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Automation has been changing the types and causes of hazards, and influencing the way in which users interact with complex systems, particularly challenging the notion of human control as a primary basis for hazard mitigation. In this paper, we explore this challenge and use an automotive driving example to examine the distributed nature of the driving task. We define an Enhanced Vehicle Control Model (VCM) that extends the notion of controllability and joint cognition for highly automated tasks. We apply the model to three contemporary driver assistance systems by undertaking a scenario-based evaluation. As a conceptual model, the Enhanced VCM shows potential to proactively identify the hazard causes associated with a joint cognitive control. However, to provide utility and to become an effective tool for the system analyst, an accompanying methodology is needed. This is the focus of our ongoing research.

Presents a collection of slides covering the following topics: in-wheel motors; risk management; ISO 26262 standards; automotive engineering: hazards: driver controls and safety.

In the automotive domain the standard ISO 26262 places significant emphasis on the assignment of Automotive Safety Integrity Levels (ASILs). In particular much of Part 3 of the standard is dedicated to the process that determines the three factors that contribute to the final assigned ASIL value: exposure, severity and controllability. In this paper we examine some of the issues that the authors have encountered during the development of an in-wheel electric motor and will argue that the perceived emphasis on ASIL ratings, in the context of developing a safe system, is misplaced and potentially counterproductive. (8 pages)