Abstract
Quantitative models of human-automation interaction can aid in the design of automation for effective human use. The application of signal detection theory (SDT), Bayesian analysis, and fuzzy SDT to the design of automated alerting and warning systems is discussed. SDT and Bayesian analysis can be used to design automated systems with high posterior probabilities of correct response to hazards. Fuzzy SDT can provide estimates of performance that better capture the temporal and contextual variability inherent in real-world hazards that need to be detected by automated warning systems.
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Schedule a callMore From: Human Factors and Ergonomics Society Annual Meeting Proceedings
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