2017 - Kurdistan - Flexible Pavement Crack Progression

Pavement management at a network level requires reliable accurate performance prediction models to help road agencies make useful complex decisions about highways maintenance and rehabilitating activities. The purpose of this paper is to report the approach adopted for model development and validation for heavy duty flexible pavements representing by seven rural freeways segments. Hierarchical generalized linear modelling approach has been applied to predict multilevel model to capture the effect of variations among time series data, among road sections and among highways with same duty pavements. The estimation of pavement cracking progression has been based on longitudinal dataset contain cracking data (reported as a percent of the affected area) as dependent variable and cumulative traffic loading, pavement strength and environmental conditions as independent variables. The study illustrates how panel data can be nested to predict the probability of crack progression to capture the effect of significant unobserved heterogeneity. The significance of relevant contributing factors in predicting crack progression were presented and elucidated.The validation results indicate that the model replicates the pavement behavior well, and that the inclusion of additional factors in addition to time is improving the model prediction.