Artificial Intelligence in Railway Transport and Infrastructure Applications

Dear Colleagues,

This Special Issue aims to address the urgent needs of the railway industry by exploring innovative AI-driven solutions to revolutionize the sector. This issue will present the challenges faced by the industry, such as safety concerns, efficiency bottlenecks, and sustainability issues, and how AI can offer tangible improvements. This issue will also highlight the role of data analytics, predictive maintenance, and automated control systems in enhancing operational reliability and passenger experience. Ultimately, this Special Issue will serve as a roadmap for integrating AI technologies into the railway industry, paving the way for smarter, safer, and more efficient transportation networks.

• Focus: This issue will focus on the implementations of Artificial Intelligence (AI) in the railway sector, highlighting innovative applications that could enhance transport navigation and infrastructure maintenance.
• Scope: This issue will include empirical studies, theoretical frameworks, case studies, and reviews that demonstrate AI’s role in improving efficiency, safety, and sustainability in the railway system.
• Purpose: The purpose of the Special Issue is to provide a platform for researchers and industry professionals to publish the latest railway innovations, review existing state-of-the-art systems, discuss future challenges, and propose AI solutions.

This Special Issue will supplement existing literature by providing up-to-date case studies and research findings in AI applications for the railway industry. This issue will offer a comparative analysis of traditional methods versus AI-enhanced approaches, demonstrating the benefits and potential of AI in this urgent transport domain. In doing so, this issue will help enhance the modern railway systems with AI, presenting a deeper understanding of their transformative impact on the railway sector.

Topics of interest include but are not limited to the following:

• Rail timetable optimization;
• Passenger demand and flow prediction;
• Real-time traffic management;
• Infrastructure predictive maintenance;
• Smart ticketing and revenue management;
• Smart rail energy consumption;
• AI for rail signaling system;
• AI-enhanced surveillance system;
• Automatic rail infrastructure inspection;
• Sustainable rail innovations;
• Cybersecurity in rail systems;
• Survey of AI railway innovations.

Dr. Khuong An Nguyen
Dr. Stylianos Kapetanakis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• railway navigation
• rail asset management
• railway infrastructure monitoring
• smart rail
• railway logistics
• rail safety