Master Thesis Student - ADAS Scenario Machine Learning Analysis
Göteborg, SE, 417 15
Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future. If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match.
Background
Automated emergency braking functions support drivers in avoiding accidents in traffic. However, they are intrusive and can cause discomfort or even dangerous situations if acting inappropriately, eg. too late or unexpectedly. For developers of such systems it is not only important to know if the system acts correctly in a certain situation but also to understand why the system acted the way it did, especially in situations where we would classify the action as incorrect. For evaluating and understanding function performance, the existence of high-quantity and quality data is key.
Description of thesis work
The proposed project idea is to create methods for classifying and explaining AEBS function behavior utilizing real world vehicle data.
Three areas have been identified for deeper research:
- Scenario extraction: Explore methods and implement algorithms to generate simulation-ready scenarios from recorded customer event data, including GPS, camera, and map data.
- Federated learning for classification of events: Create a model for classifying AEBS events (eg. true or false positive) and explore how splitting the data in some dimensions affects model performance by training separate models for each split.
- Data and logging design: What data is needed to accurately reconstruct the scenarios and/or classify the systems action – understand the effects of epoch length, sampling rate etc.
Suitable background for the student
Students studying their master's with a specialization in some of the following subjects:
- Machine Learning
- Computer Vision
- Deep Learning
- Statistics
- Autonomous systems
- Vehicle safety
Ready for the next move?
Are you excited to bring your skills and innovative ideas to the table? We can’t wait to hear from you. Apply today!
Last application date: November 21st, 2025.
Location: Gothenburg, Sweden.
Thesis Level: Master.
Language: English
Starting date: January 19th, 2026.
Number of students: Two (2)
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Who we are and what we believe in
We are committed to shaping the future landscape of efficient, safe, and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents across the group’s leading brands and entities.
Applying to this job offers you the opportunity to join Volvo Group. Every day, you will be working with some of the sharpest and most creative brains in our field to be able to leave our society in better shape for the next generation. We are passionate about what we do, and we thrive on teamwork. We are almost 100,000 people united around the world by a culture of care, inclusiveness, and empowerment.
Group Trucks Technology are seeking talents to help design sustainable transportation solutions for the future. As part of our team, you’ll help us by engineering exciting next-gen technologies and contribute to projects that determine new, sustainable solutions. Bring your love of developing systems, working collaboratively, and your advanced skills to a place where you can make an impact. Join our design shift that leaves society in good shape for the next generation.