A spectral approach towards analyzing air traffic network disruptions

Abstract

© 2019 EUROCONTROL. All rights reserved. The networked nature of the air transportation system leads to systemwide delays and cancellations as a result of disruptions at an airport. A comprehensive analysis of system performance requires understanding the inherent interdependencies between various airports, in order to characterize off-nominal disruptions and to aid in recovery. In this work, we apply Graph Signal Processing (GSP) techniques to the analysis of flight delay networks, yielding two novel contributions: (1) We use the notion of the total variation (TV) of a graph signal in order to identify and quantify unexpected distributions of delays across airports; and (2) we present a spectral eigendecomposition analysis of airport disruption and delay networks. We investigate and characterize different patterns of delay distribution based on the relationship between TV and total delay, using 10 years worth of operational data from major US airports. We show that attributes of the resultant eigenvector modes and energy contributions are useful metrics to characterize specific disruptions caused by events such as nor’easters, Atlantic hurricanes, and equipment outages at airports.