Artificial Intelligence in Railway Infrastructure: Current Research, Challenges, and Future Opportunities

W. Phusakulkajorn, Alfredo Nunez, Hongrui Wang*, Ali Jamshidi, Arjen Zoeteman, Burchard Ripke, Rolf Dollevoet, Bart De Schutter, Zili Li

*Corresponding author for this work

Research output: Contribution to journalLiterature reviewpeer-review

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The railway industry has the potential to strongly contribute to achieving various sustainable development goals by expanding its role in the transportation system of different countries. To realize that, complex technological and societal challenges are to be addressed, along with the development of suitable state-of-the-art methodologies fully tailored to the particular needs of the wide variety of railway infrastructure types and conditions. Artificial intelligence (AI) methods have been increasingly and successfully applied to solve practical problems in the railway infrastructure domain for over two decades. This paper proposes a review of the development of AI methods in railway infrastructure. First, we present a survey limited to selected journal papers published between 2010-2022. Bibliographical statistics are obtained, showing the increasing number of contributions in this field. Then, we select key AI methodologies and discuss their applications in the railway infrastructure. Next, AI methods for key railway components are analyzed. Finally, current challenges and future opportunities are discussed.
Original languageEnglish
Number of pages23
JournalIntelligent Transportation Infrastructure
Publication statusAccepted/In press - 2023


  • Railway Infrastructure
  • Artificial Intelligence
  • Machine Learning
  • Railway Track
  • Railway Catenary


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