A network accident causation model for monitoring railway safety
作者: Keping LiShanshan Wang
作者单位: 1State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
刊名: Safety Science, 2018, Vol.109 , pp.398-402
来源数据库: Elsevier Journal
DOI: 10.1016/j.ssci.2018.06.008
关键词: RailwayaccidentComplex networkCommunity detection
英文摘要: Abstract(#br)In railway systems, risk monitoring and accident causation analysis are important processes towards operational safety. This paper divides accident causal factors in a railway system into several error types, such as human and signal, and proposes a model based on a complex network for risk monitoring, where the risks of accident causal factors are quantified. This network accident causation model is used to identify accident causal factors and analyze how these factors affect each other, for example, how a signal error leads to a collision between two trains. The results of this case study show that in a complex environment, the proposed model can better identify the root causal factors by quantifying the accident causal factor risk, to find the causation chain based on the...
全文获取路径: Elsevier  (合作)
影响因子:1.359 (2012)

  • causation 因果关系
  • network 网络
  • accident 事故
  • railway 铁道
  • monitoring 监视
  • safety 安全
  • detection 探测
  • model 模型