Automated repair of asphalt pavement cracks and potholes utilizing 3D printing and LiDAR scanning

This study introduces a method for automatic repair of asphalt pavement cracks and potholes using 3D printing and LiDAR scanning. A scanning method was developed to accurately detect and represent cracks and potholes in a 3D model. To address the limitations of LiDAR scanning, such as missing data points caused by the irregular shapes of cracks and potholes, the screened Poisson method was applied to reconstruct the missing data points. These models were validated through both theoretical calculations and sand test. In addition, the research focuses on optimizing key 3D printing parameters, such as printing temperature and printing speed, to enhance performance of crack repair throughout semi-circular bending test. Direct tensile strength test was employed to assess the impact of waste materials (e.g., rubber tire powder and waste glass) on the bond strength of filled sample. The results indicated a volume difference of 2–5 % between the scanning method and the sand test method, demonstrating high accuracy in detecting and reconstructing 3D cracks/potholes. Binders modified with 10 % rubber tire powder, or 20 % waste glass exhibited the highest tensile strength of 212 kPa and 207 kPa, respectively. However, using more than 30 % waste materials is not recommended due to a significant reduction in bond strength compared to conventional binders. An optimal 3D printing speed of 180 mm/min and a temperature of 117 °C are recommended for use in 3D printing in laboratory conditions. It was also noted that higher printing speeds decrease indirect tensile strength, highlighting the importance of balanced parameter settings.