UNCERTAINTIES OF ASPHALT LAYER THICKNESS DETERMINATION IN FLEXIBLE PAVEMENTS INFLUENCE DIAGRAM APPROACH

The thickness of pavement layers is an important parameter used in Pav ement Management Systems (PMS). Thickness data are used for pavement c ondition assessment, performance predictions, selection of maintenance strategies and rehabilitation treatments, basic quality assessment, a nd as input to overlap thickness design. Pavement thickness is usually determined from direct testing such core samples, nondestructive test ing such as radar, or historical records such as pavements network dat abase. This paper proposes the use of Bayesian Influence Diagrams as a tool in providing a probabilistic model for thickness determination p rocedure in flexible pavements. The Bayesian Influence Diagram Model i s presented as a framework for addressing uncertainties involved in ca pturing quantitative and qualitative information in the asphalt layer thickness determination procedures. The model is also used to perform value of information analysis in the determination of pavement layer t hickness. The Influence Diagram representation facilitates the assessm ent of coherent prior distributions and makes it easier for knowledge engineers and other decision makers to express and understand more gen eral kinds of dependency and independency assumptions.