• DocumentCode
    3504357
  • Title

    Video-based trailer detection and articulation estimation

  • Author

    Caup, Lukas ; Salmen, Jan ; Muharemovic, Ibro ; Houben, Sebastian

  • Author_Institution
    Inst. for Comput. Neural Sci., Univ. of Bochum, Bochum, Germany
  • fYear
    2013
  • fDate
    23-26 June 2013
  • Firstpage
    1179
  • Lastpage
    1184
  • Abstract
    Even for experienced drivers handling a roll trailer with a passenger car is a difficult and often tedious task. Moreover, the driver needs to keep track of the trailer´s driving stability on unsteady roads. There are driver assistance systems that can simplify trajectory planning and observe the oscillation amplitude, but they require additional hardware. In this paper, we present a method for trailer detection and articulation angle measurement based on video data from a rear end wide-angle camera. It consists of two stages: to decide whether or not a trailer is coupled to the vehicle and to estimate its articulation angle. These calculations work on single video frames. The vehicle is therefore not required to be in motion. However, we stabilize the single frame estimations by temporal integration. We perform training and parameter optimization and evaluate the accuracy of our approach by comparing the results to those of an articulation measurement unit attached to a test vehicle´s hitch. Results show that it can very reliably be determined whether or not a trailer is coupled to the vehicle. Furthermore, its articulation can be estimated with a mean error of less than two degrees.
  • Keywords
    driver information systems; image sensors; learning (artificial intelligence); optimisation; video signal processing; articulation angle measurement; articulation estimation; driver assistance systems; oscillation amplitude; passenger car; rear end wide-angle camera; roll trailer; single frame estimations; temporal integration; trajectory planning; video-based trailer detection; Cameras; Estimation error; Hardware; Prototypes; Training; Vehicles;
  • 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.2013.6629626
  • Filename
    6629626