基于乘客决策行为的城市轨道交通网络韧性评估OA

[Objective]This study aims to ensure the safe operation of urban rail transit networks and enhance their emergency response and recovery capabilities during emergencies.[Methods]Based on the concept of resilience,this study developed network performance indicators from the scale of passenger flow affected by failed stations and the resulting total system delays.It also improved the network passenger flow assignment method by introducing virtual transfer edges,considering passenger decision-making behavior under failure scenarios,and generating real-time networks,thereby addressing the insufficient consideration of passenger decision-making behavior in existing studies.Finally,using Beijing Metro as a case study,simulations of single-station failure and multiple-station failures under four different attack strategies were conducted.[Results]The results indicated that:(1)during the morning peak,the network resilience indicator of Beijing Metro under single-station failure followed a power-law distribution,with the performance loss caused by failures of most stations not exceeding 5％.(2)Stations causing relatively large cumulative performance losses were primarily located in key sections connecting urban areas and suburbs.Their failures caused disruptions to a large number of passenger trips,with the maximum cumulative performance loss reaching 22.27％.(3)Under multiple-station failures in the Beijing Metro network,the network performance curve initially decreased sharply and then gradually leveled off.Under random attacks,the network maintained relatively high resilience,with the resilience indicator remaining around 0.247 2,which was 43.77％,44.96％,and 26.41％lower than those under degree-preference,betweenness-preference,and passenger-flow-preference attacks,respectively.[Conclusion]The findings provide a theoretical basis and practical guidance for improving the safety and emergency response capabilities of urban rail transit networks.