IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i18p11555-d915432.html
   My bibliography  Save this article

Resilience Assessment of an Urban Metro Complex Network: A Case Study of the Zhengzhou Metro

Author

Listed:
  • Qingjie Qi

    (Institute of Emergency Science Research, Chinese Institute of Coal Science, Beijing 100013, China)

  • Yangyang Meng

    (Institute of Emergency Science Research, Chinese Institute of Coal Science, Beijing 100013, China)

  • Xiaofei Zhao

    (Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China)

  • Jianzhong Liu

    (China Coal Technology & Engineering Group, Beijing 100013, China)

Abstract

An urban metro network is susceptible to becoming vulnerable and difficult to recover quickly in the face of an unexpected attack on account of the system’s complexity and the threat of various emergencies. Therefore, it is necessary to assess the resilience of urban metro networks. However, the research on resilience assessment of urban metro networks is still in the development stage, and it is better to conduct said research using a technique which combines many attributes, multiple methods, and several cases. Therefore, based on the complex network modeling and topological characteristics analysis of metro systems, a metro network’s robustness and vulnerability measurement method under node interruption and edge failure is proposed for the first time in this study. Then, considering the three cases of general station interruption, interchange station interruption, and traffic tunnel failure, a quantitative resilience assessment model of metro networks is put forward, and the corresponding recovery strategies are discussed. Finally, a case study of the Zhengzhou Metro Network (ZZMN) under an extreme rainstorm is conducted to demonstrate the viability of the proposed model. The results show that ZZMN possesses scale-free and small-world network properties, and it is robust to random interruptions but vulnerable to deliberate attacks. ZZMN still needs to improve its effectiveness in information transmission. The centrality distribution for each node in the ZZMN network differs significantly, and each node’s failure has a unique impact on the network. The larger the DC , BC , and PR of a node is, the lower the network’s robustness after its removal is, and the stronger the vulnerability is. Compared with the three cases of general station interruption, interchange station interruption, and traffic tunnel failure, the network loss caused by tunnel failure was the lowest, followed by general station interruption, and the interruption at interchange stations was the most costly. Given the failures under various cases, the metro management department should prioritize selecting the optimal recovery strategy to improve the resilience of the metro network system. This study’s findings can assist in making urban metro systems less vulnerable to emergencies and more resilient for a quick recovery, which can provide scientific theoretical guidance and decision support for the safety and resilient, sustainable development of urban metro systems.

