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Follow-the-Leader Approximations of Macroscopic Models for Vehicular and Pedestrian Flows

机译:车辆和行人流宏观模型的跟随领导近似

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摘要

We review recent results and present new ones on a deterministic follow-the-leader particle approximation of first and second order models for traffic flow and pedestrian movements. We start by constructing the particle scheme for the first order Lighthill-Whitham-Richards (LWR) model for traffic flow. The approximation is performed by a set of ODEs following the position of discretised vehicles seen as moving particles. The convergence of the scheme in the many particle limit towards the unique entropy solution of the LWR equation is proven in the case of the Cauchy problem on the real line. We then extend our approach to the Initial-Boundary Value Problem (IBVP) with time-varying Dirichlet data on a bounded interval. In this case we prove that our scheme is convergent strongly in L1 up to a subsequence. We then review extensions of this approach to the Hughes model for pedestrian movements and to the second order Aw-Rascle-Zhang (ARZ) model for vehicular traffic. Finally, we complement our results with numerical simulations. In particular, the simulations performed on the IBVP and the ARZ model suggest the consistency of the corresponding schemes, which is easy to prove rigorously in some simple cases.
机译:我们回顾了最近的结果,并针对交通流和行人运动的一阶和二阶模型的确定性跟随者-领导者粒子近似提出了新的结果。我们从为交通流的一阶Lighthill-Whitham-Richards(LWR)模型构建粒子方案开始。逼近由一组ODE跟随离散车辆的位置(被视为运动粒子)执行。在实线上的柯西问题的情况下,证明了该方案在许多粒子范围内朝着LWR方程的唯一熵解的收敛性。然后,将我们的方法扩展到初始边界值问题(IBVP),该方法具有在有界区间上随时间变化的Dirichlet数据。在这种情况下,我们证明了我们的方案在L1直至子序列中都具有很强的收敛性。然后,我们将这种方法的扩展范围扩展到行人运动的休斯模型和车辆交通的二阶Aw-Rascle-Zhang(ARZ)模型。最后,我们用数值模拟对结果进行补充。特别是,对IBVP和ARZ模型进行的仿真表明相应方案的一致性,这在某些简单情况下很容易得到严格证明。

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