Abstract
Policy-makers are investigating ways to reduce greenhouse gas emissions of the transportation sector. Many government agencies have studied the effects of pavement type and characteristics on fuel consumption. Such models, valid for a particular set of simulation conditions, suggest that rigid pavements perform better than flexible pavements. However, it is unclear how this type of model can be applied at the scale of a realistic road network. This paper proposes a statistical approach to assess the relative importance of pavement type and characteristics on fuel consumption of heavy vehicle traffic by considering the specificities of meteorological conditions, heavy vehicles, and driver behaviours. A case study in Canada showed that the potential advantage of using rigid pavements was offset by cold climate effects and the consideration of a realistic statistical payload distribution. Road roughness accounted on average for 1.1% of total fuel consumption, with an increased value of 1.9% in January.
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