Detecting asphalt pavement raveling using emerging 3D laser technology and macrotexture analysis.
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2015-08-01
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Abstract:This research project comprehensively tested and validated the automatic raveling detection, classification,
and measurement algorithms using 3D laser technology that were developed through a project sponsored by
the National Cooperative Highway Research Program (NCHRP) Innovations Deserving Exploratory
Analysis (IDEA) program. The raveling condition survey protocol used in the Georgia Department of
Transportation (GDOT) was adopted in the testing and validation, though it can be easily extended to other
highway agencies’ protocols. Four miles of test sections on I-85 and the entire asphalt pavements (61 miles)
on I-285 were selected for validating the developed algorithms. The ground truth data was established by in-field investigation and in-office review of videolog images and 3D laser data with the help of GDOT’s
pavement engineers. The results have demonstrated the promising capabilities of automatically detecting
and measuring asphalt pavement raveling using the developed algorithms and 3D laser technology to assist
in transportation agencies’ raveling data collection. Potentially, it will save tremendous manual effort for
field surveys, improve data accuracy, and help highway agencies make more informed decisions on
pavement maintenance and rehabilitation.
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