Influence of adverse weather on drivers’ perceived risk during car following based on driving simulations

作     者：Chen Chen Xiaohua Zhao Hao Liu Guichao Ren Xiaoming Liu 

作者机构：Operation GuaranteeCollege of Metropolitan TransportationBeijing University of TechnologyBeijing 100124China Beijing Transportation InformationBeijing 100161China 

出 版 物：《Journal of Modern Transportation》 (现代交通学报（英文版）)

年 卷 期：2019年第27卷第4期

页      面：282-292页

学科分类：04[教育学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 0802[工学-机械工程] 0814[工学-土木工程] 0801[工学-力学（可授工学、理学学位）] 0823[工学-交通运输工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China project(61672067) Science and Technology Program of Beijing(Z151100002115040) 

主　　题：Adverse weather Driving simulation Perceived risk Entropy weight method Multiple linear regression 

摘      要：Adverse weather has a considerable impact on the behavior of drivers,which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents.This research examines how drivers perceived risk changes during car following under different adverse weather conditions by using driving simulation experiment.An expressway road scenario was built in a driving simulator.Eleven types of weather conditions,including clear sky,four levels of fog,four levels of rain and two levels of snow,were designed.Furthermore,to simulate the carfollowing behavior,three car-following situations were designed according to the motion of the lead car.Seven car-following indicators were extracted based on risk homeostasis theory.Then,the entropy weight method was used to integrate the selected indicators into an index to represent the drivers perceived risk.Multiple linear regression was applied to measure the influence of adverse weather conditions on perceived risk,and the coefficients were considered as indicators.The results demonstrate that both the weather conditions and road type have significant effects on car-following behavior.Drivers perceived risk tends to increase with the worsening weather conditions.Under conditions of extremely poor visibility,such as heavy dense fog,the measured drivers perceived risk is low due to the difficulties in vehicle operation and limited visibility.