Modeling the effect of loudness and semantics of speech warnings on human performances

Yiqi Zhang, Changxu Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The quantitative prediction and understanding of human performances in the responses to speech warnings is an essential component to improve warning effectiveness. Queuing network-model human processor (QN-MHP), as a computational architecture, enables researchers to model dual-task information processing. The current study enhanced QN-MHP by modelling the effect of loudness and semantics on human responses to speech warning messages. The model predictions of crash rate were validated with two empirical studies in collision warning systems with resultant R squares of 0.73 and 0.77, respectively. The developed mathematical model could be further utilized in optimizing the design of speech warnings to achieve most safety benefits.

Original languageEnglish (US)
Title of host publication2014 International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014
PublisherHuman Factors an Ergonomics Society Inc.
Pages817-821
Number of pages5
ISBN (Electronic)9780945289456
DOIs
StatePublished - 2014
Event58th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014 - Chicago, United States
Duration: Oct 27 2014Oct 31 2014

Publication series

NameProceedings of the Human Factors and Ergonomics Society
Volume2014-January
ISSN (Print)1071-1813

Other

Other58th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2014
Country/TerritoryUnited States
CityChicago
Period10/27/1410/31/14

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics

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