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Research Article | Open Access

Urban rail transit resilience under different operation schemes: A percolation-based approach

Tianlei ZhuaXin Yanga( )Yun WeibAnthony ChencJianjun Wud
School of Systems Science, Beijing Jiaotong University, Beijing, 100044, China
Beijing Mass Transit Railway Operation Corporation Ltd., Beijing, 100044, China
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, 999077, Hong Kong, China
School of Economics and Management, Dalian University of Technology, Dalian, 116024, China
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Abstract

To assess the resilience of urban rail transit (URT) systems under various operational conditions accurately and enhance their operation, this study develops a percolation model for nonfree flow transportation networks on the basis of percolation theory, which integrates multisource information and operational characteristics. Our model accounts for the state evolution of different hierarchical structures within the network and identifies nonlinear features. Specifically, we observed significant percolation transitions in the URT network, with distinct differences in critical percolation thresholds at different times, leading to multistate behavior. Network bottlenecks spatially shift with network phase transitions, exhibiting power-law frequency characteristics. On the basis of the full-day resilience assessment results, we analyzed the impact of different operational schemes on network resilience during the morning peak, the period with the lowest resilience. The results demonstrate that our resilience analysis framework effectively evaluates URT network resilience, providing theoretical support for enhancing operational management efficiency and accident prevention measures.

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Communications in Transportation Research
Article number: 100177

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Cite this article:
Zhu T, Yang X, Wei Y, et al. Urban rail transit resilience under different operation schemes: A percolation-based approach. Communications in Transportation Research, 2025, 5(2): 100177. https://doi.org/10.1016/j.commtr.2025.100177

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Received: 11 December 2024
Revised: 07 January 2025
Accepted: 20 January 2025
Published: 01 April 2025
© 2025 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).