Applying Causal Models for the Safety Analysis of Automated Transport Systems

Kurzfassung

The increasing degree of automation in classical transport systems promises many enhancements such as an increase in performance or improved resource economy. Safety is often mentioned as a main selling point of highly automated systems as the influence of the human operator as one of the most common risk factors is minimized. However, the introduction of highly automated systems entails new classes of hazards that are not relevant for the human operator and thus not represented in current accident data bases. To identify and prevent such hazards during the development phase, a causal understanding of the system and its operational design domain is required. In this talk, we explore how the framework of causal theory can be applied to support the safety analysis process of highly automated transport systems including the identification of appropriate risk mitigation measures.