The Oklahoma Department of Transportation (ODOT) currently spends at least $600,000 per year to collect pavement condition data for their highways. Every two years, the entire pavement network is updated with new data. ODOT now has over 16 years of pavement condition assessment data which provide a rich time-series dataset. This paper presents results of a current research project sponsored by the Oklahoma Transportation Center (OkTC) that focuses on using this data to assess the current pavement deterioration curves that are central to ODOT's pavement management system. In this study, the research team assessed the pavement condition assessment data in a structured manner in order to evaluate the performance of the currently used age-based pavement management models. Furthermore, the research team developed new models or calibrated the existing models for the purpose of providing more accurate and reliable planning for pavement maintenance and rehabilitation activities. The performance of the new or calibrated models was compared with the performance of the current models in order to determine which ones are most effective. The data driven models developed in this study will provide confidence to the ODOT pavement management team in developing short-term and long-term pavement management strategies and realistic pavement budget estimates and resource allocation.
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