Designing automation for human use: empirical studies and quantitative models.
An emerging knowledge base of human performance research can provide guidelines for designing automation that can be used effectively by human operators of complex systems. Which functions should be automated and to what extent in a given system? A model for types and levels of automation that provides a framework and an objective basis for making such choices is described. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design when using the model. Four human performance areas are considered--mental workload, situation awareness, complacency and skill degradation. Secondary evaluative criteria include such factors as automation reliability, the risks of decision/action consequences and the ease of systems integration. In addition to this qualitative approach, quantitative models can inform design. Several computational and formal models of human interaction with automation that have been proposed by various researchers are reviewed. An important future research need is the integration of qualitative and quantitative approaches. Application of these models provides an objective basis for designing automation for effective human use.
Cognitive Science Laboratory, The Catholic University of America, Washington DC 20064, USA. parasuraman@cua.edu
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D001331:Automation; D006804:Ergonomics; D006801:Humans; D008328:Man-Machine Systems; D013647:Task Performance and Analysis; D014584:User-Computer Interface