VISUAL PROCESSING FOR VEHICLE CONTROL FUNCTIONS

The authors first outline the role of vision in Advanced Vehicle Control Systems (AVCS). Subsequently, a discussion is presented on how current and future vision algorithms can deliver vision functions to provide the required sensing and control capabilities. Finally highlights of three specific algorithms that address the problems of potential obstacle detection, tracking and reconstruction, model matching, and vehicle localization are presented.

• Supplemental Notes:
  • Publication Date: 1992 Published By: Institute of Electrical and Electronics Engineers, New York
• Corporate Authors:

  Princeton University

  Department of Civil Engineering and Operations Research
  Princeton, NJ  United States  08544

  Rockwell International Science Center

  ,    

  Carnegie Mellon University

  School of Computer Science
  Pittsburgh, PA  United States  15213

  University of Pennsylvania, Philadelphia

  Department of Computer and Information Science
  Philadelphia, PA  United States  19104

  Regie nationale des usines Renault. Direction de la recherche

  ,    

  Crain Communications, Incorporated

  1155 Gratiot Avenue
  Detroit, MI  United States  48207-2997

  Nihon Denso Kabushiki Kaisha

  ,    

  Ecole nationale superieure des mines de Paris

  ,    

  Daimler-Benz A.G.

  Mercedesstrade 136
  Stuttgart-Unterturk,   Germany 

  Matsushita Denki Sangyo

  ,    

  Nissan Jidosha Kabushiki Kaisha

  ,    

  Honda Gijutsu Kenkyujo

  ,    

  Daihatsu Jidosha Kabushiki Kaisha

  ,    

  Istituto per la Ricerca Scientifica e Tecnologica (Trento, Italy)

  ,    
• Authors:
  • Riseman, Edward M
• Conference:
  • Intelligent Vehicles '92 Symposium (1992 : Detroit, Mich.). Proceedings of the Intelligent Vehicles '92 Symposium
• Publication Date: 1992

Language

• English

Media Info

• Pagination: p. 397-402

Subject/Index Terms

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

Filing Info

• Accession Number: 00773126
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH
• Created Date: Nov 17 1999 12:00AM