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ZHANG Xiran, LI Zhengzhong, ZHANG Xin, CHEN Shaokuan. Status and Prospects of Studies on Urban Rail Transit Resilience[J]. Journal of Transport Information and Safety, 2024, 42(4): 1-11. doi: 10.3963/j.jssn.1674-4861.2024.04.001
Citation: ZHANG Xiran, LI Zhengzhong, ZHANG Xin, CHEN Shaokuan. Status and Prospects of Studies on Urban Rail Transit Resilience[J]. Journal of Transport Information and Safety, 2024, 42(4): 1-11. doi: 10.3963/j.jssn.1674-4861.2024.04.001
shu

Status and Prospects of Studies on Urban Rail Transit Resilience

doi: 10.3963/j.jssn.1674-4861.2024.04.001
  • 1.

    Tianjin Transportation Research Institute, Tianjin 300074, China

  • 2.

    MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China

  • Received Date: 2024-02-19
    Available Online: 2024-11-25
    Abstract
  • An urban rail transportation system with high-level resilience is able to effectively respond to emergencies caused by natural disasters, human error, equipment failure, and other factors. In order to fully grasp the research trends related to the resilience of urban rail transit, the keywords and hotspots are analyzed with bibliometric analysis. Early studies focuses on the resilience of track structure, while transportation service resilience has gradually gained attention in recent years. Based on the development process of resilience concept in the fields of physics, ecology, and urban management, the connotation of urban rail transit resilience is explained. Oriented to typical social events and natural disaster scenarios, the scope of resilience evaluation is extended from stations to lines and then to networks. However, under current technological conditions, there is a trade-off relationship between the scale and granularity of resilience evaluation. The linkage mechanisms between macro/micro and dynamic/static objects are not fully explored. In terms of resilience evaluation indicators, the indicators system based on topology, transportation capacity, comprehensive performance and operation flow are summarized. The existing indicator system is able to be further enriched in terms of spatial layout, engineering conditions, facilities, equipment, staffing, management and social forces. Four typical indicator measurement methods are sorted out, which include performance curve based on resilience modeling, big data analysis, simulation and numerical analysis. The measurement results based on a single method are easily affected by factors such as the amount of data, hypothetical conditions, and indicator weights. Multiple methods should be comprehensively used to measure indicators in different types and evaluation stages. Resilience enhancement strategies for pre-prevention, in-process adaptation and post-disaster recovery are also discussed. Most existing research primarily approaches from a perspective of operational management, and related studies on post-disaster recovery of infrastructure are still in an initial exploratory stage. Future research on urban rail transit resilience is expected from four aspects: ①Improving the authenticity of emergency scenarios modeling. ②Dynamic fine-grained analysis integrating spatial and functional division of the city. ③Exploring the propagation mechanism of emergencies to characterize system internal changes. ④Verifying effectiveness of resilience evaluation and improvement methods.

     

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