Thesis Student - Raw GNSS and IMU Integration for Robust Vehicle Localization

Introduction

A thesis project at TRATON provides a unique opportunity to gain practical experience, expand your professional network, and contribute to the future of sustainable transportation. Many of our current employees began their careers at Traton by completing their degree projects within the organization.

TRATON Group includes leading commercial vehicle brands such as Scania, MAN, Volkswagen Truck & Bus, and International. Together, we are committed to driving the transformation toward sustainable transport solutions. As a thesis student, you will work closely with experienced engineers and specialists, contributing to real-world product development while gaining valuable industry experience.

Background

Robust localization is a key enabler for future transport systems and from a SOTIF and ODD perspective, it must also be understood in corner cases such as GNSS disturbance, urban canyons, underground or indoor operation, and situations with few visible satellites.

Loosely coupled navigation uses position and velocity updates from the GNSS receiver. Tightly or deeply coupled GNSS/INS integration instead uses raw GNSS observables, such as pseudo range and carrier phase, directly in the navigation filter. This can allow the fused system to use partial satellite information even when fewer than three satellites are available and the receiver cannot provide a conventional GNSS solution.

The thesis will also extract stochastic MEMS IMU error parameters from real data for a specific mounting location. This is important because heavy-duty vehicle vibration and installation effects are not fully described by manufacturer specifications. Site-specific IMU error models can make tuning of complex localization filters more systematic, and Monte Carlo simulations will support validation.

Assignment

Phase 1: Establish a stochastic filtering and validation foundation for 3D GNSS/INS navigation using IMU, vehicle odometry and baseline GNSS. The work can use MATLAB, Python or C++, with Python/Databricks, likely preferable because Databricks contains ground truth for fusion-error evaluation.

Phase 2: Extend the foundation toward tightly/deeply coupled GNSS/INS integration using raw GNSS observables, for example pseudo range and carrier phase. Also include Allan variance analysis, stochastic IMU error parameters from real data, and Monte Carlo comparison.

Additional comments: Phase 1 should preferably be done together with the companion thesis student. The students establish a common foundation and then split into their Phase 2 tracks. The methods should support autonomous driving and ADAS Next Generation functions requiring robust localization and well-characterized sensor performance.

Education / Program / Qualifications

We are looking for a curious, motivated, and hands-on student with a strong interest in embedded systems, multiple sensor technologies, electrical architecture, and sustainable transportation.

Preferred Qualifications

Interest in sensor technology, embedded systems and automated driving systems.

Fluency in English, both written and spoken.

Education:

Students from engineering with emphasis in robotics, signal processing, control, automation, autonomous systems, computer science, electrical engineering, mechatronics, mathematics, applied physics or similar.

Thesis Start Date

• February 2027

The exact start date and project timeline will be agreed upon between TRATON, the selected candidate, and the academic institution.

Contact Information

For questions regarding the thesis project, please contact:

• Bengt Boberg, Senior Development Engineer - TGRAAP1

bengt.boberg@scania.com

• Laís Ramos, Manager - TGRAAP1

lais.carolina.ramos@scania.com

Application

Your application must include:

• CV
• Personal letter
• Transcript of grades

We welcome applicants from all backgrounds and believe that diverse perspectives contribute to better innovation, stronger teams, and improved solutions.

Please note that a background check may be conducted for this position. Interviews will be held continuously, and the recruitment process may close before the stated application deadline.

Join us in shaping the future of battery technology and sustainable transportation. We look forward to receiving your application.

Requisition ID: 34688

Number of Openings: 1.0

Part-time / Full-time: Full-time

Permanent / Temporary: Temporary

Country / Region: SE

Location(s):
Södertälje, SE, 151 38

Required Travel: 0%

Workplace: Hybrid