Vehicle-following model in mixed traffic flow considering interaction potential of multiple front vehicles

被引:0
|
作者
Zong F. [1 ]
Wang M. [1 ]
Zeng M. [2 ]
Shi P.-X. [1 ]
Wang L. [3 ]
机构
[1] College of Transportation, Jilin University, Jilin
[2] College of Engineering, Zhejiang Normal University, Jinhua
[3] Beijing Key Lab of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing
基金
中国国家自然科学基金;
关键词
Automated vehicle; Mixed traffic flow; Regular vehicle; Traffic control; Traffic simulation; Vehicle-following model;
D O I
10.19818/j.cnki.1671-1637.2022.01.021
中图分类号
学科分类号
摘要
The mixed traffic flow consisting of automated vehicle (AV) and regular vehicle (RV) was analyzed. Based on the full velocity difference (FVD) model, a vehicle-following model for two types of vehicles (AV and RV) in mixed traffic flow was constructed by considering the factors of the headway, velocity, velocity difference and acceleration difference of multiple front vehicles and one rear vehicle. By introducing the molecular dynamics, the model also quantitatively expressed the influence degree of a surrounding vehicle on the host vehicle. According to the data collected from the vehicle-following field test mixed with AVs and RVs, the model parameters were globally optimized to obtain the highest accuracy. The stability of traffic flow for the vehicle-following model and FVD model was compared, and the influence of velocity on the stability of traffic flow was analyzed. Numerical simulation was designed to simulate the common traffic scenarios including urban areas and expressways, and the accuracy of the proposed model was analyzed. Simulation results indicate that the stability of traffic flow improves by considering the information from surrounding multiple vehicles, and the small velocity can reduce the stability. The proposed model can respond to the behaviours of the whole platoon in advance and simulate the dynamics characteristics of AVs better. In urban areas, compared with the FVD model, the average maximum error and average error of RV for the proposed model reduce by 0.18 m• s-1and 13.12%, respectively, and the accuracy improves by 4.47%. In expressways, compared with the adaptive cruise control (ACC) model provided by PATH Laboratory, the average maximum error and average error of AV for the proposed model reduce by 7.78% and 26.79%, respectively, and the accuracy improves by 1.12%. In addition to providing model basis for AV-following control and queue control in mixed traffic flow, the proposed model can be utilized in vehicle-following behavior simulation for AV and RV. © 2022, Editorial Department of Journal of Traffic and Transportation Engineering. All right reserved.
引用
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页码:250 / 262
页数:12
相关论文
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