Achieving Stable and Optimal Passenger-Driver Matching in Ride-Sharing System

Yixuan Zhong, Lin Gao, Tong Wang, Shimin Gong, Baitao Zou, Deliang Yu
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引用次数: 4

Abstract

Ride-sharing systems enable individual car owners with idle time to provide commercial taxi-like services via an online platform. By crowdsourcing a large population of individual car owners, it can provide more flexible services with a lower serving cost, comparing with the traditional taxi system. Due to the autonomous nature of car owners (drivers), a decentralized driver dispatching algorithm that can achieve a stable (self-motivated) and optimal passenger-driver matching is highly desired for a ride-sharing system. In this paper, we will study such a driver dispatching algorithm systematically. We first show that the optimal passenger-driver matching achieved by the centralized driver dispatching algorithm is often not stable, in the sense that some drivers and passengers may break with their matched partners and form new matching pairs. To this end, we introduce a virtual order fee on each passenger (which the platform will charge the drives who want to serve the passenger) to motivate the behaviors of drivers. Specifically, we propose a novel auction-based decentralized driver dispatching algorithm, where each driver proposes the most profitable passenger that he wants to serve, considering the potential profit that he can achieve and the order fee that he needs to pay from/to serving each passenger. The virtual order fee on a passenger will be gradually increased when multiple drivers want to serve the passenger, until there exists only one driver who is willing to serve. We analytically show that such a decentralized driver dispatching algorithm will converge to an equilibrium (stable) outcome, which achieves the optimal passenger-driver matching (i.e., that maximizes the social income of the whole system). Simulation results further show how the converging speed and the achieved social income change with the system parameters such as the step size of order fee increasement. Moreover, it is easy to implement the proposed distributed algorithm in a practical system.
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实现拼车系统中稳定最优的乘客-司机匹配
拼车系统使有空闲时间的个人车主可以通过在线平台提供类似商业出租车的服务。与传统的出租车系统相比,通过众包大量的个体车主,它可以以更低的服务成本提供更灵活的服务。由于车主(司机)的自主性,一种能够实现稳定(自我激励)和最优的乘客-司机匹配的分散式司机调度算法是拼车系统迫切需要的。本文将对这种驾驶员调度算法进行系统的研究。首先,集中式调度算法实现的最优乘客-司机匹配往往不稳定,即一些司机和乘客可能会与匹配的伙伴决裂,形成新的匹配对。为此,我们对每位乘客征收虚拟订货费(平台将向想为乘客服务的司机收费),以激励司机的行为。具体来说,我们提出了一种新的基于拍卖的去中心化司机调度算法,每个司机考虑到他可以实现的潜在利润和他为每个乘客服务所需支付的订单费用,提出他想要服务的最有利可图的乘客。当有多个司机想为乘客服务时,乘客的虚拟订单费会逐渐增加,直到只有一个司机愿意为乘客服务。分析表明,这种去中心化的驾驶员调度算法将收敛于一个均衡(稳定)结果,从而实现最优的乘客-驾驶员匹配(即整个系统的社会收入最大化)。仿真结果进一步显示了收敛速度和已实现的社会收入随系统参数(如订单费增加步长)的变化规律。此外,该算法易于在实际系统中实现。
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