MODEL-BASED RECOGNITION OF INTERSECTIONS AND LANE STRUCTURES

This paper presents a model-based machine vision system to estimate the location of incoming as well as outgoing lanes at an intersection. Image sequences recorded from a moving vehicle are used to detect and track intersections using a Kalman Filter. Results obtained from real world data are presented.

• Supplemental Notes:
  • Publication Date: 1995 Published By: IEEE Service Center, Piscataway NJ
• Corporate Authors:

  Universitat der Bundeswehr Munchen

  ,    

  Ohio State University, Columbus

  Department of Electrical Engineering
  Columbus, OH  United States  43210

  Ford Motor Company

  1 American Road
  Dearborn, MI  United States  48126-2798

  Johns Hopkins University, Laurel

  Applied Physics Laboratory, 11100 Johns Hopkins Road
  Laurel, MD  United States  20723-6099

  University of Washington, Seattle

  Department of Electrical Engineering
  Seattle, WA  United States  98195

  Texas A&M University, College Station

  Department of Electrical Engineering
  College Station, TX  United States  77843

  Universite Paris-Sud. Institut d'electronique fondamentale

  ,    

  Ruhr-Universitat Bochum. Institut fur Neuroinformatik

  ,    

  GERMANY. BUNDESSTELLE FSUR FLUGUNFALL-UNTERSUCHUNG

  ,    

  Bayerische Motoren Werke

  ,    

  University of Michigan Transportation Research Institute

  IVHS Program Office, 2901 Baxter Road
  Ann Arbor, MI  United States  48109

  Great Lakes Center for Truck and Transit Research

  201 UMTRI Building, 2901 Baxter Road
  Ann Arbor, MI  United States  48109-2150

  General Motors Corporation

  Research and Development Center, 30500 Mound Road
  Warren, MI  United States  48090

  Daimler-Benz A.G.

  Mercedesstrade 136
  Stuttgart-Unterturk,   Germany 

  Prometheus (Program)

  ,    

  Carnegie Mellon University

  Robotics Institute, 5000 Forbes Avenue
  Pittsburgh, PA  United States  15213-3890

  University of California, Berkeley

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

  Centre d'automatique de Lille

  ,    

  California Department of Transportation

  1120 N Street
  Sacramento, CA  United States  95814
• Authors:
  • Gengenbach, V
• Conference:
  • Intelligent Vehicles '95 Symposium (1995 : Detroit, Mich.). Proceedings of the Intelligent Vehicles '95 Symposium
• Publication Date: 1995

Language

• English

Media Info

• Pagination: p. 512-517

Subject/Index Terms

• TRT Terms: Advanced vehicle control systems; Computer vision; Kalman filtering
• Subject Areas: Operations and Traffic Management;

Filing Info

• Accession Number: 00787471
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH, STATEDOT
• Created Date: Nov 17 2000 12:00AM