相继故障下城市轨道交通系统韧性评估方法  

Resilience assessment method of urban rail transit system under cascading failure

作　　者：陈津怡 李铁柱[1,2] 郭竞文 刘慧 陈海波 CHEN Jinyi;LI Tiezhu;GUO Jingwen;LIU Hui;CHEN Haibo(School of Transportation,Southeast University,Nanjing Jiangsu 211189,China;Nanjing Rail Transit Smart Transportation Research Station,Nanjing Jiangsu 210012,China;Transportation Management Division,Nanjing Metro Operation Co.,Ltd.,Nanjing Jiangsu 210012,China;School of Transport Management,Nanjing Vocational Institute of Railway Technology,Nanjing Jiangsu 210031,China;Institute for Transport Studies,University of Leeds,Leeds LS29JT,UK)

机构地区：[1]东南大学交通学院,江苏南京211189 [2]南京轨道交通智慧运输研究工作站,江苏南京210012 [3]南京地铁运营有限责任公司运输管理事业部,江苏南京210012 [4]南京铁道职业技术学院运输管理学院,江苏南京210031 [5]利兹大学交通研究所,英国利兹LS29JT

出　　处：《中国安全科学学报》2024年第9期202-208,共7页China Safety Science Journal

基　　金：江苏轨道交通产业发展协同创新基地开放基金资助(GCXC2103)。

摘　　要：为确定城市轨道交通系统中的高风险节点,提升网络韧性和运营安全性,选取网络效率、平均最短路径长度和最大连通子图3个指标,构建评估网络韧性的性能函数模型,提出一种考虑拓扑结构和客流分布均衡性的运营关键站点评估方法,并以南京城市轨道交通系统为例,在无权和加权网络中,探究关键程度降序、介数中心性降序和随机顺序3种相继故障模式下差异性的韧性失效过程。结果表明:关键站点在工作日和周末差异较小;按照关键站点降序的相继故障前期,网络韧性性能下降最为迅速;与拓扑网络相比,客流加权网络在相继故障前期韧性指数下降更快。在网络相继故障未大面积扩散时重点强化关键站点的管控,有助于缩小网络韧性损失。In order to identify high-risk stations in urban rail transit systems and improve network resilience and operational safety,a performance function model was constructed to evaluate the network resilience by selecting network efficiency,average shortest path length and maximum connection sub-graph as indicators,and an evaluation method for critical stations was proposed,considering topological structure and passenger flow distribution equilibrium.Taking Nanjing Metro as an example,three cascading failure modes,descending critical degree,descending betweenness centrality and random sequence,are adopted.The characteristics of resilience degradation under different cascading failures are simulated respectively in the unweighted network and the weighted network.The results show that the critical stations are similar on weekdays and weekends.The resilience performance decreases most rapidly in the early stages of failures in descending order of critical stations.Compared with topology networks,the resilience index of passenger flow-weighted networks decreases faster in the early stages of cascading failures.Strengthening the control of critical stations when cascading failures do not spread widely can help reduce the loss of network resilience.

关 键 词：城市轨道交通 网络韧性 相继故障 关键站点 加权网络 

分 类 号：X951[环境科学与工程—安全科学] U239.5[交通运输工程—道路与铁道工程]