Modeling Task Performance Using the Queuing Network Model Human Processor (QNMHP)
Erik M. Altmann, Axel Cleeremans, Christian D. Schunn, Wayne D. Gray · Psychology Press eBooks · 2001
Human performance modeling approaches (HPMAs) that are comprehensive and computational are particularly useful for engineering design. Current approaches have strengths in modeling a person’s actions, but lack underlying mathematical foundations on which to base predictions of time and capacity related performance measures. This paper presents a complementary approach that combines elements of the GOMS/Model Human Processor approach with the mathematical concepts and methods of queuing networks. Called the Queuing Network Model Human Processor (QNMHP), the approach provides quantitative predictions and theoretical insights regarding a person’s performance. The general queuing network and the approach are discussed with respect to human performance and neuroscience findings. The QNMHP is used to model reaction time tasks and the results compare favorably to prior literature; these findings are discussed briefly along with current efforts to model a driving task.