© ASCE. Automated and semi-Automated pavement distress surveys are being used increasingly to collect pavement condition data. This data, along with other information, is used to measure pavement performance and support pavement maintenance, preservation, and rehabilitation decisions. Generally, these automated and semi-Automated systems consist of image capturing technology (i.e., hardware) and image processing and analysis algorithms (i.e., software). This paper provides a review of quality assurance practices for automated and semi-Automated pavement condition surveys, including quality of images, accuracy and repeatability of measurements, data delivery requirements, equipment calibration, and control and verification sites. The information on these practices was obtained through a review of seven request for proposals (RFPs) issued by seven state departments of transportation (DOTs) between 2010 and 2015, and supplemented by a review of three manuals for these surveys.