论文标题
在一系列新的非局部交通流模型上，具有look-apavear规则
On a class of new nonlocal traffic flow models with look-ahead rules
论文作者
论文摘要
本文提出了一类新的一维（1D）流量模型，并提出了审视规则，这些规则考虑了两种效果：非本地慢速下降效果和基本图中的右旋转非偏见的不对称性。提出的具有Arrhenius类型的1D蜂窝自动机（CA）模型在每辆汽车前的交通配置后，为汽车运动实现了随机规则。特别是，我们采用了两个不同的外观规则：一个是基于从所考虑的汽车到它前面汽车的距离；另一个取决于前方的汽车密度。这两种规则都具有多种动作的新颖概念，在恢复宏观动力学中的非covave通量方面起着关键作用。通过半分化的介绍随机过程，我们得出了CA模型的粗粒宏观动力学。我们还设计了一种数值方案，以模拟提出的基于列表的动力学蒙特卡洛（KMC）算法的CA模型。我们的结果表明，在各种参数设置下，KMC仿真的通量与不同的look-aphead规则的粗粒宏平均通量一致。
This paper presents a new class of one-dimensional (1D) traffic models with look-ahead rules that take into account of two effects: nonlocal slow-down effect and right-skewed non-concave asymmetry in the fundamental diagram. The proposed 1D cellular automata (CA) models with the Arrhenius type look-ahead interactions implement stochastic rules for cars' movement following the configuration of the traffic ahead of each car. In particular, we take two different look-ahead rules: one is based on the distance from the car under consideration to the car in front of it; the other one depends on the car density ahead. Both rules feature a novel idea of multiple moves, which plays a key role in recovering the non-concave flux in the macroscopic dynamics. Through a semi-discrete mesoscopic stochastic process, we derive the coarse-grained macroscopic dynamics of the CA model. We also design a numerical scheme to simulate the proposed CA models with an efficient list-based kinetic Monte Carlo (KMC) algorithm. Our results show that the fluxes of the KMC simulations agree with the coarse-grained macroscopic averaged fluxes for the different look-ahead rules under various parameter settings.
