A game-theoretic approach for route planning on traveling by public transportation in the PM2.5 pollution: A case study in Bangkok

Extremely high levels of PM 2.5 (particulate matter with a diameter of 2.5 micrometers or less) in Bangkok’s major areas can cause a variety of issues, particularly health issues. It is an unavoidable situation for an individual traveling through affected areas by using Bangkok public transportation, which is an affordable travel choice for low- and middle-income Bangkok residents. In this study, a scenario of taking public transportation through affected areas is simulated using graphs and game-theoretic ideas. A game is played on a directed graph constructed from an example of traveling routes between two places in Bangkok. The game consists of players, who are people at a bus stop in Bangkok with the same destination; strategies for each player, which are the possible public transits; and the payoff for a player, which is the maximum amount of PM 2.5 breathed in during the trip. The game’s equilibrium is investigated in terms of how the game responds to the PM 2.5 situation. One of the goals is to use the results in public transportation planning that can make community health and well-being affordable for everyone, which is a part of sustainable development. • A scenario models public transit in PM 2.5 areas using graph and game theory. • The game’s equilibrium was studied to see how it responds to the PM 2.5 situation. • A method is proposed to find a solution for a game where the equilibrium cannot be solved.

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Publication Details

Journal
Transportation Research Interdisciplinary Perspectives
Published
2024-08-12
DOI
https://doi.org/10.1016/j.trip.2024.101185
Citations
3
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
2.05

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article

A game-theoretic approach for route planning on traveling by public transportation in the PM2.5 pollution: A case study in Bangkok

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Transportation Research Interdisciplinary Perspectives
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article

A game-theoretic approach for route planning on traveling by public transportation in the PM2.5 pollution: A case study in Bangkok

Chanun Lewchalermvongs, Phakaporn Lewchalermvongs, Chettaporn Chuesuphan, Chutchawon Weeranukunjit, Montika Chaikittiporn, Patid Srikirinth, Chanon Boonkangwan, Tanaphoom Glinpatgij
article en
3 citations

Abstract

Extremely high levels of PM 2.5 (particulate matter with a diameter of 2.5 micrometers or less) in Bangkok’s major areas can cause a variety of issues, particularly health issues. It is an unavoidable situation for an individual traveling through affected areas by using Bangkok public transportation, which is an affordable travel choice for low- and middle-income Bangkok residents. In this study, a scenario of taking public transportation through affected areas is simulated using graphs and game-theoretic ideas. A game is played on a directed graph constructed from an example of traveling routes between two places in Bangkok. The game consists of players, who are people at a bus stop in Bangkok with the same destination; strategies for each player, which are the possible public transits; and the payoff for a player, which is the maximum amount of PM 2.5 breathed in during the trip. The game’s equilibrium is investigated in terms of how the game responds to the PM 2.5 situation. One of the goals is to use the results in public transportation planning that can make community health and well-being affordable for everyone, which is a part of sustainable development. • A scenario models public transit in PM 2.5 areas using graph and game theory. • The game’s equilibrium was studied to see how it responds to the PM 2.5 situation. • A method is proposed to find a solution for a game where the equilibrium cannot be solved.

Transportation Research Interdisciplinary PerspectivesVol. 27
Mahidol University (TH), Centre of Excellence in Mathematics (TH)
Mahidol University, Faculty of Science, Chiang Mai University
Sustainable cities and communities
Openalex Percentile: Top 13%
Transportation Planning and Optimization
2.05
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