Improved car-following model at signalized intersection based on vehicle-infrastructure cooperation technology

被引：0
|
作者：
An S. [1 ]
Xu L. [1 ]
Chen G. [1 ]
Luo H. [1 ]
Cao H. [1 ]
机构：
[1] School of Transportation, Wuhan University of Technology, Wuhan
来源：
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2020年 / 50卷 / 01期
关键词：
Car-following model; Guidance interval; Signalized intersection; Vehicle-infrastructure cooperation;
D O I：
10.3969/j.issn.1001-0505.2020.01.022
中图分类号：
学科分类号：
摘要：
To alleviate the interruption of traffic flow caused by signalized intersections, a speed guidance decision method was proposed based on a vehicle-infrastructure cooperation technology. Considering the phase difference of signal lights and the traffic conditions for vehicles, three speed guidance strategies were formulated, and an improved car-following model was established. The guidance effect of the model was verified by numerical simulations, and the influence of the length of the guidance interval on the speed guidance was analyzed. The results show that compared with the existing models, the improved car-following model can enable more vehicles to pass through the intersection quickly before the end of the green light, and other vehicles to smoothly decelerate to stop or follow the rear of the queue to pass through intersections without stopping after the end of the red light. Therefore, the sudden change of the vehicle speed is eliminated. In addition, by increasing the length of the guidance interval, the phenomenon of vehicle stopping at a signalized intersection is relieved, thus enhancing the effects of the speed guiding. The feasibility and the superiority of the improved car-following model are proved. © 2020, Editorial Department of Journal of Southeast University. All right reserved.
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页码：169 / 174
页数：5
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