Thesis Work - Autonomous Drive & Active Safety Functions

About this opportunity - Background

In the organization Autonomous Drive & Advanced Driver Assistance Functions, we design and ensure the best behavior of our functions for our customers. We design, integrate, and verify the complete vehicle solution for autonomous cars and driver assist functions. We collaborate with some of the most innovative industry partners to reach our future visions of safety, convenience, and mobility. We develop functions such as Collision Avoidance, Automatic Parking, and Autonomous Driving. Our department will lead several master's thesis projects starting at the beginning of 2026, and we are now looking for students who are eager to help us explore new ideas in a state-of-the-art platform that will enable the delivery of autonomous drive features powered by Artificial Intelligence. With us, you will have a unique chance to make an impact in solving the “engineering problem of the century” of autonomous driving.

Scope of the thesis work

Master Thesis Projects – Spring 2026

1. Solution of Rear-Ended Collisions

Background: Rear-end collisions are common in Volvo’s accident database. This thesis explores ways to reduce such accidents.

Objectives: 

• Investigate solutions for collisions from following vehicles using Volvo accident data.
• Propose a warning function for fast-approaching threats using available vehicle sensors/signals.

Scope:

• Analyze accident data for use cases.
• Propose and implement a simple POC based on available signals and requirements.
• Verify solution and performance.

Qualifications: Mechatronics or similar, Python, control knowledge, and independent research skills.

2. Driver Behavior Models

Background: identify real-life cases that are not covered in our function's ODD.

Objectives:

• Create models to analyze logs and detect cases outside ODD (e.g., AEB speed reduction, Road Edge suppressions).
• Generate SIL scenarios from edge cases.
• Run simulations using reference driver models and identify improvements for ADAS interventions.

Scope:

• Use existing models to find patterns and edge cases in Oden/fleet insight data.
• Provide input for future function development.

Qualifications: Data analysis, programming, AI, and independent research.

3. Scenario Classification via Imagery/Videos

Background: Manual review of CTA/b (Cross Traffic Alert/Brake) and RAB (Rear Auto Brake) triggers is time-consuming. A tool for scenario classification can improve efficiency and accuracy.

Objectives: 

• Develop a model for classifying, clustering, or describing scenarios using Image Recognition/Computer Vision.
• Enable practical use by the end of the thesis; integrate with current systems.
• If possible, implement continuous learning.
• If possible, have a continuous learning process for the result.

Qualifications:

• Strong Python skills.
• Experience with ML libraries (PyTorch, Keras, TensorFlow, scikit-learn).
• Knowledge of image recognition/computer vision.
• Familiarity with CRISP-DM or similar methodology.

4. Parking Spot Recommendation

Background: Parking functions require validation in varied conditions (narrow/broad roads, surfaces, curbs, malls, etc.). Currently, spots are found manually, which is inefficient.

Objective: Develop a solution to classify and suggest parking spots based on user needs.

Scope:

• Allow users to input parking requirements; the tool provides recommendations.
• Maintain a database of chosen spots for validation and vehicle usage.

Qualifications: Programming, data analysis, and the ability to design practical solutions.

Indicate which project interests you most in your application.

What you'll bring

You are a highly motivated, self-driven student in a master’s program. You have a genuine interest and curiosity in the subject matter with good analytical skills. You have excellent communication skills, both verbal and written English, and you are a collaborative team player with a preference to do your thesis in a pair. Your academic field is in areas such as Automotive Engineering, Computer Science, Computer Engineering, Data Science, Electrical Engineering, or Systems, Control, and mechatronics.

Duration

• The work will start in January 2026 (can be discussed).
• The duration for this thesis work is 20 weeks.
• 30 ECTS (academic credits) if in agreement with your Thesis Advisor at the University.
• Each thesis is to be conducted by 2 students working in pairs. If you apply as a pair, make sure both of you submit your applications.