Hierarchical control and driving

This dissertation begins with an overview of skilled performance and how hierarchical control theory (HCT) has been successful in explaining skilled performance. Next, two novel premises of HCT are generated that provide evidence for distinct, hierarchical control systems (outer and inner loops). These control systems have unique properties and lead to very different predictions when applied to complex skills. By manipulating primary task predictability and secondary task workload of a complex skill, these properties can be dissociated. This is followed by an application of HCT to driving and driver distraction. I discuss how secondary task cognitive workload affects driving performance and how previous research has not explained paradoxical patterns of driving performance (i.e., lane maintenance). Then two premises of HCT are generated and used to make predictions about lane maintenance. Next, another influential theory of skilled performance (ACT-R) is discussed, and this theory is contrasted with HCT in terms of predictions regarding lane maintenance. Two experiments are designed to test HCT and differentiate it from ACT-R. The results support the predictions of HCT and suggest that ACT-R is somewhat limited in its ability to fully explain lane maintenance. HCT provides a framework for future driving research as well as future research on a variety of complex skills.