Multiple mental models, automation strategies, and intelligent vehicle systems

Abstract

An automobile driver interprets and responds to sensory input according to the context established by a mental model-an internal representation employed to encode, predict, and evaluate the consequences of perceived and intended changes to the operator's current state within the dynamic environment. Skilled driving is organized into behavioral quanta that correspond to separate mental models, each with their own perceptually delineated operational domain. Automation design should account for these behavioral quanta and the resulting switches among multiple mental models. Two automation strategies are considered: management by consent and management by exception. Satisficing decision theory provides a framework of multiple interacting mental models that offers not only a description of switching of mental models with and without automation, but also guidelines for designers of vehicle automation systems.