Approach to Real-Time Commercial Vehicle Monitoring

Vehicle classification algorithms allocate vehicles to predefined classes based on selected vehicle characteristics. Such algorithms have many important applications in transportation systems analysis and policy development, including travel forecasting, goods movement studies, road design and maintenance, setting user fees, safety studies, traffic flow modeling, environmental impact analysis, traffic management and automated toll collection. This research will collect a large and unique dataset of commercial vehicle (CV) signatures using conventional inductive loops and a new wireless sensor with potential for cost-effective and widespread use. The data will be used to develop detailed and accurate vehicle classification algorithms for CVs, and will provide important insights into the strengths and limitations of a new wireless traffic sensor.

Language

• English

Project

• Status: Active
• Funding: $57349.00
• Sponsor Organizations:

  California Department of Transportation

  1227 O Street
  Sacramento, CA  United States  95843
• Project Managers:

  Briseno, Coco

• Performing Organizations:

  University of California Transportation Center (UCTC)

  University of California, Berkeley
  2614 Dwight Way, 2nd Floor
  Berkeley, CA  United States  94720-1782
• Principal Investigators:

  Ritchie, Stephen

• Start Date: 20060801
• Expected Completion Date: 0
• Actual Completion Date: 20080731
• Source Data: RiP Project 15164

Subject/Index Terms

• TRT Terms: Algorithms; Commercial vehicles; Loop detectors; Real time control; Real time information; Research projects; Vehicle classification; Wireless sensor networks
• Uncontrolled Terms: Traffic sensors
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01460127
• Record Type: Research project
• Source Agency: University of California Transportation Center (UCTC)
• Files: UTC, RIP, STATEDOT
• Created Date: Jan 3 2013 1:19PM