Model Predictive Control for Self Driving Cars: A Case Study Using the Simulator CARLA within a ROS Framework

Over the past few years, autonomous driving vehicles have been growing rapidly due to advances in technology, namely computing power and improvements in sensors and actuators. This paper presents a research work that addresses the autonomous driving problem. More specifically, a Model Predictive Control (MPC) is implemented for the lateral and longitudinal control of an autonomous vehicle. The main goal of this study is to validate the robustness, performance and safety of the developed algorithm in simulation, using the widely known self-driving simulator CARLA together with the Robot Operating System (ROS) framework. The implemented method provides a realistic simulation and contributes to the area of software development for driving cars offering passengers a more comfortable and safer control of the vehicle.