othdiscr,coef_joint_ride_hail_ASC_tnc_single_atwork +joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared,coef_joint_ride_hail_ASC_tnc_shared +walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty,walk_express_penalty +adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared,adjust_tnc_shared +origin_density_applied,coef_origin_density_applied_work_univ_school,coef_origin_density_applied_work_univ_school,coef_origin_density_applied_work_univ_school,coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork,coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork,coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork,coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork,coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork,coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork,coef_origin_density_applied_escort_shopping_eatout_othmaint_social_othdiscr_atwork diff --git a/activitysim/examples/prototype_mwcog/configs/trip_purpose.yaml b/activitysim/examples/prototype_mwcog/configs/trip_purpose.yaml new file mode 100644 index 000000000..10668a618 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_purpose.yaml @@ -0,0 +1,7 @@ + +preprocessor: + SPEC: trip_purpose_annotate_trips_preprocessor + DF: trips + TABLES: + - persons + - tours diff --git a/activitysim/examples/prototype_mwcog/configs/trip_purpose_and_destination.yaml b/activitysim/examples/prototype_mwcog/configs/trip_purpose_and_destination.yaml new file mode 100644 index 000000000..76f592348 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_purpose_and_destination.yaml @@ -0,0 +1,6 @@ + +MAX_ITERATIONS: 5 + +# drop failed trips and cleanup failed trip leg_mates for consistency +# (i.e. adjust trip_count, trip_num, first for missing failed trips) +CLEANUP: True diff --git a/activitysim/examples/prototype_mwcog/configs/trip_purpose_annotate_trips_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/trip_purpose_annotate_trips_preprocessor.csv new file mode 100644 index 000000000..782116aa9 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_purpose_annotate_trips_preprocessor.csv @@ -0,0 +1,5 @@ +Description,Target,Expression +#,, +,ptype,"reindex(persons.ptype, df.person_id)" +,person_type,ptype.map(PTYPE_NAME) +,start,"reindex_i(tours.start, df.tour_id)" diff --git a/activitysim/examples/prototype_mwcog/configs/trip_purpose_probs.csv b/activitysim/examples/prototype_mwcog/configs/trip_purpose_probs.csv new file mode 100644 index 000000000..3cd1aaa27 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_purpose_probs.csv @@ -0,0 +1,132 @@ +primary_purpose,outbound,depart_range_start,depart_range_end,person_type,work,univ,school,escort,shopping,othmaint,eatout,social,othdiscr +work,TRUE,1,18,PTYPE_FULL,0.198,0.004,0,0.466,0.083,0.086,0.093,0.004,0.066 +work,TRUE,1,18,PTYPE_PART,0.094,0,0,0.657,0.076,0.07,0.067,0.009,0.027 +work,TRUE,1,18,PTYPE_UNIVERSITY,0.067,0.081,0,0.433,0.005,0.038,0.153,0.108,0.115 +work,TRUE,19,48,PTYPE_FULL,0.278,0.008,0,0.172,0.18,0.193,0.107,0.016,0.046 +work,TRUE,19,48,PTYPE_PART,0.442,0,0,0.089,0.105,0.175,0.102,0.03,0.057 +work,TRUE,19,48,PTYPE_UNIVERSITY,0.049,0.086,0,0.392,0.159,0.157,0.069,0.073,0.015 +work,TRUE,1,48,PTYPE_DRIVING,0,0,0,0,0.2,0.2,0.2,0.2,0.2 +univ,TRUE,1,48,PTYPE_FULL,0.526,0.178,0,0.016,0.16,0.035,0.028,0.057,0 +univ,TRUE,1,48,PTYPE_PART,0.059,0.941,0,0,0,0,0,0,0 +univ,TRUE,1,48,PTYPE_UNIVERSITY,0.109,0.034,0,0.382,0.136,0.147,0.094,0.048,0.05 +school,TRUE,1,48,PTYPE_DRIVING,0,0,0,0.548,0.015,0.1,0.206,0.073,0.058 +school,TRUE,1,48,PTYPE_SCHOOL,0,0,0,0.53,0.025,0.084,0.112,0.048,0.201 +school,TRUE,1,48,PTYPE_PRESCHOOL,0,0,0,0.772,0.007,0.086,0.023,0.071,0.041 +escort,TRUE,1,48,PTYPE_FULL,0,0,0,0.55,0.153,0.084,0.104,0.049,0.06 +escort,TRUE,1,48,PTYPE_PART,0,0,0,0.449,0.194,0.07,0.167,0.059,0.061 +escort,TRUE,1,48,PTYPE_UNIVERSITY,0,0,0,0.509,0.193,0.158,0.048,0.058,0.034 +escort,TRUE,1,48,PTYPE_NONWORK,0,0,0,0.444,0.216,0.084,0.108,0.118,0.03 +escort,TRUE,1,48,PTYPE_RETIRED,0,0,0,0.37,0.204,0.192,0.03,0.068,0.136 +escort,TRUE,1,48,PTYPE_DRIVING,0,0,0,0.586,0.227,0,0.072,0.115,0 +escort,TRUE,1,48,PTYPE_SCHOOL,0,0,0,0.37,0.183,0.29,0.064,0.013,0.08 +escort,TRUE,1,48,PTYPE_PRESCHOOL,0,0,0,0.531,0.064,0,0.131,0.196,0.078 +shopping,TRUE,1,48,PTYPE_FULL,0,0,0,0.102,0.456,0.226,0.11,0.06,0.046 +shopping,TRUE,1,48,PTYPE_PART,0,0,0,0.182,0.291,0.311,0.108,0.031,0.077 +shopping,TRUE,1,48,PTYPE_UNIVERSITY,0,0,0,0.13,0.262,0.36,0.124,0.06,0.064 +shopping,TRUE,1,48,PTYPE_NONWORK,0,0,0,0.144,0.336,0.274,0.122,0.068,0.056 +shopping,TRUE,1,48,PTYPE_RETIRED,0,0,0,0.058,0.357,0.418,0.05,0.047,0.07 +shopping,TRUE,1,48,PTYPE_DRIVING,0,0,0,0.076,0.193,0.298,0.047,0.13,0.256 +shopping,TRUE,1,48,PTYPE_SCHOOL,0,0,0,0.121,0.142,0.232,0.291,0.03,0.184 +shopping,TRUE,1,48,PTYPE_PRESCHOOL,0,0,0,0.138,0.292,0.301,0.187,0.064,0.018 +othmaint,TRUE,1,48,PTYPE_FULL,0,0,0,0.201,0.252,0.366,0.117,0.032,0.032 +othmaint,TRUE,1,48,PTYPE_PART,0,0,0,0.27,0.259,0.325,0.109,0,0.037 +othmaint,TRUE,1,48,PTYPE_UNIVERSITY,0,0,0,0.489,0.13,0.167,0.025,0.15,0.039 +othmaint,TRUE,1,48,PTYPE_NONWORK,0,0,0,0.279,0.229,0.344,0.078,0.039,0.031 +othmaint,TRUE,1,48,PTYPE_RETIRED,0,0,0,0.224,0.139,0.321,0.098,0.064,0.154 +othmaint,TRUE,1,48,PTYPE_DRIVING,0,0,0,0.135,0,0.259,0.083,0.523,0 +othmaint,TRUE,1,48,PTYPE_SCHOOL,0,0,0,0.191,0.408,0.344,0.041,0.008,0.008 +othmaint,TRUE,1,48,PTYPE_PRESCHOOL,0,0,0,0.143,0.301,0.464,0.017,0.029,0.046 +eatout,TRUE,1,48,PTYPE_FULL,0,0,0,0.144,0.283,0.202,0.036,0.129,0.206 +eatout,TRUE,1,48,PTYPE_PART,0,0,0,0.169,0.374,0.179,0.013,0.135,0.13 +eatout,TRUE,1,48,PTYPE_UNIVERSITY,0,0,0,0.32,0.085,0.111,0,0.153,0.331 +eatout,TRUE,1,48,PTYPE_NONWORK,0,0,0,0.201,0.224,0.269,0.063,0.082,0.161 +eatout,TRUE,1,48,PTYPE_RETIRED,0,0,0,0.142,0.237,0.237,0.034,0.123,0.227 +eatout,TRUE,1,48,PTYPE_DRIVING,0,0,0,0.175,0.289,0.346,0,0.105,0.085 +eatout,TRUE,1,48,PTYPE_SCHOOL,0,0,0,0.124,0.135,0.135,0.04,0.048,0.518 +eatout,TRUE,1,48,PTYPE_PRESCHOOL,0,0,0,0.055,0.329,0.165,0.061,0,0.39 +social,TRUE,1,48,PTYPE_FULL,0,0,0,0.186,0.382,0.144,0.122,0.126,0.04 +social,TRUE,1,48,PTYPE_PART,0,0,0,0.175,0.153,0.167,0.147,0.183,0.175 +social,TRUE,1,48,PTYPE_UNIVERSITY,0,0,0,0,0.212,0.091,0.432,0.234,0.031 +social,TRUE,1,48,PTYPE_NONWORK,0,0,0,0.311,0.392,0.149,0.071,0.058,0.019 +social,TRUE,1,48,PTYPE_RETIRED,0,0,0,0.12,0.407,0.203,0.151,0.102,0.017 +social,TRUE,1,48,PTYPE_DRIVING,0,0,0,0,0,0,0,0.415,0.585 +social,TRUE,1,48,PTYPE_SCHOOL,0,0,0,0.322,0.11,0.05,0,0.378,0.14 +social,TRUE,1,48,PTYPE_PRESCHOOL,0,0,0,0.294,0,0.159,0,0.547,0 +othdiscr,TRUE,1,48,PTYPE_FULL,0,0,0,0.236,0.169,0.143,0.19,0.093,0.169 +othdiscr,TRUE,1,48,PTYPE_PART,0,0,0,0.223,0.208,0.181,0.193,0.129,0.066 +othdiscr,TRUE,1,48,PTYPE_UNIVERSITY,0,0,0,0.135,0.123,0.061,0.342,0.123,0.216 +othdiscr,TRUE,1,48,PTYPE_NONWORK,0,0,0,0.263,0.295,0.148,0.088,0.082,0.124 +othdiscr,TRUE,1,48,PTYPE_RETIRED,0,0,0,0.225,0.056,0.389,0.16,0.091,0.079 +othdiscr,TRUE,1,48,PTYPE_DRIVING,0,0,0,0.311,0.126,0.051,0.018,0.142,0.352 +othdiscr,TRUE,1,48,PTYPE_SCHOOL,0,0,0,0.222,0.112,0.172,0.173,0.141,0.18 +othdiscr,TRUE,1,48,PTYPE_PRESCHOOL,0,0,0,0.271,0.108,0.393,0.146,0.043,0.039 +atwork,TRUE,1,48,PTYPE_FULL,0.206,0,0,0.122,0.166,0.247,0.241,0.004,0.014 +atwork,TRUE,1,48,PTYPE_PART,0.206,0,0,0.122,0.166,0.247,0.241,0.004,0.014 +atwork,TRUE,1,48,PTYPE_UNIVERSITY,0.206,0,0,0.122,0.166,0.247,0.241,0.004,0.014 +atwork,TRUE,1,48,PTYPE_DRIVING,0.206,0,0,0.122,0.166,0.247,0.241,0.004,0.014 +#,,,,,,,,,,,,, +work,FALSE,1,30,PTYPE_FULL,0.175,0,0,0.14,0.27,0.162,0.134,0.05,0.069 +work,FALSE,1,30,PTYPE_PART,0.097,0,0,0.252,0.211,0.192,0.159,0.089,0 +work,FALSE,1,30,PTYPE_UNIVERSITY,0.134,0,0,0.329,0.114,0.212,0.169,0.042,0 +work,FALSE,31,48,PTYPE_FULL,0.151,0.011,0,0.201,0.28,0.127,0.103,0.035,0.092 +work,FALSE,31,48,PTYPE_PART,0.11,0,0,0.243,0.281,0.13,0.119,0.036,0.081 +work,FALSE,31,48,PTYPE_UNIVERSITY,0.058,0.127,0,0.224,0.269,0.079,0.072,0.108,0.063 +work,FALSE,1,48,PTYPE_DRIVING,0,0,0,0,0.2,0.2,0.2,0.2,0.2 +univ,FALSE,1,48,PTYPE_FULL,0.352,0.032,0,0.032,0.146,0.114,0.177,0.028,0.119 +univ,FALSE,1,48,PTYPE_PART,0,0,0,0.822,0.178,0,0,0,0 +univ,FALSE,1,48,PTYPE_UNIVERSITY,0.054,0.025,0,0.194,0.209,0.179,0.159,0.067,0.113 +school,FALSE,1,48,PTYPE_DRIVING,0,0,0,0.301,0.117,0.098,0.169,0.186,0.129 +school,FALSE,1,48,PTYPE_SCHOOL,0,0,0,0.166,0.158,0.147,0.122,0.133,0.274 +school,FALSE,1,48,PTYPE_PRESCHOOL,0,0,0,0.38,0.148,0.089,0.146,0.102,0.135 +escort,FALSE,1,48,PTYPE_FULL,0,0,0,0.343,0.235,0.114,0.222,0.039,0.047 +escort,FALSE,1,48,PTYPE_PART,0,0,0,0.24,0.298,0.128,0.157,0.045,0.132 +escort,FALSE,1,48,PTYPE_UNIVERSITY,0,0,0,0.195,0.319,0.287,0.02,0.027,0.152 +escort,FALSE,1,48,PTYPE_NONWORK,0,0,0,0.28,0.325,0.169,0.103,0.05,0.073 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to add to probs column index to get time period it represents. +# e.g. depart_alt_base = 5 means first column (column 0) represents period 5 +DEPART_ALT_BASE: 1 + +MAX_ITERATIONS: 100 + +#FAILFIX: drop_and_cleanup +FAILFIX: choose_most_initial + diff --git a/activitysim/examples/prototype_mwcog/configs/trip_scheduling_probs.csv b/activitysim/examples/prototype_mwcog/configs/trip_scheduling_probs.csv new file mode 100644 index 000000000..93c9bcdb1 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/trip_scheduling_probs.csv @@ -0,0 +1,3457 @@ +primary_purpose,outbound,tour_hour,trip_num,HR1,HR2,HR3,HR4,HR5,HR6,HR7,HR8,HR9,HR10,HR11,HR12,HR13,HR14,HR15,HR16,HR17,HR18,HR19,HR20,HR21,HR22,HR23,HR24,HR25,HR26,HR27,HR28,HR29,HR30,HR31,HR32,HR33,HR34,HR35,HR36,HR37,HR38,HR39,HR40,HR41,HR42,HR43,HR44,HR45,HR46,HR47,HR48 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b/activitysim/examples/prototype_mwcog/configs/work_from_home.csv new file mode 100644 index 000000000..b6f9853df --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/work_from_home.csv @@ -0,0 +1,15 @@ +Label,Description,Expression,work_at_home,work_away_from_home +util_work_from_home_constant,Constant for Working from home,1,coef_work_from_home_constant,0 +util_full_time_worker,Full time worker (1 if true),@df.pemploy==PEMPLOY_FULL,coef_full_time_worker,0 +util_female_worker,Female Worker,@df.SEX==2,coef_female_worker,0 +util_female_worker_preschool_child,Female worker with a Preschool Child in Household,"@df.SEX==2 & other_than(df.household_id, df.ptype == PTYPE_SCHOOL)",coef_female_worker_preschool_child,0 +util_access_to_workplaces,Accessibility to workplaces of the home mgra,@df.workplace_location_logsum,coef_access_to_workplaces,0 +util_non_working_adult_in_hh,Presence of Non Working Adult in the Household,"@other_than(df.household_id, df.ptype == PTYPE_NONWORK)",coef_non_working_adult_in_hh,0 +util_education_ba_plus,Education Level Bachelors or higher degree,0,coef_education_ba_plus,0 +util_low_income,Household income Less than 30K,@df.income < 30000,coef_low_income,0 +util_age_lt_35,Age Group - Less than 35 years,@df.age < 35,coef_age_lt_35,0 +util_age_35_to_45,Age Group - 35 yrs to 45 yrs,"@df.age.between(35, 45)",coef_age_35_to_45,0 +util_age_45_to_55,Age