Geometric quantification of potholes in flexible pavements using consumer-grade mobile LiDAR sensors

Abstract

Road agencies with limited resources require agile, low-cost auscultation methods to quantify flexible pavement deterioration. This study evaluated the geometric accuracy and operational efficiency of the LiDAR sensor embedded in a consumer-grade smartphone (iPhone 16 Pro Max, 3D Scanner App) for quantifying potholes, using an Optical Level as the reference method. Five potholes located on the internal road network of a university campus in Jipijapa, Ecuador were measured in parallel, recording maximum width, maximum length, maximum depth, and capture time with both technologies. Analysis of absolute error, relative error, and the Wilcoxon test showed no relevant systematic differences in the dimensional variables (mean absolute error between 0.8 and 1.0 cm), while LiDAR capture time was markedly shorter and constant (5 minutes versus 18–35 minutes for the reference method). Consumer-grade mobile LiDAR is a technically viable and more efficient alternative to optical leveling for geometric pothole quantification in moderate-demand contexts, although the small sample size limits the generalizability of the findings.