Adaptive video-based vehicle classification technique for monitoring traffic : [executive summary].

Details

• Creators:
  Wei, Heng ; Abrishami, Hedayat ; Xiao, Xinhua ; Allam, Karteek Kumar
• Corporate Creators:
  University of Cincinnati
• Corporate Contributors:
  United States. Federal Highway Administration
• Subject/TRT Terms:
  • Vehicle classification
  • Vehicle length
  • Axles
  • Video
  • Image processing
  • Machine vision
  • Automatic vehicle identification
  • Traffic surveillance
• Publication/ Report Number:
  FHWA/OH-2015/20
• Resource Type:
  Brief
• Geographical Coverage:
  Ohio
• Corporate Publisher:
  Ohio. Dept. of Transportation. Office of Statewide Planning and Research
• Abstract:
  Federal Highway Administration (FHWA) recommends axle-based classification standards to map ; passenger vehicles, single unit trucks, and multi-unit trucks, at Automatic Traffic Recorder (ATR) stations ; statewide. Many state Departments of Transportation (DOT), including Ohio DOT (or ODOT), adapts the ; FHWA’s scheme F, axle-based classification standards in defining length-based classification boundaries ; to map various vehicles, such as passenger vehicles, single unit trucks, and multi-unit trucks, at Automatic ; Traffic Recorder (ATR) stations statewide. It is suggested that no single set of vehicle lengths work "best" ; for all states, because truck characteristics may vary from state to state. It’s also technically difficult to ; estimate each of the FHWA 13 categorized vehicles by the length-based approach.
• Format:
  PDF
• Funding:
  134874
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/29362/dot_29362_DS1.pdf
• File Type:
  [PDF - 34.46 KB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:5137d4e1091975744844b3e9f22675b22dab57b5e50948c698f58e3570dc027c