Group - 45 yrs to 55 yrs,"@df.age.between(45, 55)",coef_age_45_to_55,0 +util_age_55_to_65,Age Group - 55 yrs to 65 yrs,"@df.age.between(55, 65)",coef_age_55_to_65,0 +util_age_65_plus,Age Group - Older than 65yrs,@df.age > 65,coef_age_65_plus,0 +util_calibration,ABM2 calibration - work from home,1,coef_calibration,0 diff --git a/activitysim/examples/prototype_mwcog/configs/work_from_home.yaml b/activitysim/examples/prototype_mwcog/configs/work_from_home.yaml new file mode 100644 index 000000000..c4f265ced --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/work_from_home.yaml @@ -0,0 +1,12 @@ + +# borrowed from free parking model + +SPEC: work_from_home.csv +COEFFICIENTS: work_from_home_coeffs.csv + +#LOGIT_TYPE: NL +LOGIT_TYPE: MNL + +WORK_FROM_HOME_ALT: 0 + +DEST_CHOICE_COLUMN_NAME: workplace_zone_id diff --git a/activitysim/examples/prototype_mwcog/configs/work_from_home_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/work_from_home_coeffs.csv new file mode 100644 index 000000000..a3868e981 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/work_from_home_coeffs.csv @@ -0,0 +1,15 @@ +coefficient_name,value,constrain +coef_work_from_home_constant,0.438361,T +coef_full_time_worker,-0.811935,F +coef_female_worker,-0.347009,F +coef_female_worker_preschool_child,0.572657,F +coef_access_to_workplaces,-0.140426,F +coef_non_working_adult_in_hh,-0.372481,F +coef_education_ba_plus,0.284678,F +coef_low_income,-0.393068,F +coef_age_lt_35,-0.573545,F +coef_age_35_to_45,0,F +coef_age_45_to_55,0.21438,F +coef_age_55_to_65,0.451657,F +coef_age_65_plus,0.583518,F +coef_calibration,-0.0162,T diff --git a/activitysim/examples/prototype_mwcog/configs/workplace_location.csv b/activitysim/examples/prototype_mwcog/configs/workplace_location.csv new file mode 100644 index 000000000..1fef3349c --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/workplace_location.csv @@ -0,0 +1,20 @@ +Label,Description,Expression,coefficient +local_dist,,_DIST@skims['DIST'],1 +util_dist,Distance,@_DIST,coef_dist +util_dist_squared,"Distance squared, capped at 30 miles","@(_DIST).clip(0,30)**2",coef_dist_squared +util_dist_cubed,"Distance cubed, capped at 30 miles","@(_DIST).clip(0,30)**3",coef_dist_cubed +util_dist_logged,Distance logged,@(_DIST).apply(np.log1p),coef_dist_logged +util_dist_low,"Distance,low income (<50)",@(df['income_segment']==WORK_LOW_SEGMENT_ID) * _DIST,coef_dist_low_inc +util_dist_med,"Distance,med income (50-100)",@(df['income_segment']==WORK_MED_SEGMENT_ID) * _DIST,coef_dist_med_inc +util_dist_very_high,"Distance,very high income (>150)",@(df['income_segment']==WORK_VERYHIGH_SEGMENT_ID) * _DIST,coef_dist_very_high_inc +util_dist_female,"Distance,female",@(df['female']==True) * _DIST,coef_dist_female +util_dist_part_time,"Distance,part_time",@(df['pemploy']==2) * _DIST,coef_dist_part_time +util_dist_student,"Distance,student",@(df['is_student']==True) * _DIST,coef_dist_student +util_dist_young,"Distance,young person (<25)",@(df['young']==True) * _DIST,coef_dist_young +util_dist_old,"Distance,young person (>65)",@(df['old']==True) * _DIST,coef_dist_old +util_dist_zero_auto,"Distance,zero auto HH",@(df['auto_ownership']==0) * _DIST,coef_dist_zero_auto +util_size_variable,Size variable,@(df['size_term'] * df['shadow_price_size_term_adjustment']).apply(np.log1p),1 +util_utility_adjustment,utility adjustment,@df['shadow_price_utility_adjustment'],1 +util_no_attractions,No attractions,@df['size_term']==0,-999 +util_mode_logsum,Mode choice logsum,mode_choice_logsum,coef_mode_logsum +util_sample_of_corrections_factor,Sample of alternatives correction factor,"@np.minimum(np.log(df.pick_count/df.prob), 60)",1 diff --git a/activitysim/examples/prototype_mwcog/configs/workplace_location.yaml b/activitysim/examples/prototype_mwcog/configs/workplace_location.yaml new file mode 100644 index 000000000..dba0fa9e9 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/workplace_location.yaml @@ -0,0 +1,81 @@ +SAMPLE_SIZE: 30 + +SIMULATE_CHOOSER_COLUMNS: + - income_segment + - home_zone_id + - is_student + - pemploy + - young + - old + - female + - auto_ownership + +SAMPLE_SPEC: workplace_location_sample.csv +SPEC: workplace_location.csv +COEFFICIENTS: workplace_location_coeffs.csv + +LOGSUM_SETTINGS: tour_mode_choice.yaml +LOGSUM_PREPROCESSOR: nontour_preprocessor +LOGSUM_TOUR_PURPOSE: work + +# model-specific logsum-related settings +CHOOSER_ORIG_COL_NAME: home_zone_id +ALT_DEST_COL_NAME: alt_dest +IN_PERIOD: 30 +OUT_PERIOD: 9 + +DEST_CHOICE_COLUMN_NAME: workplace_zone_id +# comment out DEST_CHOICE_LOGSUM_COLUMN_NAME if not desired in persons table +DEST_CHOICE_LOGSUM_COLUMN_NAME: workplace_location_logsum + +# comment out DEST_CHOICE_LOGSUM_COLUMN_NAME if saved alt logsum table +DEST_CHOICE_SAMPLE_TABLE_NAME: workplace_location_sample + +annotate_persons: + SPEC: annotate_persons_workplace + DF: persons + TABLES: + - land_use + +annotate_households: + SPEC: annotate_households_workplace + DF: households + TABLES: + - persons + +# - shadow pricing + + +# income_segment is in households, but we want to count persons +CHOOSER_TABLE_NAME: persons_merged + +# size_terms model_selector +MODEL_SELECTOR: workplace + +# we can't use use household income_segment as this will also be set for non-workers +CHOOSER_SEGMENT_COLUMN_NAME: income_segment + +# boolean column to filter choosers (True means keep) +CHOOSER_FILTER_COLUMN_NAME: is_worker + +# FIXME - these are assigned to persons in annotate_persons. we need a better way to manage this +# FIXME - these