Mary Fendley, Ph.D. (Advisor); Subhashini Ganapathy , Ph.D. (Committee Member); Josh Ash, Ph.D. (Committee Member)
Master of Science in Industrial and Human Factors Engineering (MSIHE)
Human collaboration with targeting aids have allowed analysts to achieve a greater level of coordination and productivity in a variety of fields. This project investigates the impact that an Assisted Target Recognition (ATR) algorithm’s false alarm rate and the task Target of Interest (TOI) level has on user-system trust and use in a targeting decision task. Previous studies suggest that an increased number of false alarms in an ATR task negatively impacts analyst trust in the system. This study will further contribute to this research, aiming to provide a better framework for appropriate tolerance levels within ATR algorithms, utilizing pre-truthed ATR footage. Two studies, a pilot and a main study, were conducted. Participants performed computer simulated search tasks with or without the help of the detection aid at four false alarm rates. Trust and use in the decision aid were recorded by participant gaze behavior and a trust in automation scale.
Year Degree Awarded
Copyright 2020, all rights reserved. My ETD will be available under the "Fair Use" terms of copyright law.