{"title":"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","authors":"Elnaz Emami, Mohsen Ramezani","doi":"10.1016/j.commtr.2024.100155","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"4 ","pages":"Article 100155"},"PeriodicalIF":12.5000,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated operator and user-based rebalancing and recharging in dockless shared e-micromobility systems\",\"authors\":\"Elnaz Emami, Mohsen Ramezani\",\"doi\":\"10.1016/j.commtr.2024.100155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":100292,\"journal\":{\"name\":\"Communications in Transportation Research\",\"volume\":\"4 \",\"pages\":\"Article 100155\"},\"PeriodicalIF\":12.5000,\"publicationDate\":\"2024-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications in Transportation Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772424724000386\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Transportation Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772424724000386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Integrated operator and user-based rebalancing and recharging in dockless shared e-micromobility systems
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.