Resiliency assessment of urban rail transit networks: Shanghai metro as an example

Zhang, Dong-ming, Du, Fei, Huang, Hongwei, Zhang, Fan, Ayyub, Bilal M and Beer, Michael ORCID: 0000-0002-0611-0345
(2018) Resiliency assessment of urban rail transit networks: Shanghai metro as an example. SAFETY SCIENCE, 106. pp. 230-243.

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This paper presents a general framework to assess the resilience of large and complex metro networks by quantitatively analyzing its vulnerability and recovery rapidity within unifying metrics and models. The connectivity performance of network is indicated by the network efficiency. The resilience of a metro network can be associated to the network performance loss triangle over the relevant timeline from the occurrence of a random or intentional disruption to full recovery. The proposed resilience model is applied to the Shanghai metro network with its 303 stations and 350 links as an example. The quantitative vulnerability analysis shows that the Shanghai metro with its L-space type of topology has a strong robustness regarding connectivity under random disruption but severe vulnerability under intentional disruption. This result is typical for small-world and scale-free networks such as the Shanghai metro system, as can be shown by a basic topological analysis. Considering the case of one disrupted metro station, both the vulnerability and resilience of the network depend not only on the node degree of the disrupted station but also on its contribution to connectivity of the whole network. Analyzing the performance loss triangle and the associated cost from loss of operational income and repair measures, an appropriate recovery strategy in terms of the optimum recovery sequence of stations and the optimum duration can be identified in a structured manner, which is informative and helpful to decision makers.

Item Type: Article
Uncontrolled Keywords: Network resilience, Shanghai metro, Node connectivity, Topology, Robustness, Vulnerability
Depositing User: Symplectic Admin
Date Deposited: 09 Apr 2018 06:08
Last Modified: 19 Jan 2023 06:36
DOI: 10.1016/j.ssci.2018.03.023
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