Paper Info
Title
Game Theory Based Recommendation Mechanism for Taxi-Sharing
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 (GPS) 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 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
2014
10.1109/WAINA.2014.106
AINA Workshops
Keywords
DocType
Citations 
time-dependent r-tree,taxi revenue,trees (mathematics),taxi-sharing, trajectory, recommendation mechanism, non-cooperative game theory,traffic engineering computing,transportation,gps trajectories,recommendation mechanism,trajectory,taxi-sharing,recommender systems,global positioning system,game theory,non-cooperative game theory,nash equilibrium,noncooperative game theory
Conference
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Sheng-Tzong Cheng129344.23
Jian-Pan Li2154.05
Gwo-Jiun Horng39923.82