No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

<p dir="ltr">Human interaction with different levels of automation, ranging from simpler decision aids to fully autonomous systems, is becoming increasingly common in society. This is particularly true in safety-critical applications. If humans exhibit inappropriate reliance, meaning depending either too much or too little, the consequences can range from failure in completing a task to injuring a human worker. For this reason, researchers have studied human reliance behavior on different levels of automation. Seminal results have shown that human reliance decisions are strongly influenced by their self-confidence and trust in the automation. However, even if a user trusts the automation, the environmental conditions may be sufficiently risky such that the user should not use it. Indeed, researchers have shown that risk perception can influence decisions, but despite this, relatively little research has studied human risk perception as it relates to decisions about reliance on automation. In this thesis, a new model for how human risk perception (RP) and human self-confidence (SC) affect their reliance on a visual aid is proposed and validated. A novelty of the model is its emphasis on the relative difference between RP and SC and demonstrating that this difference can accurately predict human reliance behavior. A secondary contribution of this thesis is the utilization of the model to design an algorithm that automatically decides when to provide the aid to the user. Main findings include the ability to calibrate a user’s cognitive state when using the algorithm that automatically provides the aid to the user. Another finding is the improvement in cognitive states during trials without the aid after trials in which an algorithm decided when to provide the aid. Other findings include analyses of the statistical differences in cognitive states based on an individual participant’s subpopulation membership. Extensions of these contributions to human-machine interaction contexts is discussed in future work.</p>

Drywall finishing operations have been associated with worker exposure to dust that contains known particulate respiratory health hazards, such as silica, talc, and mica. Despite the existence of engineering, work-practice, and personal-protective-equipment (PPE) control technologies for the mitigation of this hazard, worker exposures persist in the drywall finishing industry. This research employed a macroergonomic framework to evaluate this problem and identify barriers to dust control technology adoption in the key subsystems: personnel, technological, and organizational. In the first study, the organizational subsystem was evaluated through a telephone interview of 264 drywall finishing firm owners. This study found the most commonly used dust control technology was respiratory protection. Cost, usability, environmental factors, and productivity were barriers identified in preventing adoption of other technologies. In the second study, of the technological subsystem, 16 participants performed simulated drywall finishing tasks with each of four methods, in a laboratory setting. Dust particles were monitored and compared among the technologies used. Participants performed usability evaluations of the four tools. The ventilated sander produced less respirable-size class dust than did the other three tools. The block sander produced more dust than the other three tools. Usability evaluations revealed that the block sander was easiest to learn, easiest to use, and perceived to be the best overall, while the wet method and pole sander were considered to have poor usability in terms of ease of use and productivity. Usability problems associated with perceived comfort and ease of use were identified for the ventilated sander, but it was tied for "overall best" with the block sander. The third study, of drywall finishing worker perceptions, employed the Health Belief Model to assess barriers to technology adoption, risk, susceptibility, and benefits. Results showed that workers have a high perception of the risk associated with drywall dust, but a lower perception of individual susceptibility to disease as a result of occupational exposure. Barriers to the use of dust control technologies were identified as being associated with organizational and usability factors. Most participants indicated having access only to respiratory protection, among the available dust control methods. / Ph. D.