Image-based 3D reconstruction using traditional and UAV datasets for analysis of road pavement distress

Abstract

On local and urban networks, the enduring issue of scarce resources for Maintenance, Rehabilitation, and Reconstruction strategies (MR&R) has led, in many cases, to using unadjusted or poor techniques for road pavement distress detection and analysis, yielding ineffective or even counterproductive results. Therefore, it is necessary to have tools that can carry out quick, reliable and low-cost assessment surveys. This paper aims at validating the use of innovative and low-cost technologies for road pavement analysis, assessing their potentialities for improving the automation and reliability of distress detection. A Structure from Motion (SfM) technique is analyzed at different altitudes. The technique was applied on a distressed road pavement inside the University Campus in Palermo. The models obtained were compared with a terrestrial laser scanned 3D model to analyze the technique's metric accuracy and reliability. The results have shown that the technique accurately replicates pavement distresses, inciting an integrated approach to optimize pavement management strategies.