Statistical Characterization of Airplane Delays

TL;DR

This paper provides a statistical analysis of airplane delays at UK airports, revealing power-law decay in large delays, pandemic-related changes, and a superstatistics model for delay distribution.

Contribution

It introduces a novel statistical framework for comparing delays across airlines and airports, including extreme events and superstatistics modeling.

Findings

Power-law decay in large delays

Significant delay changes during COVID-19

Delays modeled by superstatistics

Abstract

The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.