Deliverables: Results Published in May 2026

ACADEMICS4RAIL

D7.1 Digital communications for virtual coupling

Academics4Rail aims to establish a stable and long-lasting scientific community that facilitates structured knowledge exchange between academia, EU-RAIL, and ERRAC. This collaboration spans multiple levels, from strategic research agendas to concrete technical innovations through coordinated scientific contributions.

WP7 focuses on improving the safety and dependability of Train-to-Train (T2T) communications, particularly for Virtual Coupling Train Sets (VCTS). The work combines established safety methodologies, including Failure Mode Effects and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA), with advanced modelling approaches such as Coloured Petri Nets. This enables both static hazard identification and dynamic simulation of communication performance, including the analysis of message loss and key indicators like delay, throughput, and delivery reliability. Mitigation strategies, such as retransmission mechanisms and message timestamping, are also evaluated.

Ongoing research extends these models by integrating advanced communication technologies such as 5G New Radio V2X (Vehicle-to-Everything), aiming to improve reliability under realistic operational conditions. This work supports the development of robust and safe communication systems, which are essential for enabling more automated and efficient train operations, including virtual coupling, and contributes to a more innovative and sustainable railway system in Europe.

How it brings us closer to achieving better rail for Europe: By improving the safety and reliability of wireless train communication systems, this work supports the development of more automated and efficient rail operations. It enables innovations like virtual coupling, increasing capacity and flexibility while ensuring high safety standards, and contributes to a more advanced and sustainable European rail system.

Target audience: Rail stakeholders, Member States, Researchers

More information on this topic: ACADEMICS4RAIL 

ACADEMICS4RAIL

D9.1 AI-based Driving Assistance

Academics4Rail aims to establish a stable and long-lasting scientific community that facilitates structured knowledge exchange between academia, EU-RAIL, and ERRAC. This collaboration spans multiple levels, from strategic research agendas to concrete technical innovations through coordinated scientific contributions.

WP9 focuses on advancing knowledge in intelligent train operations, particularly through the application of ICT and artificial intelligence to driver assistance systems. The work includes a comprehensive state-of-the-art review of technologies related to train cabins, driving assistance, and their impact on driver behaviour. Building on this, the project develops models for driver assistance and monitoring within different Grades of Automation (GoA). Additional efforts, including research visits and academic exchanges (notably with University of Applied Sciences and Arts of Southern Switzerland (SUPSI), have strengthened the development of AI competencies. Current work is exploring innovative methodologies for designing and validating AI-based driving assistance systems, contributing to safer and more efficient train operations.

How it brings us closer to achieving better rail for Europe: Academics4Rail strengthens Europe’s research and innovation capacity in railway technologies. The development of AI-based driver assistance systems and advanced ICT solutions contributes to safer, more efficient, and increasingly automated rail operations.

Target audience: Rail stakeholders, Member States, Researchers

More information on this topic: ACADEMICS4RAIL

FP2-R2DATO

D6.1 Report on sets of non-functional and functional requirements (SRS) for automating functions 

FP2 R2DATO advances rail safety and efficiency by developing the system requirements needed for automating functions in future train operations.Deliverable D6.1 provides a set of 994 requirements that has derived from 47 use cases from WP5 (complemented by inputs from the X2Rail‑4 ATO up to GoA4 SRS).
This deliverable describes the functional and non‑functional system requirements for automating functions by following the FP2‑R2DATO WP5 top‑down approach. The relevant technical enabler (TE1 Automating Functions) covers processes such as train preparation, incident handling or self‑healing while ensuring compatibility with existing specifications. As a result, D6.1 provides the main input for the subsequent system architecture definition in WP6 (Automation processes specifications), WP8 (Safety analysis and risk assessment), WP9 (Prototype development of automating functions) and the demonstrator cluster.

How it brings us closer to achieving better rail for Europe: By defining a common and harmonized set of requirements for Remote requirements for Automating Functions, D6.1 supports the development of interoperable architectures and prototypes that can be deployed across Europe. This enables safer, more efficient operations by reducing manual workload, operational processes and allowing higher levels of automation for both passenger and freight. As a result, it contributes to a rail system that is more digital, resilient, cost‑efficient in order to increase capacity and reliability.

Target audience: Rail stakeholders, Policy-makers, national safety authorities, notified bodies

More information on this topic: FP2-R2DATO

Pods4Rail

D8.1 Basic Design Concept Proposal Vessel Variants

Pods4Rail addresses the door-to-door travel and logistic needs of customers and enhances seamless experience. This new type of sustainable collaborative transport system may emerge as a new mobility offer, diverging from the current combination of individual and mass transport services. The study aims to establish a scalable design framework accommodating both passenger and cargo transport while adapting to diverse operational conditions and route topographies. Key transport unit parameters including size, materials, seating, HVAC, doors, and structural components – were identified and organised in a morphological box, enabling exploration of multiple design combinations.

How it brings us closer to achieving better rail for Europe: This new transport solution is expected to contribute to strengthening the railway transport position in the future mobility market, with the use of cutting-edge technology for automation, digitalisation and electrification.

Target audience: Rail stakeholders, Member States, Policy-makers

More information on this topic: Pods4Rail