  While current research and development of autonomous driving primarily
focuses on developing new features and algorithms, the transfer from isolated
software components into an entire software stack has been covered sparsely.
Besides that, due to the complexity of autonomous software stacks and public
road traffic, the optimal validation of entire stacks is an open research
problem. Our paper targets these two aspects. We present our autonomous
research vehicle EDGAR and its digital twin, a detailed virtual duplication of
the vehicle. While the vehicle's setup is closely related to the state of the
art, its virtual duplication is a valuable contribution as it is crucial for a
consistent validation process from simulation to real-world tests. In addition,
different development teams can work with the same model, making integration
and testing of the software stacks much easier, significantly accelerating the
development process. The real and virtual vehicles are embedded in a
comprehensive development environment, which is also introduced. All parameters
of the digital twin are provided open-source at
https://github.com/TUMFTM/edgar_digital_twin.
