Artificial intelligence in railway traffic planning and management Taxonomy, a systematic review of the state-of-the-art of AI, and transferability analysis
R. Tang (TU Delft - Transport and Planning, University of Leeds)
Zhiyuan Lin (University of Leeds)
Ronghui Liu (University of Leeds)
Rob M P Goverde (Transport and Planning)
Nikola Besinovic (Transport and Planning, Technische Universität Dresden)
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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.
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