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Number: MER000470R Mercedes-Benz Group AG is one of the most successful automotive companies in the world. With Mercedes-Benz AG, the vehicle manufacturer is one of the largest providers of premium and luxury cars and vans. A central component for automated driving is a complete understanding of the vehicle environment. The environment detection is based primarily on sensors such as Lidar, camera and radar, but an important role is also played by a digital high-definition (HD) road map. The HD card provides context information to evaluate the current situation, which cannot be detected or can only be detected with difficulty by the sensors and completes the environment detection. In addition, the HD card provides important planning information about the route ahead. Such a HD card for automated driving must be significantly more accurate, more complete, more current and safer than the map previously known in navigation systems. In order to achieve this, sensor data from the vehicles are used, among other things, to update the road map and to guarantee a correct HD card at any time via a closed loop process. In the Scene Mining team, we are engaged in analyzing and preparing vehicle data to implement tasks such as the automatic generation of HD cards. The master thesis is embedded in the development of an AI based and scalable approach in order to derive as complete as possible and accurate HD card based on sensor data of the vehicle fleet. The focus of the work is the derivation of a track model including topological information. For this purpose, a prototypical implementation is already present which is to be expanded within the scope of the master thesis. These challenges come to you: Integration into existing software framework and state-of-the-art algorithms

Modification and improvement of existing deep learning models for generating HD cards

Evaluation of the model Performance for the respective approaches

The activity can start from October 2026. The final topics will be discussed with the university, you and us.

Course in Computer Science, Data Science, Big Data & Data Analytics or a comparable study programme

Very good knowledge of German and English in word and writing

Very good knowledge of Python

Experiences with deep learning frameworks (especially PyTorch)

Ideally experience with Transformer Architectures, Object Detection, Geometric Data Processing

Analytical, structured and independent thinking and working methods

Additional information: We are looking forward to your online application with CV, lettering, certificates, current enrollment certificate with an indication of the semester and proof of the regular study period. Please do not forget to mark your documents as ''relevant for this application' in the online form and to observe the maximum file size of 5 MB. Further information on the setting criteria can be found here. Disabled and equalized applicants are welcome! The severely disabled representative (sbv-sindelfingen@mercedes-benz.com) is happy to support you in the application process. People Solutions will be happy to help you with questions about the application process. You can reach us by email via myhrservice@mercedes-benz.com or by phone at 0711/17-99000 (Mo-Fr 10-12am & 13-15am).

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