The Taxi‐Sharing: User Equilibrium, System Optimum and Pricing Scheme Design

ABSTRACT Taxi‐sharing service involves three stakeholders: passengers, taxi drivers and platform. From the interests of different stakeholders, taxi‐sharing equilibrium assignment and taxi‐sharing system optimum assignment can be obtained which may be not consistent with each other. This paper addresses two decisions for taxi‐sharing service: matching passengers and taxis and pricing with compensation. Nonlinear equations are formulated to describe the equilibrium assignment of taxis to passengers. A price scheme is designed to steer a taxi‐sharing equilibrium assignment to a system optimum assignment. The models of taxi‐sharing equilibrium assignment, optimum assignment, equilibrium assignment with compensation and the algorithm for finding optimum compensation vectors are validated by case studies based on data of Dalian taxi companies. The findings show that in some cases, a sub‐optimal assignment is achieved. After relaxing the equilibrium constraint, most of the cases can get system optimum assignment by compensations.

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Publication Details

Journal
IET Intelligent Transport Systems
Published
2025-01-01
DOI
https://doi.org/10.1049/itr2.70043
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00

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article

The Taxi‐Sharing: User Equilibrium, System Optimum and Pricing Scheme Design

Peng Jia, Zixuan Peng
IET Intelligent Transport Systems
Transportation and Mobility Innovations
article

The Taxi‐Sharing: User Equilibrium, System Optimum and Pricing Scheme Design

Peng Jia, Zixuan Peng
article en

Abstract

ABSTRACT Taxi‐sharing service involves three stakeholders: passengers, taxi drivers and platform. From the interests of different stakeholders, taxi‐sharing equilibrium assignment and taxi‐sharing system optimum assignment can be obtained which may be not consistent with each other. This paper addresses two decisions for taxi‐sharing service: matching passengers and taxis and pricing with compensation. Nonlinear equations are formulated to describe the equilibrium assignment of taxis to passengers. A price scheme is designed to steer a taxi‐sharing equilibrium assignment to a system optimum assignment. The models of taxi‐sharing equilibrium assignment, optimum assignment, equilibrium assignment with compensation and the algorithm for finding optimum compensation vectors are validated by case studies based on data of Dalian taxi companies. The findings show that in some cases, a sub‐optimal assignment is achieved. After relaxing the equilibrium constraint, most of the cases can get system optimum assignment by compensations.

IET Intelligent Transport SystemsVol. 19(1)
Beijing Jiaotong University (CN), Dalian Maritime University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 84%
Transportation and Mobility Innovations
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