ACCURATE LOCAL VEHICLE DEAD-RECKONING FOR A PARKING ASSISTANCE SYSTEM

In this paper, two new approaches for dead reckoning are compared to the established rear-axle based algorithm. One method combines wheel revolution data with the steering angle measurement, while the other computes the position estimates using velocity and steering angle measurement. It is shown that the performance of the two proposed approaches is superior to the simple rear axle-based algorithm, and that the position data provided is precise enough for control purposes.

  • Supplemental Notes:
    • Publication Date: 2002. IEEE Service Center, Piscataway NJ
  • Corporate Authors:

    Polytechnic Institute of New York University, Brooklyn

    Department of Mechanical Engineering, 6 MetroTech Center
    Brooklyn, NY  United States  11201

    Honda Gijutsu Kenkyujo

    ,    

    University of California, Berkeley

    Department of Mechanical Engineering
    Berkeley, CA  United States  94720-1740

    University of California, Berkeley

    California PATH Program, Institute of Transportation Studies
    Richmond Field Station, 1357 South 46th Street
    Richmond, CA  United States  94804-4648

    California Polytechnic State University, San Luis Obispo

    Department of Electrical Engineering, 1 Grand Avenue
    San Luis Obispo, CA  United States  93407

    Technische Universiteit Delft

    ,    

    University of Minnesota, Twin Cities

    Department of Mechanical Engineering, 111 Church Street, SE
    Minneapolis, MN  United States  55455

    DaimlerChrysler Powersystems

    ,    

    Technische Universitat Darmstadt

    ,    
  • Authors:
    • Kochem, M
    • Neddenriep, R
    • ISERMANN, R
    • Wagner, N
    • Hamann, C D
  • Conference:
  • Publication Date: 2002

Language

  • English

Media Info

  • Pagination: p. 4297-4302

Subject/Index Terms

Filing Info

  • Accession Number: 00963558
  • Record Type: Publication
  • Source Agency: UC Berkeley Transportation Library
  • Files: PATH
  • Created Date: Oct 2 2003 12:00AM