Designing human-centered automation: trade-offs in collision avoidance system design

Human-centered automation problems have multiple attributes: an attribute reflecting human goals and capabilities, and an attribute reflecting automation goals and capabilities. In the absence of a general theory of human interaction with complex systems, it is difficult to define and find a unique optimal multiattribute resolution to these competing design requirements. We develop a systematic approach to such problems using a multiattribute decomposition of human and automation goals. This paradigm uses both the satisficing decision principle which is unique to two-attribute problems, and the domination principle which is a common manifestation of the optimality principle in multiattribute domains. As applied to human-centered automation in advanced vehicle systems, the decision method identifies performance evaluations and compares the safety benefit of a system intervention against the cost to the human operator. We illustrate the method by analyzing an automated system to prevent lane departures.