Tianlei Zhu , Xin Yang , Yun Wei , Anthony Chen , Jianjun Wu
{"title":"Urban rail transit resilience under different operation schemes: A percolation-based approach","authors":"Tianlei Zhu , Xin Yang , Yun Wei , Anthony Chen , Jianjun Wu","doi":"10.1016/j.commtr.2025.100177","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"5 ","pages":"Article 100177"},"PeriodicalIF":12.5000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Transportation Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772424725000174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
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.