Adaptive geometric-semantic building model (SFB/TRR 339 digital twin Road)Copyright: © TU Dresden
Subproject B01 - Adaptive geometric-semantic multi-LOD construction model of road infrastructure as Cyber-Physical System (CPS)
The current SFB/TRR 339 (TU Dresden, RWTH Aachen) is researching the methodological foundations for constructing digital twins of the roads as a physical-informational representation of the "future road" system are being researched.Copyright: © gia
For this purpose, a spatially and temporally multidimensional, digital image (reality model in space and time) of the vehicles, tires and road surfaces (concrete as well as asphalt) is being developed and investigated, taking the road pavements (integrated multifunctionality) into account. The reality model combines all available and relevant information about the road system from physical investigations and modeling as well as from informational and traffic data (sensor data, data models, and so on). It enables and requires interaction between the physical-engineering and the informational-traffic design levels. This interactive reality model in space and time is referred to as the digital twin road and is used in perspective for the analysis, control and prognosis of the physical original (real system road consisting of vehicle, tires, roadway, nearby road space) by means of common interfaces. The extension of the road to a high-tech platform is being developed by means of the new, interdisciplinary research approach (civil engineering-informatics society).
In subproject B01, gia is developing an adaptive geometric-semantic model (GSM) with several abstraction levels, which enables the spatial multi-scale representation of the physical existing structure and thus serves as a homogeneous spatial reference for all geometry-related questions in the SFB/TRR 339. The automatic model derivation is based on the combination of algorithmic geometry, knowledge-based approaches, and machine learning methods. The GSM data can be used in different levels of detail (LOD) for simulations, visualizations and other purposes. A novel combined quality measure is being developed to describe the geometric-semantic reliability of the data, which provides a fuzziness quantification to the required LOD.