中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (5): 144-151.doi: 10.16265/j.cnki.issn1003-3033.2023.05.1068

• 公共安全 • 上一篇    下一篇

基于风险场的高速公路高风险区域甄别方法

张驰1(), 王博1, 陈星光2, 任士鹏2, 翟艺阳1   

  1. 1 长安大学 公路学院,陕西 西安 710064
    2 广东省交通规划设计研究院集团股份有限公司,广东 广州 510630
  • 收稿日期:2022-12-23 修回日期:2023-02-16 出版日期:2023-05-28
  • 作者简介:

    张 驰 (1981—),男,四川宜宾人,博士,教授,主要从事交通安全与交通BIM研究。E-mail:

  • 基金资助:
    国家重点研发计划(2020YFC1512005); 四川省科技计划资助项目(2022YFG0048); 四川省交通运输科技项目(2019-ZL-12); 四川省交通运输科技项目(2022-ZL-04)

High-risk area identification method of expressway based on risk field

ZHANG Chi1(), WANG Bo1, CHEN Xingguang2, REN Shipeng2, ZHAI Yiyang1   

  1. 1 School of Highway, Chang'an University, Xi'an Shaanxi 710064, China
    2 Guangdong Communication Planning & Design Institute Group Co., Ltd., Guangzhou Guangdong 510630, China
  • Received:2022-12-23 Revised:2023-02-16 Published:2023-05-28

摘要:

为有效识别高速公路高风险区域,首先,在理论阐述和量化解释行车风险演化机制基础上引入势场理论,提出道路静态风险场的基本概念及性质;然后,在分析道路要素对行车安全影响的基础上,构建路域范围内的构造物、线形、路侧等要素的静态风险场计算模型,提出高速公路高风险区域甄别方法,同时,基于交通事故统计数据,对静态风险场计算模型的风险量进行参数标定;最后,依托实际项目,进行区域风险等级预测和有效性验证。结果表明:研究路段的33处区域中26处甄别结果与实际风险等级相同,仅有7处结果不一致,风险等级结果相差一个等级内的区域数量为30处; 风险等级预测结果准确率达78.79%,与实际风险等级结果相差一个等级内的准确率达90.91%。静态风险场能够有效应用于高风险区域甄别,研究有助于设计及运营阶段高速公路安全治理。

关键词: 风险场, 高速公路, 高风险区域甄别, 行车风险, 道路静态风险场

Abstract:

In order to effectively identify high risk areas of expressways, firstly, the potential field theory was introduced on the basis of theoretical exposition and quantitative interpretation of driving risk evolution mechanism, and the basic concept and properties of road static risk field were proposed. Then, on the basis of analyzing the influence of road factors on traffic safety, the static risk field calculation model of structures, alignments, roadsides and other factors in the road domain was constructed, and the method of identifying high risk areas of expressways was proposed. At the same time, based on the statistical data of traffic accidents, the risk quantity parameters of the static risk field calculation model were calibrated. Finally, based on the actual project, the regional risk level prediction and effectiveness verification were carried out. The results show that among the 33 areas of the study section, 26 of the screening results are the same as the actual risk level, only 7 of the results are inconsistent, and the number of areas within one level of risk level difference is 30. The accuracy of the risk level prediction results is 78.79%, and the accuracy of the actual risk level results is 90.91%. The static risk field can be effectively applied to the identification of high-risk areas, and the research is helpful to the highway safety management in the design and operation stages.

Key words: risk field, expressway, high-risk areas identification, driving risk, road static risk field