PhD Theses in Experimental Software Engineering, Band 67
Hrsg.: Frank Bomarius, Peter Liggesmeyer, Dieter Rombach; Fraunhofer IESE, Kaiserslautern
2020, 162 S., num. illus. and tab., Softcover
Software-controlled technical systems are omnipresent in our daily lives. In many domains, such as automotive, avionics, and robotics, engineers are currently building systems that act without human assistance, in only partly defined open environments. The most prominent example are self-driving vehicles. To achieve this automation in an open environment, technical systems need to be able to behave adequately in unthought-of situations. We refer to systems with this capability as autonomous systems.
Autonomous systems inevitably contain some degree of uncertainty regarding their behavior in such unthought-of situations. Consequently, it is not possible to analyze the full space of their behavior at development time. The current risk assessment approaches in Safety Engineering - the discipline responsible for creating systems with acceptable risk - rely on extensive analyses conducted during development time. This is not feasible for assessing the risk associated with the behavior of autonomous systems. This dissertation presents a novel approach for Dynamic Behavior Risk Assessment for autonomous systems to overcome this limitation.