中国安全科学学报 ›› 2019, Vol. 29 ›› Issue (S1): 114-119.doi: 10.16265/j.cnki.issn1003-3033.2019.S1.021

• 安全工程技术科学 • 上一篇    下一篇

基于复杂网络理论的铁路事故致因分析*

花玲玲1,2, 郑伟1,2 教授   

  1. 1 北京交通大学 国家轨道交通安全评估研究中心,北京 100044;
    2 北京交通大学 智能交通数据安全与隐私保护技术北京市重点实验室,北京 100044
  • 收稿日期:2018-03-15 修回日期:2019-05-10 出版日期:2019-06-30 发布日期:2020-10-28
  • 作者简介:花玲玲 (1994—),女,山西长治人,硕士研究生,研究方向为铁路事故致因分析。E-mail:17120228@bjtu.edu.cn。

Research on causation of railway accidents based on complex network theory

HUA Lingling1,2, ZHENG Wei1,2   

  1. 1 National Research Center of Railway Safety Assessment, Beijing Jiaotong University, Beijing 100044, China;
    2 Beijing Key Laboratory of Intelligent Traffic Data Security and Privacy Protection Technology, Beijing Jiaotong University, Beijing 100044, China
  • Received:2018-03-15 Revised:2019-05-10 Online:2019-06-30 Published:2020-10-28

摘要: 为确定导致铁路事故的多种因素间的相互关系,预防铁路事故,收集263份中国铁路事故报告;根据这些事故发生的特点,结合现有事故致因分类模型和专家意见,从人为、机械设备、环境、管理4个方面确定了43个影响因素;基于Pearson相关系数,分析因素间的相关性,确定了268种影响因素间的相互关系,并据此建立铁路事故致因网络模型;利用度、网络直径及平均路径长度、聚类系数、中介中心性等复杂网络指标分析网络的整体结构,确定需要防控的关键因素。结果表明:管理因素和人为因素是最容易导致铁路事故发生的主因素,同时子因素中违规操作、沟通失效、零部件机械故障等因素对于铁路安全运营也有较大的影响。

关键词: 铁路事故, 影响因素, Pearson相关系数, 致因网络模型, 复杂网络

Abstract: In order to determine the relationship between various factors leading to railway accidents, and prevent railway accidents,263 reports of Chinese railway accidents were collected. Based on the characteristics of these railway accidents, combined with the existing accident causal classification model and expert opinions, 43 influencing factors were identified from four aspects,including the act of man, mechanical equipment, environment and management. Based on the correlation coefficient of Pearson, the correlation between factors was analyzed, and the interrelationship between 268 kinds of influencing factors were established. A network of railway accident causation factors was established. The whole network structure was analyzed by using complex network indicators, such as degree and degree distribution, network diameter and average path length, clustering coefficient and betweenness centrality. And the key factors that need to prevent and control were determined. The results show that management factors and human factors are the most likely to cause railway accidents. At the same time, sub-factors such as illegal operation, communication failure, mechanical failure of components have great influence on railway safety operation.

Key words: railway accidents, influencing factors, Pearson correlation coefficient, network of causation factors, complex network

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