Integration of Model Predictive Control for autonomous racing

Autonomous driving is one of the technologies that could impact significantly society in the next decades. While various advanced driver assistance systems (ADAS) have already been introduced in commercial passenger vehicles, the technology for fully self- driving cars is not yet ready. The Indy Autonomous Challenge is a competition between universities and research centers, born to advance the technology in this field by com- peting in autonomous racecar events. The IAC seeks to increase public awareness of the transformational impact that automation can have on society and solve edge-case scenarios unlikely to happen in an urban scenario but with the need of be addressed to ensure safety. The focus of this thesis is on the integration of the controller, a model predictive control (MPC), used in two of these challenges. This class of control, based on a constrained op- timal control scheme, is usually used to cope with challenging situations and was suitable for handling an autonomous car at high speeds.