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A hybrid human and organizational analysis method for railway accidents based on HFACS-Railway Accidents (HFACS-RAs)

  • Qingjian Zhan
  • , Wei Zheng*
  • , Bobo Zhao
  • *Corresponding author for this work
  • Beijing Jiaotong University

Research output: Contribution to journalArticlepeer-review

Abstract

Accidents continue to be the major concern in the railway industry, and human factors have been proved to be the prime causes to railway accidents. In this paper, the Human Factors Analysis and Classification System-Railway Accidents (HFACS-RAs) framework is proposed to identify and classify human and organizational factors involved in railway accidents. To establish an applicable HFACS-RAs framework, large amount of incident and accident data are collected and the existing safety flaws are identified by safety experts, manufactures and railway managers who have attended the HFACS workshop. To find out the leading accident casual factors, the Analytical Network Process (ANP) method combined with Fuzzy Decision Making Trail and Evaluation (DEMATEL) method is adopted to analyze the influence relationships of human and organization factors classified by HFACS-RAs framework after its reliability is demonstrated. The expert judgement is required in most phases in this study for the uncertainty and complexity of the human and organizational factors and the proposed method to identify the main casual factors is elaborated in the case study. The relevant preventative measures can be raised to avoid the recurrence of similar accidents after the investigation. Finally some considerations on further work are discussed.

Original languageEnglish
Pages (from-to)232-250
Number of pages19
JournalSafety Science
Volume91
DOIs
StatePublished - 1 Jan 2017
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • ANP
  • Fuzzy DEMATEL
  • HFACS-RAs
  • Human factor

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