Welcome to AI4RAILS 2026

The 7th International Workshop on “Artificial Intelligence for RAILwayS”

co-located with the International Conference on Optimization and Decision Science – ODS2026

September 7 – 8 (provisional), 2026, Venice, Italy

Artificial Intelligence is becoming increasingly integral to the evolution of modern railway systems, supporting advancements in automation, operations and service delivery. As railways embrace digitalisation, AI offers significant opportunities to enhance efficiency, capacity and overall performance. Similar trends can be observed across other sectors such as logistics and manufacturing, where AI adoption continues to deliver substantial benefits. At the same time, the growing use of AI introduces ongoing challenges related to safety, reliability and security that require careful consideration.

Now in its 7th year, the AI4RAILS workshop provides an established annual forum for researchers, practitioners and industry leaders to exchange insights on the dependable application of AI in rail-based transport. Building on the foundations set by the RAILS project (Roadmaps for A.I. Integration in the Rail Sector, funded by Shift2Rail), the workshop continues to support a growing community focused on both the opportunities and the responsible deployment of AI within the railway domain.

Each year, the programme features:

• A keynote lecture from a leading expert
• Technical presentation sessions (detailed programme announced closer to the event)

The workshop aims to foster ongoing dialogue, share practical experiences and highlight emerging research directions that support the safe and effective integration of AI technologies into contemporary railway systems.

Keynote talk

To be announced

Themes and Goals

AI4RAILS workshop is addressing topics related to the adoption of artificial intelligence technologies in railway transport. AI4RAILS is set to showcase AI opportunities over the holistic railway system including traffic planning and management, passenger mobility, predictive maintenance, autonomous driving, transport safety and policy, and including mainline and high-speed railways, metro, tram, and hyperloop. We welcome various applications of AI including machine learning, neural networks and reinforcement learning, evolutionary algorithms, computer vision, large language model (LLM) applications and knowledge-based approaches in railway transport for both freight and passenger transport. Also, both pure AI models as well as hybrid models combining AI and optimization are foreseen.

Topics of interest include, but are not limited to:

• AI for rail traffic state predictions
• AI for train timetabling, rolling stock and crew scheduling
• Self-organising, decentralised and conventional real-time rail traffic and disruption management
• Railway predictive maintenance and defect detection and prediction
• Predicting passenger demand and flows
• Data analytics for railway transport
• Using AI for improving optimization models for planning and management
• Using optimization for improving machine learning models
• Using large language models (LLMs) for improving railway systems and services
• Novel problems enabled by AI techniques
• Autonomous and cooperative driving, including virtual coupling
• Cognitive Digital Twins for Railways
• Explainable and trustworthy AI in railway applications
• Transferability to railways of AI approaches from other sectors (e.g., aviation, road, etc.)
• Datasets and real-world case studies

Important Dates

To be announced

Short paper / abstract submission

All researchers, academics, practitioners, and students working on the conference themes are invited to participate to ODS2024/AI4RAILS2024 submitting either a short paper (8-10 pages, including front matter and references) or an abstract (max 2000 characters, space included). Please use the official Word template provided by the conference.

Submit your abstract/paper via the official ODS submission system and select the “AI4RAILS” option.

Workshop Organizers

• Paola Pellegrini, Gustav Eiffel University, France
• Nikola Bešinović, Technical University of Dresden, Germany
• Zhiyuan Lin, University of Leeds, United Kingdom

Workshop Program Committee

• Nikola Bešinović, Technical University of Dresden, Germany
• Valentina Cacchiani, University of Bologna, Italy
• Lorenzo De Donato, Unversity of Naples Federico II, Italy
• Francesco Flammini, Mälardalen University & Linnaeus University, Sweden
• Rob Goverde, TU Delft Transport Institute, Netherlands
• Bisheng He, Southwest Jiaotong University , China
• Zhiyuan Lin, University of Leeds, United Kingdom
• Ronghui Liu, University of Leeds, United Kingdom
• Zhenliang Ma, Royal Institute of Technology (KTH), Sweden
• Stefano Marrone, University of Naples Federico II, Italy
• Roberto Nardone, University of Naples “Parthenope”, Italy
• Paola Pellegrini, Gustav Eiffel University, France
• Felipe Rodrigues, Technical University of Denmark
• Stefania Santini, University of Naples Federico II, Italy
• Valeria Vittorini, University of Naples Federico II, Italy
• Pengling Wang, Tongji University, China
• Jiateng Yin, Beijing Jiaotong University, China
• Shuguang Zhan, Hefei University of Technology, China
• Yongqiu Zhu, TU Delft Transport Institute, Netherlands

Contact

For all questions related to the workshop, contact the organizers via email: [email protected]

Welcome to AI4RAILS 2025

The 6th International Workshop on
“Artificial Intelligence for RAILwayS”

co-located with the 20th European Dependable Computing Conference

 For more information please visit the AI4RAIL2025 website

Welcome to AI4RAILS 2024

The 5th International Workshop on “Artificial Intelligence for RAILwayS”

co-located with the International Conference on Optimization and Decision Science – ODS2024

September 8th-9th (provisional), 2024, Badesi, Sardinia, Italy

The impact of Artificial Intelligence (AI) on the industry has been so disruptive that it gave rise to a new wave of research and applications. Several industries, mainly in logistics and manufacturing, have benefited significantly from AI adoption and this positive trend is planned to be kept in the future. Modern and future railways represent one of the fields in which AI is expected to have a significant impact in a medium to long term perspective, to get higher levels of automation. Despite this opening for unprecedented scenarios in railway systems, it also raises concerns regarding system dependability and new threats associated with a high level of autonomy.

