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Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China

Author

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  • Daniel (Jian) Sun

    (State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    Transportation Research Center, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Yuhan Zhao

    (Transportation Research Center, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    Department of Management, Technology and Economics, ETH Zurich, CH-8093 Zurich, Switzerland)

  • Qing-Chang Lu

    (State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

Abstract

Rail transit is developing rapidly in major cities of China and has become a key component of urban transport. Nevertheless, the security and reliability in operation are significant issues that cannot be neglected. In this paper, the network and station vulnerabilities of the urban rail transit system were analyzed based on complex network and graph theories. A vulnerability evaluation model was proposed by accounting metro interchange and passenger flow and further validated by a case study of Shanghai Metro with full-scale network and real-world traffic data. It is identified that the urban rail transit network is rather robust to random attacks, but is vulnerable to the largest degree node-based attacks and the highest betweenness node-based attacks. Metro stations with a large node degree are more important in maintaining the network size, while stations with a high node betweenness are critical to network efficiency and origin-destination (OD) connectivity. The most crucial stations in maintaining network serviceability do not necessarily have the highest passenger throughput or the largest structural connectivity. A comprehensive evaluation model as proposed is therefore essential to assess station vulnerability, so that attention can be placed on appropriate nodes within the metro system. The findings of this research are of both theoretical and practical significance for urban rail transit network design and performance evaluation.

Suggested Citation

  • Daniel (Jian) Sun & Yuhan Zhao & Qing-Chang Lu, 2015. "Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:6:p:6919-6936:d:50346
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    References listed on IDEAS

    as
    1. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    2. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    3. Raveau, Sebastián & Muñoz, Juan Carlos & de Grange, Louis, 2011. "A topological route choice model for metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 138-147, February.
    4. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    5. Angeloudis, Panagiotis & Fisk, David, 2006. "Large subway systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 553-558.
    6. Jenelius, Erik, 2009. "Network structure and travel patterns: explaining the geographical disparities of road network vulnerability," Journal of Transport Geography, Elsevier, vol. 17(3), pages 234-244.
    7. Zhang, Jianhua & Xu, Xiaoming & Hong, Liu & Wang, Shuliang & Fei, Qi, 2011. "Networked analysis of the Shanghai subway network, in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4562-4570.
    8. Cadarso, Luis & Marín, Ángel & Maróti, Gábor, 2013. "Recovery of disruptions in rapid transit networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 15-33.
    9. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    10. Michael Taylor & Somenahalli Sekhar & Glen D'Este, 2006. "Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks," Networks and Spatial Economics, Springer, vol. 6(3), pages 267-291, September.
    11. Nguyen, T.P. Khanh & Beugin, Julie & Marais, Juliette, 2015. "Method for evaluating an extended Fault Tree to analyse the dependability of complex systems: Application to a satellite-based railway system," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 300-313.
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