This demonstrator shows the design and adaption of virtual simulation environments based on high resolution mapping data. By generating a digital twin for simulation-based testing, human as well as model-based research can be conducted. In the context of future mobility transformation this research is particularly interesting for cities and municipalities.
Data Integration Process for the Digital Twin Environment
Visualized sequence of processing and transferring raw data into the digital twin environment for simulation-based analysis.
OD evaluation for safe operation of automated vehicles (AV)
The approach to virtualize real life environments enables researchers to assess vital information concerning the redistribution of available space as well as traffic flow analysis concerning those changes. Especially in the context of autonomous and connected vehicles these environments enable testing in the context of Operational Domain (OD) evaluation. This qualifies stakeholders to make informed decisions concerning possible domains where e.g. public transportation could safely operate autonomously in the future. With this simulative approach the requirements and challenges of those ODs can be assessed easily.
Twin of a real Intersection in Brunswick
Screenshot of the digital intersection model used for simulation-based testing of realistic traffic scenarios.
Also, AVs can be tested in the context of their sensor setup, giving OEMs crucial insight in the suitability of their sensor configurations in a dedicated operational area. By adjusting and testing the virtual sensor setup, this approach is also able to recommend more suitable configurations based on the specific requirements of the OD. Finally, simulated automation and real human test subjects can interact in the same environment to gain insight in the human perspective of human-machine-interaction and therefore allowing manifold research in the context of interaction, ergonomics and acceptance.
