Follow-the-leader approximations of macroscopic models for vehicular and pedestrian flows

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Abstract

We review the 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 discretized vehicles seen as moving particles. The convergence of the scheme in the many particle limit toward 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.

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Di Francesco, M., Fagioli, S., Rosini, M. D., & Russo, G. (2017). Follow-the-leader approximations of macroscopic models for vehicular and pedestrian flows. In Modeling and Simulation in Science, Engineering and Technology (Vol. 1, pp. 333–378). Springer Basel. https://doi.org/10.1007/978-3-319-49996-3_9

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