Abstract
For complex systems that embed automation, but also rely on human interaction for guidance and contingency management, holistic models are needed that provide for an understanding of the individual human and computer elements, and address the critical interactions of such complex systems. Discrete event simulation (DES) models and system dynamics (SD) models are two different approaches that can be used to address these requirements. Both modelling approaches can support the designers of future autonomous vehicle (AV) systems by simulating the impact of alternate designs on vehicle, operator, and system performance. However, the DES modelling approach is likely best suited for using probabilistic distributions to accurately model an operator who is a serial processor of discrete tasks, as well as an environment with randomly occurring events. The SD modelling approach is better suited for modelling continuous performance feedback that is temporally dependent and is affected by qualitative variables such as trust.
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