Shared mobility services are announced as a game changer in transportation and a promising solution to reduce congestion and improve performance of urban mobility. However, only few studies aim at identifying if it really exists a significant demand for such services. This paper propose a first attempt toward this objective by finding twin travelers into ridesourcing trips data. Using the Didi Chuxing's dataset, a general methodology is defined to assess the similarity between trips and to cluster analogous travelers. The study reveals, among others, that at least 18% of the trips can be paired with introducing tolerable delays.


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    Titel :

    Identifying Twin Travelers Using Ridesourcing Trip Data


    Beteiligte:
    Nicolas Chiabaut (Autor:in) / Cyril Veve (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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