Self-driving Cars

About

Autonomous driving represents a transformative shift in modern transportation, combining cutting-edge advancements in machine learning, robotics, and real-time systems engineering. By enabling vehicles to navigate and operate independently, this technology aims to enhance safety, reduce traffic congestion, and revolutionize mobility solutions. Central to autonomous driving is the development of algorithms and systems that allow vehicles to perceive their surroundings, interpret data from sensors, and make intelligent decisions. The field draws on interdisciplinary expertise, providing an exciting challenge for researchers and developers looking to shape the future of transportation.

The course "Self-driving Cars" introduces basic concepts of self-driving cars using Autoware Mini, the software developed in University of Tartu Autonomous Driving Lab, as an example. The students implement core components of modular autonomy stack from scratch in the Python programming language. They will test their software in virtual Tartu simulation, which is a decimeter-level digital twin of the real city. The course ends with a demo ride in a self-driving Lexus vehicle that is using the very same Autoware Mini software they learned about in the course. The target group of the course is MSc and PhD students interested in furthering their knowledge about autonomous driving systems

Course leader

Tambet Matiisen, Autonomous Driving Lab Technology Lead, University of Tartu

Target group

MSc/PhD

Course aim

Upon completion of the course, a student will be able to:

1. Understand the software implemented in Robot Operating System (ROS)
2. Describe the modular architecture of the autonomous driving systems
3. Implement core modules for modular architecture: perception, planning, and control
4. Explain different approaches to the planning and control of autonomous vehicles
5. Have an overview of possible validation and testing methods for autonomous driving

Fee info