State of the art of railway onboard systems for driver-machine cooperation

This research presents a comprehensive review of existing literature on train driver assistance systems and associated technologies suitable for onboard railway implementation. The primary objective is to systematically identify recent technological advancements, analyze their development patterns and prevalence, and gain a deeper understanding of current research trends in railway onboard systems. To achieve this, articles published since 2015 were retrieved from the Scopus database, resulting in a selection of 179 relevant studies. Each article was manually reviewed to ensure a thorough evaluation of its objectives, methodologies, and reported impacts. The selected studies were categorized into five key domains: train condition monitoring, which focuses on predictive maintenance and system health diagnostics; environment monitoring, addressing external conditions such as weather and track status; object detection, involving obstacle identification and collision avoidance; driver monitoring, which examines human factors such as attention, fatigue, and cognitive state; and brake assistance systems, aimed at improving safety and operational efficiency. This structured classification enabled a clearer comparison of technological maturity and research emphasis across different areas. Furthermore, the review explores opportunities to enhance human-machine cooperation by linking these findings with the latest developments in railway driver advisory systems (R-DAS). Based on this synthesis, four promising future research directions are identified: adaptive trajectory optimization for energy-efficient and context-aware driving, cooperative R-DAS (CR-DAS) enabling collaborative decision-making between human drivers and automation, human-in-the-loop (HITL) shared control strategies to balance authority between operator and system, and robust remote operation with reliable authority transfer mechanisms. These directions highlight the potential for more intelligent, adaptive, and cooperative onboard systems in next-generation railways.