Fuel Efficient High-Density Platooning Using Future Conditions Prediction

A promising application of cooperative driving is high-density platooning, which main goal to reduce fuel consumption by with inter-vehicle distances below ten meters. The prediction factors influencing the platoon capability drive such derived safe distances, drives potential saving. Our aim study influence prediction, especially horizon, on achieved saving as a function different maneuver parameters. contributions this paper are: introducing concept reference distribute effort maneuvering in truck platooning; linking compensation time, that time during will counterbalance benefiting from reduced air drag; presenting an optimization method for maximizing depending some predictive quality service To model and duration maneuvers, we use lasso regressions data obtained simulation. We then these regression models our framework, based particle swarm optimization. show benefit magnitude order horizon required five-truck minimum hundred seconds.