Optimization of Signal Timing Based on Pedestrian Intervals Using Computer Vision and Deep Learning Technology

This project is to conduct extensive use of computer vision based deep learning methodologies for detection, tracking and prediction of pedestrian movements. This will in turn aid in achieving the following objectives: (1) Increase pedestrian compliance with crossing phases by (a) Reduced wait times with skipped phases (b) Reduced false calls (2) Increase signal efficiency by (a) Reduced cycle length and split times to accommodate pedestrians (b) Reduced false calls (3) Identify a methodology and display to provide feedback to pedestrians that a call has been placed and the approximate wait time.

    Language

    • English

    Project

    • Status: Active
    • Contract Numbers:

      BED26 977-03

    • Sponsor Organizations:

      Florida Department of Transportation

      Research Center
      605 Suwannee Street MS-30
      Tallahassee, FL  United States  32399-0450
    • Managing Organizations:

      Florida Department of Transportation

      Research Center
      605 Suwannee Street MS-30
      Tallahassee, FL  United States  32399-0450
    • Project Managers:

      Dilmore, Jeremy

    • Performing Organizations:

      University of Central Florida, Orlando

      12443 Research Parkway, Suite 207
      Orlando, FL  United States  32826-
    • Principal Investigators:

      Abdel-Aty, Mohamed

    • Start Date: 20230103
    • Expected Completion Date: 20240430
    • Actual Completion Date: 0

    Subject/Index Terms

    Filing Info

    • Accession Number: 01869590
    • Record Type: Research project
    • Source Agency: Florida Department of Transportation
    • Contract Numbers: BED26 977-03
    • Files: RIP, STATEDOT
    • Created Date: Jan 4 2023 7:28AM