RemODtrAIn – Remote Operated Train with AI based Obstacle Detection
RemODtrAIn is advancing automated rail transport by developing a safe remote control architecture for trains – followed by validation in real-world operations. The project is also testing a modular, AI-supported obstacle detection system for shunting, works and depot runs.
As part of the RemODtrAIn project (“Remote Operated Train with AI-based Obstacle Detection”), a secure remote control architecture for trains, as well as a modular, AI-based obstacle detection system for shunting, factory and depot runs, is being developed and tested in close cooperation with academic partners, industry partners and operators, a safe remote control architecture for trains and a modular, AI-based obstacle detection system are being developed and tested for shunting, works and depot journeys.
The aim is to create a safety-oriented, modular system and safety architecture based on a modular design, which will subsequently be validated in real-world operations. Validation will initially take place at the ICE depot in Cologne-Nippes using an ICE 4, and subsequently at the Smart Rail Connectivity Campus in Annaberg-Buchholz using a Desiro Classic.
Further objectives of RemODtrAIn:
- Specifications recognised by the sector
- From operational concept to system architecture in accordance with the CENELEC process
- a modular concept (modular system) as the basis for implementation
- Development of a prototype system for RTO (for retrofitting and new vehicles)
- Testing and demonstration of RTO in the laboratory and in real-world operating environments (on two vehicles)
- Security concept for an RTO and obstacle detection system using AI
By consistently integrating requirements specifications, modular system architecture, verifiable safety, TRL 6-compliant remote control technology and AI-based obstacle detection, the aim is to create a scalable end-to-end system that supports both existing and newly designed rail vehicles in long-distance and regional transport. Systematic integration and validation in laboratory and field environments will then lay the foundation for subsequent certification and widespread industrial deployment, thereby sustainably enhancing the competitiveness of rail transport.
Project title:
RemODtrAIn - Remote Operated Train with AI‑based Obstacle Detection
Duration:
10/2025 to 09/2028
This project is managed by the department:
