交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (5): 46-55.DOI: 10.16097/j.cnki.1009-6744.2026.05.004

• 青年基金项目成果 • 上一篇    下一篇

多种风险下城市地铁网络脆弱性及不确定性研究

段金肖*1a ,刘亚楠1a ,吴可儿1a ,武一丹1a ,曾冠文1b ,王云1a ,闫学东2   

  1. 1.北京交通大学,a.交通运输学院,b.系统科学学院,北京100044;2.西南交通大学,交通运输与物流学院,成都611756
  • 收稿日期:2026-04-17 修回日期:2026-07-15 接受日期:2026-07-25 出版日期:2026-10-25 发布日期:2026-10-21
  • 作者简介:段金肖(1994—),女,陕西咸阳人,讲师,博士。
  • 基金资助:
    国家自然科学基金青年科学基金 (72501019, 72501024)。

Vulnerability and Uncertainty of Urban Metro Networks Under Multiple Risks

DUAN Jinxiao*1a, LIU Yanan1a, WU Ke'er1a, WU Yidan1a, ZENG Guanwen1b, WANG Yun1a,YAN Xuedong2   

  1. 1a. School of Traffic and Transportation, 1b. School of Systems Science, Beijing Jiaotong University, Beijing 100044, China; 2. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China
  • Received:2026-04-17 Revised:2026-07-15 Accepted:2026-07-25 Online:2026-10-25 Published:2026-10-21
  • Supported by:
    Young Scientists Fund of the National Natural Science Foundation of China (72501019, 72501024)。

摘要: 综合分析地铁网络在不同类型扰动下的脆弱不确定性,挖掘其影响因素是全面提高地铁运行可靠性的关键所在。本文考虑地铁系统典型风险,提出一种基于渗流理论的地铁网络脆弱性及不确定性量化方法,定义了地铁系统的风险抵抗能力和性能损失程度,以及两类脆弱性指标的不确定性。以我国40个城市的地铁网络为对象,模拟了随机攻击、度攻击和介数攻击下网络渗流过程,并分析线网布局、结构冗余、结构瓶颈等特征对地铁网络脆弱性的影响。研究发现:平均聚类系数和桥总数对风险抵抗能力与性能损失程度两种脆弱性表现出一致的改善或加剧趋势,连接密度对两者的作用效果则相反;风险抵抗能力不确定性的影响因素较多元,性能损失程度不确定性的影响因素单一。综合分析脆弱性及不确定性的非线性影响因素发现,网络连接密度、瓶颈割集和线路数量是关键特征。本文为面向多风险防控的韧性网络设计提供理论依据与实践指导。

关键词: 城市交通, 脆弱性不确定性, 渗流理论, 地铁网络, 多风险影响

Abstract: Comprehensively analyzing the vulnerability and its uncertainty of metro networks under different disturbances, as well as identifying their influencing factors is the key to improve the operational reliability. Considering the typical risks of metro systems, this paper proposes a percolation theory-based method to quantify the vulnerability and uncertainty. This method defines the risk-resistance ability and performance-loss degree of metro systems, as well as the uncertainty of these two vulnerability indicators. Taking the metro networks of 40 cities in China as research object, this study simulates the network percolation process under random attacks, degree attacks, and betweenness attacks, and analyzes the influence of network layout, structural redundancy, and structural bottlenecks on metro network vulnerability. The results show that the average clustering coefficient and the bridge count have consistent effects on risk-resistance ability and performance-loss degree, while the influence of connection density on them is opposite. The influencing factors for the uncertainty of risk-resistance ability are diverse, while those for uncertainty of performance-loss degree are simple. The comprehensive analysis of the nonlinear factors on network vulnerability and its uncertainty, reveals that connection density, network bottleneck cuts, and the number of lines are the most key factors. This study provides a theoretical support and practical guidance for the design of resilient metro networks.

Key words: urban transportation, vulnerability and uncertainty, percolation theory, metro network, multi-risk impacts

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