Europe’s Rail Newsletter – May Edition The May Newsletter is filled with the latest updates, key insights, and...
The potential of digital twins (a dynamic, virtual replica of a physical object, system, or process) in rail is limited by fragmented implementations and a lack of modular, interoperable approaches. Without reusable components and standardised integration, building complex digital representations remains costly and inefficient.
This constrains the ability to fully leverage bidirectional data exchange for simulation, optimization, and data-driven decision-making.
In particular, simulation of train traffic remains constrained by inconsistent modelling assumptions and key innovations such as Hybrid Train Detection, Automatic Train Operation, Next Generation Brakes, and advanced Traffic Management Systems results not yet uniformly integrated into simulation frameworks. This limits the ability to accurately assess their impact under different scenarios and parameter settings.
To address this, Europe’s Rail (EU-Rail) Flagship Project FP1-MOTIONAL has developed a combination of digital solutions:
It has been provided digital twins: a virtual representation of a physical object or asset with which sensor data and other information can be exchanged bidirectionally. The primary purpose in Rail is to observe, analyze, simulate and optimize the performance of the asset in order to reduce failures and costs, improve quality and support data-driven decision making. Its modularisation offers efficient ways to create complex, high-order digital twin assemblies leveraging reusable components.
Thanks to the capacity simulation methods developed through this solution for new digital train operations:
The Modularised Digital Twins for Rail in 2026 mainly addresses the conceptual, exemplary and prototype level. It is part of the MOTIONAL Project that is targeted on the organization of interoperability, modularity and composability of railway Digital Twins components in order to facilitate the design of high order Digital Twin assemblies.
Part of the Capacity Simulation Methods for new Digital Train Operations are available with just changing parameter settings and therefore usable in any software with the proper level of detail. Another part of the solutions require more adaptations in simulation software and these have been implemented in several simulation environments and used by specific users in the related organisations or been implemented in commercial software, where these specific functions aren’t available to the big public yet. The solutions for the 4 mentioned techniques have been validated and used in various cases (urban high-density, rural low-density, mixed traffic, high-speed, freight).
TRL 5 (Technology validated in relevant environment) and 6 (Technology demonstrated in relevant environment)
Undoubtedly, “data is the new oil”. Therefore, digital twins are intended to provide, analyse and exploit data in order to reduce costs, improve reliability and increase capacity as well as allow for faster project execution. Prominent examples are continuous monitoring of assets that supports predictive maintenance or DT-based simulations, which help to substitute some time-consuming and expensive real by early and comparable cheap virtual testing.
Moreover, the four Capacity Simulation Methods support the design choices for new digital train operations by analysing the network capacity and robustness benefits. The results can be used in cost-benefit analyses for the various techniques or for detailed comparison of implementation variants. The result can be that train operations can benefit (more capacity, improved robustness) without additional steel tracks, but only by adding digital technologies.
By reducing costs, improving reliability, increasing capacity and allowing faster project execution, this solution is enabling:
