README.md

POLIDriving

POLIDriving is an 18-hour driving dataset with data from five heterogeneous sources (driver, vehicle, weather conditions, traffic accidents, and road geometrics characteristics). It contains around 61k observations and 32 attributes. Additionally, it contains 1980 labeled observations with four classes (low, medium, high, and very high) that represent the risk levels of suffering a traffic accident. Data was collected using an OBD-II scanner, a GPS receiver, and a health monitor. Four CUV, PICKUP, and SEDAN-type vehicles were used in the acquisition sessions. Finally, two routes through roads with high traffic accident rates and heavy traffic in the urban area of Quito (Ecuador) were considered for the acquisition sessions.

Dataset structure

Directory structure

POLIDriving contains driving data from 5 drivers (alonso, andres, pablo, richard, and yolanda) and also synthetic data from one unreal driver (furious).

The folder structure of POLIDriving is the following.

dataset
|
+-- alonso
|   |
|   +-- 20231229_151643
|       |
|       +-- 2023-12-29 15-16-43.csv (raw vehicle data)
|       +-- 20231229_151643_col.csv (consolidated data file)
|       +-- 20231229_151643_pre.csv (data file after preprocessing)
|       +-- 13281086609_ACTIVITY-record.csv (driver's data from health monitor)
|   +-- 20240103_141959
|   +-- 20240208_120000
|   +-- 23241201_290300
+-- andres
+-- furious
+-- labeled
|       |
|       +-- 20240208-120000_lss.csv (labeled data using semi-supervised learning)
|       +-- 20240208-120000_vld.csv (labeled data verified by an expert)
+-- pablo
+-- richard
+-- yolanda

Data file format

Data files contain the following attributes.

#	Attribute	Class	Units	Data source
1	time	Timestamp		Vehicle data
2	speed	Numeric	km/h	Vehicle data
3	revolutions per minute	Numeric	rpm	Vehicle data
4	acceleration	Numeric	m/s2	Vehicle data
5	throttle position	Numeric	%	Vehicle data
6	engine temperature	Numeric	C	Vehicle data
7	system voltage	Numeric	volts	Vehicle data
8	distance traveled	Numeric	km	Vehicle data
9	engine load value	Numeric	%	Vehicle data
10	latitude	Numeric		Vehicle data
11	longitude	Numeric		Vehicle data
12	altitude	Numeric	m	Vehicle data
13	id vehicle	Numeric		Vehicle data
14	heart rate	Numeric	bpm	Driver's data
15	body temperature	Numeric	C	Driver's data
16	id driver	Numeric		Driver's data
17	current weather	Categorical		Weather data
18	has precipitation	Boolean		Weather data
19	is day time	Boolean		Weather data
20	temperature	Numeric	C	Weather data
21	wind speed	Numeric	km/h	Weather data
22	wind direction	Numeric		Weather data
23	relative humidity	Numeric	%	Weather data
24	visibility	Numeric	km	Weather data
25	uv index	Numeric		Weather data
26	cloud cover	Numeric		Weather data
27	ceiling	Numeric	m	Weather data
28	pressure	Numeric	mb	Weather data
29	precipitation	Numeric	mm	Weather data
30	accidents on site	Numeric	deaths	Traffic accidents
31	design speed	Numeric	km/h	Road geometrics characteristics
32	accidents time	Numeric	deaths	Road geometrics characteristics

Publication

If you use POLIDriving in your research, please cite it as follows.

@article{marcillo2024polidriving,
title={POLIDriving: A Public-Access Driving Dataset for Road Traffic Safety Analysis},
author={Marcillo, Pablo and Arciniegas-Ayala, Cristian and Valdivieso Caraguay, {'A}ngel Leonardo and Sanchez-Gordon, Sandra and Hern{'a}ndez-{'A}lvarez, Myriam},
journal={Applied Sciences}, volume={14},
number={14},
pages={6300},
year={2024},
publisher={MDPI}
}

Downloads

The size of POLIDriving is about 150 MB.

Contact

For questions or suggestions, please contact [email protected]