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
- Record URL:
Language
- English
Project
- Status: Completed
- Funding: $84818.00
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Contract Numbers:
69A3551747111
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Sponsor Organizations:
Carnegie Mellon University
Mobility21 National USDOT UTC for Mobility of Goods and People
Pittsburgh, PA United States 15213Office of the Assistant Secretary for Research and Technology
University Transportation Center Program
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Managing Organizations:
Carnegie Mellon University
Mobility21 National USDOT UTC for Mobility of Goods and People
Pittsburgh, PA United States 15213 -
Project Managers:
Kline, Robin
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Performing Organizations:
The Ohio State University
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Principal Investigators:
Redmill, Keith
- Start Date: 20181001
- Expected Completion Date: 20230630
- Actual Completion Date: 20230803
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Behavior; Drivers; Image processing; Machine learning; Private passenger vehicles; Risk assessment; Traffic flow theory; Traffic lanes; Traffic safety; Transit buses
- Subject Areas: Data and Information Technology; Highways; Passenger Transportation; Public Transportation; Safety and Human Factors; Vehicles and Equipment;
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 3:29PM