In this study, an eco-driving strategy is proposed to enhance the fuel efficiency of the connected autonomous vehicle (CAV) in car-following scenarios. First, the longitudinal dynamic model and fuel-consumption model of the vehicle are established. The speed trajectory of the preceding vehicles is obtained via vehicle-to-vehicle/vehicle-to-infrastructure communication function of CAVs, which is used as the reference of the following vehicles. Second, a model predictive controller is presented to optimise fuel consumption of the following vehicle. Finally, simulations in urban and highway driving conditions demonstrate that the proposed controller enables effective tracking of the preceding vehicle in an energy-efficient way. Comparisons between the second and the third following vehicles verify the fuel-saving benefits of the proposed method.
Model predictive control-based eco-driving strategy for CAV
IET Intelligent Transport Systems ; 13 , 2 ; 323-329
30.10.2018
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
vehicle dynamics , speed trajectory , velocity control , fuel-consumption model , urban driving condition , road vehicles , highway driving condition , CAV , vehicle-to-vehicle communication function , connected autonomous vehicle , preceding vehicles , fuel efficiency , fuel economy , robot dynamics , mobile robots , trajectory control , longitudinal dynamic model , fuel-saving benefits , predictive control , fuel consumption optimisation , vehicle-to-infrastructure communication function , car-following scenarios , model predictive control-based eco-driving strategy
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