Digitalization of railway transportation through AI-powered services: digital twin trains

Abstract

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.

Keywords

• Digital twin trains
• Smart train
• Data-driven services
• Circular economy in railway