Using Markov method to predict pavement condition and fund allocation at the network level, relying on the safety

In this paper، the necessity of using the network-level pavement management in the roads across the country has been accomplished besides the Markov probabilistic model studying to predict the pavement. The qualitative and quantitative criterion to evaluate the pavement is PCI. A network of 1،000 kilometers was studied، and future status was predicted by the Markov probabilistic model. The best matrices of transition probabilities were obtained by Gaussian Elimination method and solving the equation of Ax=B and applying Markov model assumptions. The error may range between 4. 8-39. 3% (on average 25%) and the graph of outgoing data was shown with suitable approximation and coefficient correlation of R2=0. 86. The Markov method for determination of transition probability matrix was explained in this paper with the help of programming in the MATLAB environment، comprehensively and step by step.