[关键词]
[摘要]
本文以综合交通枢纽中的地铁车站安全为研究目标,综合考虑综合交通枢纽中特殊的客流组成和乘客特征,以踩踏、火灾、水灾、公共卫生和大面积滞留五类易发风险事故作为研究对象,基于FTA-BN方法对其影响因素进行分析,识别其风险因素,建立相应的事故树模型,转化为贝叶斯网络模型进行风险评价;引入三角模糊数处理专家自然语言,得到贝叶斯网络中的先验概率和条件概率分布,然后通过贝叶斯网络模型进行网络推理计算和敏感性分析,找出地铁车站中的薄弱部分,制定相应的风险管控措施,从而提高枢纽中地铁车站对于紧急事件的应对能力。并以广州南站地铁车站为例进行了快速评价,结果表明:广州南站在公共卫生安全方面存在一定危险,发生概率为42.98%,且较易发生大面积滞留事件,可能性为30.40%。
[Key word]
[Abstract]
This paper takes the subway station safety in the integrated transportation hub as the research objective, and comprehensively considers the special passenger flow composition and passenger characteristics in the integrated transportation hub. Taking five types of prone risk accidents as the research objects: stampede, fire, flood, public health, and large-area detention. Analyze its influencing factors based on the FTA-BN method, identify its risk factors, establish a corresponding fault tree model, and transform it into a Bayesian network model for risk assessment. The prior probability and conditional probability distributions in Bayesian networks are obtained by introducing expert natural language for triangular fuzzy number processing. Then the Bayesian network model is used to perform network reasoning calculations and sensitivity analysis to find the weak parts in the subway station, and formulate corresponding risk control measures, so as to improve the ability of the subway station in the hub to respond to emergencies. Taking The subway station of Guangzhou South Metro Station as an example, the rapid evaluation results show that Guangzhou South Metro Station has a certain risk in terms of public health safety, with a probability of 42.98%, and is prone to large area detention, with a probability of 30.40%.
[中图分类号]
X951 ? ??????????????
[基金项目]
广东省科技计划资助项目(2017A050501005);亚热带建筑科学国家重点实验室开放基金资助项目(2020ZB25)