are not needed for this model and should be re/factored out +SEGMENT_IDS: + work_low: 1 + work_med: 2 + work_high: 3 + work_veryhigh: 4 + +CONSTANTS: + WORK_LOW_SEGMENT_ID: 1 + WORK_MED_SEGMENT_ID: 2 + WORK_HIGH_SEGMENT_ID: 3 + WORK_VERYHIGH_SEGMENT_ID: 4 + + +# model adds these tables (informational - not added if commented out) +SHADOW_PRICE_TABLE: workplace_shadow_prices +MODELED_SIZE_TABLE: workplace_modeled_size + +# not loaded if commented out +SAVED_SHADOW_PRICE_TABLE_NAME: final_workplace_shadow_prices.csv diff --git a/activitysim/examples/prototype_mwcog/configs/workplace_location_coeffs.csv b/activitysim/examples/prototype_mwcog/configs/workplace_location_coeffs.csv new file mode 100644 index 000000000..521f88ce5 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/workplace_location_coeffs.csv @@ -0,0 +1,15 @@ +coefficient_name,value,constrain +coef_dist,-0.045010687,F +coef_dist_squared,0.002654513,F +coef_dist_cubed,-7.39E-05,F +coef_dist_logged,-0.855216378,F +coef_dist_low_inc,-0.018844727,F +coef_dist_med_inc,-0.004762151,F +coef_dist_very_high_inc,0.005722937,F +coef_dist_female,-0.010731711,F +coef_dist_part_time,-0.016178149,F +coef_dist_student,-0.025985743,F +coef_mode_logsum,0.25,F +coef_dist_young,-0.036726831,F +coef_dist_old,-0.013668916,F +coef_dist_zero_auto,-0.033718425,F diff --git a/activitysim/examples/prototype_mwcog/configs/workplace_location_sample.csv b/activitysim/examples/prototype_mwcog/configs/workplace_location_sample.csv new file mode 100644 index 000000000..8cae71719 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/workplace_location_sample.csv @@ -0,0 +1,17 @@ +Label,Description,Expression,coefficient +local_dist,,_DIST@skims['DIST'],1 +util_dist,Distance,@_DIST,coef_dist +util_dist_squared,"Distance squared, capped at 30 miles","@(_DIST).clip(0,30)**2",coef_dist_squared +util_dist_cubed,"Distance cubed, capped at 30 miles","@(_DIST).clip(0,30)**3",coef_dist_cubed +util_dist_logged,Distance logged,@(_DIST).apply(np.log1p),coef_dist_logged +util_dist_low,"Distance,low income",@(df['income_segment']==WORK_LOW_SEGMENT_ID) * _DIST,coef_dist_low_inc +util_dist_med,"Distance,med income",@(df['income_segment']==WORK_MED_SEGMENT_ID) * _DIST,coef_dist_med_inc +util_dist_very_high,"Distance,very high income (>150)",@(df['income_segment']==WORK_VERYHIGH_SEGMENT_ID) * _DIST,coef_dist_very_high_inc +util_dist_part_time,"Distance,part_time",@(df['pemploy']==2) * _DIST,coef_dist_part_time +util_dist_student,"Distance,student",@(df['is_student']==True) * _DIST,coef_dist_student +util_dist_young,"Distance,young person (<25)",@(df['young']==True) * _DIST,coef_dist_young +util_dist_old,"Distance,young person (>65)",@(df['old']==True) * _DIST,coef_dist_old +util_dist_zero_auto,"Distance,zero auto HH",@(df['auto_ownership']==0) * _DIST,coef_dist_zero_auto +util_size_variable,Size variable,@(df['size_term'] * df['shadow_price_size_term_adjustment']).apply(np.log1p),1 +util_utility_adjustment,utility adjustment,@df['shadow_price_utility_adjustment'],1 +util_no_attractions,No attractions,@df['size_term']==0,-999 diff --git a/activitysim/examples/prototype_mwcog/configs/write_trip_matrices.yaml b/activitysim/examples/prototype_mwcog/configs/write_trip_matrices.yaml new file mode 100644 index 000000000..4ce9b1e4f --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/write_trip_matrices.yaml @@ -0,0 +1,259 @@ +# read trips table post preprocessor and run expressions to code +# additional data fields, with one data fields for each matrix specified below + +preprocessor: + SPEC: write_trip_matrices_annotate_trips_preprocessor + DF: trips + TABLES: + - tours + +# divide trip counts by household expansion factor +HH_EXPANSION_WEIGHT_COL: sample_rate # added when households read in + +# save preprocessed trips table to pipeline if desired +SAVE_TRIPS_TABLE: False + +MATRICES: + - file_name: auto_trips_am.omx + tables: + - name: DRIVEALONE + data_field: DRIVEALONE_AM + - name: SHARED2 + data_field: SHARED2_AM + - name: SHARED3 + data_field: SHARED3_AM + - file_name: nm_trips_am.omx + tables: + - name: WALK + data_field: WALK_AM + - name: BIKE + data_field: BIKE_AM + - file_name: trn_trips_am.omx + tables: + - name: WALK_AB + data_field: WALK_AB_AM + - name: WALK_BM + data_field: WALK_BM_AM + - name: WALK_MR + data_field: WALK_MR_AM + - name: WALK_CR + data_field: WALK_CR_AM + - name: PNR_AB + data_field: PNR_AB_AM + - name: PNR_BM + data_field: PNR_BM_AM + - name: PNR_MR + data_field: PNR_MR_AM + - name: PNR_CR + data_field: PNR_CR_AM + - name: KNR_AB + data_field: KNR_AB_AM + - name: KNR_BM + data_field: KNR_BM_AM + - name: KNR_MR + data_field: KNR_MR_AM + - name: PNRE_AB + data_field: PNRE_AB_AM + - name: PNRE_BM + data_field: PNRE_BM_AM + - name: PNRE_MR + data_field: PNRE_MR_AM + - name: PNRE_CR + data_field: PNRE_CR_AM + - name: KNRE_AB + data_field: KNRE_AB_AM + - name: KNRE_BM + data_field: KNRE_BM_AM + - name: KNRE_MR + data_field: KNRE_MR_AM + - file_name: sb_trips_am.omx + tables: + - name: SCHOOLBUS + data_field: SCHOOLBUS_AM + - file_name: auto_trips_md.omx + tables: + - name: DRIVEALONE + data_field: DRIVEALONE_MD + - name: SHARED2 + data_field: SHARED2_MD + - name: SHARED3 + data_field: SHARED3_MD + - file_name: nm_trips_md.omx + tables: + - name: WALK + data_field: WALK_MD + - name: BIKE + data_field: BIKE_MD + - file_name: trn_trips_md.omx + tables: + - name: WALK_AB + data_field: WALK_AB_MD + - name: WALK_BM + data_field: WALK_BM_MD + - name: WALK_MR + data_field: WALK_MR_MD + - name: WALK_CR + data_field: WALK_CR_MD + - name: PNR_AB + data_field: PNR_AB_MD + - name: PNR_BM + data_field: PNR_BM_MD + - name: PNR_MR + data_field: PNR_MR_MD + - name: PNR_CR + data_field: PNR_CR_MD + - name: KNR_AB + data_field: KNR_AB_MD + - name: KNR_BM + data_field: KNR_BM_MD + - name: KNR_MR + data_field: KNR_MR_MD + - name: PNRE_AB + data_field: PNRE_AB_MD + - name: PNRE_BM + data_field: PNRE_BM_MD + - name: PNRE_MR + data_field: PNRE_MR_MD + - name: PNRE_CR + data_field: PNRE_CR_MD + - name: KNRE_AB + data_field: KNRE_AB_MD + - name: KNRE_BM + data_field: KNRE_BM_MD + - name: KNRE_MR + data_field: KNRE_MR_MD + - file_name: sb_trips_md.omx + tables: + - name: SCHOOLBUS + data_field: SCHOOLBUS_MD + - file_name: auto_trips_pm.omx + tables: + - name: DRIVEALONE + data_field: DRIVEALONE_PM + - name: SHARED2 + data_field: SHARED2_PM + - name: SHARED3 + data_field: SHARED3_PM + - file_name: nm_trips_pm.omx + tables: + - name: WALK + data_field: WALK_PM + - name: BIKE + data_field: BIKE_PM + - file_name: trn_trips_pm.omx + tables: + - name: WALK_AB + data_field: WALK_AB_PM + - name: WALK_BM + data_field: WALK_BM_PM + - name: WALK_MR + data_field: WALK_MR_PM + - name: WALK_CR + data_field: WALK_CR_PM + - name: PNR_AB + data_field: PNR_AB_PM + - name: PNR_BM + data_field: PNR_BM_PM + - name: PNR_MR + data_field: PNR_MR_PM + - name: PNR_CR + data_field: PNR_CR_PM + - name: KNR_AB + data_field: KNR_AB_PM + - name: KNR_BM + data_field: KNR_BM_PM + - name: KNR_MR + data_field: KNR_MR_PM + - name: PNRE_AB + data_field: PNRE_AB_PM + - name: PNRE_BM + data_field: PNRE_BM_PM + - name: PNRE_MR + data_field: PNRE_MR_PM + - name: PNRE_CR + data_field: PNRE_CR_PM + - name: KNRE_AB + data_field: KNRE_AB_PM + - name: KNRE_BM + data_field: KNRE_BM_PM + - name: KNRE_MR + data_field: KNRE_MR_PM + - file_name: sb_trips_pm.omx + tables: + - name: SCHOOLBUS + data_field: SCHOOLBUS_PM + - file_name: auto_trips_nt.omx + tables: + - name: DRIVEALONE + data_field: DRIVEALONE_NT + - name: SHARED2 + data_field: SHARED2_NT + - name: SHARED3 + data_field: SHARED3_NT + - file_name: nm_trips_nt.omx + tables: + - name: WALK + data_field: WALK_NT + - name: BIKE + data_field: BIKE_NT + - file_name: trn_trips_nt.omx + tables: + - name: WALK_AB + data_field: WALK_AB_NT + - name: WALK_BM + data_field: WALK_BM_NT + - name: WALK_MR + data_field: WALK_MR_NT + - name: WALK_CR + data_field: WALK_CR_NT + - name: PNR_AB + data_field: PNR_AB_NT + - name: PNR_BM + data_field: PNR_BM_NT + - name: PNR_MR + data_field: PNR_MR_NT + - name: PNR_CR + data_field: PNR_CR_NT + - name: KNR_AB + data_field: KNR_AB_NT + - name: KNR_BM + data_field: KNR_BM_NT + - name: KNR_MR + data_field: KNR_MR_NT + - name: PNRE_AB + data_field: PNRE_AB_NT + - name: PNRE_BM + data_field: PNRE_BM_NT + - name: PNRE_MR + data_field: PNRE_MR_NT + - name: PNRE_CR + data_field: PNRE_CR_NT + - name: KNRE_AB + data_field: KNRE_AB_NT + - name: KNRE_BM + data_field: KNRE_BM_NT + - name: KNRE_MR + data_field: KNRE_MR_NT + - file_name: sb_trips_nt.omx + tables: + - name: SCHOOLBUS + data_field: SCHOOLBUS_NT + +CONSTANTS: + time_periods: + AM: + first_hour: 7 + last_hour: 12 + MD: + first_hour: 13 + last_hour: 24 + PM: + first_hour: 25 + last_hour: 32 + NT: + first_hour: 33 + last_hour: 6 + + # SHARED2 and SHARED2 Occupancies + OCC_SHARED2: 2.0 + OCC_SHARED3: 3.33 diff --git a/activitysim/examples/prototype_mwcog/configs/write_trip_matrices_annotate_trips_preprocessor.csv b/activitysim/examples/prototype_mwcog/configs/write_trip_matrices_annotate_trips_preprocessor.csv new file mode 100644 index 000000000..f56185ddc --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs/write_trip_matrices_annotate_trips_preprocessor.csv @@ -0,0 +1,109 @@ +Description,Target,Expression +# add additional fields,, +,tour_participants,trips.tour_id.map(tours.number_of_participants) +,distance,od_skims['DIST'] +# code time periods,, +,is_am,"trips.depart.between(time_periods['AM']['first_hour'], time_periods['AM']['last_hour'])" +,is_md,"trips.depart.between(time_periods['MD']['first_hour'], time_periods['MD']['last_hour'])" +,is_pm,"trips.depart.between(time_periods['PM']['first_hour'], time_periods['PM']['last_hour'])" +,is_nt,(trips.depart >= time_periods['NT']['first_hour']) | (trips.depart <= time_periods['NT']['last_hour']) +# am trips,, +,DRIVEALONE_AM,((trips.trip_mode == 'DRIVEALONE') & is_am) * tour_participants +,SHARED2_AM,"((trips.trip_mode.isin(['SHARED2', 'TAXI', 'TNC_SINGLE'])) & is_am) * tour_participants / OCC_SHARED2" +,SHARED3_AM,"((trips.trip_mode.isin(['SHARED3', 'TNC_SHARED'])) & is_am) * tour_participants / OCC_SHARED3" +,WALK_AM,((trips.trip_mode == 'WALK') & is_am) * tour_participants +,BIKE_AM,((trips.trip_mode == 'BIKE') & is_am) * tour_participants +,WALK_AB_AM,((trips.trip_mode == 'WALK_AB') & is_am) * tour_participants +,WALK_BM_AM,((trips.trip_mode == 'WALK_BM') & is_am) * tour_participants +,WALK_MR_AM,((trips.trip_mode == 'WALK_MR') & is_am) * tour_participants +,WALK_CR_AM,((trips.trip_mode == 'WALK_CR') & is_am) * tour_participants +,PNR_AB_AM,((trips.trip_mode == 'PNR_AB') & is_am & trips.outbound) * tour_participants +,PNR_BM_AM,((trips.trip_mode == 'PNR_BM') & is_am & trips.outbound) * tour_participants +,PNR_MR_AM,((trips.trip_mode == 'PNR_MR') & is_am & trips.outbound) * tour_participants +,PNR_CR_AM,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_am & trips.outbound) * tour_participants" +,KNR_AB_AM,((trips.trip_mode == 'KNR_AB') & is_am & trips.outbound) * tour_participants +,KNR_BM_AM,((trips.trip_mode == 'KNR_BM') & is_am & trips.outbound) * tour_participants +,KNR_MR_AM,((trips.trip_mode == 'KNR_MR') & is_am & trips.outbound) * tour_participants +,PNRE_AB_AM,((trips.trip_mode == 'PNR_AB') & is_am & ~trips.outbound) * tour_participants +,PNRE_BM_AM,((trips.trip_mode == 'PNR_BM') & is_am & ~trips.outbound) * tour_participants +,PNRE_MR_AM,((trips.trip_mode == 'PNR_MR') & is_am & ~trips.outbound) * tour_participants +,PNRE_CR_AM,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_am & ~trips.outbound) * tour_participants" +,KNRE_AB_AM,((trips.trip_mode == 'KNR_AB') & is_am & ~trips.outbound) * tour_participants +,KNRE_BM_AM,((trips.trip_mode == 'KNR_BM') & is_am & ~trips.outbound) * tour_participants +,KNRE_MR_AM,((trips.trip_mode == 'KNR_MR') & is_am & ~trips.outbound) * tour_participants +,SCHOOLBUS_AM,((trips.trip_mode == 'SCHOOLBUS') & is_am) * tour_participants +# md trips,, +,DRIVEALONE_MD,((trips.trip_mode == 'DRIVEALONE') & is_md) * tour_participants +,SHARED2_MD,"((trips.trip_mode.isin(['SHARED2', 'TAXI', 'TNC_SINGLE'])) & is_md) * tour_participants / OCC_SHARED2" +,SHARED3_MD,"((trips.trip_mode.isin(['SHARED3', 'TNC_SHARED'])) & is_md) * tour_participants / OCC_SHARED3" +,WALK_MD,((trips.trip_mode == 'WALK') & is_md) * tour_participants +,BIKE_MD,((trips.trip_mode == 'BIKE') & is_md) * tour_participants +,WALK_AB_MD,((trips.trip_mode == 'WALK_AB') & is_md) * tour_participants +,WALK_BM_MD,((trips.trip_mode == 'WALK_BM') & is_md) * tour_participants +,WALK_MR_MD,((trips.trip_mode == 'WALK_MR') & is_md) * tour_participants +,WALK_CR_MD,((trips.trip_mode == 'WALK_CR') & is_md) * tour_participants +,PNR_AB_MD,((trips.trip_mode == 'PNR_AB') & is_md & trips.outbound) * tour_participants +,PNR_BM_MD,((trips.trip_mode == 'PNR_BM') & is_md & trips.outbound) * tour_participants +,PNR_MR_MD,((trips.trip_mode == 'PNR_MR') & is_md & trips.outbound) * tour_participants +,PNR_CR_MD,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_md & trips.outbound) * tour_participants" +,KNR_AB_MD,((trips.trip_mode == 'KNR_AB') & is_md & trips.outbound) * tour_participants +,KNR_BM_MD,((trips.trip_mode == 'KNR_BM') & is_md & trips.outbound) * tour_participants +,KNR_MR_MD,((trips.trip_mode == 'KNR_MR') & is_md & trips.outbound) * tour_participants +,PNRE_AB_MD,((trips.trip_mode == 'PNR_AB') & is_md & ~trips.outbound) * tour_participants +,PNRE_BM_MD,((trips.trip_mode == 'PNR_BM') & is_md & ~trips.outbound) * tour_participants +,PNRE_MR_MD,((trips.trip_mode == 'PNR_MR') & is_md & ~trips.outbound) * tour_participants +,PNRE_CR_MD,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_md & ~trips.outbound) * tour_participants" +,KNRE_AB_MD,((trips.trip_mode == 'KNR_AB') & is_md & ~trips.outbound) * tour_participants +,KNRE_BM_MD,((trips.trip_mode == 'KNR_BM') & is_md & ~trips.outbound) * tour_participants +,KNRE_MR_MD,((trips.trip_mode == 'KNR_MR') & is_md & ~trips.outbound) * tour_participants +,SCHOOLBUS_MD,((trips.trip_mode == 'SCHOOLBUS') & is_md) * tour_participants +# pm trips,, +,DRIVEALONE_PM,((trips.trip_mode == 'DRIVEALONE') & is_pm) * tour_participants +,SHARED2_PM,"((trips.trip_mode.isin(['SHARED2', 'TAXI', 'TNC_SINGLE'])) & is_pm) * tour_participants / OCC_SHARED2" +,SHARED3_PM,"((trips.trip_mode.isin(['SHARED3', 'TNC_SHARED'])) & is_pm) * tour_participants / OCC_SHARED3" +,WALK_PM,((trips.trip_mode == 'WALK') & is_pm) * tour_participants +,BIKE_PM,((trips.trip_mode == 'BIKE') & is_pm) * tour_participants +,WALK_AB_PM,((trips.trip_mode == 'WALK_AB') & is_pm) * tour_participants +,WALK_BM_PM,((trips.trip_mode == 'WALK_BM') & is_pm) * tour_participants +,WALK_MR_PM,((trips.trip_mode == 'WALK_MR') & is_pm) * tour_participants +,WALK_CR_PM,((trips.trip_mode == 'WALK_CR') & is_pm) * tour_participants +,PNR_AB_PM,((trips.trip_mode == 'PNR_AB') & is_pm & trips.outbound) * tour_participants +,PNR_BM_PM,((trips.trip_mode == 'PNR_BM') & is_pm & trips.outbound) * tour_participants +,PNR_MR_PM,((trips.trip_mode == 'PNR_MR') & is_pm & trips.outbound) * tour_participants +,PNR_CR_PM,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_pm & trips.outbound) * tour_participants" +,KNR_AB_PM,((trips.trip_mode == 'KNR_AB') & is_pm & trips.outbound) * tour_participants +,KNR_BM_PM,((trips.trip_mode == 'KNR_BM') & is_pm & trips.outbound) * tour_participants +,KNR_MR_PM,((trips.trip_mode == 'KNR_MR') & is_pm & trips.outbound) * tour_participants +,PNRE_AB_PM,((trips.trip_mode == 'PNR_AB') & is_pm & ~trips.outbound) * tour_participants +,PNRE_BM_PM,((trips.trip_mode == 'PNR_BM') & is_pm & ~trips.outbound) * tour_participants +,PNRE_MR_PM,((trips.trip_mode == 'PNR_MR') & is_pm & ~trips.outbound) * tour_participants +,PNRE_CR_PM,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_pm & ~trips.outbound) * tour_participants" +,KNRE_AB_PM,((trips.trip_mode == 'KNR_AB') & is_pm & ~trips.outbound) * tour_participants +,KNRE_BM_PM,((trips.trip_mode == 'KNR_BM') & is_pm & ~trips.outbound) * tour_participants +,KNRE_MR_PM,((trips.trip_mode == 'KNR_MR') & is_pm & ~trips.outbound) * tour_participants +,SCHOOLBUS_PM,((trips.trip_mode == 'SCHOOLBUS') & is_pm) * tour_participants +# nt trips,, +,DRIVEALONE_NT,((trips.trip_mode == 'DRIVEALONE') & is_nt) * tour_participants +,SHARED2_NT,"((trips.trip_mode.isin(['SHARED2', 'TAXI', 'TNC_SINGLE'])) & is_nt) * tour_participants / OCC_SHARED2" +,SHARED3_NT,"((trips.trip_mode.isin(['SHARED3', 'TNC_SHARED'])) & is_nt) * tour_participants / OCC_SHARED3" +,WALK_NT,((trips.trip_mode == 