Abstract
Many local agencies in the San Francisco Bay Area in California use manual surveys to collect pavement distress data to calculate pavement condition index (PCI) values for use in pavement management. Many of these agencies then use pavement performance curves and trigger values in their decision trees or matrices based on these resulting PCI values and derived parameters as major components of the agencies’ pavement management decision support systems. Automated pavement distress data collection procedures are available, but all available procedures and equipment do not necessarily reproduce the PCI from manual surveys. These differences in the PCI calculated from different distress data collection methods can lead to substantially different pavement treatment recommendations and fund needs. A 2-year project was conducted for the Metropolitan Transportation Commission of the San Francisco Bay Area to evaluate the effect of the use of different methods to determine the PCI. The study included statistical analyses and comparison of seven pavement distress types for asphalt pavements and the resulting PCI. The methodology, interpretation, and findings from the study are described. Emphasis is given to differences observed in the results and analysis of their causes. Practical recommendations for future use of automated pavement distress data collection procedures for local agencies are given.
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