Image Processing Approaches to Traffic Situation Understanding, Risk Assessment, and Safety

This project will explore several potential applications of image processing, including NN/deep learning technologies, to the analysis of traffic scenes involving passenger and transit vehicles. The project team outlines three potential applications below- the exact distribution of effort and topics addressed will depend on the availability of student and research staff. (1) Traffic scene risk assessment and driver behavior understanding (2) Methodologies for extracting information from transit vehicle video for traffic flow estimation (3) Optical flow for automated vehicle lane following

Language

  • English

Project

  • Status: Active
  • Funding: $84818.00
  • Contract Numbers:

    69A3551747111

  • Sponsor Organizations:

    Carnegie Mellon University

    Mobility21 National USDOT UTC for Mobility of Goods and People
    Pittsburgh, PA  United States  15213

    Office of the Assistant Secretary for Research and Technology

    University Transportation Center Program
    ,    
  • Managing Organizations:

    Carnegie Mellon University

    Mobility21 National USDOT UTC for Mobility of Goods and People
    Pittsburgh, PA  United States  15213
  • Project Managers:

    Kline, Robin

  • Performing Organizations:

    The Ohio State University

    ,    
  • Principal Investigators:

    Redmill, Keith

  • Start Date: 20181001
  • Expected Completion Date: 20220630
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01710710
  • Record Type: Research project
  • Source Agency: National University Transportation Center for Improving Mobility (Mobility21)
  • Contract Numbers: 69A3551747111
  • Files: UTC, RiP
  • Created Date: Jul 11 2019 10:11AM