The procedure used to determine whether performance differences exist among the Ohio Department of Transportation’s (ODOT’s) 12 districts is presented. Two performance measures were used: pavement condition rating deterioration trends and distributions. The methods used to develop the performance measures from existing pavement data are presented. Five years of actual pavement inspection data were supplied. The study was limited to divided highways with four or more lanes. To develop the deterioration trends, existing data were transformed into a probabilistic deterioration model using geographic information systems and relational database software. Monte Carlo simulation was used to establish deterioration trends and a Markovian deterioration envelope. Hypothesis testing was implemented to determine which districts were performing better or worse than the state as a whole. ODOT’s northeastern districts performed worse than the state average, and rural districts performed better than the state average.

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Highway engineers must conduct pavement evaluations before making rehabilitation decisions. Deflection tests performed at a uniform spacing are often used for structural evaluation purposes. The spacing between adjacent tests is often determined empirically. For pavements with large variability, more tests are needed. Variability is usually measured by the coefficient of variation ( CV). Several methods of determining test spacing were reviewed. A new method is proposed to calculate the test spacing based on the equivalent coefficient of variation ( CVe), which considers not only the variance but also the autocorrelation among the pavement responses. The new parameter CVe is more sensitive to test spacing than is the CV.

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