Modeling driver behavior in a cognitive architecture.
OBJECTIVE
This paper 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.


BACKGROUND
Computational modeling has emerged as a powerful tool for studying the complex task of driving, allowing researchers to simulate driver behavior and explore the parameters and constraints of this behavior.


METHODS
An integrated driver model developed in the ACT-R (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.


RESULTS
This model accounts for the steering profiles, lateral position profiles, and gaze distributions of human drivers during lane keeping, curve negotiation, and lane changing.


CONCLUSIONS
The model demonstrates how cognitive architectures facilitate understanding of driver behavior in the context of general human abilities and constraints and how the driving domain benefits cognitive architectures by pushing model development toward more complex, realistic tasks.


CONCLUSIONS
The model can also serve as a core computational engine for practical applications that predict and recognize driver behavior and distraction.
Salvucci
Dario D
DD
Department of Computer Science, Drexel University, 3141 Chestnut St., Philadelphia, PA 19104, USA. salvucci@cs.drexel.edu
D001334:Automobile Driving / Q000523:psychology*; D003071:Cognition; D006801:Humans; D008960:Models, Psychological; D014481:United States