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Evaluation of Cost-Effective Pavement Deformation Detection Technologies Using Mobile LiDAR



Project Details
Author(s) Anurag Pande, California Polytechnic State University
Co-Author(s) Alireza Shams, California Polytechnic State University, Ashraf Rahim, California Polytechnic State University, Hani Alzraiee, California Polytechnic State University
CTEDD Funding Year 2020 General RFP
Project Status In Progress

SummarySummary

Lateral water drainage on roadways is important to ensure safe and efficient operation and structural condition of the pavement. Pavement rutting could lead to failure in draining water, which poses a hydroplaning risk to drivers due to ponding and loss of skid resistance in wet weather. Traditional data collection methods to identify pavement sections with deformation such as rutting are time-consuming, labor-intensive, and require data collectors to be located on the road, which poses a safety hazard. Local county agencies and States Department of Transportation DOTs could benefit from the use of Mobile Terrestrial Light Detection and Ranging LiDAR Scanning MTLS to collect accurate pavement cross-section data on roads in their jurisdictions. This study will provide technical and economic evaluation of the MTLS system through comparison of the data collected through MTLS with traditional data collection processes such as Rut Bar System. MTLS system could acquire three-dimensional 3D coordinates in the form of dense point clouds for multiple travel lanes at highway speed with a single pass leading to potential cost-savings. The research will result ...in a framework to calibrate, collect, and process pavement cross-section and condition data. The project has significant potential for tech transfer to stakeholder agencies as the MTLS data and related processes will be relevant for several applications using spatial data for asset Read more


Subjects#: Big Data, MTLS, Maintenance, Mobile LiDAR, Pavement