Development of Roughness Prediction Models for Low-Volume Road Networks in Northeast Brazil

Abstract

Roughness evaluation is the most effective way to diagnose pavement condition for design and decision making. The index most commonly used worldwide to indirectly describe the surface condition of asphalt pavements is the international roughness index (IRI). However, few studies have tried to predict the pavement performance of low-volume roads (LVRs) on the basis of the IRI, especially for LVRs in tropical regions. In an attempt to remedy that lack of knowledge, this paper presents IRI-based prediction models developed for asphalt pavement LVR networks in northeast Brazil. The following independent variables were considered to affect the IRI: Thornthwaite's aridity index, which describes local climate; the modified structural number, representing pavement bearing capacity; and the cumulative number of equivalent single-axle loads, representing the traffic applied to the pavements. A multiple regression analysis was carried out, and the results showed that the IRI increases exponentially over time. The analysis of the model parameters confirmed their significance, and the R-square values were 0.87 and 0.94, respectively, for low-volume roads with hot asphalt mixes and bituminous surface treatments. The hot-mix asphalt model was compared with that of the Highway Development and Management Model and with other models developed in research also sponsored by the World Bank. Because of regional differences (especially climate and materials), the models proposed in this paper provide a better estimation of roughness progression in LVRs of the northeast of Brazil.