M.S. (Master of Science)
Department of Electrical Engineering
In the last few years, several research groups and companies have worked on developing autonomous vehicles. Among the first automation layers, the safety layer plays a significant role in this field. However, considering safety should not diminish the importance of the efficiency of the vehicle in terms of path tracking with the desired speed. This thesis introduces a multi-constraint predictive control algorithm along with a safety layer to guarantee object avoidance in emergency situations. First, there is a quick review of autonomous cars and their functionalities. In the following, a controller switching mechanism is proposed and designed. It switches the controller between the main controller and emergency controller. As the main controller, a nonlinear multi-constraint model predictive control (MPC) is designed and implemented based on a kinematic model of the car and the polynomial fitting method. The MPC algorithm is compared with Stanley and PID methods in terms of their efficiency to validate the MPC as the main controller. However, in unexpected situations, the high computational time of the planner and MPC modules threatens the safety concerns. In order to respond as quickly as possible, an emergency braking system incorporates the main controller. If the controller predicts that the emergency braking system is no longer useful via calculating stopping distance, another emergency control system will be triggered to keep away from possible collisions by maneuvering properly. Two different emergency scenarios have been implemented in CARLA simulator and Python environment to evaluate the proposed method. The thesis concludes that the proposed controller is a reliable mechanism to ensure safety in terms of object avoidance and also, it is able to follow the desired path with a negligible tracking error and smooth steering even in relatively high speeds.
Partovi Ebrahimpour, Farhad, "A Multi-Constraint Predictive Control System with Auxiliary Emergency Controllerfor Autonomous Vehicles" (2020). Graduate Research Theses & Dissertations. 7530.
Northern Illinois University
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