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Introducing robots to future construction sites will impose extra uncertainties and necessitate workers’ situational awareness (SA) of them. While previous literature has suggested that system errors, trust changes, and time pressure may affect SA, the linkage between these factors and workers’ SA in the future construction industry is understudied. Therefore, this study aimed to fill the research gap by simulating a future bricklaying worker-robot collaborative task where participants experienced robot errors and time pressure during the interaction. The results indicated that robot errors significantly impacted subjects’ trust in robots. However, under time pressure in time-critical construction tasks, workers tended to recover their reduced trust in the faulty robots (sometimes over-trust) and reduce their situational awareness. The contributions of this study lie in providing insights into the importance of SA in future jobsites and the need for investigating effective strategies for better preparing future workers.
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This content will become publicly available on July 13, 2026
AI-Driven Assistant for Worker Safety in Future Construction: Examining Opportunity and Challenges
The integration of robots, particularly drones, into future construction sites introduces new safety challenges requiring enhanced situational awareness (SA) among workers. To address these challenges, this study explores the effectiveness of an AI-driven assistant designed to inform workers about dynamic environmental changes via auditory and visual channels. A mixed-reality bricklaying experiment was developed, simulating worker-drone interactions across three interaction levels: coexistence, cooperation, and collaboration. One hundred five construction-background students participated in tasks with and without the AI assistant, during which their eye-tracking data, productivity, and subjective perceptions were collected. Results indicated that the AI assistant significantly expedited workers’ awareness of approaching drones but concurrently reduced bricklaying productivity. Although participants reported high perceived usefulness and low distraction by the AI assistant itself, findings revealed a trade-off: improved SA toward drones came at the cost of decreased task performance, likely due to increased attentional shifts toward drones. Furthermore, the effectiveness of the assistant varied depending on the interaction level with drones. This study highlights both the opportunities and challenges of applying AI-driven informational systems in future construction environments, offering critical insights for designing human-centered AI technologies that balance safety enhancement with productivity maintenance.
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- Award ID(s):
- 2128970
- PAR ID:
- 10614868
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Volume:
- 69
- Issue:
- 1
- ISSN:
- 1071-1813
- Format(s):
- Medium: X Size: p. 2104-2107
- Size(s):
- p. 2104-2107
- Sponsoring Org:
- National Science Foundation
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