'WALK') & is_nt) * tour_participants +,BIKE_NT,((trips.trip_mode == 'BIKE') & is_nt) * tour_participants +,WALK_AB_NT,((trips.trip_mode == 'WALK_AB') & is_nt) * tour_participants +,WALK_BM_NT,((trips.trip_mode == 'WALK_BM') & is_nt) * tour_participants +,WALK_MR_NT,((trips.trip_mode == 'WALK_MR') & is_nt) * tour_participants +,WALK_CR_NT,((trips.trip_mode == 'WALK_CR') & is_nt) * tour_participants +,PNR_AB_NT,((trips.trip_mode == 'PNR_AB') & is_nt & trips.outbound) * tour_participants +,PNR_BM_NT,((trips.trip_mode == 'PNR_BM') & is_nt & trips.outbound) * tour_participants +,PNR_MR_NT,((trips.trip_mode == 'PNR_MR') & is_nt & trips.outbound) * tour_participants +,PNR_CR_NT,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_nt & trips.outbound) * tour_participants" +,KNR_AB_NT,((trips.trip_mode == 'KNR_AB') & is_nt & trips.outbound) * tour_participants +,KNR_BM_NT,((trips.trip_mode == 'KNR_BM') & is_nt & trips.outbound) * tour_participants +,KNR_MR_NT,((trips.trip_mode == 'KNR_MR') & is_nt & trips.outbound) * tour_participants +,PNRE_AB_NT,((trips.trip_mode == 'PNR_AB') & is_nt & ~trips.outbound) * tour_participants +,PNRE_BM_NT,((trips.trip_mode == 'PNR_BM') & is_nt & ~trips.outbound) * tour_participants +,PNRE_MR_NT,((trips.trip_mode == 'PNR_MR') & is_nt & ~trips.outbound) * tour_participants +,PNRE_CR_NT,"((trips.trip_mode.isin(['PNR_CR', 'KNR_CR'])) & is_nt & ~trips.outbound) * tour_participants" +,KNRE_AB_NT,((trips.trip_mode == 'KNR_AB') & is_nt & ~trips.outbound) * tour_participants +,KNRE_BM_NT,((trips.trip_mode == 'KNR_BM') & is_nt & ~trips.outbound) * tour_participants +,KNRE_MR_NT,((trips.trip_mode == 'KNR_MR') & is_nt & ~trips.outbound) * tour_participants +,SCHOOLBUS_NT,((trips.trip_mode == 'SCHOOLBUS') & is_nt) * tour_participants diff --git a/activitysim/examples/prototype_mwcog/configs_mp/logging.yaml b/activitysim/examples/prototype_mwcog/configs_mp/logging.yaml new file mode 100644 index 000000000..e932009c5 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs_mp/logging.yaml @@ -0,0 +1,57 @@ +# Config for logging +# ------------------ +# See http://docs.python.org/2.7/library/logging.config.html#configuration-dictionary-schema + +logging: + version: 1 + disable_existing_loggers: true + + + # Configuring the default (root) logger is highly recommended + root: + level: DEBUG + handlers: [console, logfile] + + loggers: + + activitysim: + level: DEBUG + handlers: [console, logfile] + propagate: false + + orca: + level: WARNING + handlers: [console, logfile] + propagate: false + + handlers: + + logfile: + class: logging.FileHandler + filename: !!python/object/apply:activitysim.core.config.log_file_path ['activitysim.log'] + mode: w + formatter: fileFormatter + level: NOTSET + + console: + class: logging.StreamHandler + stream: ext://sys.stdout + formatter: simpleFormatter + #level: NOTSET + level: !!python/object/apply:activitysim.core.mp_tasks.if_sub_task [WARNING, NOTSET] + + formatters: + + simpleFormatter: + class: logging.Formatter + #format: '%(processName)-10s %(levelname)s - %(name)s - %(message)s' + format: !!python/object/apply:activitysim.core.mp_tasks.if_sub_task [ + '%(processName)-10s %(levelname)s - %(name)s - %(message)s', + '%(levelname)s - %(name)s - %(message)s'] + datefmt: '%d/%m/%Y %H:%M:%S' + + fileFormatter: + class: logging.Formatter + format: '%(asctime)s - %(levelname)s - %(name)s - %(message)s' + datefmt: '%d/%m/%Y %H:%M:%S' + diff --git a/activitysim/examples/prototype_mwcog/configs_mp/settings.yaml b/activitysim/examples/prototype_mwcog/configs_mp/settings.yaml new file mode 100644 index 000000000..04aa781d7 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs_mp/settings.yaml @@ -0,0 +1,92 @@ +# Configs File with Sample Rate set by Model Runner +inherit_settings: True +# raise error if any sub-process fails without waiting for others to complete +fail_fast: True +# - ------------------------- dev config +multiprocess: True +strict: False +mem_tick: 30 +use_shadow_pricing: False +## - example sample +households_sample_size: 0 +chunk_size: 200_000_000_000 +#chunk_size: 0 +chunk_training_mode: production +num_processes: 20 +# - tracing +#trace_hh_id: 1205209 +trace_hh_id: 1086014 +trace_od: +#trace_hh_id: 1482966 +#trace_od: [5, 11] +# to resume after last successful checkpoint, specify resume_after: _ +resume_after: +models: + ### mp_initialize step + - initialize_landuse + - compute_accessibility + - initialize_households + ### mp_households step + - school_location + - workplace_location + - work_from_home + - transit_pass_subsidy + - transit_pass_ownership + - auto_ownership_simulate + - free_parking + - telecommute_frequency + - cdap_simulate + - mandatory_tour_frequency + - mandatory_tour_scheduling + - joint_tour_frequency + - joint_tour_composition + - joint_tour_participation + - joint_tour_destination + - joint_tour_scheduling + - non_mandatory_tour_frequency + - non_mandatory_tour_destination + - non_mandatory_tour_scheduling + - tour_mode_choice_simulate + - atwork_subtour_frequency + - atwork_subtour_destination + - atwork_subtour_scheduling + - atwork_subtour_mode_choice + - stop_frequency + - trip_purpose + - trip_destination + - trip_purpose_and_destination + - trip_scheduling + - trip_mode_choice + ### mp_summarize step + - write_data_dictionary + - write_tables + - write_trip_matrices +multiprocess_steps: + - name: mp_initialize + begin: initialize_landuse + - name: mp_households + begin: school_location + slice: + tables: + - households + - persons + - name: mp_summarize + begin: