Title
Using Non-cooperative Game Theory for Taxi-Sharing Recommendation Systems.
Abstract
This paper presents a recommendation mechanism for taxi-sharing. The first aim of our model is to respectively recommend taxis and passengers for picking up passengers quickly and finding taxis easily. The second purpose is providing taxi-sharing service for passengers who want to save the payment. In our method, we analyze the historical global positioning system trajectories generated by 10,357 taxis during 110 days and present the service region with time-dependent R-Tree. We formulate the problem of choosing the paths among the taxis in the same region by using non-cooperative game theory, and find out the solution of this game which is known as Nash equilibrium. The simulation of SUMO, MOVE, and TraCI are adopted to fit our model to verify the proposed recommendation mechanism. The results show that our method can find taxis and passengers efficiently. In addition, applying our method can reduce the payment of passengers and increase the taxi revenue by taxi-sharing.
Year
DOI
Venue
2016
10.1007/s11277-016-3202-3
Wireless Personal Communications
Keywords
Field
DocType
Taxi-sharing,Trajectory,Recommendation mechanism,Non-cooperative game theory
Recommender system,Revenue,Computer science,Computer security,Taxis,Computer network,Operations research,Game theory,Global Positioning System,Nash equilibrium,Non-cooperative game,Payment
Journal
Volume
Issue
ISSN
88
4
0929-6212
Citations 
PageRank 
References 
0
0.34
2
Authors
4
Name
Order
Citations
PageRank
Jian-Pan Li1154.05
Gwo-Jiun Horng29923.82
Yin-Jun Chen3164.11
Sheng-Tzong Cheng429344.23