Combining Perception, Action, Intention and Value: A Control Theoretic Approach to Driving Performance

Driving is a prototypical example of a closed-loop control problem. This chapter presents a tutorial introduction to the logic of closed-loop systems and the implications for theory and research on driver performance. The human-vehicle system is parsed into three coupled components: (1) the problem constraints; (2) the observer constraints; and (3) the control constraints. This paper hopes to illustrate the importance of each component to a full appreciation of the closed-loop dynamic and to consider how the coupling across these components will determine the emergent stability of human-vehicle systems. This paper hopes that this tutorial will help to provide common ground between behavioral scientists and engineers, so that each can better appreciate how the human factor, the vehicle, and the driving ecology interact to shape system performance. This paper also hopes that this will provide a theoretical context for interdisciplinary driver research using simulators. There is a growing appreciation among those who study human performance that context matters. Thus, increasingly it becomes important to be able to evaluate performance under conditions that are representative of natural life experiences. Driving simulators provide a unique bridge between the complexity of natural environments and the demands for controlled observation in order to test hypotheses about human performance. This is equally important for addressing practical issues associated with training and design, as well as for basic issues associated with understanding adaptive cognitive systems.

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