FUEL EFFICIENT HIGH - DENSITY PLATOONING USING FUTURE CONDITIONS PREDICTION USING MACHINE LEARNING
Keywords:
Machine Learning, HDPLAbstract
A promising application of cooperative driving is high density platooning, which maingoal is to reduce fuel consumption by driving with inter-vehicle distances below ten meters. The prediction of factors influencing the platoon capability to drive with such inter-vehicle distances the derived safe inter-vehicle distances, drives the potential fuel saving. Our aim is to study the influence of the prediction, especially the prediction horizon, on the achieved fuel saving as a function of different maneuver parameters.
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Al Alam, A. Gattami, and K. H. Johansson, “An experimental study on the fuel reduction potential of heavy-duty vehicle platooning,” in 13th Int. IEEE Conf. Intel. Transp. Syst. (ITSC), 2010. IEEE, 2010, pp. 306–311.
S. Tsugawa, S. Jeschke, and S. E. Shladover, “A review of truck platooning projects for energy savings,” IEEE Trans. Intell. Veh., vol. 1, no. 1, pp. 68–77, Mar. 2016.
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