Abstract: Efficient and automatic road pavement defect detection technology has become increasingly important given the transition of China's highway development from the large-scale construction stage to the large-scale conservation stage. We briefly review the study of road surface defect detection over the past two decades, and present a new method for road surface defect detection using 3D laser profiling techniques. Road surface defect detection involves the use of optical sensors such as CCD cameras and laser scanners to collect the information of road surface, and pattern recognition and machine learning algorithms to automatically locate the defects and identify the categories of defects. Comparative experiments in the laboratory and test practices on the real roads show that the road surface defect detection technology using 3D laser profiling has stronger environmental adaptability and higher recognition precision than the traditional technology based on 2D visible light imaging.