Latest project dissemination: article on Global Railway Review, poster at Big Data Conference, presentation at Europe’s Rails Innovation Days, and more

We are glad to report on the latest project dissemination events, including an article published on Global Railway Review (link below), a poster on “Dataset Challenges in Railway Machine Learning Applications” (see picture below) presented at the LNU Big Data Conference 2022, project status presentation at Europe’s Rail Innovation Days, and a research seminar given at Linnaeus University, where project-funded PhD student Lorenzo De Donato is currently spending a visiting period.

Towards ‘Roadmaps for AI Integration in the Rail Sector’


AI4RAILS 2022: keynote announcement

The program of AI4RAILS 2022 is now out !

The workshop will be held on September 12, 2022 in Zaragoza (Spain).

The program includes a keynote on Artificial intelligence, case of the railway sector: state of play and perspectives from Christian Chavanel, Director of the Rail System Department at International Union of Railways (UIC).

AI4RAILS 2022 is colocated with the EDCC 2022 conference.

Information regarding workshop registration and conference logistics may be found on the EDCC 2022 web site.


Trustworthy AI for safe autonomy of smart railways: directions and lessons learnt from other sectors

Our PhD student Lorenzo De Donato will present a talk “Trustworthy AI for safe autonomy of smart railways: directions and lessons learnt from other sectors” in the The 13th World Congress on Railway Research is coming to Birmingham, UK 6-10 June 2022 ( ). See here for details:

RAILS will attend several conferences

Members of RAILS will attend several conferences presenting output of the project in 2021.

– RAILS at 2021 INFORM Annual Meeting



– RAILS at IsoLa 2021, DisCoRail Session





Lorenzo DE DONATO PhD Student in Computer Engineering, RAILS Ambassador, University of Naples Federico II, Italy: Roadmaps for the Integration of Artificial Intelligence in Railways


– RAILS at SmartRail Europe 2021


Suicide prevention strategies & effective track detection technologies

RAILS Technical Manager

Wed 24, Nov 3:00 pm3:20 pm

During this session we examine the links between fatalities and factors such as homelessness and lifestyles and the strategies and technologies being used to effectively reduce occurrences in what is a difficult but important issue to address. We will also consider new developments in track detection technologies to prevent trespassing incidents.

Challenges and State-of-Practice Survey of Artificial Intelligence in Railways

(Original webpage:

This survey aims at obtaining a deeper understanding of the Challenges and State-of-Practice (SoP) of Artificial Intelligence (AI) in railway transportation from the perspective of diverse stakeholders. Results are collected in the context of the H2020 Shift2Rail project RAILS (Roadmaps for A.I. integration in the raiL Sector), to understand priorities and requirements when defining the roadmaps for AI integration in the rail sector.

The survey is distributed to Shift2Rail members, project partners and other project participants, as well as to other railway organizations and regulatory bodies. Aggregated and anonymous results will be disseminated primarily through the project website

You are welcome to add customized answers by using the text box “Other”.

We would like to thank you in advance for the time you will invest in filling this survey!

Please note that at the end of the questionnaire you can decide whether to share your personal data with the project team and if you are available to be contacted, otherwise you can remain fully anonymous.
Please note that even if you agree to be contacted, we will not share your name and affiliation with anyone except the project team. Only aggregated and anonymous results of the survey will be publicly disclosed.

If you encounter any problems, need clarifications, or want to report your feedback on the questionnaire, please contact:
Prof. Valeria Vittorini (project leader):
Prof. Francesco Flammini (technical leader):


AI4RAILS 2020 goes online

AI4RAILS – Call for Papers

1st International Workshop on Artificial Intelligence for RAILwayS
co-located with the 16th European Dependable Computing Conference (EDCC2020)
September 7, 2020

AI4RAILS 2020 has moved to digital mode due to pandemic COVID-19.

IMPORTANT NOTICE: Since the workshop will not be held in-site there
will be no registration fees!


The International Workshop on ?Artificial Intelligence for RAILwayS?
(AI4RAILS) is the first workshop specifically addressing topics
related to the adoption of Artificial Intelligence technologies in
railway applications. Supported by the Shift2Rail project RAILS,
AI4RAILS 2020 is the first of a series of workshops intended as a
reference forum for international researchers and industry
practitioners providing their novel ideas, results and experiences on
smart-railways in the general context of intelligent transportation

The aim of the 1st AI4RAILS workshop is to provide a forum for
researchers, practitioners and business leaders to discuss and share
new perspectives, ideas, technologies and solutions for effective and
dependable integration of AI techniques in rail-based transportation

More information, submission guidelines and contacts are available at
the workshop website.

