AI4RAILS is the acronym of a series of workshops created within the RAILS project that address 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 timetabling, rolling stock and crew scheduling
- Real-time 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
- Transferability to railways of AI approaches from other sectors (e.g., aviation, road, etc.)
- Novel problems enabled by AI techniques
AI4RAILS Steering Committee
Please find below the members of the regular steering committee of the AI4RAILS workshop series:
- Rob Goverde, TU Delft Transport Institute, Netherlands
- Ronghui Liu, University of Leeds, United Kingdom
- Zhiyuan Lin, University of Leeds, United Kingdom
- Nikola Besinovic, Dresden University of Technology, Germany
- Valeria Vittorini, University of Naples Federico II, Italy
- Francesco Flammini, Mälardalen University & Linnaeus University, Sweden
AI4RAILS Editions
Please find below the links to past and current AI4RAILS workshop editions.