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Vulnerability analysis of urban rail transit based on complex network theory: a case study of Shanghai Metro

Author

Listed:
  • Yingying Xing

    (Shanghai Jiao Tong University)

  • Jian Lu

    (Tongji University)

  • Shengdi Chen

    (Shanghai Maritime University)

  • Sunanda Dissanayake

    (Kansas State University)

Abstract

With increasing passenger flows and construction scale, metro systems in metropolises have entered a new era of networking operation and become the most effective way to alleviate and decrease traffic congestion. However, frequent occurrence of random failures and malicious attacks pose a serious threat to metro security and reliability. Thus, it is necessary to quantitatively evaluate the vulnerability of the metro network to different failures or attacks from a networking perspective. Based on the complex network theory, this study took the Shanghai Metro Network (SMN) as an example to investigate vulnerability of a weighted metro network in responding to random failures as well as malicious attacks. In particular, compared to topological networks, the vulnerability of weighted networks was analyzed to investigate how traffic and spatial constraints influence the transport system’s vulnerability, since topological features of complex networks are often associated with the weights of the edges and spatial constraints. Simulation results show that the SMN is robust against random failures but fragile for malicious attacks. The vulnerability analysis of weighted properties shows that all targeted attacks are capable to shatter the network’s communication or transport properties at a very low level of removed nodes and the highest betweenness attack strategy is the most effective mode to cause destructive effects on SMN among five attack or failure strategies. The inclusion of passenger flows provides evidence for the view that topological networks cannot convey all the information of a real-world network and traffic flow in the network should be considered as one of the key features in the finding and development of defensive strategies. Our results provide a richer view on complex weighted networks in real-world and possibilities of risk analysis and policy decisions for the metro operation department.

Suggested Citation

  • Yingying Xing & Jian Lu & Shengdi Chen & Sunanda Dissanayake, 2017. "Vulnerability analysis of urban rail transit based on complex network theory: a case study of Shanghai Metro," Public Transport, Springer, vol. 9(3), pages 501-525, October.
  • Handle: RePEc:spr:pubtra:v:9:y:2017:i:3:d:10.1007_s12469-017-0170-2
    DOI: 10.1007/s12469-017-0170-2
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    References listed on IDEAS

    as
    1. 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.
    2. Paramet Luathep & Agachai Sumalee & H. Ho & Fumitaka Kurauchi, 2011. "Large-scale road network vulnerability analysis: a sensitivity analysis based approach," Transportation, Springer, vol. 38(5), pages 799-817, September.
    3. Zengwang Xu & Daniel Sui, 2007. "Small-world characteristics on transportation networks: a perspective from network autocorrelation," Journal of Geographical Systems, Springer, vol. 9(2), pages 189-205, June.
    4. Wang, Hui & Huang, Jinyuan & Xu, Xiaomin & Xiao, Yanghua, 2014. "Damage attack on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 134-148.
    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. von Ferber, C. & Holovatch, T. & Holovatch, Yu. & Palchykov, V., 2007. "Network harness: Metropolis public transport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 585-591.
    7. Katja Berdica & Lars-Göran Mattsson, 2007. "Vulnerability: A Model-Based Case Study of the Road Network in Stockholm," Advances in Spatial Science, in: Alan T. Murray & Tony H. Grubesic (ed.), Critical Infrastructure, chapter 5, pages 81-106, Springer.
    8. 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.
    9. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    10. B. Berche & C. von Ferber & T. Holovatch & Yu. Holovatch, 2009. "Resilience of public transport networks against attacks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(1), pages 125-137, September.
    11. 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.
    12. Laporte, Gilbert & Mesa, Juan A. & Perea, Federico, 2010. "A game theoretic framework for the robust railway transit network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 447-459, May.
    13. Ghedini, Cinara G. & Ribeiro, Carlos H.C., 2011. "Rethinking failure and attack tolerance assessment in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4684-4691.
    14. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2003. "Efficiency of scale-free networks: error and attack tolerance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 622-642.
    Full references (including those not matched with items on IDEAS)

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    2. Ting Chen & Jianxiao Ma & Zhenjun Zhu & Xiucheng Guo, 2023. "Evaluation Method for Node Importance of Urban Rail Network Considering Traffic Characteristics," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
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    8. Kizhakkedath, A. & Tai, K., 2021. "Vulnerability analysis of critical infrastructure network," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
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    10. Sun, Chuanwang & Zhang, Wenyue & Luo, Yuan & Xu, Yonghong, 2019. "The improvement and substitution effect of transportation infrastructure on air quality: An empirical evidence from China's rail transit construction," Energy Policy, Elsevier, vol. 129(C), pages 949-957.
    11. Jing Liu & Huapu Lu & Mingyu Chen & Jianyu Wang & Ying Zhang, 2020. "Macro Perspective Research on Transportation Safety: An Empirical Analysis of Network Characteristics and Vulnerability," Sustainability, MDPI, vol. 12(15), pages 1-18, August.
    12. Xiaohong Yin & Jiakun Wu, 2022. "Simulation Study on Topology Characteristics and Cascading Failure of Hefei Subway Network," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    13. Kim, Seyun & Yoon, Yoonjin, 2019. "On node criticality of the Northeast Asian air route network," Journal of Air Transport Management, Elsevier, vol. 80(C), pages 1-1.
    14. Edwar Forero-Ortiz & Eduardo Martínez-Gomariz, 2020. "Hazards threatening underground transport systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(3), pages 1243-1261, February.
    15. Jiangang Shi & Shiping Wen & Xianbo Zhao & Guangdong Wu, 2019. "Sustainable Development of Urban Rail Transit Networks: A Vulnerability Perspective," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
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    17. Hong, Wei-Ting & Clifton, Geoffrey & Nelson, John D., 2022. "Rail transport system vulnerability analysis and policy implementation: Past progress and future directions," Transport Policy, Elsevier, vol. 128(C), pages 299-308.

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