Car-Following Model at Signalized Intersections Considering Driver's Estimation of Traffic Dynamics

被引:0
作者
Luo, Ying [1 ]
Chen, Yanyan [1 ]
Lu, Kaiming [1 ]
Zhang, Jian [1 ]
机构
[1] Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China
来源
CICTP 2023: INNOVATION-EMPOWERED TECHNOLOGY FOR SUSTAINABLE, INTELLIGENT, DECARBONIZED, AND CONNECTED TRANSPORTATION | 2023年
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D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
To investigate the influence of traffic dynamics of the signalized intersection on car-following behavior, a novel model considering the driver's estimation of traffic dynamics is proposed. Firstly, two patterns of car-following behavior under different traffic conditions are derived according to the two-dimensional distribution characteristics of acceleration and velocity difference processed from high-precision vehicle trajectory data extracted from UAV footage. Secondly, two parameters are introduced to the full velocity difference model (FVDM) to describe the driver's perception, estimate the traffic dynamics at signalized intersections, and propose an extended car-following model at signalized intersections (SI-FVDM). Based on the linear stability analysis theory, the stability conditions of the SI-FVDM are derived. Finally, the parameters of the original and extended models are calibrated and verified through simulation experiments. The results show that the SI-FVDM has a larger stability regime than the FVDM, and the simulation results are consistent with the theoretical stability conditions.
引用
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页码:257 / 267
页数:11
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