IET Intelligent Transport Systems · 2021 · 25 citations · 21 references
ComputingAutomotive EngineeringAutonomous SystemsAutonomous VehiclesPredictive AnalyticsTransportationAutomotive SensorsIntelligent Transportation SystemsPredictive ModelingSustainable TransportationVehicle Control SystemsVehicle PerceptionEco-driving StrategyEnergy-efficient DrivingFuel ConsumptionFuel Consumption ReductionPrediction For Autonomous DrivingSpeedSpeed Profile OptimizationVehicle Speed Profile Optimization
Abstract Eco‐driving assistance systems incorporating predictive or feedforward information are a promising technique to increase energy‐efficiency and reduce 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 ‐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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