Designs and Implementations of Automated Systems for Pavement Surface Distress Survey

Abstract

The categorization and quantification of the type, severity, and extent of surface distress is a primary method for assessing the condition of highway pavements. Various methodologies were developed to automate pavement distress surveys. Significant technical advances were made during the past years. The implementations of the image capturing subsystems include conventional analog-based area-scan, analog and digital line-scan, laser scanning, and shadow Moire method. Newer implementations of image processing include artificial neural net and parallel processing. However, problems still exist in the areas of implementation costs, processing speed, repeatability, and accuracy. This paper presents some of the key developments in recent years for automating pavement distress evaluation. These new systems are described in terms of their potential and applicability. This paper also presents a modified approach to collecting and processing surface distress through the use of high-performance digital cameras for the acquisition of surface distress data.