Planning and Control of Drift Maneuvers with the Berkeley Autonomous Race Car

In competitive sporting events, drivers operate vehicles at the limits of handling, with near full rear tire saturation. Expert drivers intentionally drift their vehicles around corners to turn the vehicle quickly. These drivers operate their vehicles in a way that is contrary to the way safety system in automotive electronic control units are designed. By investigating and understanding the physics and operating principles of these maneuvers, it may be possible to enhance safety features in automotive control systems for collision avoidance, as well as enable sports cars to autonomously perform drift within the context of racing. The main focus of this dissertation is on planning and control of drift maneuvers, in particular, steady state drift, drift parking, and drift cornering. Secondly, with the growth of research and engineering in the domain of autonomous vehicles, the dissertation also focuses on the design and development of a robotic platform called the Berkeley Autonomous Race Car (BARC). The platform is based on a 1/10-scale remote control vehicle equipped with computing hardware and a suite of sensors that make it suitable for research and instruction. The project aims to provide a low-cost, open-source testbed option for researchers and instructors interested in autonomous vehicles. The methods and algorithms provided in the first part of the dissertation are experimentally validated on the BARC platform