城市轨道交通运营中断与客流作用下的网络脆弱性OA

To address the vulnerability of urban rail transit networks during operational disruptions,this study proposes a systematic evaluation method that integrates network structure,passenger flow dynamics,and passenger behavioral responses.First,a CPT-NL model of travel choice behavior is developed based on Cumulative Prospect Theory(CPT)and the Nested Logit(NL)model.This model captures passengers'bounded rationality and risk aversion under emergency conditions.Sec-ond,a vulnerability analysis framework is designed for urban rail networks within multimodal transpor-tation systems,establishing quantitative vulnerability metrics that reflect the combined impacts of op-erational disruptions and passenger flow dynamics.Finally,using Shenzhen's rail transit network as a case study,peak-hour passenger flow data are employed to systematically simulate disruptions at sec-tions and transfer stations,quantifying network performance losses and passenger travel impacts.The results indicate that failures at critical sections or transfer stations reduce network connectivity and trig-ger large-scale passenger congestion and significant travel delays.During section disruptions,the pro-portion of affected passengers reaches up to 14.78%,with network vulnerability peaking at 12.02%.During transfer station disruptions,the proportion of affected passengers peaks at 11.73%,and net-work vulnerability reaches 5.53%.The number of delayed passengers significantly exceeds the number who abandon rail travel due to disruptions,indicating that most passengers opt for detours within the rail network or multimodal travel alternatives.Operational management should strengthen mainte-nance and emergency preparedness for high-vulnerability nodes,while optimizing multimodal transpor-tation scheduling to improve the resilience and operational stability of urban rail transit systems.