Roadmaps for AI Integration in the Rail Sector: Current Project Results and Overview of Case-Studies
Artificial Intelligence (AI) is increasingly affirming as a game-changer technology in several sectors, including rail transport. The overall objective of the H2020 Shift2Rail project RAILS (Roadmaps for AI Integration in the raiL Sector) is to investigate the potential of AI in the rail sector and to contribute to the definition of roadmaps for future research in the context of railway maintenance and inspection, autonomous train driving, and traffic planning and management.
This seminar will provide a high-level overview of the RAILS project, presenting the main topics, objectives, ongoing research activities, and preliminary results achieved. Particular attention will be given to the current investigations towards the application of Deep Learning approaches to improve the maintainability of railway assets and the safety of autonomous trains. To be specific, two main case studies will be discussed, and recent advancements presented, concerning smart maintenance at level crossings and vision-based obstacle detection on rail tracks.
Speaker: Lorenzo De Donato (Visiting PhD at LNU), Ph.D. Student in Information Technology and Electrical Engineering, Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy