The Digital Information Platform (DIP) Sub-Project of Air Traffic Management – eXploration (ATM-X) is seeking to make available in the National Airspace System a variety of live data feeds and services built on that data. The goal is to allow external partners to build advanced, data-driven services using this data and to make these services available to flight operators, who will use these capabilities to save fuel and avoid delays. Different wind directions, weather conditions at or near the airport, inoperative runway, etc., affects the runway configurations to be used and impacts the overall arrival throughputs. Knowing the arrival runway and its congestion level ahead of time will enable aviation operators to perform better flight planning and improve the flight efficiency. This competition seeks to make better predictions of runway throughputs using machine learning or other techniques. This competition engages students, faculty members, and other individuals employed by United States universities to develop a machine learning model that provides a short-term forecast of estimated airport runway throughput using simulated real-time information from historical NAS and weather forecast data, as well as other factors such as meteorological conditions, airport runway configuration, and airspace congestion.
Award: $120,000 in total prizes
Open Date: September 13, 2024
Close Date: December 8, 2024
For more information, visit: https://bitgrit.net/competition/23
