Real-time predictive eco-driving assistance considering road geometry and long-range radar measurements

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Abstract

Eco-driving assistance systems incorporating predictive or feedforward information are a promising technique to increase energy-efficiency and reduce (Formula presented.) emissions from road transportation. This work gives details of such a system that was recently developed by the authors, which uses real-time data from GPS and automotive radar to perform a predictive optimisation of a vehicle's speed profile and coaches a driver into fuel-saving and (Formula presented.) -reducing behaviour. A repeated-measures study carried out in a fixed-base driving simulator indicated an overall reduction in fuel consumption of 6.09%, which was significantly greater than improvements expected from reductions in average speed. Adjusted for average speed, fuel-efficiency improvements when using the system are similar to those observed in unassisted eco-driving, but with improvements in travel time in motorway situations. Finally, an on-road prototype is described in which the optimisation is solved using data from vehicle sensors, successfully demonstrating that real-time implementation of the system is feasible.

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Fleming, J., Yan, X., Allison, C., Stanton, N., & Lot, R. (2021). Real-time predictive eco-driving assistance considering road geometry and long-range radar measurements. IET Intelligent Transport Systems, 15(4), 573–583. https://doi.org/10.1049/itr2.12047

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