Accurate data collection and interpretation of pavement data are critical for the decision-making process in pavement management. This study focused on the data analysis portion of a new automated system capable of collecting and analyzing pavement surface distress, mainly cracks, in real time through the use of a high-resolution digital camera; efficient image processing algorithms; and multicomputer, multi-CPU-based parallel computing. Features and performance of the automated system for distress survey were surveyed. Three protocols of producing distress indices incorporated into the automated system were examined: the AASHTO interim distress protocol, the World Bank's Universal Cracking Indicator, and the Texas Department of Transportation's method. It was found that distress results from the automated system were consistent for multiple passes of the same pavement sections.