Analysis of Aircraft Arrival and Departure Delay Characteristics

The increase in delays in the National Airspace System (NAS) has been the subject of several studies in recent years. These reports contain delay statistics over the entire NAS, along with some data specific to individual airports, however, a comprehensive characterization and comparison of the delay distributions is absent. Historical delay data for these airports are summarized. The various causal factors related to aircraft, airline operations, change of procedures and traffic volume are also discussed. Motivated by the desire to improve the accuracy of demand prediction in enroute sectors and at airports through probabilistic delay forecasting, this paper analyzes departure and arrival data for ten major airports in the United States that experience large volumes of traffic and significant delays. To enable such an analysis, several data fields for every aircraft departing from or arriving at these ten airports in a 21day period were extracted from the Post Operations Evaluation Tool (POET) database. Distributions that show the probability of a certain delay time for a given aircraft were created. These delay-time probability density functions were modeled using Normal and Poisson distributions with the mean and standard deviations derived from the raw data. The models were then improved by adjusting the mean and standard deviation values via a least squares method designed to minimize the fit error between the raw distribution and the model. It is shown that departure delay is better modeled using a Poisson distribution, while the enroute and arrival delays fit the Normal distribution better. Finally, correlation between the number of departures, number of arrivals and departure delays is examined from a time-series modeling perspective. 1.