Application of Markov process to pavement management systems at network level

The rate of pavement deterioration is uncertain, and a pave-ment management system (PMS) should portray this rate of deterioration as uncertain. A wide variety of PMSs are used, hut unfortunately either these systems do not use a formal-ized procedure to determine the pavement condition rating, or they use deterministic pavement performance prediction models, or they assign the pavement state transition proba-bilities on the basis of experience. The objective of the re-search was to develop a probabilistic network-level PMS on the basis of pavement performance prediction with use of the Markov process. Pavements with similar characteristics are grouped together to define the pavement families, and the prediction models are developed at a family level. The pave-ment condition index (PCI), ranging from 0 to 100, is di-vided into 10 equal states. The results from the Marko