Document Type

Article

Publication Date

2024

DOI

10.1186/s12544-024-00679-5

Publication Title

European Transport Research Review

Volume

16

Issue

1

Pages

58 (1-17)

Abstract

Digitalization is a key concept that transformed the various industries through technologies like Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twin (DT). Although innovations provided by the advancement of digitalization have paved the way for more efficient operations and products for transportation, the rail transportation sector struggles to keep up with the rest of the transportation industry, since trains are designed to last for decades, and the insufficient infrastructure investment leads to multiple railroad derailments across the globe. Therefore, the primary aim is to transform current railway systems into human-centric, adaptable, sustainable and future-proof networks, aligning with Industry 5.0 (I5.0) and Circular Economy (CE) model supported by the restorative and long-lasting design of the trains. This transformation necessitates leveraging digitalization and emerging technologies to address the needs of passengers, operators, and maintenance personnel. This article provides a comprehensive review focusing on the application of IoT, AI, CE principles, and digital twin trains to existing railway infrastructure and assets. The analysis delves into developing system architecture for proposed solutions and their impact on operation, maintenance, sustainability, and passenger comfort, supported by track record analysis. The integration of these technologies and concepts, particularly AI-powered services, is anticipated to yield immediate advancements in the digitalization of railway transportation, enhancing efficiency and safety measures.

Rights

© The Authors 2024.

This article is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Data Availability

Article states: "Not applicable."

Original Publication Citation

Sarp, S., Kuzlu, M., Jovanovic, V., Polat, Z., & Guler, O. (2024). Digitalization of railway transportation through AI-powered services: Digital twin trains. European Transport Research Review, 16(1), 1-17, Article 58. https://doi.org/10.1186/s12544-024-00679-5

ORCID

0000-0002-8719-2353 (Kuzlu), 0000-0002-8626-903X (Jovanovic)

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