Suggested Citation

  • Qingjie Qi & Yangyang Meng & Xiaofei Zhao & Jianzhong Liu, 2022. "Resilience Assessment of an Urban Metro Complex Network: A Case Study of the Zhengzhou Metro," Sustainability, MDPI, vol. 14(18), pages 1-19, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11555-:d:915432
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/18/11555/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/18/11555/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    2. 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.
    3. Xu, Zizhen & Chopra, Shauhrat S., 2022. "Network-based Assessment of Metro Infrastructure with a Spatial–temporal Resilience Cycle Framework," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    4. Chan, Ho-Yin & Chen, Anthony & Li, Guoyuan & Xu, Xiangdong & Lam, William, 2021. "Evaluating the value of new metro lines using route diversity measures: The case of Hong Kong's Mass Transit Railway system," Journal of Transport Geography, Elsevier, vol. 91(C).
    5. Tsai-Yun Liao & Ta-Yin Hu & Yi-No Ko, 2018. "A resilience optimization model for transportation networks under disasters," 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. 93(1), pages 469-489, August.
    6. Qian Ye & Hyun Kim, 2019. "Assessing network vulnerability of heavy rail systems with the impact of partial node failures," Transportation, Springer, vol. 46(5), pages 1591-1614, October.
    7. Elisa Frutos Bernal & Angel Martín del Rey, 2019. "Study of the Structural and Robustness Characteristics of Madrid Metro Network," Sustainability, MDPI, vol. 11(12), pages 1-24, June.
    8. Jungyeol Hong & Reuben Tamakloe & Soobeom Lee & Dongjoo Park, 2019. "Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    9. Lin, Pengfei & Weng, Jiancheng & Fu, Yu & Alivanistos, Dimitrios & Yin, Baocai, 2020. "Study on the topology and dynamics of the rail transit network based on automatic fare collection data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    10. Shuyang Zhang & Hong K. Lo & Ka Fai Ng & Guojun Chen, 2021. "Metro system disruption management and substitute bus service: a systematic review and future directions," Transport Reviews, Taylor & Francis Journals, vol. 41(2), pages 230-251, March.
    11. Zhang, Jianhua & Wang, Meng, 2019. "Transportation functionality vulnerability of urban rail transit networks based on movingblock: The case of Nanjing metro," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    12. 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.
    13. Tang, Junqing & Xu, Lei & Luo, Chunling & Ng, Tsan Sheng Adam, 2021. "Multi-disruption resilience assessment of rail transit systems with optimized commuter flows," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    14. Shiping Wen & Jiangang Shi & Wei Zhang & Ali Minai, 2021. "Impact of Urban Rail Transit Network on Residential and Commercial Land Values in China: A Complex Network Perspective," Complexity, Hindawi, vol. 2021, pages 1-11, May.
    15. Qian Ye & Hyun Kim, 2019. "Partial Node Failure in Shortest Path Network Problems," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
    16. Zhang, Yifan & Ng, S. Thomas, 2022. "Robustness of urban railway networks against the cascading failures induced by the fluctuation of passenger flow," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    17. Yi Shen & Gang Ren & Bin Ran, 2021. "Cascading failure analysis and robustness optimization of metro networks based on coupled map lattices: a case study of Nanjing, China," Transportation, Springer, vol. 48(2), pages 537-553, April.
    18. Huang, Wencheng & Shuai, Bin & Sun, Yan & Wang, Yang & Antwi, Eric, 2018. "Using entropy-TOPSIS method to evaluate urban rail transit system operation performance: The China case," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 292-303.
    19. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    20. Pu, Han & Li, Yinzhen & Ma, Changxi, 2022. "Topology analysis of Lanzhou public transport network based on double-layer complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    21. Ma, Min & Hu, Dawei & Chien, Steven I-Jy & Liu, Jie & Yang, Xing & Ma, Zhuanglin, 2022. "Evolution assessment of urban rail transit networks: A case study of Xi’an, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    22. Hyun Kim & Yena Song, 2018. "An integrated measure of accessibility and reliability of mass transit systems," Transportation, Springer, vol. 45(4), pages 1075-1100, July.
    23. Chengpeng Wan & Zaili Yang & Di Zhang & Xinping Yan & Shiqi Fan, 2018. "Resilience in transportation systems: a systematic review and future directions," Transport Reviews, Taylor & Francis Journals, vol. 38(4), pages 479-498, July.
    24. Yin, Jiateng & Ren, Xianliang & Liu, Ronghui & Tang, Tao & Su, Shuai, 2022. "Quantitative analysis for resilience-based urban rail systems: A hybrid knowledge-based and data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    25. Meng, Yangyang & Tian, Xiangliang & Li, Zhongwen & Zhou, Wei & Zhou, Zhijie & Zhong, Maohua, 2020. "Comparison analysis on complex topological network models of urban rail transit: A case study of Shenzhen Metro in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    26. Sun, Lishan & Huang, Yuchen & Chen, Yanyan & Yao, Liya, 2018. "Vulnerability assessment of urban rail transit based on multi-static weighted method in Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 108(C), pages 12-24.
