DEVELOPMENT OF A MULTI-OBJECTIVE OPTIMIZATION FRAMEWORK FOR QUANTIFYING BENEFITS OF ASPHALT PAVEMENT PRESERVATION TREATMENTS

Abstract

The optimized selection of a feasible pavement preservation treatment alternative depends not only on the distresses it aims to prevent but also on the accurate quantification of its potential service life extension and associated economic and environmental benefits. However, most existing evaluation frameworks focus primarily on performance aspects, often neglecting the environmental and user-phase effects. They also fail to account for the uncertainty inherent in field performance, traffic growth, and material behavior. To address these limitations, this dissertation develops an integrated, probabilistic framework to quantify and compare the performance, economic, and environmental benefits of asphalt pavement preservation treatments using stochastic multi-objective analysis. The proposed methodology links empirical deterioration modeling, life-cycle cost assessment, and emission quantification to produce data driven insights for agency decision-making.

The methodological framework combines NCAT/MnRoad Pavement Preservation Group data derived field performance data with longitudinal data procedures, HDM-4 fuel consumption relationships and MOVES5-based emission factors to model treatment specific life extension, equivalent uniform annual cost (EUAC), and equivalent uniform annual environmental impact (EUAI). Uncertainty in key parameters, such as traffic characteristics, cost, discount rate, and deterioration slope, is propagated using Monte Carlo simulation. Kernel Density Estimation (KDE) is utilized to transform discrete simulation outputs into continuous probability surfaces, while Pareto front and probabilistic dominance-based analyses identify tradeoff regions and treatment efficiency scores. This probabilistic structure enables evaluation not only of expected outcomes but also of their relative likelihoods and probability.

The resulting framework includes an interactive tool that allows planners to compute the main economic, environmental and performance benefits of preservation treatments under uncertainty. This framework also provides agencies with an empirical measure of dominance, probability and risk-adjusted performance measures, as an extra step after benefit quantification. Ultimately, the methodology is demonstrated through case studies comparing different treatments, offering actionable insights into their economic, environmental, and performance effectiveness. Future studies might evaluate the implementation of these benefits throughout the entire life cycle of the pavement structure.