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.

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Publication Details

Journal
Communications in Transportation Research
Published
2024-11-26
DOI
https://doi.org/10.1016/j.commtr.2024.100155
Citations
10
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
2.03

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article

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

Mohsen Ramezani, Elnaz Emami
10 citations
Communications in Transportation Research
Transportation and Mobility Innovations
2.03
article

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

Mohsen Ramezani, Elnaz Emami
article en
10 citations

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.

Communications in Transportation ResearchVol. 4
The University of Sydney (AU)
University of Sydney, Australian Research Council
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Transportation and Mobility Innovations
2.03
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Integrated operator and user-based rebalancing and recharging in dockless shared e-micromobility systems — Mohsen Ramezani, Elnaz Emami · Communications in Transportation Research (2024) | TGRS Research Map | TGRS