A consortium led by Siemens Mobility is developing and testing a secure remote control system with artificial intelligence-based obstacle detection for train operations in rail depots. The project, called RemODtrAIn (Remote operated train with AI based Obstacle Detection), brings together industry partners, operators, and academic institutions to advance digital train operations.
The initiative builds on previous projects such as AutomatedTrain and safe.trAIn, aiming to enhance collaboration with Deutsche Bahn. As part of the project, an ICE 4 train will be equipped with advanced 5G technology to enable remote control from a central operating station within the depot. The goal is to achieve secure and reliable remote-controlled train operations even under varying communication conditions using public 5G networks.
The Federal Ministry for Economic Affairs and Energy supports the project with €17 million through its funding program “DNS der zukunftsfähigen Mobilität. Digital – Nachhaltig – Systemfähig” (DNS of Sustainable Mobility. Digital – Sustainable – System-capable).
Marc Ludwig, CEO Rail Infrastructure at Siemens Mobility, stated: “With RemODtrAIn, we at Siemens Mobility are advancing automated rail operations. Together with strong partners from industry, research, and the railway industry, we are developing solutions that are not only technologically advanced but also precisely tailored to the current requirements of rail operations. Siemens Mobility is responsible for specification and development of a remote control system, as well as its integration and practical testing. Our goal is to make remote-controlled operations in the depot and premises safe, efficient, and scalable. This is a decisive step towards digitized rail operations.”
Dr. Jasmin Bigdon, Chief Technical Officer at Deutsche Bahn AG added: “With the RemODtrAIn project, Deutsche Bahn is taking an important step towards the remote control and automation of shunting movements. Our goal is to develop a pragmatic solution for remote-controlled train operations by closing specific technological gaps and to consider necessary adjustments in roles, processes, and regulations. The close integration of technical solutions and real-world application on-site is the focus of our actions: DB Fernverkehr AG, as the demand owner, contributes the operational requirements. Part of the testing will take place on the premises of DB RegioNetz Infrastruktur GmbH in the Erzgebirge. DB Systemtechnik GmbH contributes system engineering, architecture, safety and cybersecurity expertise, as well as experience in standardization and approval. With remote control in shunting operations, we aim to increase capacities, make processes more flexible, alleviate staff shortages, and thus achieve tangible operational improvements quickly for customers and our employees.”
RemODtrAIn focuses on improving train availability as well as depot movements using vehicle sensors designed for universal applications across all operating modes. The project aims to address challenges such as driver shortages while pushing forward automation efforts within rail systems.
Key elements include developing requirements for remote-controlled operation; specifying a modular safety-critical architecture; implementing solutions incrementally; plus conducting tests in real operational environments—including retrofitting options for existing trains alongside new models.
Testing will occur at various sites: communications solutions will be trialed using Desiro Classic trains at Smart Rail Connectivity Campus in Annaberg-Buchholz; obstacle detection systems will be evaluated during daily S-Bahn Berlin service; overall vehicle validation is planned for 2028.
The solution’s design anticipates future developments by working closely with mobile network providers while considering satellite communication potential.
Twelve organizations participate in this effort: Siemens Mobility GmbH; Siemens AG; several branches of Deutsche Bahn including DB AG; Mira GmbH; Smart Rail Connectivity Campus e.V.; German Aerospace Center (DLR); Technische Universität Berlin; Technische Universität Chemnitz; Technische Universität München.
