Human-based dynamics of mental workload in complicated systems
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Date
2019-07-11
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Abstract
As a dynamic system in which different factors affect
human performance via dynamic interactions, mental workload needs a dynamic measure to monito
r its factors and evidence in a complicated system, an approach that is
lacking in the literature. The present study introduces a system dynamics-based model for designing feedback
mechanisms related to the mental workload through literature
review and content analysis of the previous studies.
A human-based archetype of mental workload was detected
from the data collection
process. The archetype is
presented at various stages, including dynamic theory, behavior over time, leverage points and model verification.
The real validation of the dynamic model was confirmed in an urban train simulator. The dynamic model can be
used to analyze the long-term behavior of the mental workload. Decision-makers can benefit from the developed
archetypes in evaluating the dynamic impact of their decisions on accident prevention in the complicated systems.
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Keywords
Mental workload, Ergonomics, Archetype, Review, System dynamics