Automated pavement detection and artificial intelligence pavement image data processing technology

Abstract

Surging vehicle loads and changing climate environments place significant stress on road infrastructure. Pavement management requires fast and effective methods of detecting pavement distress and perform timely maintenance. This paper presents in detail the hardware devices for automated data collection and the 2D and 3D image acquisition methods. The detection methods for different pavement distresses are comprehensively analyzed and summarized in the review. In addition, the review covers the latest and classical artificial intelligence (AI) image processing algorithms, including traditional image processing, machine learning, and deep learning methods applied in pavement distress detection. The review summarizes the challenges, limitations, emerging technologies, and future trends of AI algorithms. The review findings indicate that the application of AI technology methods in pavement distress detection has grown dramatically, but challenges still exist in AI technology application in practical engineering.