Nature-Inspired Optimal Route Network Design for Shared Autonomous Vehicles

Theodoros Alpos, C. Iliopoulou, K. Kepaptsoglou
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引用次数: 1

Abstract

Emerging forms of shared mobility call for new vehicle routing models that take into account vehicle sharing, ride sharing and autonomous vehicle fleets. This study deals with the design of an optimal route network for autonomous vehicles, considering both vehicle sharing and ride sharing. The problem is modeled as a one-to-many-to-one vehicle routing problem with vehicle capacity and range constraints. An ant colony optimization algorithm is applied to the problem in order to construct a set of routes that satisfies user requests under operational constraints. Results show that the algorithm is able to produce solutions in relatively short computational times, while exploiting the possibility of ride sharing to reduce operating costs. Results also underline the potential of exploiting shared autonomous vehicles in the context of a taxi service for booking trips through electronic reservation systems.
基于自然的共享自动驾驶汽车最优路径网络设计
新兴的共享出行形式需要考虑到车辆共享、拼车和自动驾驶车队的新型车辆路线模型。本文研究了考虑车辆共享和拼车的自动驾驶汽车最优路线网络的设计。将该问题建模为具有车辆容量和距离约束的一对多对一车辆路径问题。为了在操作约束下构造一组满足用户请求的路由,将蚁群优化算法应用于该问题。结果表明,该算法能够在相对较短的计算时间内产生解决方案,同时利用拼车的可能性来降低运营成本。研究结果还强调了利用共享自动驾驶汽车在出租车服务背景下通过电子预订系统预订行程的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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