Pavement Surface Permanent Deformation Detection and Assessment Based on Digital Aerial Triangulation

Abstract

Pavement surface distress information is essential to pavement management. Assessment of surface permanent deformation is particularly important given pavement's ubiquitous use and that permanent deformation significantly influences its integrity and performance. However, current assessment methods are expensive, labor-intensive, time-consuming, and potentially dangerous to inspectors. Digital aerial triangulation (DAT) and unmanned airborne systems (UAS) provide a new method for detecting and assessing permanent deformation that hold potential to overcome these limitations. Using hyperspatial resolution multispectral digital aerial photography (HRM-DAP) acquired from an UAS as input, DAT was employed to generate digital surface models (DSMs) of the pavement surface. Permanent deformation distress estimates extracted from these DSMs were compared to ground reference data collected using standard protocols via orthogonal regression analysis. The results show that the aerial triangulation of HRM-DAP provides consistent and reliable data for permanent deformation detection and assessment.