交通运输系统工程与信息

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (4): 275-286.DOI: 10.16097/j.cnki.1009-6744.2025.04.025

• 系统工程理论与方法 • 上一篇    下一篇

基于多层网络加权投影的站内关键轨道区段识别研究

高鹏飞1a ，郑伟*1a,1b ，王洪伟1a ，李晔2   

  1. 1. 北京交通大学，a.自动化与智能学院，b.国家轨道交通安全评估研究中心，北京100044； 2. 铁科院(北京)工程咨询有限公司，北京100025
  • 收稿日期:2025-04-21 修回日期:2025-05-26 接受日期:2025-06-03 出版日期:2025-08-25 发布日期:2025-08-25
  • 作者简介:高鹏飞(1990—)，男，陕西铜川人，助理研究员，博士生。
  • 基金资助:
    中央高校基本科研业务费专项资金 (2025JBMC038)；天津市科技计划项目(24YDLQYS00110)。

Multi-layer Network Weighted Projection Approach to Identify Critical Track Sections in Railway Station

GAO Pengfei1a, ZHENG Wei*1a,1b, WANG Hongwei1a, LI Ye2   

  1. 1a. School of Automation and Intelligence, 1b. National Research Center of Railway Safety Assessment, Beijing Jiaotong University, Beijing 100044, China; 2. Beijing Engineering Consultation Co Ltd, China Academy of Railway Sciences Corporation Limited, Beijing 100025, China
  • Received:2025-04-21 Revised:2025-05-26 Accepted:2025-06-03 Online:2025-08-25 Published:2025-08-25
  • Supported by:
    Fundamental Research Funds for the Central Universities of Ministry of Education of China (2025JBMC038)；Tianjin Science and Technology Plan Project(24YDLQYS00110)。

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摘要： 站内轨道区段作为列车车列走行的基础单元，其失效直接影响站场运输效率和客货运输服务水平。为有效识别站内关键轨道区段，本文以联锁图表为数据源，基于复杂网络理论构建车站站场多层网络及其加权投影网络模型；选取度中心性、接近中心性和PageRank等12个典型节点重要性评价指标，运用改进秩和比方法融合得到节点综合重要度排序；最后，利用排序结果的站场映射及其按顺序屏蔽引起的网络效率变化验证方法的有效性。典型车站的实例分析结果表明：本文方法有效建立了包含7个网络层和72个节点的多层网络，并通过作业量比例构建了加权投影网络模型；在此基础上，识别出的关键轨道区段处于上下行咽喉，与实际情况较为契合；按节点重要性排序依次屏蔽前10，20，33个节点后，网络效率分别下降37.57%、51.26%和97.28%，证明本文方法的有效性。此外，相关性分析结果进一步证实，本文方法有效融合了拓扑结构、通信效率和影响力等多种指标特征，在多层复杂网络节点重要性评估中具有综合性优势。

关键词: 铁路运输, 关键轨道区段, 改进秩和比方法, 车站站场网络, 节点重要性综合评价

Abstract: The track sections play a critical role in train operations within a railway station. The failure of track sections can significantly reduce transportation efficiency and service quality. This study proposes a methodology to identify critical track sections based on complex network theory. Using signaling layouts and interlocking tables as primary data sources, the study first establishes a multi-layer network model of the station and its weighted projection network. Then, 12 representative node importance metrics including degree centrality, closeness centrality, and PageRank are integrated through an improved Rank-Sum Ratio method to derive comprehensive node significance rankings. The validity of the proposed methodology is verified through mapping the resulting ranking in station yards and analyzing network efficiency changes caused by node removal. A case study of a typical railway station demonstrates that the proposed method successfully establishes a multi-layer network consisting of 7 layers and 72 nodes, and derives a weighted projection network based on the actual operational volume proportions. The identified critical track sections are located at the throat areas of arrival and departure routes, which are consistent with the actual operational bottlenecks. Sequential removal of the top 10, 20, and 33 ranked nodes leads to network efficiency reductions of 37.57%, 51.26%, and 97.28%, respectively, confirming the method's marked effectiveness. Furthermore, the correlation analyses confirm that the proposed method effectively integrates topological, communicative efficiency, and influence features, thereby offering a comprehensive and robust evaluation of node importance in multi-layer complex networks.

Key words: railway transportation, critical track sections, improved rank-sum ratio method, railway station yard network; comprehensive evaluation of node importance

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