Intelligent Safety Assessment of Rural Roadways Using Automated Image and Video Analysis
Due to the significant effect of roadside safety on the number and severity of road accidents, many state DOTs are trying to detect road segments with potentially unsafe roadside attributes. This can be achieved by manually inspecting videos and images collected by third-party data providers, such as Mandli. However, this process is both time-consuming and susceptible to human error. Therefore, this project will develop an automated approach that leverages computer vision and machine learning to efficiently evaluate roadside safety.
Language
- English
Project
- Status: Active
- Funding: $81000
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Contract Numbers:
69A3551747108
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
North Dakota State University
Fargo, ND United States 58108 -
Project Managers:
Tolliver, Denver
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Performing Organizations:
Dept. of Civil and Environmental Engineering
University of Utah
Salt Lake City, UT United States -
Principal Investigators:
Markovic, Nikola
Rashidi, Abbas
- Start Date: 20210924
- Expected Completion Date: 20240731
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
- Source Data: MPC-669
Subject/Index Terms
- TRT Terms: Automation; Computer vision; Highway safety; Image analysis; Machine learning; Roadside; Rural highways; Video
- Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;
Filing Info
- Accession Number: 01785292
- Record Type: Research project
- Source Agency: Mountain-Plains Consortium
- Contract Numbers: 69A3551747108
- Files: UTC, RIP
- Created Date: Oct 22 2021 10:09AM