Autonomy in Vehicles
This graduate course provides an introduction to the growing field of automated driving vehicles and their sub-systems with a focus on concepts, architectures, problems and solution approaches. Historical developments in automotive control and mechatronics that have led to the development of autonomous road vehicles are presented.
Basic tire modeling, vehicle dynamic modeling and path tracking are covered as autonomous driving is the highest level of vehicle dynamics control where the driver is replaced by a control system. Current research projects,including the Columbus Smart Cities program, provide relevant case studies in autonomous advancements.
A basic profiency in control systems and a working knowledge of Matlab and Simulink is required.
Following this course students should be able to:
- Understand the structure and system architecture of autonomous vehicles
- Understand the complexities of system integration with multiple sensors and mobile entitities in structured and unstructured environments
- Use hybrid system control techniques for designing an autonomous system
- Map data communication within the vehicle and fusion of data from multiple sensors
- Understand the concepts of modeling for driver intent
- Understand safety issues and verification issues
Engineering and Mechanical Engineering. He leads the Automated Driving Lab at CAR.
Güvenç received a B.S. in mechanical engineering from Bogaziçi University, Istanbul, Turkey, an M.S. in mechanical engineering from Clemson University, and his Ph.D. in mechanical engineering from The Ohio State University.
He served as chair of the mechanical engineering department at Istanbul Technical University and was a professor of mechanical engineering and director of the Mekar Labs and the European Union Framework six funded Automotive Control and Mechatronics Research Center of Excellence.