摘要
为探究人、车、路和环境等因素对机非交通事故中机非双方驾驶员过错和事故严重程度的影响,选取2017年广东省发生的1357起机非交通事故的数据作为基础,分别构建二元Logistic回归模型和三元有序Logistic回归模型,分析机动车驾驶员属性、非机动车驾驶员属性、机动车辆、非机动车辆、道路和环境等因素与机非双方驾驶员过错和事故严重程度之间的关系。结果表明:模型拟合度良好;机动车驾驶员是否出现过错与机动车驾驶员的性别、机动车使用性质、道路类型和天气等9个变量显著相关;非机动车驾驶员是否出现过错与非机动车驾驶员的性别、非机动车类型和道路物理隔离等6个变量显著相关;机非交通事故的严重程度与机动车驾驶员的驾龄、机动车安全状况、道路线形和机动车驾驶员过错等7个变量显著相关。该研究结果可为降低机非交通事故严重程度提供参考依据。
In order to explore the risk factors,i.e.human,vehicle,road and environment,associated with fault and severity in motor-bicycle accidents,this paper selects 1 357accidents happening in Guangdong Province in 2017to construct the binary logistic regression and ordinal logistic regression models,considering risk factors in several dimensions,including motor vehicle driver,bicycle driver,motor vehicle,bicycle,road and environment.The results show that firstly the 3models provide good fit for data;secondly,9independent variables,including motor vehicle driver’s gender,usage of motor vehicle,type of road and weather,etc, significantly affect motor vehicle driver’s fault;thirdly,6independent variables,containing bicycle driver’s gender,type of bicycle and isolation of road,etc,were the important factors to affect bicycle driver’s fault;fourthly,motor vehicle-and bicycle accident severity significantly relates to 7factors consisting of motor vehicle driving experience,motor vehicle safety status,road alignment and motor vehicle driver’s fault,etc. The paper can provide the reference for reducing the severity in motor-bicycle accidents.
作者
林庆丰
邓院昌
胡继华
LIN Qingfeng;DENG Yuanchang;HU Jihua(Guangdong Key Laboratory of Intelligent Transportation Systems,School of Intelligent Systems Engineering,Sun Yat-sen University,Guangzhou 510006,China)
出处
《安全与环境工程》
CAS
北大核心
2019年第5期187-193,共7页
Safety and Environmental Engineering
基金
广东省科技计划项目(2017B010111007)
