Measuring the resilience of an urban rail transit network: A multi-dimensional evaluation model

Zhiao Ma, Xin Yang, Jianjun Wu, Anthony Chen, Yun Wei, Ziyou Gao

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Once an urban rail transit (URT) system breaks down or is deliberately damaged, it will cause tremendous pressure on the whole urban transportation system. Hence, its ability to deal with incidents has become an important research field. Existing studies seldom consider the entire cycle of an incident and ignore changes in passenger travel behavior during emergency events. In this paper, resilience is defined as the ability of absorbing, resisting and recovering when the URT network fails. We propose a multi-dimensional evaluation model for measuring the resilience by calculating multiple abilities with consideration of multi-source data including passenger flow, train diagram, passenger travel choice behavior, network topology, etc. Finally, we present a case study based on real-world data from the Beijing Subway network to illustrate the effectiveness and applicability of the proposed model. Through the resilience analysis, we recognize the critical stations, measure emergency recovery ability and provide necessary information support for reducing the risk of URT incidents.

Original languageEnglish
Pages (from-to)38-50
Number of pages13
JournalTransport Policy
Publication statusPublished - Dec 2022


  • Multi-dimensional model
  • Multi-source data
  • Resilience evaluation
  • Urban rail transit

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation


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