Autor:

Henry Narits

Self-driving Cars

On-site in Tartu 28 July - 8 August 2025

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.

Information about the course

Focus area:	Self-driving Cars	Coordinating unit:
Study Field:		Course Leader:
Format:	Summer Course	Location:	University of Tartu Delta Centre (Narva mnt 18, Tartu)
Course dates:	28 July - 8 August 2025	Language:	English
ECTS:		Study group:	MSc/PhD

Lecturers

Tambet Matiisen	Dmytro Zabolotnii	Karl-Johan Pilve	Edgar Sepp
Autonomous Driving Lab technology lead Lectures	PhD student Practical sessions	Autonomous Driving Lab engineer Practical sessions	Autonomous Driving Lab engineer Live Demos

Application deadline: 30 April 2025

Application period: 1 April - 30 April 2025
NB! All of the applicants are required to pay a non-refundable application fee of EUR 25. Your application will only be processed after the University has received the fee. The application fee is required to facilitate the admissions process and will not be refunded, regardless of the admission result.

Course fee:

Includes:
Study materials
10 days of academic work with lecturers
Certificate of completion (? ECTS)
5 cultural events in the evenings

NB! Transportation and accommodation costs are not included. The course fee does not cover participant's lunch during the summer school.

NB! This is a preliminary programme. The final schedule will be sent to the participants two weeks before the course starts.

All lectures, practices and independent work will take place in computer class 2006 in Delta building. There are 25 computers available with Ubuntu and ROS pre-installed.

Sunday, 27 July
Arrival

Day 1: Monday, 28 July
Introduction to ROS
2h lecture
2h guided practice
4h independent work

The students learn the main concepts in ROS: nodes, topics, messages.
Assignment 1: implement simple publisher and subscriber.

Day 2: Tuesday, 29 July
Localization
2h lecture
2h guided practice
4h independent work

The students learn how the car determines its position on the map.
Assignment 2: implement GNSS localizer.

Day 3: Wednesday, 30 July
Control
2h lecture
2h guided practice
4h independent work

The students learn how the car follows a given trajectory by producing longitudinal and latitudinal commands.
Assignment 3: implement pure pursuit controller

Day 4: Thursday, 31 July
Global planner
2h lecture
2h guided practice
4h independent work

The students learn how the car plans a path from point A to point B.
Assignment 4: implement global planner using Lanelet2 library.

Day 5: Friday, 1 August
Catchup day
4h tutors available
4h independent work

Saturday, 2 August: free day
Sunday, 3 August: free day

Day 6: Monday, 4 August
Obstacle detection
2h lecture
2h guided practice
4h independent work

The students learn how obstacle detection works with different sensors.
Assignment 5: implement lidar-based object detector.

Day 7: Tuesday, 5 August
Local planner
2h lecture
2h guided practice
4h independent work

The students learn how the car reacts to the obstacles.
Assignment 6: implement rule-based local planner.

Day 8: Wednesday, 6 August
Traffic light detection
2h lecture
2h guided practice
4h independent work

The students learn how the car detects the traffic lights and reacts to them.
Assignment 7: implement camera-based traffic light detector

Day 9: Thursday, 7 August
Validation & testing
2h lecture
2h guided practice
4h independent work

The students learn about different ways to validate and test self-driving cars.
Assignment 8: implement test scenario in Carla simulation.

Day 10: Friday, 8 August
Demo day
The students experience an autonomous ride around Tartu in the self-driving Lexus vehicle. The students will be divided into groups of 2-3 people. Each demo ride lasts 40 minutes. They can use the rest of the day to catch up with final assignment revisions.

Saturday, 9 August/Sunday, 10 August
Departure

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

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

The students should submit all 8 homework assignments and these will be reviewed by the teaching assistants. Feedback is given and revisions are expected before students can proceed with further assignments.

Upon completing the course, the student will receive a certificate of participation with grading (pass/fail).

Which previous knowledge is required?

Familiarity with Linux command line
Basic understanding of git version control workflow
Good command of Python programming language

Recommended:

Prior exposure to Robot Operating System (ROS)
Prior experience with machine learning

Entry requirements:

Online application form (application period April 1 - April 30 2025)
Motivation letter (up to 1 page) that demonstrates the applicant’s motivation to participate, his/her expectations about the programme, how participation in the summer programme relates to his/her studies and interests, and how the applicant plans to use the gained experience and knowledge in the future.
Transcript of academic records
Copy of passport

PS: Only complete applications including all annexes submitted by the deadline will be considered for selection.

Housing and transportation

Are you wondering how to get to Tartu and where to stay? Tartu is the second biggest city in Estonia and is, therefore, quite easily reachable. Tartu is famous for its sustainable transportation methods which make moving around the city very quick, cheap and convenient. In the City of Education there are many options of accommodation. You'll get to choose between a cheap stay at the dormitory with other international students or pick a fancier option in a hotel or apartment.

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Social programme

While the academic course is broaden your knowledge and learning skills, the cultural programme offers a range of fun and engaging cultural activities, introducing you to Estonia and the opportunity to interact and network with other participants in a lively environment. Students will have the opportunity to enjoy a range of day trips and events offered through the programmes and their experience in Tartu! Please scroll down to see the information about the social programme events, fees, refund policy, etc.

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Self-driving Cars

Information about the course

Lecturers

Application deadline: 30 April 2025

Course fee: