Case Study: Effect of the Condition Data of Automated Pavement Surveys on Pavement Performance Indicators

State departments of transportation (DOTs) have been transitioning from manual to automated pavement condition surveys with the advantages such as safe and speedy data collection and consistency and repeatability in data collected. The manual and automated data collection methods have inherently different capabilities for measuring pavement distress. When state DOTs use pavement performance indicators developed based on manually collected data and have already introduced an automated data collection process, the different capabilities can be problematic by either overestimating or underestimating actual pavement conditions. This study investigated the effect of the condition data of automated pavement surveys on a manual-based pavement performance indicator through a case study. The case study was a structural cracking index (SCI) used for the West Virginia Division of Highways. This study investigated the effect of automated pavement condition surveys on manual-based pavement performance indicators. The study found that automated surveys can lead to changes in distress data compared to manual inspections, suggesting non-random change patterns. These changes can lead to significant budget losses for state agencies. The study also demonstrated the applicability of the approach used for a case study for other state agencies to evaluate their current pavement performance indexes.