Excess Delay from GDP: Measurement and Causal Analysis
This work addresses inefficiencies in air traffic management for aviation authorities and airlines, though it is incremental as it builds on existing GDP analysis with new measurement methods.
The paper measured excess delay caused by Ground Delay Programs (GDPs) at U.S. airports, finding a mean of 35.4 minutes per flight, and used ridge regression to identify factors like program settings and flight time variations that influence this delay.
Ground Delay Programs (GDPs) have been widely used to resolve excessive demand-capacity imbalances at arrival airports by shifting foreseen airborne delay to pre-departure ground delay. While offering clear safety and efficiency benefits, GDPs may also create additional delay because of imperfect execution and uncertainty in predicting arrival airport capacity. This paper presents a methodology for measuring excess delay resulting from individual GDPs and investigates factors that influence excess delay using regularized regression models. We measured excess delay for 1210 GDPs from 33 U.S. airports in 2019. On a per-restricted flight basis, the mean excess delay is 35.4 min with std of 20.6 min. In our regression analysis of the variation in excess delay, ridge regression is found to perform best. The factors affecting excess delay include time variations during gate out and taxi out for flights subject to the GDP, program rate setting and revisions, and GDP time duration.