中国安全科学学报 ›› 2024, Vol. 34 ›› Issue (5): 17-27.doi: 10.16265/j.cnki.issn1003-3033.2024.05.1497

• 安全社会科学与安全管理 • 上一篇    下一篇

山区高速公路交通事故风险多维度耦合研究

胡立伟(), 贺雨, 侯智, 张瑞杰, 陈琛, 刘冰   

  1. 昆明理工大学 交通工程学院,云南 昆明 650500
  • 收稿日期:2023-11-08 修回日期:2024-02-22 出版日期:2024-05-28
  • 作者简介:

    胡立伟 (1978—),男,山东潍坊人,博士,教授,主要从事交通安全、城市交通流特性分析及控制理论与方法研究。E-mail:

  • 基金资助:
    国家自然科学基金资助(42277476)

Multi-dimensional coupling study on traffic accident risk of highway in mountainous areas

HU Liwei(), HE Yu, HOU Zhi, ZHANG Ruijie, CHEN Chen, LIU Bing   

  1. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming Yunnan 650500, China
  • Received:2023-11-08 Revised:2024-02-22 Published:2024-05-28

摘要:

为有效降低山区高速公路事故率,以2016—2021年云南省山区高速公路交通事故数据为研究对象,基于集成决策实验法-对抗解释结构模型(DEMATEL-AISM),筛选识别山区高速公路交通风险要素,从人-车-路-环境-管理时空全维度出发,分析风险要素因果并绘制UP和DOWN型有向拓扑层级图,最终确定19种风险因素;构建N-K-耦合度模型量化风险因素,对山区高速公路交通事故风险因素间进行时空全维度耦合,探究风险因素间的关系,并提出山区高速公路交通事故全维耦合交通风险弹性解耦模型。研究结果表明:单维度中,人因的跟车太近与疲劳驾驶耦合值为0.741,路因长大下坡与急弯耦合值为0.816,为单维度中对系统影响较大的2种作用情况;双维度下,较大的作用情况为人-车及人-路,耦合值为0.157、0.124,其中,路因的长大下坡、人因的跟车太近与其他要素易形成强耦合;多维度下最大的作用情况为人-路-环,耦合值为0.891,其中,驾驶人的不良驾驶行为、道路的急弯与长大下坡、环境的雨天、雾天、冰雪天极易与其他因素耦合结果超过70%,构成强耦合关系,发生交通事故概率较大。

关键词: 山区高速公路, 交通事故, 风险因素, 多维度耦合, 耦合度模型, 集成决策实验法-对抗解释结构模型(DEMATEL-AISM)

Abstract:

In order to effectively reduce the accident rate of mountain highways, the traffic accident data of mountain highways in Yunnan province from 2016 to 2021 was taken as the research object, based on the DEMATEL-AISM. This paper analyzes the causality of risk factors and draws the UP and DOWN directed topological hierarchical diagrams, and finally determines 19 risk factors, constructs an N-K-coupling degree model to quantify the risk factors, couples the risk factors of mountain highway traffic accidents in all dimensions, explores the relationship between risk factors, and proposes a full-dimensional coupling model of traffic accidents in mountainous areas. The results show that in the single dimension, the coupling value of human factors being too close to the vehicle and fatigue driving is 0.741, and the coupling value of road factors is 0.816, which are the two effects that have a greater impact on the system in the single dimension, and the coupling values of human-vehicle and human-road are 0.157 and 0.124 in the two-dimensional. The maximum effect of human factors is human-road-ring in multi-dimensional, with a coupling value of 0.891, in which the driver's bad driving behavior, the sharp bend of the road and the long downhill, and the rain, fog, and ice and snow days of the environment are easy to be coupled with other factors more than 70%, which constitutes a strong coupling relationship and the probability of traffic accidents is large.

Key words: mountain highways, traffic accidents, risk factors, multi-dimensional coupling, coupling degree model, decision experimental method-adversarial interpretative structural model (DEMATEL-AISM)

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