Development of probabilistic models for predicting roughness in asphalt pavement

The objective of this paper was to develop probabilistic models based on the transition probability matrices obtained through knowledge and experience from those responsible for highway management so that this knowledge can be applied in places where there are no historical series of data collection related to the pavement condition. On the probabilistic models, experts' opinions are formalised through transition processes such as the Markov process, used in this research. This process allows workers to estimate the future pavement condition based on the knowledge of the current condition through a transition probability matrix. For setting up the matrices, some factors such as traffic density and climate have been considered. The considered dependent variable was the International Roughness Index which is widely used for safety and comfort evaluation of a pavement. The developed models indicate that there is a variation in pavement behaviour, inferred by experiences from experts, which is associated to factors such as traffic and climate.