Abstract Due to the potential to reduce energy consumption and greenhouse gas emission, electric vehicles have been widely adopted in ride-hailing services Besides the frequently considered immediate requests, reservation gives precise information on future requests, which may help to increase ride-hailing system performance. In this study, an integrated modelling framework is developed for coordinating the highly correlated matching, rebalancing and charging of ride-hailing EVs under hybrid requests, including both immediate and reservation requests. A heuristic algorithm is then proposed so that relatively large instances can be solved in a reasonable time. Through extensive empirical experiments constructed with real-world trip data, we show that the proposed framework is able to improve ride-hailing system performance. Managerial insights on the impacts of ratio of reservation requests, fleet size, and spatial coverage of charging infrastructures are also provided to promote sustainable transportation.


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    Title :

    Coordinating matching, rebalancing and charging of electric ride-hailing fleet under hybrid requests


    Contributors:
    Yu, Xinlian (author) / Zhu, Zihao (author) / Mao, Haijun (author) / Hua, Mingzhuang (author) / Li, Dawei (author) / Chen, Jingxu (author) / Xu, Hongli (author)


    Publication date :

    2023-08-28




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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