This study developed an understanding of the relationship between pavement condition and road safety on rural two-lane undivided arterial and collector roads in the province of New Brunswick for consideration as a decision-making criterion in asset management programs. Two crash prediction models were developed for single-vehicle and multiple vehicle accidents separately using a negative binomial regression that relate pavement condition indicators to accident frequency. International Roughness Index was found to be significant in both models which indicates that IRI is a contributing factor to single vehicle and multiple-vehicle accident involvements. Indeed, the coefficient of IRI was determined to be negative in both models which means that there is a negative correlation between pavement condition and accidents. Crash modification functions were developed for both single-vehicle and multiple-vehicle collisions. The results indicate that a unit of decrease in IRI in m/km is expected to increase single and multiple-vehicle accidents by 8% and 17% respectively. The impact of different pavement rehabilitation treatments used by NBDTI were quantified and found to produce increases in collisions ranging from 0.7 and 16.5%.
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