Correlation of New Sensor Types vs. Retroreflectivity Ratings
Annually, the Ohio Department of Transportation (ODOT) invests millions of dollars in replacing pavement markings (PMs). However, the process for determining the replacement is neither driven by numbers nor followed by assessments to ensure high-quality work has been performed. Instead, PMs are replaced according to a blanket, systematic replacement schedule. This leaves questions if PMs could be unnecessarily replaced while other that are of poorer quality are left in the field simply because they were installed more recently. There are a variety of existing methods for determining PM retroreflectivity. However, these methods are arduous, subjective and segment. A process that is rapid, objective and more continuous is desired. Previous research has shown that LiDAR can be used as an indicator of PM retroreflectivity intensity. As automated vehicles continue to progress, mobile LiDAR has also emerged as a mechanism for PM evaluation. ODOT has explored the potential of equipping its own fleet with equipment, such as mobile LiDAR, for obtaining data critical to the maintenance and preservation of the roadways. The goal of this project is to analyze data from LiDAR and machine-vision based systems to correlate data from those systems with the retroreflectivity ratings. This research will explore how ODOT can capitalize on this technology by deriving a quantitative correlation between mobile LiDAR intensity values and retroreflectivity, establishing thresholds for categorizing PMs qualitatively (e.g., poor, acceptable, good) while also incorporating new FHWA minimum standards, and developing algorithms that automatically categorize PMs by type and quality.
Language
- English
Project
- Status: Active
- Funding: $452028
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Contract Numbers:
39162
136667
118078
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Sponsor Organizations:
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Managing Organizations:
Ohio Department of Transportation
Research Program
1980 West Broad Street
Columbus, OH United States 43223 -
Project Managers:
Martindale, Jill
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Performing Organizations:
Civil Engineering Department, P.O. Box 210071, 741 Baldwin Hall
Cincinnati, OH United States 45221-0071 -
Principal Investigators:
Nazzal, Munir
- Start Date: 20230911
- Expected Completion Date: 20250911
- Actual Completion Date: 0
Subject/Index Terms
- TRT Terms: Data collection; Laser radar; Machine vision; Retroreflectivity; Road markings
- Identifier Terms: Ohio Department of Transportation
- Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation;
Filing Info
- Accession Number: 01887927
- Record Type: Research project
- Source Agency: Ohio Department of Transportation
- Contract Numbers: 39162, 136667, 118078
- Files: RIP, STATEDOT
- Created Date: Jul 18 2023 4:57PM