An Approach to Quantify Workload in a System of Agents

The role of humans in aviation and other domains continues to shift from manual control to automation monitoring. Studies have found that humans are often poorly suited for monitoring roles, and workload can easily spike in offnominal situations. Current workload measurement tools, like NASA TLX, use human operators to assess their own workload after using a prototype system. Such measures are used late in the design process and can result in expensive alterations when problems are discovered. Our goal in this work is to provide a quantitative workload measure for use early in the design process. We leverage research in human cognition to define metrics that can measure workload on belief-desire-intentions based multi-agent systems. These measures can alert designers to potential workload issues early in design. We demonstrate the utility of our approach by characterizing quantitative differences in the workload for a single pilot operations model compared to a traditional two pilo...

• Type: Journal
• Year: 2015
• Where: ATAL
• Authors: Richard Stocker, Neha Rungta, Eric Mercer, Franco Raimondi, Jon Holbrook, Colleen Cardoza, Michael A. Goodrich
• Keywords: ATAL 2015, Intelligent Agents