Rail is now widely regarded as the most environmentally friendly form of surface transport, and yet there is an urgent need to increase rail capacity, productivity, and quality. These key challenges will be tackled by the TARO (Towards Automated Railway Operation) project.
TARO focuses on 3 different areas in order to take rail transport in Austria – already one of the leading railway countries in the European Union (no. 1 for passenger-kilometres per capita, no. 2 for freight transport volumes, no. 1 for night trains) with its highly competitive railway industry (no. 5 for global exports, no.1 for railway patents per capita) – to the next level:
- Development of digital twin vehicle with special regard to condition-based maintenance and predictive maintenance
- Development and simulation of digital twin infrastructure, one of the fundamentals of automated train operation
- Process automation in freight transport, in particular in terms of automated coupling, shunting, and planning. Automated railway solutions such as low-cost autonomous on-track side elements, low-cost train control systems for regional lines, as well as location of vehicles.
TARO explores highly reliable communication for branch lines between traction unit and stationary installed safety components (railroad crossings) using massive MIMO over the path of a 5G base station. The measurement data will be used to create geometry-based channel models that can be used in digital twins to test radio communication systems.
Start: 15.06.2020
End: 14.06.2023
Goals: The estimated project results are expected to contribute to an increase in capacity, productivity and quality of the entire railway system.
Results:
In TARO, highly reliable communication for branch lines between traction unit and a stationary installed safety components (railroad crossings) using massive MIMO over the path of a 5G base station is explored. The measurement data will be used to create geometry-based channel models that can be used in digital twins to test radio communication systems.
Webpage: https://projekte.ffg.at/projekt/3764867
Funding: FFG Mob. d. Z.
Partner:
- RENERCON e.U.
- Supercomputing Systems AG
- Rechenraum GmbH
- Hex GmbH
- EBE Solutions GmbH
- Universität Klagenfurt
- FH Campus Wien Forschungs- und Entwicklungs GmbH
- FH OÖ Forschungs & Entwicklungs GmbH
- ÖBB-Infrastruktur Aktiengesellschaft
- ÖBB-Technische Services-Gesellschaft mbH
- Rail Cargo Austria Aktiengesellschaft
- ÖBB-Personenverkehr Aktiengesellschaft
- Technische Universität Graz
- Dr. techn. Josef Zelisko, Fabrik für Elektrotechnik und Maschinenbau Gesellschaft m.b.H.
- AIT Austrian Institute of Technology GmbH
- JOANNEUM RESEARCH Forschungsgesellschaft mbH
