城市轨道交通网络韧性优化研究  

Research on optimizing the resilience of urban rail transit networks

作　　者：张开冉[1,2,3] 殷苏平 蒋明君 ZHANG Kairan;YIN Suping;JIANG Mingjun(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 611756,China;National United Engineering Laboratory of Integrated and Intelligent Transportation,Chengdu 611756,China;National Engineering Laboratory of Integrated Transportation Big Data Application Technology,Chengdu 611756,China)

机构地区：[1]西南交通大学交通运输与物流学院,成都611756 [2]综合交通运输智能化国家地方联合工程实验室,成都611756 [3]综合交通大数据应用技术国家工程实验室,成都611756

出　　处：《安全与环境学报》2025年第2期527-535,共9页Journal of Safety and Environment

基　　金：四川省科技厅重点研发计划项目(2020YFG0120)。

摘　　要：修复策略优化是提高突发事件发生后城市轨道交通网络韧性的重要手段。当前的研究多集中在单一层面的韧性评估,对乘客出行行为的考虑也较少关注对网络熟悉度的随机性。为此构建了城市轨道交通网络韧性优化双层模型,以提高网络对不利因素的应对能力。综合考虑多个层面提出了恢复速度和网络性能双韧性指标,以双韧性指标最大化为目标,考虑乘客出行行为决策,构建了基于修复策略的韧性优化双层模型。并以杭州地铁网络作为实际案例进行验证分析。结果表明:模型所求的修复策略优于其他修复策略;在一定范围内恢复速度韧性随着预算修复资金增加而减小,网络性能韧性随之增大而增大,恢复速度韧性随着修复队伍数量增大而增大,网络性能韧性随之增大而减小。This study seeks to optimize repair strategies to improve the resilience of urban rail transit networks in the face of unexpected events.While existing research predominantly concentrates on single-layer resilience assessments,it often overlooks the considerable variability in passenger travel behavior,which is significantly influenced by their familiarity with the transit network.This variability introduces significant randomness into the network's response during disruptions,impacting recovery efforts.To tackle these challenges,we have developed a bilevel optimization model specifically aimed at enhancing the resilience of urban rail transit networks.The model incorporates two essential resilience indicators:recovery speed,which measures how quickly the network can resume normal operations,and network performance,which assesses the quality and efficiency of the network during the recovery phase.By incorporating passengers decision-making processes during disruptions,the model recognizes that travel choices may vary depending on their familiarity with different routes.The main objective of this optimization framework is to strategically enhance both resilience indicators,thereby improving resource allocation for repair efforts.The proposed model was validated through an in-depth case study of the Hangzhou Metro network,demonstrating its superiority over existing repair strategies.The results indicate that,within specific budget constraints,increasing the allocation of repair funds can enhance network performance resilience but may reduce recovery speed resilience.Additionally,our findings show that increasing the number of repair teams improves recovery speed resilience,although this may result in a slight decline in network performance resilience.This trade-off underscores the importance of balancing resources to optimize both recovery times and overall network efficiency.A key innovation of this research is its incorporation of passenger behavior,particularly their familiarity with the transit network,into the

关 键 词：安全系统学 城市轨道交通网络 韧性优化 客流分配 双层规划 修复策略 

分 类 号：X951[环境科学与工程—安全科学] U121[交通运输工程]