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Statistical analysis of resilience in an air transport network

  • Guoqiang Xu
  • , Xuejun Zhang*
  • *Corresponding author for this work
  • Beihang University
  • Beijing Key Laboratory for Network-based Cooperative Air Traffic Management

Research output: Contribution to journalArticlepeer-review

Abstract

The resilience of an air transport network represents its ability to adapt and stay operational at the required level of safety and efficiency during the impact of various disturbances. These disturbances, which can compromise the resilience of a given air transport network, include inclement weather conditions, human-intended interruptions (such as terrorist attacks, air traffic controller strikes, or pilots strikes), or unexpected mechanical failures (such as aircraft component breakdown or runway system failures). The mitigating actions such as delaying, canceling, and rerouting affected flights aim at maintaining both the network’s resilience and safety at the acceptable level under given conditions. It is of great significance to understand and quantify resilience in the complex socio-technical air transport network, which has attracted extensive attentions. In this study, statistical analysis of China air traffic data is applied to investigate the emergence of resilience in the air transport network. The Granger causality test is adopted to evaluate the causality relationship between different elements of a complex system. We construct the hourly delay propagation networks and analyze the resilience of the air transport system through the evolution of delay propagation networks. The useful measurement metric of resilience is proposed, and evolution patterns of generation and recovery of flight delays are also investigated. In addition, the relationship between initial delay, scheduled flights, and resilience loss is studied to reveal further understanding of resilience in the air transport system.

Original languageEnglish
Article number969311
JournalFrontiers in Physics
Volume10
DOIs
StatePublished - 4 Oct 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions

Keywords

  • Granger causality
  • air transport network
  • complex network theory
  • resilience
  • statistical analysis

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