ABSTRACT
Pavement skid resistance has a significant role in traffic accidents, especially in wet conditions. Pavement surface characteristics are affected by both materials and mixture properties. This study explored a ‘novel’ approach to pavement friction analysis in modelling and relating pavement friction to materials and mixture properties. Structural equation modelling (SEM) takes advantage of the correlation/collinearity among one or more predictor variables in generating predictive models for a response variable. While SEM has been used in a variety of fields, in pavement friction the use of such statistic approach has not been explored, and thus it is a ‘novel approach’ to pavement friction modelling in relation to the past modelling efforts. Thus, in this study the selection of SEM modelling is advantageous so as to, (i) capture the interdependency of mixture and material variables in hot mix asphalts; and (ii) address the high number of predictor variables in relation to the number of observations (small sample size of observations). While data from Maryland were used in this analysis the methodology can be used elsewhere reflecting similar materials and pavement conditions.