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Title: Urban rail transit resilience under different operation schemes : a percolation-based approach
Authors: Zhu, T
Yang, X
Wei, Y
Chen, A 
Wu, J
Issue Date: Dec-2025
Source: Communications in transportation research, Dec. 2025, v. 5, 100177
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.
Keywords: Network bottlenecks
Operation schemes
Percolation
Resilience assessment
Urban rail transit (URT)
Publisher: Elsevier Ltd
Journal: Communications in transportation research 
EISSN: 2772-4247
DOI: 10.1016/j.commtr.2025.100177
Rights: © 2025 The Authors. Published by Elsevier Ltd on behalf of Tsinghua University Press. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The following publication Zhu, T., Yang, X., Wei, Y., Chen, A., & Wu, J. (2025). Urban rail transit resilience under different operation schemes: A percolation-based approach. Communications in Transportation Research, 5, 100177 is available at https://doi.org/10.1016/j.commtr.2025.100177.
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