Optimal Multi-taxi Dispatch for Mobile Taxi-Hailing Systems

Guoju Gao, Mingjun Xiao, Zhenhua Zhao
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引用次数: 26

Abstract

Traditional taxi-hailing systems through wireless networks in metropolitan areas allow taxis to compete for passengers chaotically and accidentally, which generally result in inefficiencies, long waiting time and low satisfaction of taxi-hailing passengers. In this paper, we propose a new Mobile Taxi-hailing System (called MTS) based on optimal multi-taxi dispatch, which can be used by taxi service companies (TSCs). Different from the competition modes used in traditional taxi-hailing systems, MTS assigns vacant taxis to taxi-hailing passengers proactively. For the taxi dispatch problem in MTS, we define a system utility function, which involves the total net profits of taxis and waiting time of passengers. Moreover, in the utility function, we take into consideration the various classes of taxis with different resource configurations, and the cost associated with taxis' empty travel distances. Our goal is to maximize the system utility function, restricted by the individual net profits of taxis and the passengers' requirements for specified classes of taxis. To solve this problem, we design an optimal algorithm based on the idea of Kuhn-Munkres (called KMBA), and prove the correctness and optimality of the proposed algorithm. Additionally, we demonstrate the significant performances of our algorithm through extensive simulations.
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移动叫车系统的最优多车调度
在大都市地区,传统的无线网约车系统存在着出租车竞争无序、偶然性大的问题,普遍存在效率低下、等待时间长、乘客满意度低等问题。本文提出了一种基于多车最优调度的移动叫车系统(MTS),供出租车服务公司使用。与传统打车系统的竞争模式不同,MTS将空置的出租车主动分配给打车乘客。对于MTS中的出租车调度问题,我们定义了一个系统效用函数,该函数涉及出租车的总净利润和乘客的等待时间。此外,在效用函数中,我们考虑了不同类型的出租车具有不同的资源配置,以及与出租车空行距离相关的成本。我们的目标是在出租车个体净利润和乘客对特定类别出租车需求的限制下,使系统效用函数最大化。为了解决这个问题,我们设计了一个基于Kuhn-Munkres思想的最优算法(KMBA),并证明了该算法的正确性和最优性。此外,我们通过大量的模拟证明了我们的算法的显著性能。
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