A VISION BASED AUTOMATED VEHICLE CLASSIFICATION SYSTEM

Vision based vehicle classification offers substantial advantages compared with traditional vehicle classification systems, which use information from inductive loops, axle counters, Doppler radar and infra red light curtains to classify vehicles. The principle benefits include the ease of installation and maintenance, as well as much greater flexibility, performance and cost effectiveness. This paper details a vision based classification system, which uses image processing and neural network techniques to classify vehicles, looks at the performance of the system, and discusses problems associated with vision systems.

• Supplemental Notes:
  • Full conference proceedings available on CD-ROM.
• Corporate Authors:

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036
• Authors:
  • Till, J
• Conference:
  • 8th World Congress on Intelligent Transport Systems
  • Location: Sydney, Australia
  • Date: 2001-9-30 to 2001-10-4
• Publication Date: 2001

Language

• English

Media Info

• Features: Figures;
• Pagination: 8p

Subject/Index Terms

• TRT Terms: Automatic vehicle classification; Benefits; Cost effectiveness; Image processing; Installation; Intelligent transportation systems; Maintenance; Neural networks; Performance; Vision
• Subject Areas: Highways; Maintenance and Preservation; Operations and Traffic Management;

Filing Info

• Accession Number: 00964155
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Oct 15 2003 12:00AM