摘要
为评估智能网联环境下高速公路辅助驾驶车辆编队的效果,首先基于V2X(Vehicle to Everything)和智能驾驶人模型(Intelligent Driver Model,IDM)对网联环境下的车辆跟驰行为进行建模,并对其进行参数校准;其次从安全性评价指标和通行效率两方面构建编队效果评价体系;然后通过VISSIM和VBA联合仿真,改变编队的车道、交通流量、网联车渗透率等变量进行试验。仿真结果表明,网联环境下车辆辅助驾驶编队在不同层面对于安全性与效率性都有提升;最后以不同期望速度在网联环境和非网联环境下分别进行实车辅助驾驶编队试验,以验证评价指标体系以及仿真试验的有效性。其中,实车试验结果显示,期望速度为70 km·h-1时,网联环境下的辅助驾驶编队通行效率比非网联环境提升56%,90 km·h-1时提升37.2%,110 km·h-1时提升39.8%。通过与仿真试验结果对比,表明网联环境下车辆辅助驾驶编队对交通流安全性有一定程度的提升。
This study examines the effects of assisted driving platooning on traffic safety and efficiency in an intelligent networked expressway environment.In order to evaluate traffic safety and efficiency,vehicle-following behavior in a connected vehicle(CV)environment was modeled on Vehicle-to-Everything(V2 X)and intelligent driver models.Once the parameters were calibrated,a safety evaluation index and traffic efficiency were used to construct the platooning-effect evaluation system.Through the joint use of VISSIM and VBA simulation software,variables such as lane choice,traffic flow,and the CV penetration rate of platooning were tested with results showing improved safety and efficiency for assisted driving platooning in the CV environment.Vehicle platoon field tests for both CV and non-CV environments were then conducted using different expected speeds to verify the evaluation index and accuracy of the simulation.The field tests showed that the traffic efficiency of assisted driving platooning in a CV environment was 56%higher than that in the non-CV environment when the expected speed of tested vehicles was 70 km·h-1.When the speeds increased to 90 km·h-1 and 110 km·h-1,traffic efficiency increased by 37.2%and 39.8%,respectively.A comparison with simulation test results showed that vehicle-assisted driving platooning in the CV environment can improve traffic flow safety and efficiency.
作者
邱志军
杨唐涛
檀基稳
韩海航
QIU Zhi-jun;YANG Tang-tao;TAN Ji-wen;HAN Hai-hang(Intelligent Transportation Systems Research Center,Wuhan University of Technology,Wuhan 430063,Hubei,China;Department of Civil and Environmental Engineering,University of Alberta,Edmonton T6G2W2,Alberta,Canada;Zhejiang Scientific Research Institute of Transport,Hangzhou 311305,Zhejiang,China)
出处
《中国公路学报》
EI
CAS
CSCD
北大核心
2019年第12期66-75,共10页
China Journal of Highway and Transport
基金
国家自然科学基金项目(61673307).
关键词
交通工程
智能交通
车辆编队
辅助驾驶
车联网
安全性评估
traffic engineering
intelligent transportation
platooning
driver assistance
connected vehicle
safety evaluation
