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Nonlinear analysis of a new car-following model accounting for the optimal velocity changes with memory

机译:一种新的跟随模型的非线性分析,考虑了带有记忆的最佳速度变化

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We, in this study, construct a new car-following model by accounting for the effect of the optimal velocity changes with memory in terms of the full velocity difference (FVD) model. The stability condition and mKdV equation concerning the optimal velocity changes with memory are derived through both linear stability and nonlinear analyses, respectively. Then, the space concerned can be divided into three regions classified as the stable, the metastable and the unstable ones. Moreover, it is shown that the effect of the optimal velocity changes with memory could enhance the stability of traffic flow. Furthermore, the numerical results verify that not only the sensitivity parameter of the optimal velocity changes with memory of driver but also the memory step could effectively stabilize the traffic flow. In addition, the stability of traffic flow is strengthened by increasing the memory step-size of optimal velocity changes and the intensity of drivers' memory with such changes. Most importantly, the effect of the optimal velocity changes with memory may avoid the disadvantage of historical information, which decreases the stability of traffic flow on road. (C) 2016 Elsevier B.V. All rights reserved.
机译:在这项研究中,我们通过考虑全速差(FVD)模型中记忆的最佳速度变化的影响,构造了一个新的跟车模型。通过线性稳定性和非线性分析分别推导了关于最佳速度随记忆变化的稳定性条件和mKdV方程。然后,可以将有关空间划分为三个区域,分别分为稳定区域,亚稳定区域和不稳定区域。而且,表明最佳速度随记忆变化的效果可以增强交通流的稳定性。此外,数值结果证明,不仅最佳速度的灵敏度参数随着驾驶员的记忆而变化,而且记忆步骤也可以有效地稳定交通流量。另外,通过增加最佳速度变化的记忆步长和随着这种变化的驾驶员记忆强度,来增强交通流的稳定性。最重要的是,最佳速度随记忆变化的效果可以避免历史信息的缺点,从而降低道路上交通流量的稳定性。 (C)2016 Elsevier B.V.保留所有权利。

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