Modeling of Stimulus-Response Secondary Tasks with Different Modalities while Driving in a Computational Cognitive Architecture
Abstract
This paper introduces a computational human performance model based upon the queueing network cognitive architecture to predict driver’s eye glances and workload for four stimulus-response secondary tasks (i.e., auditorymanual, auditory-speech, visual-manual, and visual-speech types) while driving. The model was evaluated with the empirical data from 24 subjects, and the percentage of eyes-off-road time and driver workload generated by the model were similar to the human subject data. Future studies aim to extend the types of voice announcements/commands to enable Human-Machine-Interface (HMI) evaluations with a wider range of usability test for in-vehicle infotainment system developments.
How to Cite:
Jeong, H. & Liu, Y., (2017) “Modeling of Stimulus-Response Secondary Tasks with Different Modalities while Driving in a Computational Cognitive Architecture”, Driving Assessment Conference 9(2017), 58-64. doi: https://doi.org/10.17077/drivingassessment.1615
Rights: Copyright © 2017 the author(s)
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