Volume 42 Issue 3
Jun.  2024
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FAN Bosong, SHAO Chunfu, ZHAO Dan, MA Sheqiang. Modelling on the Risk Dynamic Evolution of Urban Rail Transit Operation Emergency[J]. Journal of Transport Information and Safety, 2024, 42(3): 122-130. doi: 10.3963/j.jssn.1674-4861.2024.03.013
Citation: FAN Bosong, SHAO Chunfu, ZHAO Dan, MA Sheqiang. Modelling on the Risk Dynamic Evolution of Urban Rail Transit Operation Emergency[J]. Journal of Transport Information and Safety, 2024, 42(3): 122-130. doi: 10.3963/j.jssn.1674-4861.2024.03.013

Modelling on the Risk Dynamic Evolution of Urban Rail Transit Operation Emergency

doi: 10.3963/j.jssn.1674-4861.2024.03.013
  • Received Date: 2023-12-28
    Available Online: 2024-10-21
  • In order to analyze the dynamic evolution characteristics of urban rail transit operation emergencies, and to explore risk factors affecting normal operations, this paper investigates a dynamic evolution model for such emergencies. The bow-tie model is used to integrate the causes of operational risks, estimated time margins and the severity of the emergencies, developing a risk dynamic model which reflects the operational risk status of urban rail transit systems at different moments. Based on a complex network model, the degree distribution of nodes is improved by introducing connected edge weights and structural hole theory, leading to the development of a risk dynamic evolution model which characterizes risk dynamic modes and their evolution process. Relying on the data from Beijing urban rail transit emergency operations, the research explores the evolution patterns of operation emergencies and identifies significant risk factors. The results show that the risk dynamic evolution model for Beijing urban rail transit operation emergency network exhibits the characteristics of a scale-free network, where 19.90% of risk dynamic modes account for 77.76% of the dynamic evolution process of the whole system. The risk dynamic evolution model demonstrates both robustness and fragility, with"train fulfillment"and"punctuality"identified as risk factors for the"more severe"and"severe"modes, respectively. These few but critical risk factors have significant consequences for the dynamic evolution of the system. Therefore, it is necessary to focus on risk factors that may bring serious consequences, and carry out targeted risk prevention, control and resilience enhancement, according to the dynamic evolution characteristics of the system.

     

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