Artificial intelligence in railway traffic planning and management Taxonomy, a systematic review of the state-of-the-art of AI, and transferability analysis

Ruifan Tang*, Zhiyuan Lin, Ronghui Liu, Rob M.P. Goverde, Nikola Bešinović

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeChapterScientificpeer-review

Abstract

In this chapter, applications of artificial intelligence (AI) in railway traffic planning and management (RTPM) are discussed. To begin, a definition of AI is offered with a particular emphasis on its relationship with RTPM. This is followed by a systematic literature review of the state-of-the-art of AI in RTPM covering strategic, tactical, and operational challenges. Next, a transferability analysis is conducted of AI approaches for traffic planning and management from related sectors to railways, specifically from aviation and road transport. The results show that the majority of AI research in RTPM is still in its infancy. Several future research areas that are important to academic and professional communities in AI and RTPM are identified based on reviews and analysis of transferability.
Original languageEnglish
Title of host publicationHandbook on Artificial Intelligence and Transport
EditorsHussein Dia
PublisherEdward Elgar Publishing
Chapter8
Pages222-248
Number of pages27
ISBN (Electronic)9781803929545
ISBN (Print)9781803929538
DOIs
Publication statusPublished - 2023

Keywords

  • Artificial intelligence
  • Railway traffic planning and management
  • Taxonomy
  • Literature review
  • Transferability analysis

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