Enregistré dans:
Détails bibliographiques
Auteurs principaux: Machtalay, Amal, Habbal, Abderrahmane, Ratnani, Ahmed, Kissami, Imad
Format: Preprint
Publié: 2023
Sujets:
Accès en ligne:https://arxiv.org/abs/2306.13543
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866912296759984128
author Machtalay, Amal
Habbal, Abderrahmane
Ratnani, Ahmed
Kissami, Imad
author_facet Machtalay, Amal
Habbal, Abderrahmane
Ratnani, Ahmed
Kissami, Imad
contents We address a multi-class traffic model, for which we computationally assess the ability of mean-field games (MFGs) to yield approximate Nash equilibria for traffic flow games of intractable large finite-players. We introduce ad hoc numerical methodologies, with recourse to techniques such as High-Performance Computing (HPC) and regularization of Loose Generalized Minimal Residual (LGMRES) solvers. The developed apparatus allows us to perform simulations at significantly larger space and time discretization scales. For three generic scenarios of cars and trucks, and three cost functionals, we provide numerous numerical results related to the autonomous vehicles (AVs) traffic dynamics, which corroborate for the multi-class case the effectiveness of the approach emphasized in [22]. We additionally provide several original comparisons of macroscopic Nash mean-field speeds with their microscopic versions, allowing us to computationally validate the so-called $ε-$Nash approximation, with a rate slightly better than theoretically expected.
format Preprint
id arxiv_https___arxiv_org_abs_2306_13543
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Computational investigations of a multi-class traffic flow model: mean-field and microscopic dynamics
Machtalay, Amal
Habbal, Abderrahmane
Ratnani, Ahmed
Kissami, Imad
Optimization and Control
We address a multi-class traffic model, for which we computationally assess the ability of mean-field games (MFGs) to yield approximate Nash equilibria for traffic flow games of intractable large finite-players. We introduce ad hoc numerical methodologies, with recourse to techniques such as High-Performance Computing (HPC) and regularization of Loose Generalized Minimal Residual (LGMRES) solvers. The developed apparatus allows us to perform simulations at significantly larger space and time discretization scales. For three generic scenarios of cars and trucks, and three cost functionals, we provide numerous numerical results related to the autonomous vehicles (AVs) traffic dynamics, which corroborate for the multi-class case the effectiveness of the approach emphasized in [22]. We additionally provide several original comparisons of macroscopic Nash mean-field speeds with their microscopic versions, allowing us to computationally validate the so-called $ε-$Nash approximation, with a rate slightly better than theoretically expected.
title Computational investigations of a multi-class traffic flow model: mean-field and microscopic dynamics
topic Optimization and Control
url https://arxiv.org/abs/2306.13543