Computational modeling allows researchers to simulate driver behavior and explore the parameters and constraints of this behavior. This study explores the development of a rigorous computational model of driver behavior in a cognitive architecture--a computational framework with underlying psychological theories that incorporate basic properties and limitations of the human system. An integrated driver model developed in the Adaptive Control of Thought-Rational cognitive architecture is described that focuses on the component processes of control, monitoring and decision making in a multilane highway environment. The model accounts for the steering profiles, lateral position profiles and gaze distributions of drivers during lane keeping, curve negotiation and lane changing. This model demonstrates how cognitive architecture can facilitate understanding of driver behavior in the context of general human abilities and constraints. It also demonstrates how the driving domain can benefit cognitive architecture by pushing model development toward more complex and realistic tasks.
Abstract