Optimization-Based Analysis of Collaborative Airport Arrival Planning
Transportation Science
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ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 03
Distributed feedback control for an Eulerian model of the national airspace system
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The maintenance of airport acceptance rates for arrivals and departures is critical to the performance of the National Airspace System (NAS). This paper develops a novel automated decision support system, named ADTOS, intended to assist traffic flow management specialists select the most optimal arrival and departure strategies. We have built and maintained a data warehouse using streams of aviation data as part of an internal research and development project at Boeing Advanced Air Traffic Management in Chantilly, VA. ADTOS leverages this data warehouse, making use of Aircraft Situation Display to Industry (ASDI) surveillance, Meteorological Aerodrome Reports (METAR), Terminal Aerodrome Forecast (TAF) data, and runway configurations. The warehouse database architecture and the arrival/departure tradeoff optimization module is presented with a validation case study in which ADTOS is utilized for strategic planning of arrival and departure traffic and airport capacity from 1 hour to 24 hours into the future at Dulles International Airport (IAD). The experiments demonstrate ADTOS' capability for rapidly processing large amounts of streaming aviation data and effectiveness over the existing traffic flow management by increasing airport throughput and reducing traffic delays during the time period of interest. The paper also presents initial results of the case study.