Theoretical Implications and Practical Applications of the a-b Signal Detection Theory Model for Human-Automation Interaction

Abstract

The purpose of this research was threefold: 1) Present the a-b Signal Detection Theory (SDT) model as an alternative theoretical framework to overcome the limitations of traditional SDT, 2) Provide basic empirical support to validate the adequacy of the model, and 3) Show the potential generalizability of the model to different domain-specific areas within applied settings. The results from the basic empirical study suggest that the a-b SDT model provides a more accurate theoretical framework for examining the underlying processes involved in signal detection and decision making. Furthermore, the findings from the domain-specific study show the potential applicability and generalizability of the a-b SDT model for examining human-automation interaction. The end product of this work is particularly important for researchers and practitioners who are interested in applying a basic fundamental framework for examining how sensory, perceptual, and cognitive factors may affect humans' decision-making accuracy and response bias while interacting with automated systems in a wide range of applied settings.