Machine Learning for Air Traffic Management

Airsense (a division of Airbus - München) organized this 2 day ADS-B Hackathon at Airbus Leadership University, Toulouse on Oct 29 and Oct 30, 2018. This repository is a collection of the various Machine Learning algorithms (such as LSTMs, MLPs and XGBoost) that I implemented for predicting various parameters related to Air Traffic Control such as Flight Trajectory, ETA and Runway Classification.

USER STORY - Runway and Holding Pattern Detection:

The participants had to pick a particular user story (team) and I joined the following team:

• Our Project Title: Runway and Holding analysis - LHR arrivals case
• My Task : Detect holding patterns and do runway classification with flight arrivals data for LHR (London Heathrow) airport.

Presentation Slides:https://diliprk.github.io/post/adsb_hackathon/