Predictive ADAS: A predictive trajectory guidance scheme for advanced driver assistance in public traffic

In recent years, semi-autonomous vehicle control solutions have been aggressively developed in the form of various advanced driver assistance systems. It is expected that these developments will facilitate the eventual customer acceptance of fully autonomous vehicles. In this paper, we present a configuration of a nonlinear model predictive control scheme for predictive driver assistance. The human driver´s steering and acceleration inputs to the vehicle are first interpreted into the driver-desired vehicle responses. These are then configured to be tracked by a coordination of the predictive and the lower level control systems as long as safe motion is predicted for these driver inputs. As soon as a violation of motion constraints is predicted from the driver inputs, the control scheme augments the driver inputs with active steering, brake and/or engine interventions so that the constraints of the vehicle dynamics, road boundaries and dynamic objects are respected. The performance of this proposed scheme is illustrated and discussed considering closed-loop-simulations of some typical driving events in public traffic.