| As pavement condition raises more and more concerns in the highway system across the United States, a new challenge emerges in developing reliable pavement deterioration prediction models that are easily applicable by highway pavement management system in state departments of transportation and other agencies. Transportation agencies typically employ a process to evaluate pavement performance on a regular basis and identifying sections with a need for maintenance or rehabilitation. Some states in the U.S. utilize an index based on ride quality alone, while others utilize a pavement rating system that is based solely on visible surface distresses in order to regularly perform evaluation of pavements. This thesis looks at the differences among the combinations of pavement types and priority systems and what effects they have on pavement roughness within the Ohio state highway system when compared with annual snowfall, quantified by the International Roughness Index (IRI).;Simple correlation studies between one of Ohios pavement condition indices, the Pavement Condition Rating (PCR), and RIRI were conducted in attempt to find a meaningful relationship. When little to no correlations were found, this thesis then separated the highways based on pavement type, priority system, and annual snowfall region to develop an annual average IRI increase trend for each combination. Statistical testing were performed to ensure results were generated with a 90% confidence level.;Slope regression and frequency prediction methods were used in three cases of annual snowfall to analyze the snowfall-DeltaRIRI relationship: one was split into four snowfall regions, and the other two were by different amount of snowfall thresholds---30 and 40 inches per year. Results from both methods confirmed that there exists a direct, positive correlation between the amount of annual snowfall and the increase of International Roughness Index per year in nearly all combinations of pavement-priority highways in Ohio. |
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