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从研究微观个体车辆行为出发 ,考虑车辆加速过程的不确定性 ,提出了随机计及相对速度的交通流跟驰模型(SR OV模型 ) .对随机相对速度的跟驰模型的动力学方程进行稳定性分析 ,得到与Bando跟驰模型不同的稳定性判据 ,其稳定性优于Bando模型 .运用摄动理论分析交通过程中密度波的变化 ,结果表明 ,在发生交通阻塞相变时 ,交通密度波以mKdV方程描述的扭结 反扭结波演化 .对随机相对速度跟驰模型进行数值模拟和分析 ,结果发现车流速度的变化小于Bando模型的速度变化 ,而且与随机概率有关 ,当随机考虑相对速度的概率增大时 ,初始的小扰动不会放大对车流产生影响 ,甚至长时间就消失 ,这与Bando模型完全不同 .数值模拟所得到的相图与解析解相符合 ,而且交通流稳定区域大于Bando模型 .从车间距 速度演化图上 ,随着随机概率的增大 ,SR OV模型在初始时存在的滞后现象 ,随着时间的增长 ,趋于稳定状态后 ,滞后曲线收敛于一小区域 ,滞后效应被削弱 .这完全不同于Bando模型 ,在Bando模型中 ,滞后曲线由一点向外扩散 ,滞后曲线区域越来越大 ,车流趋于不稳定状态 .
Starting from the study of micro-individual vehicle behavior and taking into account the uncertainty of the vehicle acceleration process, a traffic-following (SROV) model with stochastic and relative velocity is proposed. The kinetic equation of the following model of stochastic relative velocity is stabilized The stability analysis is better than that of Bando model.Using perturbation theory to analyze the change of density wave in traffic process, the results show that in the case of traffic jam, the traffic density Wave kMVV equation described kink-anti-kink wave evolution.The numerical simulation and analysis of the random relative speed following model, the results show that the change of traffic flow velocity is less than the Bando model velocity, but also with the random probability, when considering the relative velocity When the probability increases, the initial small perturbations will not amplify the impact on the traffic flow, and even disappear for a long time, which is completely different from the Bando model.The phase diagram obtained by numerical simulation is consistent with the analytical solution, and the stable traffic flow is greater than Bando Model. From the vehicle speed evolution map, with the increase of random probability, the lag of SR OV model Phenomenon, with the growth of time, stabilized to a state, the hysteresis curve converges in a small area, the hysteresis effect is weakened.This is completely different from the Bando model, in the Bando model, the hysteresis curve from a point outward diffusion, hysteresis curve region Increasingly, traffic tends to be unstable.