Land carriage is important for nowadays large goods transportation. There are three major roles in a land carriage order: guests, companies and trucks. A significant problem, for logistics companies, is the lack of trip control. Continuous monitoring the trips of freight trucks is necessary. First of all, it does help logistics companies to prevent the fraud behaviours. But more importantly, it help us understanding the trip patterns of freight truck transportation. The development of Global Position System(GPS) and wireless communication together enables the possibility to analyze large scale freight trips. In this paper, we study a large GPS trajectory dataset of 14654 freight trucks from a 3rd-party company, which helps logistics companies monitoring those freight trucks. We propose a method to extract trips from the GPS trajectories of freight trucks and mine the travel patterns, both collectively and individually. To the best of our knowledge, this is the first mining work of large scale freight truck trajectory data.


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    Titel :

    Mining freight truck's trip patterns from GPS data


    Beteiligte:
    Huang, Jun (Autor:in) / Wang, Li (Autor:in) / Tian, Chen (Autor:in) / Zhang, Fan (Autor:in) / Xu, Chengzhong (Autor:in)


    Erscheinungsdatum :

    2014-10-01


    Format / Umfang :

    1913673 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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