Environmentally Preferable Pavement Management Systems

Abstract

Many departments of transportation (DOTs) rely on pavement management systems (PMSs) to plan maintenance operations by identifying schedules that maximize overall network condition subject to cost constraints. PMSs do not typically incorporate environmental considerations, despite being ideally situated in the decision-making process to balance performance and environmental goals. This work proposes an expanded PMS framework to incorporate greenhouse gas (GHG) emissions by utilizing a multiobjective genetic algorithm (GA) validated against past DOT interstate maintenance practices in Virginia. In practice, the DOT relies heavily on corrective maintenance, a treatment of intermediate intensity, resulting in suboptimal use of financial resources and emissions of GHG. The model suggests that alternative maintenance plans exist that yield higher network pavement performance with both lower costs and GHG emissions over the same time period. For the validation area considered, an optimized management plan could achieve the same network pavement performance with 60% of the cost and 50% of the GHG emissions. The framework, as presented, uses current DOT deterioration models and cost estimates to demonstrate the feasibility of its direct integration with existing PMSs.