IDEAS home Printed from https://ideas.repec.org/a/bpj/jossai/v9y2021i4p455-468n3.html
   My bibliography  Save this article

Promoting Metro Operation Safety by Exploring Metro Operation Accident Network

Author

Listed:
  • Suo Qi
  • Wang Liyuan
  • Yao Tianzi
  • Wang Zihao

    (School of Economics and Management, Qingdao University of Science and Technology, Qingdao266061, China)

Abstract

Understanding the causation of accidents is essential to promote metro operation safety. In terms of 243 reported metro operation accident cases in China, a directed weighted network was constructed based on complex network theory, where nodes and directed edges denotes factors and event chains respectively. To reveal the key causal factors, the topological characteristics of metro operation accident network (MOAN) were analyzed from both global and local views. The results show that facility-type factors are more closely related to the occurrence of the accidents from the perspectives of average path length and cascading effects. Accident types like train delay and train suspension are the great risk recipients. Key causal factors with large out-degree, out-strength, betweenness centrality and cluster coefficient, such as communication and signal failure, vehicle failure and piling into the train should be noticed. The research framework proposed in the paper is not only applicable to China’s metro operation system, but also appropriate for other transportation system safety studies.

Suggested Citation

  • Suo Qi & Wang Liyuan & Yao Tianzi & Wang Zihao, 2021. "Promoting Metro Operation Safety by Exploring Metro Operation Accident Network," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 455-468, August.
    • Handle: RePEc:bpj:jossai:v:9:y:2021:i:4:p:455-468:n:3
    DOI: 10.21078/JSSI-2021-455-14
    as

    Download full text from publisher

    File URL: https://doi.org/10.21078/JSSI-2021-455-14
    Download Restriction: no
    File URL: https://libkey.io/10.21078/JSSI-2021-455-14?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Yongliang Deng & Liangliang Song & Zhipeng Zhou & Ping Liu, 2017. "An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network," Complexity, Hindawi, vol. 2017, pages 1-17, October.
    2. Fang, Qingxiang & Peng, Jigen, 2018. "Synchronization of fractional-order linear complex networks with directed coupling topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 542-553.
    3. Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    4. Lam, C.Y. & Tai, K., 2020. "Network topological approach to modeling accident causations and characteristics: Analysis of railway incidents in Japan," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    5. Quan He & Xishen Cao, 2019. "Pattern and Influencing Factors of Foreign Direct Investment Networks between Countries along the “Belt and Road” Regions," Sustainability, MDPI, vol. 11(17), pages 1-23, August.
    6. Yongchang Wei & Lei Chen & Yu Qi & Can Wang & Fei Li & Haorong Wang & Fangyu Chen, 2019. "A Complex Network Method in Criticality Evaluation of Air Quality Standards," Sustainability, MDPI, vol. 11(14), pages 1-15, July.
    7. Zhou, Jin & Xu, Weixiang & Guo, Xin & Ding, Jing, 2015. "A method for modeling and analysis of directed weighted accident causation network (DWACN)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 263-277.
    8. Liu, Jintao & Schmid, Felix & Zheng, Wei & Zhu, Jiebei, 2019. "Understanding railway operational accidents using network theory," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 218-231.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    2. Zhang, Hengqi & Geng, Hua, 2023. "A methodology to identify and assess high-risk causes for electrical personal accidents based on directed weighted CN," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C., 2022. "Casualty analysis methodology and taxonomy for FPSO accident analysis," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    4. Huang, Wencheng & Zhang, Rui & Xu, Minhao & Yu, Yaocheng & Xu, Yifei & De Dieu, Gatesi Jean, 2020. "Risk state changes analysis of railway dangerous goods transportation system: Based on the cusp catastrophe model," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    5. Cuiping Ren & Bianbian Chen & Fengjie Xie & Xuan Zhao & Jiaqian Zhang & Xueyan Zhou, 2022. "Understanding Hazardous Materials Transportation Accidents Based on Higher-Order Network Theory," IJERPH, MDPI, vol. 19(20), pages 1-13, October.
    6. Catelani, Marcantonio & Ciani, Lorenzo & Guidi, Giulia & Patrizi, Gabriele, 2021. "An enhanced SHERPA (E-SHERPA) method for human reliability analysis in railway engineering," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    7. Gu, Shuang & Li, Keping & Feng, Tao & Yan, Dongyang & Liu, Yanyan, 2022. "The prediction of potential risk path in railway traffic events," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    8. Zhang, Hengqi & Geng, Hua & Zeng, Huarong & Jiang, Li, 2023. "Dynamic risk evaluation and control of electrical personal accidents," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    9. Liu, Jintao & Schmid, Felix & Li, Keping & Zheng, Wei, 2021. "A knowledge graph-based approach for exploring railway operational accidents," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    10. Laihao Ma & Xiaoxue Ma & Jingwen Zhang & Qing Yang & Kai Wei, 2021. "Identifying the Weaker Function Links in the Hazardous Chemicals Road Transportation System in China," IJERPH, MDPI, vol. 18(13), pages 1-17, July.
    11. Yue Pu & Yunting Li & Jinjin Zhang, 2023. "Features and evolution of the ‘Belt and Road’ regional value chain: Complex network analysis," The World Economy, Wiley Blackwell, vol. 46(7), pages 2134-2156, July.
    12. Weiwei Sun & Xueli Zhang & Min Yuan & Zheng Zhang, 2023. "Complex Network Analysis of China National Standards for New Energy Vehicles," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    13. Li, Zhitao & Tang, Jinjun & Zhao, Chuyun & Gao, Fan, 2023. "Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    14. Lin, Boliang & Zhao, Yinan, 2021. "Synchronized optimization of EMU train assignment and second-level preventive maintenance scheduling," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Fan, Bing & Tan, Hongtao & Li, Yaqun, 2023. "Critical link identification algorithm for power communication networks in SDN architecture," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).
    16. Wang, Aijuan & Liao, Xiaofeng & Dong, Tao, 2018. "Finite-time event-triggered synchronization for reaction–diffusion complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 111-120.
    17. IAIANI, Matteo & TUGNOLI, Alessandro & BONVICINI, Sarah & COZZANI, Valerio, 2021. "Analysis of Cybersecurity-related Incidents in the Process Industry," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    18. Guo, Shengyu & Zhou, Xinyu & Tang, Bing & Gong, Peisong, 2020. "Exploring the behavioral risk chains of accidents using complex network theory in the construction industry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    19. Hosn el Woujoud Bousselmi & Lorena Caridad & Nuria Ceular Villamandos, 2019. "Structural Models in Corporate Social Responsibility: Attraction of Investment in Tunisia," Sustainability, MDPI, vol. 11(18), pages 1-11, September.
    20. Zhang, Yin-Ting & Zhou, Wei-Xing, 2023. "Quantifying the status of economies in international crop trade networks: A correlation structure analysis of various node-ranking metrics," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).

    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:bpj:jossai:v:9:y:2021:i:4:p:455-468:n:3. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.