Evaluation of Pavement Performance Using Remote Sensing Techniques

Project ID: CTEDD 017-10

Author(s): Anand J. Puppala, University of Texas at Arlington

CTEDD Funding Year: 2017 General RFP

Project Status: Complete

UTC Funding: $65,000

End Date: August 31, 2018

Annually, transportation agencies spend several millions of dollars of expenditures for their rehabilitation works due to the problematic soils underneath the infrastructure assets. The soils in Dallas-Fort Worth region have high tendency to undergo swell-shrink behavior that contributes to the premature failure of pavements.

The proposed research focused on conducting the laboratory tests on the field collected samples and validating their field performance using innovative data collection technologies. Infrastructure monitoring often requires interaction between the data collector and the traffic which leads to traffic delays as well as exposing the personnel to perilous conditions.

Of late, different sensors like Light Detection and Ranging (LiDAR) and visible range cameras mounted on various platforms classified as terrestrial and aerial have been used to remotely inspect the infrastructure assets. Due to the advancement of these sensors, application of remote sensing techniques for monitoring infrastructure has gained lot of impetus in the past decade. Safe and efficient data collection procedures using terrestrial LiDAR and UAV were adopted in this project. The laser emitted and received from the LiDAR equipment and the images collected from the camera mounted on drones was also able to provide the infrastructure condition data.

The adopted procedures for the monitoring techniques and solutions have shown immediate benefit to the transportation agencies in obtaining valuable asset condition information in a safe manner. The outcome of this research has a possible impact on the policies of transportation agencies as part of their future infrastructure monitoring tasks.