Artificial intelligence in railways
Current applications, challenges, and ongoing research
Lorenzo De Donato (Università degli Studi di Napoli Federico II)
R. Tang (University of Leeds)
Nikola Bešinović (TU Delft - Transport and Planning, Technische Universität Dresden)
Francesco Flammini (Mälardalen University, Linnaeus University - Växjö)
R.M.P. Goverde (TU Delft - Transport and Planning)
Zhiyuan Lin (University of Leeds)
Ronghui Liu (University of Leeds)
Stefano Marrone (Università degli Studi di Napoli Federico II)
Elena Napoletano (Università degli Studi di Napoli Federico II)
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Abstract
This chapter presents applications, challenges, and opportunities for the integration of artificial intelligence in rail transport, based on the current results of the European project Roadmaps for AI integration in the rail sector (RAILS). Past and ongoing research directions are briefly outlined, and then the regulatory landscape is presented as well as the main barriers to overcome. Some technical aspects are addressed to provide some valuable references, and a high-level description of ongoing research work is given, spanning from innovative studies on smart maintenance, collision avoidance, delay prediction, and incident attribution analysis to visionary scenarios such as intelligent control and virtual coupling.