Integrated operator and user-based rebalancing and recharging in dockless shared e-micromobility systems

IF 12.5 Q1 TRANSPORTATION
Elnaz Emami, Mohsen Ramezani
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引用次数: 0

Abstract

This study proposes a rebalancing method for a dockless e-micromobility sharing system, employing both trucks and users. Platform-owned trucks relocate and recharge e-micromobility vehicles using battery swapping technology. In addition, some users intending to rent an e-micromobility vehicle are offered incentives to end their trips in defined locations to assist with rebalancing. The integrated formulation of rebalancing and recharging accounts for each e-micromobility vehicle's characteristics, such as location and charge level. The problem is formulated as a mixed binary problem, which minimizes operational costs and total unmet demand while maximizing the system's profit. To solve the optimization problem, a Branch and Bound method is employed. Rebalancing decisions and routing plans of each truck are obtained by solving the optimization problem. We simulate an on-demand shared e-micromobility system with the proposed integrated rebalancing method and conduct numerical studies. The results indicate that the proposed method enhances system performance and user travel times.
无桩共享电动交通系统中基于运营商和用户的综合再平衡和再充电功能
本研究提出了一种无桩电动移动共享系统的再平衡方法,同时使用卡车和用户。平台所属的卡车利用电池交换技术为电动车重新定位和充电。此外,一些打算租用电动车的用户还可获得奖励,在指定地点结束行程,以帮助实现再平衡。重新平衡和充电的综合表述考虑到了每辆电动微型车的特点,如位置和充电水平。该问题被表述为混合二元问题,即在最大化系统利润的同时,最小化运营成本和未满足的总需求。为解决优化问题,采用了分支和边界法。通过求解优化问题,可以获得重新平衡决策和每辆卡车的路线计划。我们利用所提出的综合再平衡方法模拟了一个按需共享电动交通系统,并进行了数值研究。结果表明,建议的方法提高了系统性能和用户出行时间。
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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CiteScore
15.20
自引率
0.00%
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