Environmentally Preferable Pavement Management SystemsEPA Grant Number: FP917275
Title: Environmentally Preferable Pavement Management Systems
Investigators: Gosse, Conrad A
Institution: University of Virginia
EPA Project Officer: Zambrana, Jose
Project Period: August 1, 2011 through July 31, 2014
Project Amount: $126,000
RFA: STAR Graduate Fellowships (2011) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Fellowship - Science & Technology for Sustainability: Green Engineering/Building/Chemical Products & Processes/Materials Development
Many departments of transportation (DOTs) rely on pavement management systems (PMS) to plan maintenance operations by identifying schedules that maximize overall network condition subject to cost constraints. PMS do not typically incorporate environmental considerations, despite ideally being situated in the decision making process to balance performance and environmental goals. This work seeks to develop a practical and computationally tractable algorithm that will allow DOTs to add a third (environmental) dimension to the two implicit in current practice: cost and performance.
The large, multi-objective and discrete design space of pavement maintenance planning is well suited to genetic optimization. The first phase of the work applied a genetic algorithm and basic model of greenhouse gas (GHG) emissions from paving operations to the interstate highway pavements in a western district of Virginia as a proof of concept. This framework will be extended to incorporate a more comprehensive and geographically aware life-cycle estimation of roadway maintenance GHG emissions by employing the numerical power of computer graphics hardware to allow a fully stochastic treatment of uncertainty, allowing the selection of robustly optimal maintenance plans by DOTs.
Preliminary results showed a strong correspondence between economic expenditure and GHG emissions, making reducing environmental burden compatible with budget concerns. Optimized maintenance plans were found that both exceeded the performance of current DOT practice in the study area despite lower costs and reduced GHG emissions. Incorporating more specific sources of GHG emissions into the model, such as those of vehicles delayed by work zones, should allow the optimized results to further improve on current practice by exploiting site-specific information that would be impractical to consider without a framework such as that proposed here. Asphalt pavements also are highly recyclable, but only within the closed loops of individual construction firms. Stochastic simulation of this market will provide valuable insight into DOT contract bidding policies to encourage environmentally preferable outcomes.
Potential to Further Environmental / Human Health Protection
Maintenance of existing paved infrastructure impacts human and environmental health in numerous ways, including GHG emissions, airborne particulates, noise, emissions of volatile organic compounds and impacts to aquatic environments from both silt and potential surfactant leaching from emulsified asphalt coatings, to name a few. This research seeks to use computational optimization to minimize the amount of maintenance work performed in the first place, and to incorporate an explicitly environmental objective in maintenance planning to capture and minimize impacts that would otherwise be externalized in a traditional cost-based asset management program.