Infrastructure-based digital twins for cooperative, connected, automated
driving and smart road services
Abstract
Driving requires continuous decision making from a driver taking into
account all available relevant information. Automating driving tasks
also automates the related decisions. However, humans are very good at
dealing with bad quality, fuzzy, informal and incomplete information,
whereas machines generally require solid quality information in a
formalized format. Therefore, the development of automated driving
functions relies on the availability of machine-usable information. A
digital twin contains quality controlled information collected and
augmented from different sources, ready to be supplied to such an
automated driving function. An information model that describes all
conceivably relevant information is necessary. To this end, a list of
requirements that such an information model should meet is proposed and
each requirement is argued for. Based on the anticipated services and
applications that such a system should support, a collection of
requirements for system architecture is derived. Information modeling is
performed for selected relevant information groups. A system
architecture has been proposed and validated with three different
implementations, addressing several different applications to support
decisions at a highway tunnel construction site in Austria and
throughout the Test Bed Lower Saxony in Germany.