Program for Sustainable Pavement Engineering and Research

About the research

The limited availability of high-quality aggregates and rising transportation costs present ongoing challenges for pavement construction and maintenance in Minnesota. To address this, local agencies are increasingly exploring the use of lower-quality, locally available materials in pavement foundation layers. This study evaluates the performance and cost-effectiveness of aggregate base and subbase layers with varying material qualities and thicknesses to develop optimized pavement designs. A comprehensive aggregate index property (AIP) database is updated to include more than 1,100 aggregate sources and used to develop predictive models for resilient modulus and shear strength using both multiple linear regression analyses and artificial neural networks. Aggregates are categorized into low-, medium-, and high-quality categories and incorporated into MnPAVE simulations under a range of traffic levels, asphalt layer thicknesses, subgrade stiffnesses, and climatic conditions. In parallel, cost-benefit analyses based on historical MnDOT bid data are conducted to identify optimal-quality thickness combinations. A flowchart-based design framework is also introduced to iteratively determine the required aggregate base and subbase thicknesses corresponding to aggregate quality levels that meet fatigue and rutting life targets. The findings offer practical guidance for the efficient use of regional materials, supporting the development of resilient and economically optimized pavement infrastructure across Minnesota.