基于多车状态变化特征的网联车跟驰模型

Car-Following Model for Connected Vehicles Based on Multiple Vehicles with State Change Features

针对前车速度单双向突变引起的交通流不稳定问题,提出一种基于多车状态变化特征的网联车跟驰模型(MVSCF)。首先引入多前车加速度差变化特征和优化的速度期望估计改进MVCM模型;然后利用微小扰动法和约化摄动法求解MVSCF模型的临界稳定条件,同时结合环形道路场景推导多前车加速度差系数k、多前车数q和多前车最优速度权重ε的相对最优值;最后利用直行道路场景对比分析MVSCF模型在前车速度非平稳变化作用下的交通流稳定效果。仿真结果表明:前车速度单双向突变时,MVSCF模型能够较好吸收前车扰动,速度波动峰谷差值和加速度波动幅度均有所减小,有利于提升交通流的稳定性。

For the unstable problem of traffic flow caused by the unidirectional and bidirectional abrupt change of speed of the preceding vehicle,a car following model for connected vehicles based on Multiple Vehicles with State Change Features(MVSCF)is proposed.Firstly,the acceleration difference change characteristics of mul⁃tiple preceding vehicles and the optimized estimation of speed expectation are introduced in to improve the model of Multiple Vehicles Changes with Memory(MVCM).Secondly,the critical stability conditions of MVSCF model are obtained by utilizing the micro perturbation method and the reductive perturbation method,respectively.Mean⁃while,for the multiple preceding vehicles,the acceleration difference coefficient k,the preceding vehicle quantity q and the optimal speed weightεare deduced in the circular road scenario,respectively.Finally,the traffic flow sta⁃bility effect of the MVSCF model is simulated and analyzed in the straight road scenario under the influence of nonstationary change of the preceding vehicle speed.The simulation results show that when the speed of the preceding vehicle is influenced by either unidirectional or bidirectional abrupt change,the MVSCF model can better absorb the disturbance from the preceding vehicle,with the peak-to-valley difference of speed change and the fluctuation amplitude of acceleration reduced,which is conducive to improving the stability of traffic flow.