Extending Three Existing Models to Analysis of Trust in Automation: Signal Detection, Statistical Parameter Estimation, and Model-Based Control

Human Factors
Thomas B Sheridan

Abstract

The objective is to propose three quantitative models of trust in automation. Current trust-in-automation literature includes various definitions and frameworks, which are reviewed. This research shows how three existing models, namely those for signal detection, statistical parameter estimation calibration, and internal model-based control, can be revised and reinterpreted to apply to trust in automation useful for human-system interaction design. The resulting reinterpretation is presented quantitatively and graphically, and the measures for trust and trust calibration are discussed, along with examples of application. The resulting models can be applied to provide quantitative trust measures in future experiments or system designs. Simple examples are provided to explain how model application works for the three trust contexts that correspond to signal detection, parameter estimation calibration, and model-based open-loop control.

References

Jan 1, 1974·Irish Journal of Medical Science·D J SheridanP B Gatenby
Sep 19, 1969·Science·C Starr
May 21, 2004·Human Factors·John D Lee, Katrina A See
May 1, 2010·Journal of Pediatric Nursing·Deborah L McBride
Aug 13, 2011·Human Factors·Joseph B LyonsAlex J Barelka
Nov 4, 2011·Human Factors·Peter A HancockRaja Parasuraman
Apr 16, 2015·Human Factors·Kevin Anthony Hoff, Masooda Bashir
Apr 29, 2015·Human Factors·Eric T ChanceyPoornima Madhavan

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