Master Thesis - Free space detection using machine learning and truck-mounted fisheye cameras
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
Large commercial trucks have significant blind spots that pose a safety risk to other road users, particularly in dense urban environments, and during complex maneuvers like lane changes or docking. Traditional cameras and mirrors offer a limited field of view (FoV). Fisheye cameras, with their ultra-wide FoV (often 150 degrees or more), present a cost-effective and efficient solution for creating a complete surround-view system. This information is valuable to include Advanced Driver Assistance Systems (ADAS) and future autonomous driving applications. By processing the distorted images unique to fisheye lenses, it is possible to create a comprehensive understanding of the truck’s immediate environment, drastically reducing blind spots and improving overall road safety.
In the ADAS Sensor fusion team within the department of Safe and Efficient Driving, we are always striving to create the best estimate of the surrounding environment for our safety functions. Efficient use of fisheye cameras in our products is an important topic for us, and by joining us for a master thesis in this area you will contribute to our ambition to create solutions that are 100% safe.
Description of thesis work
This project proposes the development of a real-time free-space detection algorithm tailored for fisheye camera systems mounted on trucks.
The thesis will be useful for the Safe and Efficient Driving and Services department, to understand the following use cases:
- Free Space detection in trucks for driver assistance
- Segmentation of Drivable regions for trucks and how the path planning algorithm can be improved
- Bird’s Eye View of Camera data, for assisting drivers in various tasks like parking, reversing towards docking bays, etc.
The thesis will be mainly divided into the following steps:
- Generate images using an internal software platform
- Train a model for converting images into Bird’s Eye View
- Train a model to find the free space in either the Bird’s Eye View or in traditional image space
- Combine the models and show real-time inferred output
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
- Sensor Fusion
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 7th, 2025
Location: Gothenburg, Sweden
Thesis Level: Master
Language: English
Starting date: week 4 or week 6, 2026
Number of students: One to Two (1-2)
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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.