MIT study proposes greener approach to road maintenance
Researchers at Massachusetts Institute of Technology (MIT) in the USA have published a paper that proposes using ‘big data’ to identify specific sections of roads where improvements will have the greatest impact.
The paper in the Journal of Cleaner Production, written by researchers with the MIT Concrete Sustainability Hub (CSHub), is intended to reduce emissions across a road network.
CSHub researchers Arghavan Louhghalam and Mehdi Akbarian and faculty director Professor Franz-Josef Ulm studied over 5,000 lane-miles of Virginia’s interstate highway system.
“We found that the maintenance of just a few lane miles allows for significant performance improvement, along with lowered environmental impact, across the entire network,” said Louhghalam, the paper’s lead author. “Maintaining just 1.5% of the road network would lead to a reduction of 10% in greenhouse gas emissions statewide.”
CSHub models recreate the interaction between the wheel and pavement and allow researchers to observe the interplay with varying road conditions, pavement properties, traffic loads, and climatic conditions.
The method presented in the paper integrates those pavement vehicle interaction (PVI) models into several databases used by transportation agencies. A ranking algorithm allows local results to be scaled up and applied to state or national sustainability goals.
“The quantitative approach is less subjective than qualitative methods, and it’s easy to use,” Louhghalam said. “Decision-makers can take more factors into account and make smart choices that are economically and also environmentally optimal.”
The study quantified the impact of deflection-induced PVI (which refers to the stiffness of the pavement) and roughness-induced PVI (which refers to the unevenness of a road’s surface) on the excess fuel consumption of vehicles. Results showed deflection-induced PVI is a major contributor to excess fuel consumption for trucks, due to their higher weights, and roughness-induced PVI impacts are larger for passenger vehicles, mainly due to higher traffic volume.
The researchers compared their approach to other methods, such as random maintenance, choosing roads based on traffic volume, and the current common practice of selecting roads based on their International Roughness Index values. The data-driven method allows for a maximum reduction in CO2 emissions with minimum lane-mile road maintenance, they found.
“There is huge potential to improve efficiency and lower environmental impact through better design and maintenance of roadways,” said Ulm. “This work supports one of our major goals, which is to aid decision makers, including engineers and politicians, in thinking about infrastructure as part of the solution in a carbon-constrained environment.”
The MIT Concrete Sustainability Hub is supported by the Portland Cement Association and the Ready Mixed Concrete Research & Education Foundation.
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This article was published on 27 Jul 2016 (last updated on 27 Jul 2016).