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


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.


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

February 24, 2024

March 4th, 2024 (extended)

Deadline for short papers
February 24, 2024

March 8th, 2024 (extended)

  Deadline for abstracts
March 15, 2024 Abstract acceptance notification
March 17, 2024 Short paper acceptance notification
March 24, 2024   Deadline for camera-ready papers
March 24, 2024   Deadline for early registration
March 31, 2024   Deadline for the payment of the deposit at the discounted rates to the resort Le Dune (25% of the total amount due is requested). After this date, available rooms can be booked at higher rates by mail to by the same deposit.
June 30, 2024   Registration deadline for inclusion in the final program and deadline for payment of the balance to the resort “Le Dune”  
September 8-9, 2024 Workshop

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:

Please email your abstract directly to our AI4RAILS official email address:

Workshop Organizers

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


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