Bike Sharing Systems (BSS) represent a sustainable and efficient urban transportation solution. A major challenge in BSS is repositioning bikes to avoid shortage events when users encounter empty or full bike lockers. Existing algorithms unrealistically rely on precise demand forecasts and tend to overlook substantial operational costs associated with reallocations. This paper introduces a novel Cost-aware Adaptive Bike Repositioning Agent (CABRA), which harnesses advanced deep reinforcement learning techniques in dock-based BSS. By analyzing demand patterns, CABRA learns adaptive repositioning strategies aimed at reducing shortages and enhancing truck route planning efficiency, significantly lowering operational costs. We perform an extensive experimental evaluation of CABRA utilizing real-world data from Dublin, London, Paris, and New York. The reported results show that CABRA achieves operational efficiency that outperforms or matches very challenging baselines, obtaining a significant cost reduction. Its performance on the largest city comprising 1765 docking stations highlights the efficiency and scalability of the proposed solution even when applied to BSS with a great number of docking stations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Cost-Aware Adaptive Bike Repositioning Agent Using Deep Reinforcement Learning


    Beteiligte:


    Erscheinungsdatum :

    01.04.2025


    Format / Umfang :

    20791047 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    A multiple type bike repositioning problem

    Li, Yanfeng | Online Contents | 2016


    E-Bike Station Management using Deep Reinforcement Learning

    Chirag Anirudh, S / Bagrodia, Alokpunj / Ubaradka, Achal Shetty et al. | IEEE | 2024


    Reward Design for Driver Repositioning Using Multi-Agent Reinforcement Learning

    Shou, Zhenyu / Di, Xuan | ArXiv | 2020

    Freier Zugriff

    Repositioning Bikes with Carrier Vehicles and Bike Trailers in Bike Sharing Systems

    Zheng, Xinghua / Tang, Ming / Zhuo, Hankz Hankui et al. | ArXiv | 2019

    Freier Zugriff