Multi-Constraint Predictive Control System with Auxiliary Emergency Controllers for Autonomous Vehicles

This paper introduces a multi-constraint predictive control algorithm along with a safety layer to guarantee path tracking and object avoidance in emergency situations. A controller switching mechanism is designed which switches the controller between a main and an emergency controller. As the main controller, a nonlinear multi-constraint model predictive controller (MPC) is designed. 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 of the vehicle. In order to respond as quickly as possible, emergency braking and maneuver systems are added which could be triggered separately per different situations. Two different emergency scenarios have been implemented in CARLA simulator and Python environment to evaluate the proposed method.