混入智能网联汽车的交通流稳定性与安全性分析

Stability and safety analysis on traffic flow mixed with ICV

为揭示智能网联汽车(ICV)对交通流的影响特征,首先,考虑ICV的退化机制,分析混合交通流中的跟驰模式及其比例关系;然后,采用不同参数的智能驾驶员模型(IDM)来描述不同的跟驰模式,在此基础上推导出混合交通流稳定性的判别条件;最后,选取车速标准差变异系数、碰撞时间(TTC)、碰撞暴露时间(TET)和碰撞积分时间(TIT)等作为混合交通流安全性评价指标,并基于元胞自动机进行数值仿真试验。结果表明:随着ICV渗透率的增加,车速的离散程度逐渐降低,且尾部碰撞风险逐渐减小。因此,ICV的应用能够显著提高交通流的稳定性和安全性。

In order to reveal influence mechanism of ICV on traffic flow,firstly,considering degradation mechanism of ICV,its following mode and proportion in mixed traffic flow were analyzed.Then,different following modes were described by utilizing intelligent driver model(IDM)with different parameters,based on which criteria to determine stability of mixed traffic flow were derived.Finally,standard deviation coefficient of car speed,time-to-collision(TTC),exposed time-to-collision(TET)and integrated time-to-collision(TIT)were selected as safety evaluation indexes of the traffic flow,and numerical simulation experiments were conducted based on cellular automata.The results show that as penetration rate of ICV increases,dispersion degree of vehicle speed gradually decreases,so does the risk of rear collision.Therefore,application of ICV can significantly improve stability and safety of traffic flow.