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Game Theory Based Recommendation Mechanism for Taxi-Sharing

机译:基于博弈论的出租车共享推荐机制

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摘要

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.
机译:本文提出了出租车共享的推荐机制。我们模型的第一个目标是分别推荐出租车和乘客,以便快速上车并轻松找到出租车。第二个目的是为想要节省费用的乘客提供出租车共享服务。在我们的方法中,我们分析了110天内10,357辆出租车产生的历史全球定位系统(GPS)轨迹,并向服务区域显示了随时间变化的R树。我们运用非合作博弈理论提出了在同一地区的出租车之间选择路径的问题,并找到了该博弈的解决方案,即纳什均衡。结果表明,我们的方法可以有效地找到出租车和乘客。此外,采用我们的方法可以减少乘客的付款,并通过共享出租车增加出租车收入。

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