Deutsche Bahn (DB), in partnership with Siemens Mobility, Bosch, and several other key industry players, is embarking on an ambitious research and development project called "AutomatedTrain". The project, which is supported by the German Federal Ministry of Economics and Climate Protection with substantial funding of around €42.6 million, aims to test fully automated train provisioning and stabling over the next three years.
The "AutomatedTrain" project, which is part of the larger Digital Rail Germany initiative, is intended to revolutionize rail traffic and explore the possibilities of driverless train travel. Using advanced sensor technology, similar to autonomous driving in the automotive industry, trains will be able to sense their surroundings and react precisely to obstacles. This approach not only promises to improve safety but also opens the door to greater flexibility in train scheduling and frequency.
"Fully automated, driverless driving will enable us to operate our trains more frequently and flexibly in the future and thus offer our passengers an even more attractive service,” said Daniela Gerd tom Markotten, DB Board Member for Digitalisation and Technology.
As an important step towards realizing this vision, Siemens Mobility will equip the Mireo Smart train as a prototype by 2026. This driverless train will travel autonomously from the depot to the first station, ensuring obstacle detection and automatic braking. The project will also evaluate the feasibility of fully automated train upgrades and downgrades. Meanwhile, a second train from the Stuttgart S-Bahn will support data collection for obstacle detection and use different software solutions to compare sensor data and software responses.
"Fully automated driving has great potential for rail transport,” said Frank Schmidt, Managing Director of Bosch Engineering GmbH, and continued: “The aim is to locate the position of trains reliably and accurately on the track and to enable automated approach and departure. For this, it is important to record the course of the track in real-time and to detect potential obstacles that are in front of the vehicle."
