中国安全科学学报 ›› 2020, Vol. 30 ›› Issue (8): 151-157.doi: 10.16265/j.cnki.issn1003-3033.2020.08.022

• 公共安全 • 上一篇    下一篇

Tropos-FRAM法在道路客运事故分析中的应用

尹德志1,2,3, 帅斌**1,2,3 教授, 黄文成1,2,3 讲师, 张玥1,2,3, 张锐1,2,3, 左博睿1,2,3   

  1. 1 西南交通大学 交通运输与物流学院,四川 成都 611756;
    2 西南交通大学 综合交通运输智能化国家地方联合工程实验室,四川 成都 611756;
    3 综合交通大数据应用技术国家工程实验室,四川 成都 611756
  • 收稿日期:2020-05-13 修回日期:2020-07-17 出版日期:2020-08-28 发布日期:2021-07-15
  • 通讯作者: ** 帅 斌(1967—),男,四川乐山人,博士,教授,主要从事危险品运输路网建模与规划、危险品运输系统评价等方面的研究。E-mail:shuaibin@home.swjtu.edu.cn。
  • 作者简介:尹德志 (1997—),男,黑龙江齐齐哈尔人,硕士研究生,研究方向为铁路、公路运输事故分析、多层运输网络级联失效及抗毁性分析。E-mail:983734416@qq.com。
  • 基金资助:
    国家自然科学基金资助(71173177);国家铁路局科技计划项目(KF2013-020,KF2014-041);西南交通大学研究生创新实验实践项目(YC201507103);西南交通大学研究生学术培养提升计划(跨学科创新培育)专题项目(2018KXK04)。

Application of Tropos-FRAM method in road passenger traffic accident analysis

YIN Dezhi1,2,3, SHUAI Bin1,2,3, HUANG Wencheng1,2,3, ZHANG Yue1,2,3, ZHANG Rui1,2,3, ZUO Borui1,2,3   

  1. 1 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 611756, China;
    2 National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu Sichuan 611756, China;
    3 National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Chengdu Sichuan 611756, China
  • Received:2020-05-13 Revised:2020-07-17 Online:2020-08-28 Published:2021-07-15

摘要: 为深入探究道路旅客运输事故致因,预防事故发生,运用功能共振分析法(FRAM)中的功能模块替换Tropos目标风险框架中的任务节点,提出Tropos-FRAM事故分析方法;采用该方法构建Tropos-FRAM失效功能—事件网络,并分析事故,根据分析结果建立Tropos处理层;以“8·10”特别重大道路交通事故实例验证该方法。结果表明:Tropos-FRAM能弥补原有FRAM模型的不足,从源头深入探究参与者功能模块失效、功能连接失效原因,从而提出更有效的事故预防方法。

关键词: Tropos目标风险框架, 功能共振分析法(FRAM), 道路客运事故, 事故分析, 事故预防

Abstract: In order to deeply explore causes of road passenger traffic accidents as well as prevent them, a Tropos-FRAM accident analysis method was proposed by replacing functional modules in FRAM with task nodes in Tropos framework. Then, a Tropos-FRAM failure function-event network was constructed by using this method to analyze accidents, and Tropos processing layers were established based on analysis results. Finally, this method was verified with "8·10" especially serious road traffic accidents as an example. The results show that Tropos-FRAM can make up for deficiencies of original model, and deeply explore root causes for failure of participants' functional modules and functional connections, which helps to put forward more effective accident prevention methods.

Key words: Tropos target risk framework, functional resonance analysis method (FRAM), road passenger traffic accident, accident analysis, accident prevention

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