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Fairness versus Optimality in Ridesharing

机译:Ridesharing中的公平与最优

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摘要

As a spatio-temporal data-management problem, taxi ridesharing has received a lot of attention recently in the database literature. The broader scientific community, and the commercial world have also addressed the issue through services such as UberPool and Lyftline. The issues addressed have been efficient matching of passengers and taxis, fares, and savings from ridesharing. However, ridesharing fairness has not been addressed so far. Ridesharing fairness is a new problem that we formally define in this paper. We also propose a method of combining the benefits of fair and optimal ridesharing, and of efficiently executing fair and optimal ridesharing queries.
机译:作为时空数据管理问题,出租车共享最近在数据库文献中受到了广泛关注。更广泛的科学界和商业界也已通过UberPool和Lyftline等服务解决了这一问题。解决的问题是乘客和出租车的高效匹配,票价以及乘车共享的节省。但是,到目前为止,共享乘车的公平性尚未得到解决。拼车公平性是我们在本文中正式定义的一个新问题。我们还提出了一种结合公平和最优乘车共享的好处,以及有效执行公平和最优乘车共享查询的方法。

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