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An evaluation of the urgency, similarity, and identification of aural alerts with implications for flight deck use

The only way to simplify and promote the effective use of an alerting system that must be comprehensive in its coverage of hazardous or non-normal conditions is to convey top level information that provides an indication of criticality and identity. In order to prevent the continued proliferation of aural alerting signals presented in the flight deck, a simple aural alert categorization scheme that provides flight deck function and urgency level information was proposed and evaluated in this study. Specifically, the present investigation examined the ability of a population having "normal" hearing to: 1) distinguish among four sets of aural alerting signals having distinctive rhythmic patterns and pitch contours, 2) perceive three urgency levels having distinctive tempos within each alerting set, and 3) associate each alerting set and its related urgency levels with one of the four major flight deck functions. Magnitude estimation ratings revealed that subjects perceived differences between low urgency level alerts and moderate urgency level alerts and between low urgency level alerts and high urgency level alerts. Pair comparison ratings of similarity revealed that subjects differentiated among the four within of the alerting sets relatively well after participating in a brief training session. alerting sets. A sound identification task revealed that subjects were able to associate functional categories with four aural alerting sets and were also able to simultaneously distinguish among and perceive three urgency levels within each of the alerting sets relatively well after participating in a brief training session. / Master of Science

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/45076
Date07 October 2005
CreatorsBurt, Jennifer L.
ContributorsIndustrial and Systems Engineering, Casali, John G., Prestrude, Albert M., Williges, Robert C.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
LanguageEnglish
Detected LanguageEnglish
TypeThesis, Text
Formatx, 146 leaves, BTD, application/pdf, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/
RelationOCLC# 36516346, LD5655.V855_1996.B878.pdf

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