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M. D. Rosini

Publications and source records attributed to M. D. Rosini.

3 recordsLinked to original sources

Fully discrete follow-the-leader approximation of one-dimensional scalar conservation laws with vacuum

We present a fully discrete particle approximation for one-dimensional scalar conservation laws. Under suitable monotonicity assumptions on the macroscopic velocity, we construct a vacuum-compatible family of time-discrete particle equations and show that an appropriate piecewise-constant density reconstruction from the particle setting converges to the unique entropy weak solution of the macroscopic scalar conservation law.

math.AP

Many particle approximation of the Aw-Rascle-Zhang second order model for vehicular traffic

We consider the Follow-The-Leader approximation of the Aw-Rascle-Zhang (ARZ) model for traffic flow in a multi-population formulation. We prove rigorous convergence to weak solutions of the ARZ system in the many particle limit in presence of vacuum. The result is based on uniform $\mathbf{BV}$ estimates on the discrete particle velocity. We complement out result with numerical simulations of the particle method compared with some exact solutions to the Riemann problem of the ARZ system.

math.AP

Deterministic particle approximation of the Hughes model in one space dimension

In this paper we present a new approach to the solution to a generalized version of Hughes' models for pedestrian movements based on a follow-the-leader many particle approximation. In particular, we provide a rigorous global existence result under a smallness assumption on the initial data ensuring that the trace of the solution along the turning curve is zero for all positive times. We also focus shortly on the approximation procedure for symmetric data and Riemann type data. Two different numerical approaches are adopted for the simulation of the model, namely the proposed particle method and a Godunov type scheme. Several numerical tests are presented, which are in agreement with the theoretical prediction.

math.AP