Benedikt Schwab

Benedikt Schwab is a Researcher at the Chair of Geoinformatics at the Technical University of Munich (TUM), specializing in semantic road space modeling and geospatial technologies for automated driving systems. His work focuses on the intersection of 3D city modeling, sensor data analysis, and autonomous vehicle testing.

His primary research interests include semantic road space modeling, HD cards development, spatial-semantic analysis of sensor data, simulation of LiDAR, RADAR and camera sensors, and submicroscopic driving simulation. He has developed multiple Rust-based libraries for geospatial data processing including ecitygml, epoint, and evoxel, demonstrating strong technical expertise in both geospatial concepts and software development.

His recent publications reveal a strong focus on 3D city modeling applications for autonomous driving, with particular emphasis on OpenDRIVE to CityGML conversion (r:trån), road space validation, and sensor simulation. His work frequently appears in ISPRS conferences and journals, showing consistent contribution to the geospatial research community.

As an educator, Schwab teaches Advanced GIS for Environmental Engineering, Applied Geoinformatics 2, and Geo Sensor Networks courses at TUM, demonstrating his commitment to training the next generation of geospatial professionals.

He has led multiple research projects including SAVeNoW (2021-2023) focused on functional and traffic safety for automated and connected mobility, and has contributed to the development of open data resources such as LOD3 Road Space Models and TUM2TWIN.