Volume 26 Issue 2
Feb.  2026
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YANG Yang, CHEN Jun-ting, YAO En-jian, LIU Dong-mei. Resilience evaluation method of external transportation network of integrated transit hub cluster under time-varying demand[J]. Journal of Traffic and Transportation Engineering, 2026, 26(2): 155-169. doi: 10.19818/j.cnki.1671-1637.2026.148
Citation: YANG Yang, CHEN Jun-ting, YAO En-jian, LIU Dong-mei. Resilience evaluation method of external transportation network of integrated transit hub cluster under time-varying demand[J]. Journal of Traffic and Transportation Engineering, 2026, 26(2): 155-169. doi: 10.19818/j.cnki.1671-1637.2026.148
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Resilience evaluation method of external transportation network of integrated transit hub cluster under time-varying demand

doi: 10.19818/j.cnki.1671-1637.2026.148
  • 1.

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

  • 2.

    School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

  • 3.

    RIOH High Science and Technology Group, Beijing 100088, China

Funds:

Fundamental Research Funds for the Central Universities 2024JBZY009

National Natural Science Foundation of China 52432011

More Information
  • Corresponding author: YAO En-jian, professor, PhD, E-mail: enjyao@bjtu.edu.cn
  • Received Date: 2025-07-31
  • Accepted Date: 2026-01-08
  • Rev Recd Date: 2026-01-06
  • Publish Date: 2026-02-28
    Abstract
  • To scientifically evaluate the resilience of the external transportation network of the integrated hub cluster, a travel resilience measurement indicator was proposed, covering three dimensions: robustness, redundancy and resilience. The multimodal traffic network passenger flow assignment method was employed to characterize the influence results of different node attack and recovery strategies. The travel resilience measurement method was constructed. Taking the integrated transit hub cluster in the Beijing-Tianjin-Hebei urban agglomeration as an example, an example verification was carried out. Research results show that, the external comprehensive transportation network has been basically formed between the Beijing-Tianjin-Hebei urban agglomeration and the core cities of typical urban agglomerations such as Shanghai, Guangzhou, and Chengdu. The overall anti-interference and recovery capabilities are strong. The unit travel resilience is generally higher than 0.95 under different disturbance scenarios. Taking a single-node recovery time of 1 h in October 7th (National Day) as an example, the network recovery effect of the node strength recovery strategy is the best, with the network resilience of 0.990 2 and only 140 2 people affected, which is significantly superior to other strategies. In the morning peak period, due to the large network load and low redundancy of shifts, the resilience decreases to 0.976 1, lower than that in the afternoon and evening peaks. In most cases, the network resilience reduces with the longer single-node recovery time, while the number of affected people also increases. For different dates, resilience is affected by both the dispersion of passenger flow distribution and network redundancy. According to the TOPSIS method, the highest resilience is 0.983 2 on National Day, while the lowest resilience is 0.974 6 at weekends. The proposed resilience evaluation method can provide a scientific basis for analyzing the potential traffic capacity of multimodal traffic networks such as inter-hub railways, civil aviation and urban transport, and rationally allocating transportation emergency response resources.

     

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