Abstract This extended abstract reports on recent industrial activities exploring pragmatic and controlled uses of AI in railway systems developed with formal methods. First, large language models are used to synthesize and query large-scale railway technical specifications, improving accessibility while requiring systematic human validation. Second, early experiments assess AI-assisted generation of interactive proof scripts for B method proof obligations, showing initial productivity gains but substantial research challenges. Third, AI-based perception is integrated into railway safety functions, where machine learning acts solely as a proposer whose outputs are redundantly checked by a formally verified safety controller. Finally, a proof of concept applies multimodal language models to relay-based railway interlocking systems, automatically transforming relay diagrams into propositional logic specifications applicable to new diagrams. The results confirm that AI-assisted formalization is feasible and accessible, opening promising perspectives for advancing automation and trustworthiness in railway formal verification.

The engineering of industrial systems, particularly in safety-critical domains such as railways, demands rigorous verification and validation processes to ensure system dependability. Formal methods have emerged as powerful tools to complement traditional software engineering practices. In the railway sector, which increasingly relies on complex, distributed, and cyber-physical control systems, formal methods have demonstrated particular value for many decades now. In this article, we provide a retrospective overview of the application of formal methods and tools in the railway domain, with emphasis on two prominent verification approaches and one frequently verified railway system: modeling and validation with the B method and tools and formal verification of interlocking systems by model checking. We explore their role in the design and development of key railway systems, highlighting both academic research and industrial success stories, as witnessed by international projects and initiatives. We conclude with an outlook on the potential of integrating AI and formal methods to enhance the efficiency of next-generation railway systems.

Formal methods encompass a wide choice of techniques and tools for the specification, development, analysis, and verification of software and hardware systems. Formal methods are widely applied in industry, in activities ranging from the elicitation of requirements and the early design phases all the way to the deployment, configuration, and runtime monitoring of actual systems. Formal methods allow one to precisely specify the environment in which a system operates, the requirements and properties that the system should satisfy, the models of the system used during the various design steps, and the code embedded in the final implementation, as well as to express conformance relations between these specifications. We present a broad scope of successful applications of formal methods in industry, not limited to the well-known success stories from the safety-critical domain, like railways and other transportation systems, but also covering other areas such as lithography manufacturing and cloud security in e-commerce, to name but a few. We also report testimonies from a number of representatives from industry who, either directly or indirectly, use or have used formal methods in their industrial project endeavours. These persons are spread geographically, including Europe, Asia, North and South America, and the involved projects witness the large coverage of applications of formal methods, not limited to the safety-critical domain. We thus make a case for the importance of formal methods, and in particular of the capacity to abstract and mathematical reasoning that are taught as part of any formal methods course. These are fundamental Computer Science skills that graduates should profit from when working as computer scientists in industry, as confirmed by industry representatives.

Securing a safety-critical system is a challenging task, because safety requirements have to be considered alongside security controls. We report on our experience to develop a security architecture for railway signalling systems starting from the bare ...

Abstract In this paper, we review software-based technologies already known to be, or expected to become essential for autonomous train control systems with grade of automation GoA 4 (unattended train operation) in existing open railway environments. It is discussed which types of technology can be developed and certified already today on the basis of existing railway standards. Other essential technologies, however, require modifications or extensions of existing standards, in order to provide a certification basis for introducing these technologies into non-experimental “real-world” rail operation. Regarding these, we check the novel pre-standard ANSI/UL 4600 with respect to suitability as a certification basis for safety-critical autonomous train control functions based on methods from artificial intelligence. As a thought experiment, we propose a novel autonomous train controller design and perform an evaluation according to ANSI/UL 4600. This results in the insight that autonomous freight trains and metro trains using this design could be evaluated and certified on the basis of ANSI/UL 4600 .