The goal of this challenge is to automatically predict airport configuration changes from data sources including air traffic and weather. Better algorithms for predicting future airport configurations can support critical decisions, reduce costs and fuel use, and mitigate delays across the national airspace network.
Coordinating our nation’s airways is the role of the National Airspace System (NAS): “a network of both controlled and uncontrolled airspace, both domestic and oceanic.” The NAS is arguably the most complex transportation system in the world. Operational changes can save or cost airlines, taxpayers, consumers, and the economy at large thousands to millions of dollars on a regular basis. It is critical that decisions to change procedures are done with as much lead time and certainty as possible. The NAS is investing in new ways to bring vast amounts of data together with state-of-the-art machine learning to improve air travel for everyone.
An important part of this equation is airport configuration, the combination of runways used for arrivals and departures and the flow direction on those runways. For example, one configuration may use a set of runways in a north-to-south flow (or just “south flow”) while another uses south-to-north flow (“north flow”). Air traffic officials may perform an airport configuration change depending on weather, traffic, or other inputs.
These changes can result in delays to flights, which may have to alter their flight paths well ahead of reaching the airport to get into the correct alignment or enter holding patterns in the air as the flows are altered. The decisions to change the airport configuration are driven by data and observations, meaning it is possible to predict these changes in advance and give flight operators time to adjust schedules, avoiding delays and wasted fuel.
All eligible participants are invited to register to participate in the Open Arena.
For this challenge, cash prizes are restricted to Official Representatives (individual participants or team leads, in the case of a group project) who, at the time of entry, are age 18 or older, a U.S. citizen or permanent resident of the United States or its territories, and are affiliated with an accredited U.S. university either as an enrolled student or faculty member. Proof of enrollment or employment is required to demonstrate university affiliation.
For complete rules on eligibility and prizes see the Competition Rules.
This challenge features two competition arenas which provide different access levels and capabilities.
The Open arena is the first step in the competition process. Here all participants can enter the outputs of their solutions-in-development to see how they fare against others on the open leaderboard.
After submitting proof of eligibility, you will be able to access the Prescreened arena. Here participants can continue to tweak their solutions, submit their executable code, and see how they perform on the prescreened leaderboard. A submission to the Prescreened arena is required to be eligible for prizes.
Available to all registered participants
Access the public ground truth data
Submit CSV files with predictions for the leaderboard set
View the open leaderboard with live results from the best-scoring submissions
Available to approved university-affiliated participants
Access the public ground truth data
Submit trained models and code to run in the cloud
View the prescreened leaderboard with live results from the best-scoring submissions
Submit Final Scoring code submissions
Only participants in the Prescreened Arena will be eligible to win Final Scoring prizes. For more information on staging, submissions, check out the challenge guidelines.
Awards:- Total: $40,000