LiDAR-Based Pothole Patching Quantity Estimation and Cost Saving Analysis Using Segmented TIN Model

Potholes represent a significant form of road distress, and the conventional method for estimating the required repair material typically assumes a cuboidal shape for each pothole. This approximation often leads to an overestimation of pothole volume, resulting in excessive patching material and increased costs. To address this limitation, the present study introduces a LiDAR-based segmentation and digitization method. This approach utilizes only the point cloud data of potholes obtained via terrestrial laser scanning to generate accurate 3D surfaces, contours, and a Triangulated Irregular Network (TIN), thereby enabling precise volume and patching quantity calculations. The findings revealed that the volume and patching quantity estimated using the traditional cuboidal method are two to four times greater than those calculated through the proposed LiDAR-based approach. This clearly demonstrates that the conventional method leads to unnecessary procurement of patching materials. Cost analysis further indicated that the LiDAR-based approach could result in savings of approximately INR 3,500 per pothole in India, $262 in the USA, and £150 in the UK. Given that millions of potholes are repaired annually in each country, adopting the proposed LiDAR-based method has the potential to yield substantial cost savings on a national scale.