Multiobjective optimization of asphalt pavement design and maintenance decisions based on sustainability principles and mechanistic-empirical pavement analysis

Highway pavement as an important component of transport infrastructure has significant impacts on economy, society, and environment. The management of highway pavement has been traditionally focused on economy. In this study, the impacts of management decisions are examined in three dimensions, including life-cycle cost (LCC), energy consumption, and greenhouse gas (GHG) emissions. Quantitative models to predict the three dimensions are developed from mechanistic-empirical pavement analysis results. Two decision variables, pavement thickness and threshold roughness level for pavement resurfacing, are found to be significant in affecting the three dimensions. These two variables are subsequently used as decision variables in multiobjective optimization. The ranges of decisions that result in minimum LCC, energy consumption, and GHG emissions are identified through multiobjective optimization. Although the analysis is illustrated in the context of pavement design and management in Hong Kong, the analysis techniques and procedures can be easily applied in other regions.