With the growing need to maintain roadway systems amidst increasingly competitive resources while assuring safety and comfort for travelers, sound network-level decision-making becomes more vital than ever. A stochastic process known as Markov chain has been used extensively to capture the uncertainty associated with pavement performance over time and support this critical decision-making process. In applying Markov chain, this paper investigates the crack history of flexible pavements with an insight into the impacts of two primary factors contributing to the rapid deterioration of surface cracks in flexible pavements; excessive traffic loading and delayed maintenance and rehabilitation. Empirical results of the investigation are presented using the data from the Florida Department of Transportation's (FDOT's) pavement condition survey database. The results show that the impacts of the above two factors are statistically different from one another in terms of the deterioration rate of Florida's pavements with respectto cracks. Hence the findings of this paper would assist the highway authorities in making more timely and efficient network-level decisions.
Abstract