Evaluating AI-Based Components in Autonomous Railway Systems

Recent breakthroughs in n Artificial Intelligence (AI) are poised to transform many domains, including autonomous railway transportation systems. However, safety is essential in this high-stake, safety-critical domain. To ensure compliance with current safety certification standards, we propose a comprehensive methodology for evaluating AI-based components in railway applications. It combines ontology-driven systematic testing and data generation, formal verification techniques, and real-time monitoring. By leveraging these methods, we provide a comprehensive safety assurance and hopefully pave the way for the widespread adoption of AI in railway transportation systems.