Chapter 43: Combining Perception, Action, Intention and Value: A Control Theoretic Approach to Driving Performance
Handbook of Driving Simulation for Engineering, Medicine, and Psychology
Combining Perception, Action, Intention and Value: A Control Theoretic Approach to Driving Performance
John M. Flach, Wright State University
Richard J. Jagacinski, Ohio State University
Matthew R. H. Smith, Delphi Electronics and Safety
Brian P. McKenna, Resilient Cognitive Solutions
The Problem. 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. We hope 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. We hope 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. We hope that this will provide a theoretical context for interdisciplinary driver research using simulators. Role of Driving 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.
Abstraction Hierarchy, Control Theory, Optimal Control Model, Regulator Paradox, Observer, Stability
• The human-vehicle and the human-simulator systems are complex control systems.
• Control theory can provide an important framework when using simulators for performance evaluation to meet the applied goals of performance evaluation and training design.
• Control theory can provide an important framework for integrating simulators into basic research programs to evaluate humans as adaptive cognitive systems.
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Jagacinski, R. J., and Flach, J. M. (2003). Control theory for humans. Mahwah, NJ: Lawrence Erlbaum Associates.