• DocumentCode
    3467411
  • Title

    Dynamic cluster tracking technique for traffic monitoring using on-vehicle radar

  • Author

    Zorka, Nicholas ; Cheok, Ka C.

  • Author_Institution
    Ford Sci. Res. Lab., Ford Motor Co., Dearborn, MI, USA
  • fYear
    2004
  • fDate
    14-17 June 2004
  • Firstpage
    728
  • Lastpage
    731
  • Abstract
    Predictive sensing applications are starting to find wide applications in automotive safety applications. In collision situations the need to alert the driver and to take effective countermeasures to meet the needs of the vehicle occupant safety is becoming increasingly more dependent on sensors. Electronic systems to provide warning and to implement active adaptation of occupant restraints to provide for enhanced safety protection are becoming more dependent on active safety sensors. This paper deals with a system that uses radar sensors that provides the ability to cluster the number of vehicles based on radar return signals and to actively track their movement with a Kalman filter.
  • Keywords
    Kalman filters; driver information systems; filtering theory; image sensors; pattern clustering; radar tracking; road safety; road vehicle radar; Kalman filter; active safety sensors; automotive safety; collision situations; countermeasures; dynamic cluster tracking; electronic systems; occupant restraints; on-vehicle radar; predictive sensing; radar return signals; radar sensors; safety protection; traffic monitoring; vehicle occupant safety; Automotive engineering; Driver circuits; Electronic countermeasures; Monitoring; Radar countermeasures; Radar tracking; Road accidents; Sensor systems; Vehicle dynamics; Vehicle safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2004 IEEE
  • Print_ISBN
    0-7803-8310-9
  • Type

    conf

  • DOI
    10.1109/IVS.2004.1336474
  • Filename
    1336474