Car-following Model and Safety Characteristics of Connected Autonomous Vehicle Based on Molecular Force Field

被引：0
作者：
Qu D.-Y. [1 ]
Meng Y.-M. [1 ]
Wang T. [1 ,3 ]
Song H. [1 ]
Chen Y.-C. [2 ]
机构：
[1] School of Mechanical and Automotive Engineering, Qingdao University of Technology, Shandong, Qingdao
[2] School of Civil Engineering, Qingdao University of Technology, Shandong, Qingdao
[3] School of Artificial Intelligence and Big Data, Zibo Vocational Institute, Shandong, Zibo
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2023年 / 23卷 / 06期
基金：
中国国家自然科学基金;
关键词：
car-following model; connected autonomous vehicles; intelligent transportation; molecular force field; stability analysis;
D O I：
10.16097/j.cnki.1009-6744.2023.06.004
中图分类号：
学科分类号：
摘要：
To describe the dynamic characteristics of multi-dimensional perception and interaction of heterogeneous traffic flow under the complex environment of human-vehicle-road more accurately, this paper proposes a vehicle-following model based on the molecular dynamics potential field function. The characteristics of self-driven particles and the safety characteristics of vehicle to vehicle interaction behavior of connected autonomous vehicles are analyzed from the perspective of molecular force field, which is helpful for systematically analyzing the synergy relationship and safety situation evolution law of networked heterogeneous vehicle groups. First, the connected autonomous vehicles under complex traffic conditions are taken as self-driven particles. The vehicle-following model for the connected autonomous vehicle is established based on the molecular dynamics potential field theory. The molecular force field model for the following behavior of the connected autonomous vehicles is developed by introducing the velocity synergy term. Then, the Artificial Bee Colony Algorithm is used to calibrate the parameters of the existing car-following model and the intelligent driver model using the High_D vehicle trajectory data. The rationality and safety of the molecular force field car- following model are verified. The numerical simulation is designed to verify the fitting effect and stability performance of the molecular force field model on the real vehicle following behavior. The results show that the Mean Absolute Error and Root Mean Squared Error of the vehicle acceleration results obtained by the molecular force field model were lower and the fluctuation was smaller than actual data when disturbed. The proposed model improves the safety and efficiency of the following behavior of the connected autonomous vehicles, and the macroscopic traffic flow operation has better stability. The proposed model can systematically describe the dynamic characteristics, microscopic car-following behavior and the vehicle to vehicle safety interaction relationship of connected heterogeneous vehicle groups, which provides a theoretical basis for improving driving safety and traffic operational efficiency. © 2023 Science Press. All rights reserved.
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页码：33 / 41
页数：8
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