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The human systems literature is littered with conceptual models of human-automation interaction presented as a basis for understanding and explaining human performance effects. Unfortunately, the discrete and ordinal nature of existing models of levels of automation limits reliable prediction of operator performance, workload and situation awareness (SA). This paper presents enhanced quantitative models for determination of system automation proportion (AP) and SA in human-in-the-loop systems, building on an earlier preliminary model. We refine the AP concept as a continuous measure of level of system automation and introduce a generalised SA function that accounts for operator characteristics. The AP is calculated using hierarchical task analysis according to information processing stages. An overall proportion is then calculated for the system. The practicality and feasibility of this model are verified through a case study. We further propose a relationship between the AP and operator SA responses, based on existing empirical research findings.
Liu et al. (Sun,) studied this question.