About this Research Topic

Background

The railway is widely recognized as an environmentally friendly transportation system worldwide. Consequently, the utilization of railway transportation systems in various countries is experiencing significant growth. However, ensuring the sustainability of railway systems necessitates addressing key challenges such as monitoring, maintenance, retrofitting, and rehabilitation of railway tracks. These aspects are vital to maintaining a safe and reliable railway operation. Unfortunately, unforeseen defects or damages, coupled with insufficient information about the geometry and structural conditions of the tracks, can compromise train safety. Consequently, train derailments and other unfortunate incidents can occur, resulting in substantial damage to tracks, trains, and potential injuries or fatalities to passengers. Given this context, the monitoring and assessment of railway track conditions, including structure and geometry, are of utmost importance.

To address these challenges, researchers have been actively involved in enhancing approaches to monitoring railway track conditions and predicting optimal maintenance timing. In recent years, the application of Artificial Intelligence (AI) has gained traction in solving critical engineering problems worldwide. It has been noted that AI can contribute to the development of effective tools and solutions to tackle diverse issues. Consequently, several AI-based approaches and methods have been developed to monitor and evaluate the health condition of railway tracks. However, a review of prior studies reveals that not all aspects and capabilities of AI have been fully explored in this domain. Therefore, further attention should be given to the application of AI in the monitoring, maintenance, and rehabilitation of railway tracks.

The objective of this special issue is to focus on studies that explore and showcase the application of AI in addressing the monitoring, maintenance, and rehabilitation of railway tracks. By delving deeper into this topic, we aim to contribute to the advancement of knowledge and the development of innovative solutions in the field. We welcome research that examines various AI-based approaches, highlighting their potential effectiveness and practicality in addressing the challenges faced in rail track management.


This Research Topic covers different specific themes. The manuscripts published in this special issue should include but are not exclusive to the research areas described below:

- Application of artificial intelligence on different aspects of railway transportation system

- Application of artificial intelligence on maintenance of railway track

- Application of artificial intelligence on rehabilitation of railway track

- Application of artificial intelligence on monitoring of railway track

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Editorial
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review

Keywords: Artificial Intelligence, Railway transportation system, Maintenance, Rehabilitation, Monitoring, Railway track

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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