write_data_dictionary +output_tables: + action: include + prefix: final_ + tables: + - checkpoints + - accessibility + - land_use + - households + - persons + - tours + - trips + - school_shadow_prices + - workplace_shadow_prices + - joint_tour_participants +# read cached skims (using numpy memmap) from output directory (memmap is faster than omx ) +#read_skim_cache: True +# write memmapped cached skims to output directory after reading from omx, for use in subsequent runs +#write_skim_cache: True diff --git a/activitysim/examples/prototype_mwcog/configs_mp/settings_source.yaml b/activitysim/examples/prototype_mwcog/configs_mp/settings_source.yaml new file mode 100644 index 000000000..63db1d86e --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs_mp/settings_source.yaml @@ -0,0 +1,95 @@ +inherit_settings: True + +# raise error if any sub-process fails without waiting for others to complete +fail_fast: True + +# - ------------------------- dev config +multiprocess: True +strict: False +mem_tick: 30 +use_shadow_pricing: False + + +## - example sample +households_sample_size: %sample_size% +chunk_size: 200_000_000_000 +#chunk_size: 0 +chunk_training_mode: %training_mode% +num_processes: 20 +# - tracing +#trace_hh_id: 1205209 +trace_hh_id: 1086014 +trace_od: +#trace_hh_id: 1482966 +#trace_od: [5, 11] +# to resume after last successful checkpoint, specify resume_after: _ +resume_after: +models: + ### mp_initialize step + - initialize_landuse + - compute_accessibility + - initialize_households + ### mp_households step + - school_location + - workplace_location + - work_from_home + - transit_pass_subsidy + - transit_pass_ownership + - auto_ownership_simulate + - free_parking + - telecommute_frequency + - cdap_simulate + - mandatory_tour_frequency + - mandatory_tour_scheduling + - joint_tour_frequency + - joint_tour_composition + - joint_tour_participation + - joint_tour_destination + - joint_tour_scheduling + - non_mandatory_tour_frequency + - non_mandatory_tour_destination + - non_mandatory_tour_scheduling + - tour_mode_choice_simulate + - atwork_subtour_frequency + - atwork_subtour_destination + - atwork_subtour_scheduling + - atwork_subtour_mode_choice + - stop_frequency + - trip_purpose + - trip_destination + - trip_purpose_and_destination + - trip_scheduling + - trip_mode_choice + ### mp_summarize step + - write_data_dictionary + - write_tables + - write_trip_matrices +multiprocess_steps: + - name: mp_initialize + begin: initialize_landuse + - name: mp_households + begin: school_location + slice: + tables: + - households + - persons + - name: mp_summarize + begin: write_data_dictionary +output_tables: + action: include + prefix: final_ + tables: + - checkpoints + - accessibility + - land_use + - households + - persons + - tours + - trips + - school_shadow_prices + - workplace_shadow_prices + - joint_tour_participants +# read cached skims (using numpy memmap) from output directory (memmap is faster than omx ) +#read_skim_cache: True +# write memmapped cached skims to output directory after reading from omx, for use in subsequent runs +#write_skim_cache: True diff --git a/activitysim/examples/prototype_mwcog/configs_mp/shadow_pricing.yaml b/activitysim/examples/prototype_mwcog/configs_mp/shadow_pricing.yaml new file mode 100644 index 000000000..fda98f4d4 --- /dev/null +++ b/activitysim/examples/prototype_mwcog/configs_mp/shadow_pricing.yaml @@ -0,0 +1,37 @@ + +inherit_settings: True + +shadow_pricing_models: + school: school_location + workplace: workplace_location + +# global switch to enable/disable loading of saved shadow prices +# (ignored if global use_shadow_pricing switch is False) +LOAD_SAVED_SHADOW_PRICES: False + +# number of shadow price iterations for cold start +MAX_ITERATIONS: 10 + +# number of shadow price iterations for warm start (after loading saved shadow_prices) +MAX_ITERATIONS_SAVED: 1 + +# ignore criteria for zones smaller than size_threshold +SIZE_THRESHOLD: 10 + +# zone passes if modeled is within percent_tolerance of predicted_size +PERCENT_TOLERANCE: 5 + +# max percentage of zones allowed to fail +FAIL_THRESHOLD: 1 + +# CTRAMP or daysim +SHADOW_PRICE_METHOD: ctramp +#SHADOW_PRICE_METHOD: daysim + +# ctramp-style shadow_pricing_method parameters +DAMPING_FACTOR: 1 + +# daysim-style shadow_pricing_method parameters +# FIXME should these be the same as PERCENT_TOLERANCE and FAIL_THRESHOLD above? +DAYSIM_ABSOLUTE_TOLERANCE: 50 +DAYSIM_PERCENT_TOLERANCE: 10 diff --git a/activitysim/examples/prototype_mwcog/data/LU_taz3722_rnd91a_2018_adj_enrollment.csv b/activitysim/examples/prototype_mwcog/data/LU_taz3722_rnd91a_2018_adj_enrollment.csv new file mode 100644 index 000000000..db0b013fb --- /dev/null +++ b/activitysim/examples/prototype_mwcog/data/LU_taz3722_rnd91a_2018_adj_enrollment.csv @@ -0,0 +1,54 @@ +TAZ,HH,HHPOP,GQPOP,TOTPOP,TOTEMP,INDEMP,RETEMP,OFFEMP,OTHEMP,JURCODE,LANDAREA,HHINCIDX,ADISTTOX,TAZXCRD,TAZYCRD,K_8,G9_12,COLLEGE,Park_Acres,GC_Acres,PRKCST,OPRKCST,TERMINAL,AREATYPE +1,0,0,0,0,12623,29,149,11731,714,0,0.0424,10,29.08,1298543,446898,0,0,0,2.906924,0.0,117.875,200,5,1 +2,0,0,0,0,0,0,0,0,0,0,0.1553,5,29.28,1298807,445281,0,0,0,106.70806699999999,0.0,103.75,200,5,1 +7,0,0,0,0,0,0,0,0,0,0,0.0814,10,29.09,1299596,445915,0,0,0,51.717837,0.0,116.125,200,5,1 +8,0,0,0,0,0,0,0,0,0,0,0.0708,10,28.68,1301916,446878,0,0,0,42.722665,0.0,126.5,200,5,1 +9,0,0,0,0,837,32,32,679,94,0,0.1368,10,28.9,1302004,445336,0,0,0,91.542163,0.0,118.75,200,5,1 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