Airport Pavement Performance Estimation Based on Transition Probabilities in Markov Chain

Abstract:

The logistic regression equation was used to establish regression relationship among continuous variables such as thickness, traffic level, pavement age, categorical variables such as maintenance grade, climate sector, pavement structure types and the Markov probability prediction. Some airports’ actual measurement pavement condition index (PCI) data were used as data source in the parameter estimation and significance test of the model. The parameter calibration method of Markov probability prediction model, and the accuracy of the predictions were improved. The scope of the application of model was expanded and the problems of insufficient observation data and unstable parameter estimation using the traditional forecasting model were resolved.

Key words:Markov process; pavement performance; Logistic model; prediction; transition probabilities matrices