The purpose of this research was to investigate the effects of varying the threshold of alarm systems and workload on human response to alarm signals and performance on a complex task. A receiver operating characteristic (ROC) curve was selected to reflect the sensitivity of the alarm system. The threshold of the alarm system was manipulated by changing the value of beta along the ROC curve. A total of 84 students participated in experiment 1 and 48 students participated in experiment 2. Participants performed a compensatory-tracking, a resource management and a monitoring task. As expected, results showed that participants responded significantly faster to true alarm signals when they were using the system with the highest threshold under low-workload conditions. Results also indicated that changing the threshold of the alarm system had a significant effect on overall performance and this effect was greater under high-workload conditions. However, contrary to expectations, the highest level of performance was achieved by setting the threshold at a low level. Results from both experiments revealed that the advantage of faster alarm reaction time as a result of increasing the system's threshold was lost because of its increased probability of missed events.

The purpose of this research was to examine the effects of system technology (binary vs. likelihood) and probability type (false-alarm prone vs. miss-prone) on trust, compliance and reliance using a false alarm forgiving task. Onehundred university students participated in this study. Participants completed three simulated flight missions composed of two primary flight tasks and a secondary engine-monitoring task. During the first mission, participants performed the engine-monitoring task without the aid of an automated alarm system. During the second and third sessions, participants had the opportunity to perform the engine-monitoring task with the aid of an alarm system. Results partially supported our hypotheses. Consistent with prior research, system probability type had a statistically main effect on trust. As expected, system technology and probability type had a statistically significant interaction effect on compliance. However, contrary to our prediction, results showed an unexpected interaction effect between system technology and probability type on reliance. The results of this study assist in defining the association among these three constructs and will aid in the future development of application principles for human-automation interaction.

We investigated the effects of false-alarm prone (FP) vs. miss-prone (MP) automation and the effects of likelihood alarm technology (LAT) on trust, reliance, and compliance. One hundred participants completed simulated unmanned aerial vehicle missions consisting of two primary tasks and a secondary weapon-deployment task aided by automation. It was predicted that MP automation would increase trust, LAT would increase trust, FP automation would increase reliance, and MP automation would increase compliance whereas LAT would decrease compliance when used with a FP system. Results indicated that trust was higher with the FP system, reliance was higher with the FP system, and compliance was higher with the MP system. This paper further informs the relationships among trust, reliance, and compliance, and it adds to our understanding of operator behavior in miss-prone tasks. Practical applications of this research include improving automation design and choosing the appropriate type of automation to implement for specific situations.

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Mental workload is one of the most important constructs of interests for Human Factors researchers. Adequately assessing the amount of mental workload that people experience while performing tasks under specific conditions is essential for the design of safe and efficient systems. Due to its ease of use, the NASA TLX has become the most widely used method of measuring mental workload. However, its psychometric properties are still questionable. The purpose of this study was to examine the extent of measurement invariance of the TLX and raise awareness in the Human Factors community. Two hundred participants reported the amount of mental workload they typically experience while driving in urban and rural areas and across the country. Results indicated that the TLX lacked scalar invariance, thereby biasing the estimation of mean scores and making the examination of mean differences misleading. These findings suggest that researchers should first examine the extent of measurement invariance of the TLX before they proceed to make inferences about mean differences in the amount of mental workload reported by participants under different conditions.