A Model Predictive Approach to Emergency Maneuvers in Critical Traffic Situations

Abstract

Advanced Driver Assistance Systems (ADAS) that support drivers during emergency maneuvers have been considered in research and development projects before. It is commonplace that the two problems trajectory planning and vehicle control are solved in two different steps. The paper at hand proposes a real time capable method that solves the planning and control problem in one step. This is achieved by using a scheme similar to model predictive control combined with an environmental model to avoid the necessity of a precalculated reference signal, i.e. a trajectory. The real time capability is achieved by a rough discretization of the inputs, which yields the possibility to predict the plant's state trajectory for all possible combinations of discretized input values. Compared to an iterative minimization the computational burden is lower and can be determined deterministically. This contribution contains collision avoidance maneuvers in different traffic situations evaluated in simulation and a fixed base driving simulator.