An integrated model of flight and passenger delay for policy analysis in the National Air Transportation System

Demand for air travel has increased over the years and so have airport delays and congestion. Delays have a huge impact on airline costs and influence the satisfaction of passengers, thus becoming an important topic of research in the field of air transportation. In recent literature, a Passenger Delay Calculator (PDC) was proposed to estimate passenger delays. The PDC computes passenger delays for a specified day based on actual flight schedules, fight cancellation information, and ticket booking information. However, since actual fight schedules are a necessary input, the PDC cannot be applied directly to hypothetical scenarios, in which different cancellation strategies are implemented and their impact on passenger delays are evaluated. A different model. Airport Network Delays (AND), has also been developed recently. The AND model estimates fight delays and relies on an input in which demand consists of the national planned fight schedule for any given day. In this thesis, we have attempted to incorporate these two models, the AND and the PDC, within a single framework, so that the resulting new integrated model can compute passenger delays without requiring an actual flight-schedule input. The integrated model would certainly increase the usefulness and applicability of the PDC since it could be used with hypothetical scenarios, different flight cancellation strategies, etc. We first describe the framework of the integrated model for studying flight delays and passenger delays at a daily scale. The integrated model includes four components: a Tail Recovery Model, Flight Cancellation Algorithms, a Refined Airport Network Delay (RAND) model, and the PDC. The Tail Recovery Model recovers missing tail numbers for many flights recorded in the Aviation System Performance Metrics (ASPM) database. The Flight Cancellation Algorithms implement alterna-