华南理工大学学报(自然科学版) ›› 2021, Vol. 49 ›› Issue (8): 12-18.doi: 10.12141/j.issn.1000-565X.200699

所属专题: 2021年交通运输工程

• 交通运输工程 • 上一篇    下一篇

高速公路单车事故等级的影响因素分析

温惠英 张璇 曾强   

  1. 华南理工大学 土木与交通学院,广东 广州 510640
  • 收稿日期:2020-11-16 修回日期:2021-03-06 出版日期:2021-08-25 发布日期:2021-08-01
  • 通信作者: 曾强(1988-),男,博士,副教授,主要从事交通安全和交通组织等研究。 E-mail:zengqiang@scut.edu.cn
  • 作者简介:温惠英(1965-),女,博士,教授,主要从事交通安全、交通规划和物流系统优化等研究。E-mail:hywen@ scut.edu.cn
  • 基金资助:
    政府间国际科技创新合作重点专项(2017YFE0134500);国家自然科学基金资助项目(71801095);华南理工大学中央高校基本科研业务费专项资金资助项目(2020ZYGXZR007)

Influence Factor Analysis of Freeway Single-Vehicle Crash Severity

WEN Huiying ZHANG Xuan ZENG Qiang   

  1. School of Civil Engineering and Transportation, South China University of Technology,Guangzhou 510640,Guangdong, China
  • Received:2020-11-16 Revised:2021-03-06 Online:2021-08-25 Published:2021-08-01
  • Contact: 曾强(1988-),男,博士,副教授,主要从事交通安全和交通组织等研究。 E-mail:zengqiang@scut.edu.cn
  • About author:温惠英(1965-),女,博士,教授,主要从事交通安全、交通规划和物流系统优化等研究。E-mail:hywen@ scut.edu.cn
  • Supported by:
    Supported by the International Science & Technology Cooperation Program of China(2017YFE0134500)and the National Natural Science Foundation of China(71801095)

摘要: 单车事故作为高速公路上一种常见的事故类型,每年给我国人民生命财产造成了严重的损失。为降低该类事故带来的负面影响,将高速公路单车事故等级作为因变量,建立计量模型,探究其主要影响因素,并从工程和管理角度提出相应的安全改善措施。在获取2013至2015年广东省开阳高速公路的单车事故数据的基础上,为对事故发生时的天气状况进行更全面、具体和准确的描述,根据事故的发生时间和地点,为每起事故匹配了相应的实时气象数据。考虑到事故等级的有序性与事故数据中潜在的异质性,建立了随机参数有序logit模型对数据进行拟合。结果表明:车辆类型和空气湿度对单车事故等级的影响存在显著的异质性;单车事故等级的显著影响因素还包括驾驶员类型、救援到达时长、风速和事故时间。相对于非职业驾驶员,职业驾驶员发生重特大事故的概率高6.22%;相对于客运车辆等,货车发生重特大事故的概率低0.59%;相对于白天,夜晚发生重特大事故的概率低0.31%;路政救援到达时长每增加1min、湿度每增加1%、风速每降低1m/s,重特大事故的发生概率将分别增加0.01%、0.02%和0.10%。最后,根据该分析结果,提出了相应的安全改善措施。


关键词: 高速公路, 单车事故, 事故等级, 有序logit模型, 实时气象数据

Abstract: Single-vehicle crash, as a common crash type of freeway crash, leads to great loss to society every year.  To reduce the negative impact brought by this type of crash, this study took freeway single-vehicle crash severity as dependent variable and constructed a econometric model to investigate the major influence factors. And some engineering and management countermeasures were put forward. The single-vehicle crash data of Guangdong Kaiyang freeway in 2013—2015 was collected. To describe the weather condition at the time when crash occurred more comprehensively, specifically and accurately, real-time weather data was matched to each crash according to the crash time and location. In terms of methodology, considering that the crash severity was ordered and there might exist heterogeneity in crash data, random parameter ordered logit model was established to fit the data. The results show that, the impact of vehicle type and humidity on crash severity has significant heterogeneity. The significant variables also include driver type, emergency medical services (EMS) response time, wind speed and crash time. Compared to non-professional driver, professional driver has a 6.22% higher probability for severe crash. Compared to other vehicles like coach, truck has a 0.59% lower probability for severe crash. Compared to daytime, the probability of severe crash at night decreases 0.31%. When the EMS response time increases 1min, the humidity increases 1%, and the wind speed decreases 1m/s, the probability of severe crash would increase 0.01%, 0.02% and 0.10% respectively. Finally, according to the results, some safety countermeasures were put forward.

Key words: freeway, single-vehicle crash, crash severity, ordered logit model, real-time weather data

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