Linearly Solvable Mean-Field Road Traffic Games

Takashi Tanaka; Ehsan Nekouei; Karl Henrik Johansson

doi:10.1109/ALLERTON.2018.8636077

Linearly Solvable Mean-Field Road Traffic Games

Takashi Tanaka, Ehsan Nekouei, Karl Henrik Johansson

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

We analyze the behavior of a large number of strategic drivers traveling over an urban traffic network using the mean-field game framework. We assume an incentive mechanism for congestion mitigation under which each driver selecting a particular route is charged a tax penalty that is affine in the logarithm of the number of agents selecting the same route. We show that the mean-field approximation of such a large-population dynamic game leads to the so-called linearly solvable Markov decision process, implying that an open-loop ∈-Nash equilibrium of the original game can be found simply by solving a finite-dimensional linear system.

Original language	English
Title of host publication	2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
Publisher	IEEE
Pages	283-289
ISBN (Print)	9781538665961
DOIs	https://doi.org/10.1109/ALLERTON.2018.8636077
Publication status	Published - Oct 2018
Externally published	Yes
Event	56th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2018) - Monticello, United States Duration: 2 Oct 2018 → 5 Oct 2018

Publication series

Name	Annual Allerton Conference on Communication, Control, and Computing, Allerton

Conference

Conference	56th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2018)
Place	United States
City	Monticello
Period	2/10/18 → 5/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

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10.1109/ALLERTON.2018.8636077

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@inproceedings{89319ed420b44cb2b69d76fa83f6d709,

title = "Linearly Solvable Mean-Field Road Traffic Games",

abstract = "We analyze the behavior of a large number of strategic drivers traveling over an urban traffic network using the mean-field game framework. We assume an incentive mechanism for congestion mitigation under which each driver selecting a particular route is charged a tax penalty that is affine in the logarithm of the number of agents selecting the same route. We show that the mean-field approximation of such a large-population dynamic game leads to the so-called linearly solvable Markov decision process, implying that an open-loop ∈-Nash equilibrium of the original game can be found simply by solving a finite-dimensional linear system.",

author = "Takashi Tanaka and Ehsan Nekouei and Johansson, {Karl Henrik}",

year = "2018",

month = oct,

doi = "10.1109/ALLERTON.2018.8636077",

language = "English",

isbn = "9781538665961",

series = "Annual Allerton Conference on Communication, Control, and Computing, Allerton",

publisher = "IEEE",

pages = "283--289",

booktitle = "2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)",

address = "United States",

note = "56th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2018) ; Conference date: 02-10-2018 Through 05-10-2018",

}

Tanaka, T, Nekouei, E & Johansson, KH 2018, Linearly Solvable Mean-Field Road Traffic Games. in 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)., 8636077, Annual Allerton Conference on Communication, Control, and Computing, Allerton, IEEE, pp. 283-289, 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2018), Monticello, Illinois, United States, 2/10/18. https://doi.org/10.1109/ALLERTON.2018.8636077

Linearly Solvable Mean-Field Road Traffic Games. / Tanaka, Takashi; Nekouei, Ehsan; Johansson, Karl Henrik.
2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2018. p. 283-289 8636077 (Annual Allerton Conference on Communication, Control, and Computing, Allerton).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Linearly Solvable Mean-Field Road Traffic Games

AU - Tanaka, Takashi

AU - Nekouei, Ehsan

AU - Johansson, Karl Henrik

PY - 2018/10

Y1 - 2018/10

N2 - We analyze the behavior of a large number of strategic drivers traveling over an urban traffic network using the mean-field game framework. We assume an incentive mechanism for congestion mitigation under which each driver selecting a particular route is charged a tax penalty that is affine in the logarithm of the number of agents selecting the same route. We show that the mean-field approximation of such a large-population dynamic game leads to the so-called linearly solvable Markov decision process, implying that an open-loop ∈-Nash equilibrium of the original game can be found simply by solving a finite-dimensional linear system.

AB - We analyze the behavior of a large number of strategic drivers traveling over an urban traffic network using the mean-field game framework. We assume an incentive mechanism for congestion mitigation under which each driver selecting a particular route is charged a tax penalty that is affine in the logarithm of the number of agents selecting the same route. We show that the mean-field approximation of such a large-population dynamic game leads to the so-called linearly solvable Markov decision process, implying that an open-loop ∈-Nash equilibrium of the original game can be found simply by solving a finite-dimensional linear system.

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DO - 10.1109/ALLERTON.2018.8636077

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781538665961

T3 - Annual Allerton Conference on Communication, Control, and Computing, Allerton

SP - 283

EP - 289

BT - 2018 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

PB - IEEE

T2 - 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2018)

Y2 - 2 October 2018 through 5 October 2018

ER -

Linearly Solvable Mean-Field Road Traffic Games

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