Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Telerobotics, automation, and human supervisory control
Telerobotics, automation, and human supervisory control
Simulation Modeling and Analysis
Simulation Modeling and Analysis
ACM Transactions on Computer-Human Interaction (TOCHI)
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations
An Introduction to MultiAgent Systems
An Introduction to MultiAgent Systems
Identifying Predictive Metrics for Supervisory Control of Multiple Robots
IEEE Transactions on Robotics
Queuing Network Modeling of Driver Workload and Performance
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
Queueing network modeling of human performance of concurrent spatial and verbal tasks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Validating human-robot interaction schemes in multitasking environments
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Predicting Controller Capacity in Supervisory Control of Multiple UAVs
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Discrete-event simulations for futuristic unmanned vehicle (UV) systems enable a cost- and time-effective methodology for evaluating various autonomy and human-automation design parameters. Operator mental workload is an important factor to consider in such models. We suggest that the effects of operator workload on system performance can be modeled in such a simulation environment through a quantitative relation between operator attention and utilization, i.e., operator busy time used as a surrogate real-time workload measure. To validate our model, a heterogeneous UV simulation experiment was conducted with 74 participants. Performance-based measures of attention switching delays were incorporated in the discrete-event simulation model by UV wait times due to operator attention inefficiencies (WTAIs). Experimental results showed that WTAI is significantly associated with operator utilization (UT) such that high UT levels correspond to higher wait times. The inclusion of this empirical UT-WTAI relation in the discrete-event simulation model of multiple UV supervisory control resulted in more accurate replications of data, as well as more accurate predictions for alternative UV team structures. These results have implications for the design of future human-UV systems, as well as more general multiple task supervisory control models.