A Matching Model for Ride-Sharing: A Non-Cooperative Game Approach Between Drivers and Riders

This study proposes an optimal matching problem between drivers and riders as a generalised Nash equilibrium problem, which finds a solution where no drivers and riders have the incentive to change their strategy. The proposed model is formulated as a (D + R) person pure strategy game, where D and R are the number of drivers and riders, respectively. We further reformulate the proposed model as a two-person pure strategy game. A solution algorithm that iteratively solves the drivers’ and riders’ sub-problem is proposed, which is proven to converge to a Nash equilibrium solution within a finite number of iterations. Finally, we numerically confirm that the proposed model yields a Nash equilibrium solution and then perform sensitivity analysis over the parameters of the proposed model.

Authors

Institutions

Publication Details

Journal
Smart Cities
Published
2025-03-04
DOI
https://doi.org/10.3390/smartcities8020040
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Matching Model for Ride-Sharing: A Non-Cooperative Game Approach Between Drivers and Riders

Hiroshi Shimamoto
Smart Cities
Transportation and Mobility Innovations
article

A Matching Model for Ride-Sharing: A Non-Cooperative Game Approach Between Drivers and Riders

Hiroshi Shimamoto
article en

Abstract

This study proposes an optimal matching problem between drivers and riders as a generalised Nash equilibrium problem, which finds a solution where no drivers and riders have the incentive to change their strategy. The proposed model is formulated as a (D + R) person pure strategy game, where D and R are the number of drivers and riders, respectively. We further reformulate the proposed model as a two-person pure strategy game. A solution algorithm that iteratively solves the drivers’ and riders’ sub-problem is proposed, which is proven to converge to a Nash equilibrium solution within a finite number of iterations. Finally, we numerically confirm that the proposed model yields a Nash equilibrium solution and then perform sensitivity analysis over the parameters of the proposed model.

Smart CitiesVol. 8(2)
University of Miyazaki (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 97%
Transportation and Mobility Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.