关键词: 交通流, 跟驰模型, 线性稳定性分析, 后视效应, 多前车

Abstract: 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 looking λi and the sensitivity coefficient of memory effect γi are k=3,λi=［0.2,0.15,0.1］,γi=［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.

Key words: traffic flow, car-following model, linear stability analysis, backward looking effect, multi-preceding vehicles