Stochastic Approach for Design of Flexible Pavement

ABSTRACT A stochastic approach has been developed to estimate the required design thickness for flexible pavement using typical design factors and new additional stochastic-based factors. The stochastic design approach incorporates new design factors that can better control the long-term performance of flexible pavement. The new stochastic design factors are mainly the initial and terminal transition probabilities. These two transition probabilities, representing initial and terminal deterioration rates, have been shown to be essential in controlling the long-term performance of flexible pavement. The long-term performance of pavement has been traditionally defined using a pavement performance curve. Pavement performance curves can be stochastically developed using mainly the initial and terminal transition probabilities. The discrete-time Markov model typically applies the transition probabilities (transition matrix) along with the initial state probabilities to predict the future pavement distress ratings over an analysis period. The predicted pavement distress ratings are used to construct the corresponding performance curve. The transition probabilities can be estimated from a “back-calculation” of the Markov model using state probabilities obtained from two consecutive surveys of pavement distress. Sample empirical models have been developed for the case of low volume roads to predict the initial and terminal transition probabilities from relevant pavement design factors and to predict the required pavement design thickness based on the initial and terminal transition probabilities. In addition, two long-term performance indicators, namely the area under the performance curve and the corresponding average distress rating, have been used in developing sample empirical design models considering the case of low volume roads.