Assessment of pavement degradation through statistical analysis model A case study of the Department of Transportation (DOT) of Iowa, USA

Abstract

Transportation network, especially highways, is considered a national or international asset, and by proper maintenance system, public and private organizations can prioritize the budgeting of repair and reconstruction. The problem is to have a reliable and practical model creating a solid understanding of the pavement degradation condition by inexpensive measurable parameters for municipalities. This study focuses on the road pavement condition, particularly the statistical evaluation of the processes of degradation involved in various road sections. Quantitative statistical analysis of a sample taken from the Iowa Department of Transportation (DOT) in the United States provides a better understanding of the needs in pavement maintenance processes. In addition, it can identify the critical factors of pavement maintenance. Through a case study, it is shown that organizations can develop a solid based statistical decision-making model using basic and low-priced parameters. The model has two approaches, with and without pavement type (used by creating several dummy variables to include each pavement type as independent variables). This study will positively enhance the pavement degradation prediction through a statistical analysis model and a case study of the Department of Transportation (DOT) of Iowa, USA. These details include explanatory models, bivariate correlation, principal component analysis, hierarchical and non-hierarchical clustering, creating dummy variables, and developing multivariate regression models.