Ecodriving Potentiality Assessment of Road Infrastructures According to the Adequacy Between Infrastructure Slopes and Speed Limits

The energy associated with the use of the road infrastructure exceeds in a few years the energy needed for its construction. The link between infrastructure and energy use has not been, however, studied in depth, particularly as the legitimate transport societal expectations are related to efficiency and safety. However, reducing the energy use can be considered by working out minor optimizations of the road infrastructure itself. This is a major challenge in a context of overall decrease of resources and increasing pressure on the environment. Experimental work is carried out here to develop one of these optimizations by improving the eco-driving potential of roads. It is based on the adequacy between vehicle dynamics, the road longitudinal profile and the speed sectioning of the infrastructure. This sectioning corresponds to the succession of speed limitations (road signs, roundabouts, intersections, etc). It may allow drivers to eco-drive or not, depending on dynamics, slopes, and secondary parameters such as driver reaction time or distance of visibility. Optimal speed sectioning aims to limit the mechanical braking needed by potential energy reduction, due to slopes, which can be encountered simultaneously with the needed kinetic energy reduction. Evaluation has been made on actual road sections, while recording both vehicle dynamics, driver commands, road signs positions and road longitudinal profile. Results show that energy consumption of vehicles approaching a speed reduction sign can be reduced by moving the sign back about 700 meters, without penalizing the primary safety function. The associated gain, for this optimization, has been evaluated to 14 liters of fuel per day for one of the experimental sites, considering traffic data. Application of this method on a network could then lead to considerable energy savings by allowing eco-driving.


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  • Accession Number: 01632731
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 27 2017 9:25AM