AI4RAILS invites researchers, practitioners and business leaders to
present and discuss their latest research results on theory,
approaches and tools for design, development, operation and
maintenance of smart-railways by means of AI techniques.
Topics of interest include, but are not limited to:
– AI for railway safety, availability, reliability and security
– Transferability to railways of AI approaches from other sectors
(e.g., avionics, automotive, etc.)
– Autonomous and cooperative train driving, including virtual coupling
– Automatic detection of railway signals and obstacles
– Railway predictive maintenance and defect detection
– AI for rail traffic planning and management
– Adversarial perturbations to AI with a focus on railway case-studies
– Resource allocation with a focus on railway case-studies
– Run-time model checking and AI with a focus on railway case-studies
– Explainable and trustworthy AI in railway applications
– Safe autonomy standards and railway certification of compliance
– Railway datasets and real-world case studies

***Submission and Publication***
AI4RAILS 2020 invites original paper not submitted elsewhere,
presenting original contribution. Papers must be in English, up to 12
pages in Springer format, including references and appendices. Paper
submission instructions and publication details are available on the
workshop website.

The AI4RAILS proceedings will be published to Springer Communications
in Computer and Information Science (CCIS).
Distinguished papers will be invited to submit an extended version in
a dedicated Special Issue on high ranked journals.

***Important Dates***
Regular paper submission:  June 1, 2020
Authors notification: June 29, 2020
Camera-ready paper due: July 10, 2020

***Workshop Chairs***
Valeria Vittorini, University of Naples Federico II, Italy
Francesco Flammini, Mälardalen University & Linnaeus University, Sweden
Roberto Nardone, University Mediterranea of Reggio Calabria, Italy
Stefano Marrone, University of Naples Federico II, Italy

News: PhD Studentship on Artificial Intelligence for Railway Operations and Management

Type of research degree: PhD
Application deadline: Ongoing
Country eligibility: UK/EU (full) or International (only covering tuition fees)
Funding: Funded (UK/EU) or partially funded (international)
Prof Ronghui Liu and Dr Zhiyuan Lin
Institute for Transport Studies, University of Leeds, UK (with up to 1 year exchange opportunity at TU Delft, the Netherlands)

There is an exciting opportunity for a motivated student with research interests in optimisation, AI and their applications in transport planning.

Project description:

Applications are invited for a PhD studentship in innovative approaches in artificial intelligence for railway scheduling and operations, to be based in Institute for Transport Studies at University of Leeds. The position is an opportunity to combine cutting-edge research at the intersection of railway scheduling and artificial intelligence techniques such as machine learning, neural networks. The overall objective of the PhD research project is to investigate the potential of Artificial Intelligence (AI) in the rail sector and contribute to the definition of roadmaps for future research in operational intelligence and network management. In particular, the student will develop and compare different AI approaches, e.g. machine learning, deep and reinforcement learning, for railway traffic planning and management. He or she will have a chance to investigate using AI for solving combinatorial optimization problems, AI for supporting optimization models, with special focus on the optimization models for railway operations and management.

This PhD research forms part of the RAILS project, funded by EU Shift2Rail and in collaboration with other European universities from Italy, Sweden and the Netherlands. The student will have the opportunity to work with the academic leads from these institutions, including spending up to one year at Digital Rail Traffic Lab at TU Delft ( The project is suitable for a student with a top MSc (preferable) or first-class bachelor’s degree in artificial intelligence, transport, computer science, operational research (optimisation), mathematics, physics, or a subject of highly quantitative nature. Previous coursework or experiences in at least one of the above areas is necessary. A strong programming background will be essential for this project. Prior experiences in one or more of the following areas is desirable but not mandatory: supervised machine learning in transport prediction, transport timetabling/scheduling, and applying artificial intelligence in theoretical or real-world combinatorial optimisation problems.

To apply for the scholarship, please visit For informal enquiries about the position, please contact Professor Ronghui Liu ( or Dr Zhiyuan Lin ( with a short summary of your background and research interests in the technical themes mentioned above.

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