Aktuelle Themenstellungen - Automatisiertes Fahren

Key Data
Type of thesis: Master thesis
Prior knowledge: Python or C++
Language: German or English
Entry Date: Earliest possible date
Department: Automated Driving

Topic and Goal of the Thesis

In the context of validation of automated driving functions, the road network (i.e. the static part of a traffic scenario) is an important aspect. The goal of this research is to model intersections that are fictional but realistic. Meaning that it is required to find out what characteristics an actual junction has and then generate synthetic road networks that fulfil those characteristics. Therefore, different data sources (e.g. Google Maps, OpenStreetMap, Here Maps, etc.) must be analysed and then relevant data to generate road networks must be extracted.
The goal is to develop a process that can analyse a huge amount of data and then calculate probability distributions for some key quantities. This way fictional simulation maps shall be generated which are validated to be realistic.

Working Points

• Literature/Web research on road network data sources
• Analysis of different APIs and implementation of a data extraction tool for at least one data source
• Generation of road networks and conception of a validation concept for realism of these

Requirements

• Good English or German language skills
• Reliability, commitment, and enjoyment of working independently
• Experience with python or other programming languages
• Experience with road network APIs is an advantage (not a must)

Note: Please attach to your application a short CV as well as an academic transcript (grades).