Modeling Pavement Distress Index
Investigator:	Ghassan Abu-Lebdeh, Department of Civil and Environmental Engineering

This research is focused on the exploration of various of statistical and neural-based modeling techniques to capture the behavior of pavement distress over time and the selection of the best- fitting model. Finding such model is critical since the ability to reliably project pavement conditions has significant implications to allocation of maintenance resources. Currently, univariate models are used but in most cases fail to reliably project future pavement conditions.