Various techniques, either statistical or stochastic, have been applied to predict highway structure conditions. Researchers found the stochastic approach more appropriate than the statistical approach in highway project selections using dynamic optimisation techniques. However, it was also found that condition predictions using the Markov chain could be biased, depending on the values of transition probabilities. In an attempt to minimise the bias in Markov chain predictions, the Monte Carlo simulation technique was applied in the present study in combination with transition probabilities obtained from Markov chain approaches. This study showed that the simulation method could produce more realistic predictions than the analytical Markov chain approach. The Monte Carlo simulation method is described and compared with the analytical Markov chain method. An application example is presented to show the mechanism of the Monte Carlo simulation method and to compare the results of the simulation and Markov chain predictions. (Author/publisher)
Abstract