• DocumentCode
    154791
  • Title

    Mining freight truck´s trip patterns from GPS data

  • Author

    Jun Huang ; Li Wang ; Chen Tian ; Fan Zhang ; Chengzhong Xu

  • Author_Institution
    Shenzhen Inst. of Adv. Technol., Shenzhen, China
  • fYear
    2014
  • fDate
    8-11 Oct. 2014
  • Firstpage
    1988
  • Lastpage
    1994
  • Abstract
    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.
  • Keywords
    Global Positioning System; data mining; freight handling; goods distribution; logistics; GPS data; GPS trajectory dataset; Global Position System; freight truck trajectory data; freight truck transportation; goods transportation; land carriage order; logistics companies; mining freight truck; travel patterns; trip control; trip patterns; wireless communication; Cities and towns; Companies; Data mining; Global Positioning System; Logistics; Trajectory; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on
  • Conference_Location
    Qingdao
  • Type

    conf

  • DOI
    10.1109/ITSC.2014.6957996
  • Filename
    6957996