摘 要：针对人类驾驶车辆和智能网联车辆（CAV）混合的交通流，基于智能网联汽车跟驰特性，提出了一种灵敏度、平滑因子均可调的数学模型，用一个引理和一个定理来支持交通流稳定性标准，进行了一系列仿真模拟来分析车流量的稳定性。结果表明：在一定密度范围内，智能网联汽车交通流的稳定性强于混合交通流，且随着参数的增加，存在一个临界值。不同的灵敏度和平滑因子会影响交通流的稳定性，在一定边界条件下，随着灵敏度和平滑因子的增大，智能网联车流和混合交通流的稳定性均得到了增强。
关键词：智能网联汽车；跟驰模型；混合交通流；稳定性分析；数值仿真
DOI:10.19850/j.cnki.2096-4706.2022.10.034
中图分类号：TP391.9 文献标识码：A 文章编号：2096-4706（2022）10-0134-04
Analysis of Mixed Traffic Flow of CAV Based on Car-Following Model
ZHAO Hui
(Lanzhou Petrochemical University of Vocational Technology, Lanzhou 730060, China)
Abstract: Aiming at the mixed traffic flow of human-driven vehicles and CAV, this paper proposes a mathematical model with adjustable sensitivity and smoothing factor based on the car-following characteristics of CAV. A lemma and a theorem are used to support the traffic flow stability standard. A series of analog simulations are carried out to analyze the stability of traffic flow. The results show that within a certain density range, the stability of CAV traffic flow is stronger than that of mixed traffic flow, and there is a critical value with the increase of parameters. Different sensitivities and smoothing factors will affect the stability of traffic flow. Under certain boundary conditions, with the increase of sensitivity and smoothing factors, the stability of CAV and mixed traffic flow are all enhanced.
Keywords: CAV; car-following model; mixed traffic flow; stability analysis; numerical simulation
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作者简介：赵辉（1991.09—），女，汉族，甘肃金昌人，助教，教师，硕士研究生，研究方向：电气自动化、汽车故障检测与诊断、智能网联汽车。