Queueing network modeling of human performance of concurrent spatial and verbal tasks

This article describes a three-node queueing network model of human multitask performance to account for interferences between concurrent spatial and verbal tasks. The model integrates considerations of single-channel queuing theoretic models of selective attention and parallel processing, multiple-resource models of divided attention, and provides a computational framework for modeling both the serial processing and the concurrent execution aspects of human multitask performance. The single-channel and the multiple-resource concepts and their applications in engineering models are reviewed. Experimental evidence in support of the queueing network model is summarized. The potential value of using queueing network methods to integrate currently isolated concepts of human multitask performance and in modeling human machine interaction in general is discussed.

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