Model Predictive Controller Design for Lateral Behavior in Real Traffic Flow

In this paper a model-based predictive controller has been designed to control the lateral vehicle dynamics. Assuming that the road specifications are known, the main goal is to obtain a control input in order to drive along a desired path using a model-based predictive controller under the consideration of the vehicle dynamics constrains and road geometric specifications. Moreover, the curvature of the path is assumed to be specific and determinable. Steering wheel angle is the control input. Optimization problem of the designed controller is solved based on knowledge about vehicle constrains such as magnitude and rate of the steering wheel angle. These constraints are specified based on characteristics of actual vehicle to assure the safety of passengers when control system is active. In order to model the vehicle dynamics, bicycle model has been used with the assumption that considering range of the vehicle and road parameters the dynamics of the tires is in the linear part of their behavior. Using the model-base predictive controller, control input is obtained and applied to the vehicle in order to reduce the look-ahead vertical distance from the desired path to zero. The longitudinal velocity of the vehicle has been assumed to be constant. The robustness of the design controller has been investigated against environmental disturbances in dry and slippery roads. The comparison between the results of the presented control system and previous works shows that proposed method has a better performance and can increase safety of the vehicle and passengers.