Overview
Autonomy, in the context of autonomous vehicles, is the ability of a vehicle to operate without the intervention of a human operator. Such vehicles constitute a very broad spectrum of shapes and sizes including, for instance, vacuum cleaning robots, automated guided vehicles (AGVs) operating on factory floors and warehouses, and robot taxis etc.
The objective of the course is to give students knowledge in the area of autonomous vehicles, by participating in an autonomous-vehicles project. This can either be an applied project in the form of participation in an autonomous-vehicles competition, or a research project on an advanced sub-area of autonomous vehicles research.
Information about project types
The student is (in small teams, or independently) expected to work on the applied/research project agreed-upon with supervisor.
The projects can be of several types, for example:
1. The students can train a self-driving car to drive in simulation and participate in CARLA Autonomous Driving Challenge. For more details, including prizes, see CARLA project.
2. The students can take up participation in the yearly small-scale autonomous vehicles competition. In the competition, 1:10 scale vehicles equipped with vision sensing, compete in autonomous driving.
Read about the tasks and see videos of previous years on the competition webpage: https://courses.cs.ut.ee/t/DeltaXSelfDriving/
The DonkeyCar platform used in DeltaX Self-Driving competition in January 2022 and for other student projects.
3. The students can take up a research project in different areas of autonomous driving, such as behaviour modeling and prediction, road-user interaction, mapping etc. Also the same DonkeyCar 1:10 scale platfrom is available for projects beyond the competition, e.g. for developing and testing traffic sign or traffic light detection. Alternatively, one can work in simulation or on a static dataset without actually trying anything in the real world.
Deliverables
For projects based on participation in the toy car competition, and research projects, the assessment is based on an intermediate and final presentation, report, (and where applicable) demonstration and code.
Contact
Naveed Muhammad (naveed.muhammad@ut.ee)
Tambet Matiisen (tambet.matiisen@ut.ee)
Ardi Tampuu (ardi.tampuu@ut.ee)