Thesis Student - Physics-Based Modelling of Sensor Performance Under Varying Environmentalcable

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.

For more information, visit www.traton.com.

Background

Modern autonomous vehicles rely on multiple sensor technologies, such as cameras, radar, lidar and GNSS, to provide reliable information about the vehicle and its surroundings. These sensors operate according to different physical principles, and their performance can vary significantly depending on environmental conditions, infrastructure, interference and installation characteristics.

Physics-based modelling offers a systematic approach to understanding and predicting sensor performance. By decomposing the measurement process into its underlying physical mechanisms, it is possible to investigate how factors such as signal propagation, attenuation, interference, noise and sensor characteristics influence measurement quality. For example, link-budget analysis can be used to estimate received signal strength and signal-to-noise ratio under different conditions.

Job Description

Phase 1: Establish a theoretical framework for physics-based modelling of sensor performance. The work should start with a literature review of relevant physical sensor models, link-budget methods and approaches for characterizing environmental influences on sensor measurements. Investigate how individual physical effects, such as propagation losses, environmental attenuation, interference and sensor characteristics, can be modelled separately and combined to estimate sensor performance. Python or similar tools may be used.

Phase 2: Develop and evaluate physics-based performance models for one or more selected sensor technologies, depending on student interests and available data. Investigate how variations in environmental and system parameters influence relevant performance metrics, such as signal-to-noise ratio, detection probability, measurement uncertainty or signal availability. Sensitivity and uncertainty analyses should be used to identify the most influential parameters and limitations of the models. Where possible, model predictions should be compared against experimental measurements, supplier specifications or existing simulation results.

Additional comments: The thesis should focus on establishing reusable modelling methods rather than developing a complete high-fidelity sensor simulation. The scope and selection of sensor technologies will be determined together with the supervisors. The work should emphasize physically grounded and explainable models, with a suitable balance between analytical methods, empirical relationships and experimental validation. The methods should be applicable to autonomous driving and ADAS systems, as well as other applications involving environmental influences on 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:

• Mikael Salmén, Senior Development Engineer – TGRAAP1

mikael.salmen@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.