Therefore, the first step towards the adoption of AI in the railway sector is understanding to what extent AI can be considered reliable, safe and secure. In such a context, building upon the  RAILS project (Roadmaps for A.I. Integration in the Rail Sector, funded by Shift2Rail) the annual AI4RAILS workshop series are organized with the aim to provide annually 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 transport systems.

The program includes:

• Keynote speaker’s talk
• Technical presentation sessions: detailed program will be announced later.

Keynote talk

Hybrid OR-AI algorithms for Railway Traffic Management

Speaker: Prof Paola Pellegrini, Université Gustave Eiffel

Abstract: 

Real-time railway traffic management is a challenging task that is mostly carried out manually today. Several models have been proposed in the literature, and OR techniques have been used for optimizing this task. A promising research direction consists in exploiting AI techniques in combination to OR ones for optimizing traffic. This talk will present three different approaches for hybridizing AI and OR for railway traffic management optimization. First, an Ant Colony Optimization-MILP algorithm will show how we can reduce the search space of instances to promising regions, and achieve their effective exploration. Second, a Graph Convolutional Network-MILP algorithm will allow optimizing traffic considering passenger demand prediction. Third, a consensus-MILP algorithm will make self-organizing traffic an actual option for the railway system. Some unexplored research directions on hybrid AI-OR approaches for railway traffic management will be sketched to conclude the talk.

Bio:

Prof Paola Pellegrini is an expert in railway planning and operational management. Her research focuses on the development of optimization approaches to effectively exploit railway infrastructure capacity, aiming to the automation of the involved processes. Paola has participated in a number of national and international research projects, and she regularly collaborates with various SMEs to facilitate the knowledge transfers from academia to practice. She is a member of the Board of the International Association of Railway Operations Research (IAROR).

Themes and Goals

AI4RAILS workshop is addressing topics related to the adoption of artificial intelligence technologies in railway transport. AI4RAILS is set to showcase AI opportunities over the holistic railway system including traffic planning and management, passenger mobility, predictive maintenance, autonomous driving, transport safety and policy, and including mainline and high-speed railways, metro, tram, and hyperloop. We welcome various applications of AI including machine learning, neural networks and reinforcement learning, evolutionary algorithms, computer vision and knowledge-based approaches in railway transport for both freight and passenger transport. Also, both pure AI models as well as hybrid models combining AI and optimization are foreseen.

Topics of interest include, but are not limited to:

• AI for rail traffic state predictions
• AI for train timetabling, rolling stock and crew scheduling
• Self-organising, decentralised and conventional real-time rail traffic and disruption management
• Railway predictive maintenance and defect detection and prediction
• Predicting passenger demand and flows
• Data analytics for railway transport
• Using AI for improving optimization models for planning and management
• Using optimization for improving machine learning models
• Novel problems enabled by AI techniques
• Autonomous and cooperative driving, including virtual coupling
• Cognitive Digital Twins for Railways
• Explainable and trustworthy AI in railway applications
• Transferability to railways of AI approaches from other sectors (e.g., aviation, road, etc.)
• Datasets and real-world case studies

Important Dates

Short paper / abstract submission

All researchers, academics, practitioners, and students working on the conference themes are invited to participate to ODS2024/AI4RAILS2024 submitting either a short paper (8-10 pages, including front matter and references) or an abstract (max 2000 characters, space included). Please use the official Word template provided by the conference: http://www.airoconference.it/ods2024/submissions

Please email your abstract directly to our AI4RAILS official email address: [email protected]

Workshop Organizers

• Andrea D’Ariano, Roma Tre University, Italy, [email protected]
• Nikola Bešinović, Technical University of Dresden, Germany, [email protected]
• Zhiyuan Lin, University of Leeds, United Kingdom, [email protected]

Workshop Program Committee

• Valentina Cacchiani, University of Bologna, Italy
• Lorenzo De Donato, Unversity of Naples Federico II, Italy
• Francesco Flammini, Mälardalen University & Linnaeus University, Sweden
• Rob Goverde, TU Delft Transport Institute, Netherlands
• Bisheng He, Southwest Jiaotong University , China
• Ronghui Liu, University of Leeds, United Kingdom
• Zhenliang Ma, Royal Institute of Technology (KTH), Sweden
• Stefano Marrone, University of Naples Federico II, Italy
• Roberto Nardone, University of Naples “Parthenope”, Italy
• Paola Pellegrini, Gustav Eiffel University, France
• Felipe Rodrigues, Technical University of Denmark
• Stefania Santini, University of Naples Federico II, Italy
• Valeria Vittorini, University of Naples Federico II, Italy
• Pengling Wang, Tongji University, China
• Jiateng Yin, Beijing Jiaotong University, China
• Shuguang Zhan, Hefei University of Technology, China
• Yongqiu Zhu, TU Delft Transport Institute, Netherlands

Contact

For all questions related to the workshop, contact the organizers via email.