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 tracks
The student is (in small teams, or independently) expected to work on the applied/research project agreed-upon with supervisor.
The projects are divided into the following three tracks:
1. DeltaX-Track - The students can take up participation in small-scale autonomous vehicles competition. In the competition the vehicles, equipped with vision sensing, need to run autonomously on a race track.
2. Track-ADL - In this track the students will investigate software for real-world autonomous driving, and more specifically for the Autonomous-Driving-Lab Lexus vehicle. The track has sub-tracks to investigate different software including Autoware.Auto, Baidu Apollo, NVidia DriveWorks, Openpilot etc.
3. Track-Research - In this track students can take up a research project in any of the different areas in autonomous driving such as behaviour modeling and prediction, road-user interaction, mapping etc.
Deliverables
Depending on the chosen track, the assessment is based on an intermediate and final presentation, report, demonstration and code etc. Please refer to the individual pages of the three tracks for details about the respective deliverables.
Contact
Naveed Muhammad (naveed.muhammad@ut.ee)
Tambet Matiisen (tambet.matiisen@ut.ee)