Skip to main content Skip to secondary navigation
Journal Article

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.

Journal Article

Author(s)
Elvira Thonhofer
Simon Sigl
Martin Fischer
Fin Heuer
Andreas Kuhn
Jacqueline Erhart
Manfred Harrer
Wolfgang Schildorfer
Journal Name
Open Journal of Intelligent Transportation Systems
Publication Date
April, 2023
DOI
10.1109/OJITS.2023.3266800
Publisher
IEEE