A software tool for automated extraction of pavement cracks from mobile LiDAR data

点击翻译按钮获取中文摘要

Pavement surface distresses are an indicator of pavement performance. Extensive damage or degradation of pavement surfaces is the consequence of intense traffic loads accompanying with extreme weather conditions or aging effect everywhere in Canada. Surface distress evaluation is commonly performed manually. However, nowadays several agencies are replacing the manual work by automated distress data collection devices, such as mobile LiDAR scanner. Dense and high accuracy 3D point cloud data collected by a mobile laser scanning (or LiDAR) system is an emerging data source for recording pavement distresses. This new technology has overcame the limitations of the traditional manual practices that usually associated with high cost, low productivity and low accuracy. Mobile LiDAR systems is capable of scanning road surfaces at ambient lighting with low intensity contrast under normal speed. Existing studies have demonstrated that mobile LiDAR point cloud is applicable to evaluate pavement condition including rutting, ride quality, rehabilitation, texture, and