考虑后视和多前车信息反馈的车辆跟驰模型  

Car-following Model Considering Multi-preceding Vehicles’Information Feedback and Backward Looking Effect

作　　者：惠飞[1] 席辉 张凯望 魏思 HUI Fei;XI Hui;ZHANG Kai-wang;WEI Si(Dept.artment of Information Engineering,Chang’an University,Xi’an 710064,China)

机构地区：[1]长安大学信息工程学院,陕西西安710064

出　　处：《计算机与现代化》2022年第8期70-77,共8页Computer and Modernization

基　　金：河北省省级科技计划项目(20470801D);国家重点研发计划项目(2018YFB1600604)。

摘　　要：为改进车联网环境下车辆跟驰模型的稳定性,在经典OVCM模型基础上考虑后视效应、多前车速度差和多前车最优速度记忆综合信息对交通流稳定性能的影响,提出一种基于后视和多前车信息反馈的扩展车辆跟驰模型。根据线性稳定性分析法得出模型的中性稳定性判断条件,并进行数值仿真实验与分析。实验结果表明,在扰动初始条件设置一致下,所提模型相比于OV、FVD、OVCM模型,交通流稳定区域增大,速度波动幅度减小,特别是考虑的前车数k、后视敏感系数λi和记忆效应敏感系数γi取值为k=3,λi=[0.2,0.15,0.1],γi=[0.1,0.08,0.06]时,车辆的平均速度波动率低于0.1%,由此说明,所提模型能有效减少扰动影响,增强交通流的稳态保持。In order to improve the stability of the car-following model in the Internet of vehicles environment,based on the classic OVCM model,an extended car-following model is deduced with the consideration of the influence of comprehensive information,including the effect of backward looking,the speed difference of multiple preceding vehicles and the optimal speed memory of multiple preceding vehicles on the stability of traffic flow.The neutral stability judgment conditions is obtained by linear stability analysis and the numerical simulation experiments and analysis are carried out.The experimental results show that,under the same initial disturbance conditions,the proposed model has a larger traffic flow stable area and a smaller speed fluctuation range than the OV,FVD,and OVCM models.Especially when the number of vehicles ahead k,the sensitivity coefficient of backward lookingλi and the sensitivity coefficient of memory effectγi are k=3,λi=[0.2,0.15,0.1],γi=[0.1,0.08,0.06],the average speed fluctuation rate of the vehicle is less than 0.1%.Consequently,the proposed model can effectively reduce the impact of disturbances and enhance the steady-state maintenance of traffic flow.

关 键 词：交通流 跟驰模型 线性稳定性分析 后视效应 多前车 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术] U495[自动化与计算机技术—计算机科学与技术]