With the advent of GPS tracking technology, how to make use of taxi trajectories to efficiently and effectively reduce taxis cruising distance is an active and challenging research topic. In this paper, we propose a profitable taxi route recommendation method called adaptive shortest expected cruising route (ASER). In ASER, a probabilistic network model is developed to predict pick-up probability and capacity of each location by using Kalman filtering method. To recommend profitable driving routes to taxi drivers, ASER takes the load balance between passengers and taxis into consideration and the shortest expected cruising distance is introduced to formulate potential cruising distance of taxis. Moreover, MapReduce and a novel data structure kdS-tree are applied to improve recommendation efficiency. ASER is evaluated on two real trajectory datasets from San Francisco, CA, USA, and Wuhan, China. The experimental results validate that ASER significantly outperforms the existing methods by reducing the taxi cruising distance 11% and 39%.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Profitable Taxi Travel Route Recommendation Based on Big Taxi Trajectory Data


    Beteiligte:
    Qu, Boting (Autor:in) / Yang, Wenxin (Autor:in) / Cui, Ge (Autor:in) / Wang, Xin (Autor:in)


    Erscheinungsdatum :

    01.02.2020


    Format / Umfang :

    3681477 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Taxi-RS: Taxi-Hunting Recommendation System Based on Taxi GPS Data

    Xu, Xiujuan / Zhou, Jian Yu / Liu, Yu et al. | IEEE | 2015



    Recommend a profitable cruising route for taxi drivers

    Dong, Hao / Zhang, Xuedan / Dong, Yuhan et al. | IEEE | 2014


    TAXI ROUTE GENERATOR

    MILLER JASON A / THAULOW KRISTIAN I / CROYDON MATTHEW G et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    TAXI ROUTE GENERATOR

    MILLER JASON S / THAULOW KRISTIAN I / CROYDON MATTHEW G et al. | Europäisches Patentamt | 2022

    Freier Zugriff