Interactive Analysis and Visualization of Digital Twins in High-Dimensional State Spaces

Digital Twins (DTs), an emerging concept from Industry 4.0, are virtual representations of real technical assets. Multi-domain 3D simulation systems can bring DTs to life, even before their physical counterparts are finished. A DT's internal state can be fed from its real twin or generated by simulation. Access to this high-dimensional state of a DT is the key for various analysis and visualization methods presented in this paper. We introduce a generic formalism of state space for DTs and utilize it in an application scenario for automated driving. Throughout this example, methods for state logging and replays, data analysis, and visualization within 3D simulation frameworks are presented. Clear definitions for state variables, vectors, trajectories, and time series help slicing the DTs' state spaces of enormous dimensionality. The presented methodology does not only support the development of intelligent algorithms for autonomous driving, but is also the basis for further use cases of DTs involving optimization, mental models, and decision support systems.