Modeling Driver Vehicle Control in a Cognitive Architecture

Driver vehicle control models are important in understanding driving behavior and aiding design vehicle components. In this paper, we develop a computational model of driver vehicle control based on the queuing network-model human processor cognitive architecture. A comparison of the behavioral data collected with human drivers and the driver model for path following with speed change on straight and curved roads suggests that this computational model performs the speed and steering control tasks well.