• DocumentCode
    3504340
  • Title

    Road boundary detection for run-off road prevention based on the fusion of video and radar

  • Author

    Janda, Florian ; Pangerl, Sebastian ; Lang, Eva ; Fuchs, Emmerich

  • Author_Institution
    Inst. for Software Syst. in Tech. Applic. of Comput. Sci., Univ. of Passau, Passau, Germany
  • fYear
    2013
  • fDate
    23-26 June 2013
  • Firstpage
    1173
  • Lastpage
    1178
  • Abstract
    An approach for detecting the road boundary on different types of roads without any preliminary knowledge is presented. We fuse information obtained from an algorithm which detects road markings and road edges in images acquired by a video camera as well as data from a radar sensor. Each road marking, each road edge and each road barrier is tracked individually. Hence we can even capture exits or laybys. We use an edge image for road marking detection and texture information for road edge detection. Additional data provided by a radar sensor is used to measure targets referring to static barriers along the road side such as guardrails. The output of each processing unit is fused into a Kalman filter framework, where the confidence of each subsystem influences the innovation of the overall system. The underlying geometric road model comprises parameters for multiple lanes, the flanking road edge as well as the vehicle´s relative pose. The work is part of the project Interactive.
  • Keywords
    Kalman filters; edge detection; image sensors; radar imaging; road traffic; traffic engineering computing; Kalman filter framework; radar sensor; road barrier; road boundary detection; road edge detection; road markings detection; run-off road prevention; video and radar fusion; video camera; Cameras; Image edge detection; Radar detection; Radar measurements; Radar tracking; Roads;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium (IV), 2013 IEEE
  • Conference_Location
    Gold Coast, QLD
  • ISSN
    1931-0587
  • Print_ISBN
    978-1-4673-2754-1
  • Type

    conf

  • DOI
    10.1109/IVS.2013.6629625
  • Filename
    6629625