Thomas B Sheridan1. 1. Massachusetts Institute of Technology, Lexington, USA.
Abstract
OBJECTIVE: The objective is to propose three quantitative models of trust in automation. BACKGROUND: Current trust-in-automation literature includes various definitions and frameworks, which are reviewed. METHOD: 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. RESULTS: The resulting reinterpretation is presented quantitatively and graphically, and the measures for trust and trust calibration are discussed, along with examples of application. CONCLUSION: The resulting models can be applied to provide quantitative trust measures in future experiments or system designs. APPLICATIONS: 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.
OBJECTIVE: The objective is to propose three quantitative models of trust in automation. BACKGROUND: Current trust-in-automation literature includes various definitions and frameworks, which are reviewed. METHOD: 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. RESULTS: The resulting reinterpretation is presented quantitatively and graphically, and the measures for trust and trust calibration are discussed, along with examples of application. CONCLUSION: The resulting models can be applied to provide quantitative trust measures in future experiments or system designs. APPLICATIONS: 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.