    27. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    28. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shichang Xiao & Zigao Wu & Hongyan Dui, 2022. "Resilience-Based Surrogate Robustness Measure and Optimization Method for Robust Job-Shop Scheduling," Mathematics, MDPI, vol. 10(21), pages 1-22, October.
    2. Tong Wang & Yang Liu & Qiyuan Li & Peng Du & Xiaogong Zheng & Qingfei Gao, 2023. "State-of-the-Art Review of the Resilience of Urban Bridge Networks," Sustainability, MDPI, vol. 15(2), pages 1-18, January.
    3. Yangyang Meng & Xiaofei Zhao & Jianzhong Liu & Qingjie Qi, 2023. "Dynamic Influence Analysis of the Important Station Evolution on the Resilience of Complex Metro Network," Sustainability, MDPI, vol. 15(12), pages 1-15, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yangyang Meng & Qingjie Qi & Jianzhong Liu & Wei Zhou, 2022. "Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    2. Yangyang Meng & Xiaofei Zhao & Jianzhong Liu & Qingjie Qi, 2023. "Dynamic Influence Analysis of the Important Station Evolution on the Resilience of Complex Metro Network," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
    3. Hu, Jie & Wen, Weiping & Zhai, Changhai & Pei, Shunshun, 2024. "Post-earthquake functionality assessment for urban subway systems: Incorporating the combined effects of seismic performance of structural and non-structural systems and functional interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    5. Xu, Chen & Xu, Xueguo, 2024. "A two-stage resilience promotion approach for urban rail transit networks based on topology enhancement and recovery optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    6. Zhang, Li & Chen, Tingting & Liu, Zhongshan & Yu, Bin & Wang, Yunpeng, 2024. "Analysis of multi-modal public transportation system performance under metro disruptions: A dynamic resilience assessment framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 183(C).
    7. Malandri, Caterina & Mantecchini, Luca & Postorino, Maria Nadia, 2023. "A comprehensive approach to assess transportation system resilience towards disruptive events. Case study on airside airport systems," Transport Policy, Elsevier, vol. 139(C), pages 109-122.
    8. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    9. Lu, Qing-Long & Sun, Wenzhe & Dai, Jiannan & Schmöcker, Jan-Dirk & Antoniou, Constantinos, 2024. "Traffic resilience quantification based on macroscopic fundamental diagrams and analysis using topological attributes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    10. Shen, Yi & Yang, Huang & Ren, Gang & Ran, Bin, 2024. "Model cascading overload failure and dynamic vulnerability analysis of facility network of metro station," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    11. Bešinović, Nikola & Ferrari Nassar, Raphael & Szymula, Christopher, 2022. "Resilience assessment of railway networks: Combining infrastructure restoration and transport management," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    12. Zheng, Shuai & Liu, Yugang & Lin, Yexin & Wang, Qiang & Yang, Hongtai & Chen, Bin, 2022. "Bridging strategy for the disruption of metro considering the reliability of transportation system: Metro and conventional bus network," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    13. Jianhua Zhang & Ziqi Wang & Shuliang Wang & Shengyang Luan & Wenchao Shao, 2020. "Vulnerability Assessments of Urban Rail Transit Networks Based on Redundant Recovery," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    14. Li, Jin-Yang & Teng, Jing & Wang, Hui, 2024. "Measuring route diversity in spatial and spatial-temporal public transport networks," Transport Policy, Elsevier, vol. 146(C), pages 42-58.
    15. 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.
    16. Meng, Yangyang & Zhao, Xiaofei & Liu, Jianzhong & Qi, Qingjie & Zhou, Wei, 2023. "Data-driven complexity analysis of weighted Shenzhen Metro network based on urban massive mobility in the rush hours," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    17. Liu, Enze & Barker, Kash & Chen, Hong, 2022. "A multi-modal evacuation-based response strategy for mitigating disruption in an intercity railway system," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    18. Xueguo Xu & Chen Xu & Wenxin Zhang, 2022. "Research on the Destruction Resistance of Giant Urban Rail Transit Network from the Perspective of Vulnerability," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    19. Hong, Liu & Ye, Bowen & Yan, Han & Zhang, Hui & Ouyang, Min & (Sean) He, Xiaozheng, 2019. "Spatiotemporal vulnerability analysis of railway systems with heterogeneous train flows," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 725-744.
    20. Zhang, Lin & Lu, Jian & Fu, Bai-bai & Li, Shu-bin, 2019. "A cascading failures model of weighted bus transit route network under route failure perspective considering link prediction effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1315-1330.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11555-:d:915432. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.