Jing Xing

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Information complexity associated with visual displays is a bottleneck that limits their use. While automation tools are designed to bring new functions to users and increase their capacities, they also creates new tasks associated with acquiring and integrating information from displays. In particular, a complex display increases information load to human operators and reduces usability. Thus the efficiency of the tool largely depends on the complexity of displayed information. To evaluate the costs and benefits of an automation system, it is important to understand how much information is shown on the display, and whether the information is too complex for users to process. In this paper, we present a set of observable metrics to assess information complexity of visual displays. The metrics count information complexity as the combination of three basic factors: numeric size, variety, and relation; each factor is evaluated by the functions at three stages of brain information processing: perception, cognition, and action. Ideally, these measures provide an objective method to evaluate automation systems for acquisition and design prototypes.