Connected and automated vehicles (CAV) are marketed for their increased safety, driving
comfort, and time saving potential. With much easier access to information, increased …

Autonomous driving technology pledges safety, convenience, and energy efficiency. Its
challenges include the unknown intentions of other road users: communication between …

Model predictive control (MPC) has demonstrated exceptional success for the high-
performance control of complex systems. The conceptual simplicity of MPC as well as its …

Efficient operation technique has always been one of the common goals for researches both
in automobile industrial and academic areas. With the great progress of automobile …

The performance and practicality of predictive energy management in hybrid electric
vehicles (HEVs) are highly dependent on the forecast of future vehicular velocities, both in …

In the past ten years many Stochastic Model Predictive Control (SMPC) algorithms have
been developed for systems subject to stochastic disturbances and model uncertainties …

This paper develops an approach for driver-aware vehicle control based on stochastic
model predictive control with learning (SMPCL). The framework combines the on-board …

This paper proposes a stochastic model predictive control (MPC) approach to optimize the
fuel consumption in a vehicle following context. The practical solution of that problem …

Abstract Model predictive control (MPC) can effectively solve online optimization issues,
even with various constraints, when maintained at high robustness. Considering the energy …

Driving style, road geometry, and traffic conditions have a significant impact on vehicles' fuel
economy. In general, drivers are not aware of the optimal velocity profile for a given route …