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Fractional order car-following model and its simulation

机译:分数秩序车次模型及其模拟

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In order to depict the effect of driver's memory on car-following behavior, a new kind of car-following model is proposed by using fractional order differential equation in this paper. Its dynamic equation is defined by Caputo fractional order derivative. And the order of derivative is the measurement of driver's memory. In addition, discrete formulas of the position and velocity of the new model are given. The Optimal Velocity (OV) model is taken as an example to introduce how to get the fractional order car-following model from an ordinary model. The simulation results show that the Fractional Order Optimal Velocity (FOOV) model is more stable, and it can avoid unrealistic acceleration values of the OV model in the cases of starting and braking processes. Moreover, magnitudes of the speed and headway fluctuation of the FOOV model with a suitable order are smaller than those of the OV model. This indicates that the memory characteristic of drivers increases the stability of traffic flow.
机译:为了描绘驾驶员记忆对汽车跟踪行为的影响,通过在本文中使用分数级微分方程提出了一种新的汽车之后模型。它的动态方程由Caputo分数阶数定义。衍生品的顺序是驾驶员的记忆的测量。另外,给出了新模型的位置和速度的离散式。采用最佳速度(OV)模型作为示例,以便从普通模型中获取分数阶车载车型模型。仿真结果表明,分数级最优速度(FOOV)模型更稳定,并且可以避免在启动和制动过程的情况下ov模型的不切实际的加速度值。此外,具有合适阶的FOOV模型的速度和钻孔波动的幅度小于OV模型的速度波动。这表明驱动程序的内存特性增加了业务流量的稳定性。

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