Help the National Airspace System (NAS) keep flights running on time! In this challenge you will use air traffic and weather data to automatically predict the time an aircraft pushes back from its gate. Accurate estimates of pushback time can help air traffic management systems more efficiently use the limited capacity of airports, runways and the National Airspace System.
This challenge features two competition arenas:
- Phase 1: Open Arena is available for all participants to work with the data and test their solutions to see how they fare against others on the open leaderboard.
- Phase 1: Prescreened Arena is available to prize eligibile participants to build out and submit code for their solutions.
- Phase 2 is available to prize eligibile finalists from Phase 1. To qualify for a prize, finalists will develop their winning models into a federated learning models.
For this challenge, cash prizes are restricted to individual participants or team leads who are a U.S. citizen or permanent resident and are affiliated with an accredited U.S. university.
Results
The challenge has ended! Phase 1 of the challenge generated over 450 submissions to predict pushback times. The top submission predicting pushback time achieved a mean absolute error of just over 10 minutes, compared to over 19 minutes for the benchmark. Phase 2 saw the top 5 teams incorporate federated learning into their winning solutions.
You can read more about the results of the challenge and meet the winning teams in the Meet the Finalists blog post and learn from their winning code and write-ups in the competition repo!
The competitions
Phase 2: Federated Learning
Welcome Phase 1 finalists to Phase 2 of the Predict Pushback Challenge! Now's your chance to explore translating your winning Phase 1 model into a decentralized federated learning model. #civic
Phase 1: Open Arena
START HERE! Accurate estimates of pushback time can help air traffic management systems more efficiently use the limited capacity of airports, runways and the National Airspace System. Use air traffic and weather data to automatically predict pushback time! #civic
Phase 1: Prescreened Arena
CALLING PRESCREENED PARTICIPANTS! Accurate estimates of pushback time can help air traffic management systems more efficiently use the limited capacity of airports, runways and the National Airspace System. Use air traffic and weather data to automatically predict pushback time! #civic