OJ-ITS-2022-12-0079-21-12-2022.pdf (4.28 MB)
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Infrastructure-based digital twins for cooperative, connected, automated driving and smart road services

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posted on 2022-12-24, 05:54 authored by Elvira Thonhofer, Simon Sigl, Martin Fischer, Fin HeuerFin Heuer, Andreas Kuhn, Jacqueline Erhart, Manfred Harrer, Wolfgang Schildorfer

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. 


D-A-CH Call 2020, Infrastructure framework for automated and connected driving - 36281646

Holistic Approach for Driver Role Integration and Automation Allocation for European Mobility Needs

European Commission

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Submitting Author's Institution

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

Submitting Author's Country

  • Germany