Warden, Amelia C., authorCleary, Anne, advisorWickens, Christopher D., advisorGraham, Dan, committee memberArefin, Mohammad, committee member2024-09-092024-09-092024https://hdl.handle.net/10217/239265In large complex environments, such as urban driving or flying a plane, human attention may be overloaded, leading to negative consequences when encountering expected and unexpected hazards, like pedestrians crossing the street or a cart on the runway. In such situations, the searcher may benefit from attention cues presented with an HMD. The current experiments address gaps in HMD attention cueing by investigating the effectiveness of different cue properties: cue precision, dual-cueing, cue frame-of-reference, and the impact of imperfectly reliable automation. In all three experiments, participants searched for a routine target (cued or uncued) and an uncued, less expected high priority target. Search efficiency was examined across three different platforms with increasing search field sizes and realism: a static search with a 2D wide-angle desktop display (Experiment 1), a static search presented with an augmented-reality head-mounted display (AR-HMD; Experiment 2), and dynamic search in a 3D virtual reality environment (Experiment 3). Search performance benefited from cueing compared to an unaided search in all experiments. Dual-cueing provided the greatest benefit with the AR-HMD when the searcher's field-of-view (FOV) was constrained by the device's FOV because the searcher benefited from a global cue that indicated which direction they could find the locally cued target. While cueing improved search efficiency, cues showed an overall automation bias, with searchers blindly following incorrect automation. This bias was slightly amplified by the dual cue compared to the single cue. Lastly, there was a trend suggesting automation-based attentional tunneling, where the uncued, less expected high priority target was missed. Overall, attention cueing significantly enhances search performance, particularly with dual cues when targets appear outside of the searcher's FOV. But cueing also introduces an automation bias. These findings have design implications for optimizing automated cueing systems for various platforms to enhance hazard detection in real-world large scenes.born digitaldoctoral dissertationsengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.augmented realityhead-mounted displaysvisual searchdisplay designattentionvirtual realityText