Thesis in the field of autonomous driving from October 2024

Master's thesis: Investigation of approaches to represent the joint probability distribution of scenario parameters

Shape the future of mobility around highly automated driving with us!

The acquisition and evaluation of real driving data is mandatory for the design and validation of highly automated driving systems. As part of your master's thesis, you will be involved in developing a method for transferring data collected by fleet vehicles with series technology into a knowledge-based system in order to be able to make a statement about the probability of occurrence of specific driving scenarios in the population of real traffic. The method includes the qualitative abstraction and parameterization of the driving events recorded by the sensors as well as the estimation of the distributions and correlations of scenario parameters.

In your master's thesis, you will examine various approaches for their suitability to represent the joint probability distribution of all scenario parameters in real traffic. Both frequentist and Bayesian methods can be considered.

Specifically, you will deal with the following tasks:

• Familiarization with the task and the overall project goals
• Researching the relevant state of the art and previous work
• Developing a procedure for solving the task
• Implementing one or more approaches and conducting experiments based on fleet data
• Discussion of the results achieved

Further information on the objectives and methodology of the overarching project can be found in the following publications:

• https://doi.org/10.48550/arXiv.2404.06288
• https://doi.org/10.48550/arXiv.2203.03515

• Master's students in natural science subjects such as computer science, mathematics, physics or a comparable subject area
• Good knowledge in the field of deep learning
• Good programming skills in Python
• Good knowledge of mathematics
• Proficiency in written and spoken German and English
• Independent and structured way of working

Additional information:

Of course, we can't do without any formalities. Please apply online only and enclose a CV, current certificate of enrollment stating the semester of study, current transcript of records, relevant certificates (max. total size of attachments 5 MB) and mark your application documents as "relevant for this application" in the online form.

Further information on the recruitment criteria can be found"here".

Nationals from countries outside the European Economic Area should send their residence/work permit with their application.

We particularly welcome online applications from severely disabled persons and persons with equivalent disabilities. If you have any questions, you can also contact the site's representative for severely disabled employees at sbv-sindelfingen@mercedes-benz.com, who will be happy to support you in the further application process after your application.

Please understand that we no longer accept paper applications and that there is no entitlement to return postage.

If you have any questions about the application process, please contact HR Services by e-mail at myhrservice@mercedes-benz.com or by phone: 0711/17-99000 (Monday to Friday between 10 a.m. - 12 p.m. and 1 p.m. - 3 p.m.).