Estimation and Comparison of Impact of Single Airport Delay on National Airspace System with Multivariate Simultaneous Models

Abstract

U.S. air transport is under significant stress, experiencing frequent delays and high levels of congestion. At certain times, individual airports become bottlenecks within the National Airspace System (NAS). Major causes of flight delay at airports include overscheduling, en route convective weather, reduced ceiling and visibility around airports, and upstream delay propagation. Delay at one airport can be passed on to other airports in the NAS. Hence, to allocate resources for airport capacity expansion in an optimal way, the impact of single airport delay to the NAS and vice versa must be quantified. This research applies multivariate simultaneous regression models to quantify airport delay spillover effects across 34 of the 35 Operational Evolution Partnership airports and the rest of the NAS. This analysis considers such contributing factors as average daily arrival delay, deterministic queuing delay, weather patterns, aircraft equipment type, and others. The three-stage least-square method is used to regress the models and obtain coefficients for the multivariate equations. The outcomes are used to explain the interactions among airports in the NAS and to identify the major delay contributors at each.