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
2019-02-01
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
connected autonomous vehicle , vehicle‐to‐vehicle communication function , preceding vehicles , vehicle‐to‐infrastructure communication function , fuel efficiency , fuel economy , car‐following scenarios , longitudinal dynamic model , urban driving condition , mobile robots , speed trajectory , model predictive control‐based eco‐driving strategy , predictive control , highway driving condition , fuel‐saving benefits , robot dynamics , CAV , fuel consumption optimisation , fuel‐consumption model , vehicle dynamics , trajectory control , road vehicles , velocity control
Model-based predictive motion cueing strategy for vehicle driving simulators
Tema Archiv | 2009
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