Linearly Solvable Mean-Field Traffic Routing Games
Abstract
We consider a dynamic traffic routing game over an urban road network involving a large number of drivers in which each driver selecting a particular route is subject to a penalty that is affine in the logarithm of the number of drivers selecting the same route. We show that the mean-field approximation of such a game leads to the so-called linearly solvable Markov decision process, implying that its mean-field equilibrium (MFE) can be found simply by solving a finite-dimensional linear system backward in time. Based on this backward-only characterization, it is further shown that the obtained MFE has the notable property of strong time-consistency. A connection between the obtained MFE and a particular class of fictitious play is also discussed.
Keywords
Cite
@article{arxiv.1903.01449,
title = {Linearly Solvable Mean-Field Traffic Routing Games},
author = {Takashi Tanaka and Ehsan Nekouei and Ali Reza Pedram and Karl Henrik Johansson},
journal= {arXiv preprint arXiv:1903.01449},
year = {2020}
}
Comments
arXiv admin note: text overlap with arXiv:1808.05305