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Swansea University

Centre for Research in Digital Railways

Overview

Building upon the excellent track record of the Swansea Railway Verification Group (established in 2007) including, e.g., two REF Impact Case Studies in 2014 and 2021, the Swansea Centre for Research in Digital Railways, RDR, takes a wide perspective on developing the railway of the future through digitalisation. It expanded capacity, capabilities, and scope by attracting colleagues from AI and Security, and, recently, winning new members from the School of Management and Civil Engineering; the latter broadening our research expertise and reach. Our 4 pillars are: (1) Modelling, Validation, and Verification of Railway Control Systems including Signalling, (2) AI-Techniques and Optimisation (3) Frameworks for Technology Transfer, and (4) Public Outreach via our Railway Table, implementing ERTMS.

UKRRIN status

UKRRIN member

Member of the Centre of Excellence in Digital Systems (CEDS)

Research themes

Topic: Safety and Capacity
Summary:

Since 2007, the Railway Verification Group at Swansea University has been addressing questions concerning safety and network capacity to improve the development of railway signalling software. Throughout this time, the Swansea Railway Verification Group has developed novel safety assurance processes for signalling technologies, and has become recognized as an international leader in the verification of signalling systems. Our research and novel processes for improving error detection have, for example, motivated Siemens Mobility to invest in a new verification team in Chippenham to accelerate the development of their next-generation digital interlockings. Similarly, the UK Rail Safety and Standards Board has incorporated our research on formal methods in guidance they provide to their members. Internationally, we have created and lead a European community of practice on formal methods in railway control.

Project examples: Railway Control Systems / SAFECAP: Overcoming the railway capacity challenges without undermining rail network safety / DITTO: Developing Integrated Tools to Optimise Railway Systems / Ladder Logic Verifier

Centre for Research in Digital Railways – Fact File (2026-27)

14 Research staff

10 PhD students

5 Masters students

21 Publications

Capability matrix

CAPABILITY
CAPABILITY LEVEL
Easy to use for all
Accurate, accessible and understandable real-time information
Smart fare collection
Accessible to all
Multi-modal integrated journeys
Reliable and fast on-board connectivity
Freight friendly
Increased network access for freight
Safer freight operations and better asset management
Enable greater intermodality and access for freight customers
Greater asset utilisation and reduced freight journey times
Low carbon freight and On Track machines
Low emissions
Efficient new electrificaiton
Zero carbon self-powered vehicles
Low carbon freight and On Track machines
Intelligent energy management
Cleaner air
Quieter railway
Lowering embodied carbon of key material
Optimised train operations
Infrastructure and train capabilities to overcome capacity constraints
Simpler and safer real-time operations and decisions
Improved recovery from incidents and disruptions
Reliable and flexible train planning
More affordable solutions for lower-use lines
Efficient and reliable - infrastructure
“Right-time” actionable insights on infrastructure conditions
Efficient, effective and safe infrastructure maintenance
Improved resilience of infrastructure to climate change and extreme weather events
Speed up and de-risk introduction of infrastructure assets
Proactive management of infrastructure obsolescence
Efficient and reliable - rolling stock
“Right-time” actionable insights on rolling stock conditions
Efficient, effective and safe rolling stock maintenance
Improved resilience of rolling stock to climate change and extreme weather events
Speed up and de-risk introduction of rolling stock assets
Proactive management of rolling stock obsolescence
Efficient and reliable - interfaces
Improved vehicle/track interaction
Improved pantograph/overhead line interaction
Improved utilisation of constrained space
Improved whole system resilience
Data driven
Advanced computing
Advanced data analytics techniques
Data governance and standardisation
Data integration
Effective innovation culture
System and network models
Pro-innovation legal and regulatory frameworks
Testing, homologation, cross acceptance
Technically talented workforce
Job design and human performance
Workforce development and training
Safety and health
Safety assessment and evaluation
Cyber security
Fitness for duty and health assessment
Competitiveness
Demand forecasting
Cost modelling
Social value

Research Group key contacts

Name: Markus Roggenbach, Professor of Computer Science
Email: m.roggenbach@swansea.ac.uk

Name: Monika Seisenbergerd, Associate Professor of Computer Science
Email: m.seisenberger@swansea.ac.uk

Website

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