Preceding Vehicle Recognition for Lead Vehicle of Fully Automated Platooning Trucks Based on Multi-sensor Fusion

The authors have been developing an autonomous platooning system of heavy trucks aimed at enhancing its energy efficiency by shortening headway distance between trucks. This paper focused on developing a forward environment perception method for fully automated lead vehicle of the autonomous platooning system. To percept the forward environment of autonomous platooning system, it is important to robustly detect obstacles from distance. Additionally, it is also important to recognize which lane the detected obstacles exist. In this research, the obstacles are detected robustly and precisely based on multi-sensor fusion scheme between LIDAR and RADAR. Moreover, the lanes, where the obstacles exist, are recognized by using geometrical curvature of driving lane estimated from both ego-motion and lane marker position detected from cameras.

  • Supplemental Notes:
    • Abstract reprinted with permission from Intelligent Transportation Society of America.
  • Corporate Authors:

    ITS America

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    Washington, DC  United States  20036
  • Authors:
    • Koike, Shota
    • Suganuma, Naoki
  • Conference:
  • Publication Date: 2012


  • English

Media Info

  • Media Type: Digital/other
  • Features: CD-ROM; Figures; Photos; References; Tables;
  • Pagination: 8p
  • Monograph Title: 19th ITS World Congress, Vienna, Austria, 22 to 26 October 2012

Subject/Index Terms

Filing Info

  • Accession Number: 01499192
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Nov 21 2013 9:14AM