Resilience Assessment and Recovery Strategy for High‐Speed Railway Networks Considering Spatiotemporal Dynamic Characteristics

The service link in a high‐speed railway (HSR) network has an evident temporal attribute, and conventional research methods ignore the importance of temporal information in resilience assessments. Hence, in this study, an HSR service network model based on a temporal network framework is constructed, and an HSR service network resilience assessment method considering spatiotemporal dynamic characteristics is proposed. Considering the heterogeneity of train flow in different time periods and taking the time cost of the shortest temporal path as the network performance measure, a resilience assessment model is established based on the HSR temporal service network, and an algorithm for solving the network performance is designed. Taking China’s HSR network as a case study, the research results showed that the optimal recovery strategy exhibited a higher resilience value than four other recovery strategies. In different spatiotemporal dimensions, the impact of disturbance events on network resilience is different, and the corresponding optimal restoration sequence is also different, making the resilience of the HSR network to exhibit evident differences in the spatiotemporal distribution. In addition, an increase in the number of repair resources is not proportional to the improvement in network resilience. The railway emergency department should comprehensively consider the spatiotemporal characteristics of the disturbance distribution and reasonably determine the restoration sequence and the number of repair resources.

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Publication Details

Journal
Journal of Advanced Transportation
Published
2025-01-01
DOI
https://doi.org/10.1155/atr/9890906
Citations
2
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
1.91

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article

Resilience Assessment and Recovery Strategy for High‐Speed Railway Networks Considering Spatiotemporal Dynamic Characteristics

Ruichun He, Wenxia Li, Jinbo Bai, Zhuo Li
2 citations
Journal of Advanced Transportation
Infrastructure Resilience and Vulnerability Analysis
1.91
article

Resilience Assessment and Recovery Strategy for High‐Speed Railway Networks Considering Spatiotemporal Dynamic Characteristics

Ruichun He, Wenxia Li, Jinbo Bai, Zhuo Li
article en
2 citations

Abstract

The service link in a high‐speed railway (HSR) network has an evident temporal attribute, and conventional research methods ignore the importance of temporal information in resilience assessments. Hence, in this study, an HSR service network model based on a temporal network framework is constructed, and an HSR service network resilience assessment method considering spatiotemporal dynamic characteristics is proposed. Considering the heterogeneity of train flow in different time periods and taking the time cost of the shortest temporal path as the network performance measure, a resilience assessment model is established based on the HSR temporal service network, and an algorithm for solving the network performance is designed. Taking China’s HSR network as a case study, the research results showed that the optimal recovery strategy exhibited a higher resilience value than four other recovery strategies. In different spatiotemporal dimensions, the impact of disturbance events on network resilience is different, and the corresponding optimal restoration sequence is also different, making the resilience of the HSR network to exhibit evident differences in the spatiotemporal distribution. In addition, an increase in the number of repair resources is not proportional to the improvement in network resilience. The railway emergency department should comprehensively consider the spatiotemporal characteristics of the disturbance distribution and reasonably determine the restoration sequence and the number of repair resources.

Journal of Advanced TransportationVol. 2025(1)
Xidian University (CN), Lanzhou Jiaotong University (CN)
National Natural Science Foundation of China, Gansu Education Department
Openalex Percentile: Top 17%
Infrastructure Resilience and Vulnerability Analysis
1.91
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