Adaptive geometric-semantic multi-LOD construction model of road infrastructure as Cyber-Physical System (CPS)

For a consistent description of the shape and location of the road infrastructure, an adaptive geometric-semantic building model (GSM) with several abstraction levels is developed, which enables the spatially multi-scale geometric representation of the real existing building object and serves as a homogeneous spatial reference for all geometry-related questions in the SFB/TRR 339. As a georeference, the model represents the connection between the real street and its digital shadow. The automatic model derivation is based on a combination of algorithmic geometry, knowledge-based approaches and machine learning methods. The GSM will represent the interface to Building Information Modeling (BIM) and Geospatial Information Modeling (GIM), where GSM are a central component. The GSM data can be used in different modeling depths (Level of Detail, LOD) for simulations, visualizations and other purposes in order to work on questions of the involved SP. Besides the spatial resolution, the geometric-semantic reliability plays an important role. For this purpose, a novel combined quality measure is developed, which allows a fuzziness quantification of the GSM to the required LOD. For the SP, primarily point clouds from laser scans and images, digital planning models (CAD/BIM) as well as additional information from GIS are used.