Automatic Extraction of Vehicle, Motorcycle, Bicycle, and Pedestrian Traffic from Video Data

The objective of this research is to develop image processing algorithms to automatically extract vehicle counts and classifications, as well as counts of motorcycles, bicycles, and pedestrians from real-time and offline videos. An easy-to-use graphical user interface will enable SCDOT staff to obtain multimodal traffic data accurately, safely, and cost-effectively to use for HPMS reporting and prioritize infrastructure design improvements and investments.

Language

  • English

Project

  • Status: Completed
  • Funding: $148,890.00
  • Contract Numbers:

    SPR 742

  • Sponsor Organizations:

    South Carolina Department of Transportation

    955 Park Street
    P.O. Box 191
    Columbia, SC  United States  29202-0191

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Managing Organizations:

    South Carolina Department of Transportation

    955 Park Street
    P.O. Box 191
    Columbia, SC  United States  29202-0191
  • Project Managers:

    Swygert, Terry

    Heaps, Meredith

  • Performing Organizations:

    University of South Carolina, Columbia

    502 Byrnes Building
    Columbia, SC  United States  29208
  • Principal Investigators:

    Huynh, Nathan

  • Start Date: 20190115
  • Expected Completion Date: 20200715
  • Actual Completion Date: 20211231

Subject/Index Terms

Filing Info

  • Accession Number: 01733138
  • Record Type: Research project
  • Source Agency: South Carolina Department of Transportation
  • Contract Numbers: SPR 742
  • Files: RIP, STATEDOT
  • Created Date: Mar 9 2020 7:35AM