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Project # 67
Optimizing Cognitive Workload Management for Remote UAV Operations in High Drone-to-Operator Ratios
| Team Lead: | Jose Lopez |
| Other Team Members: | |
| Faculty Advisor(s): | Shuchisnigdha Deb |
| Department: | IMSE |
| Project Type: | REU |
| Title: | Optimizing Cognitive Workload Management for Remote UAV Operations in High Drone-to-Operator Ratios |
| Abstract: | Cognitive workload plays a pivotal role in the safety and efficiency of drone operations, particularly as these systems grow in complexity and demand. This study presents a comprehensive literature review to explore how cognitive workload is measured, managed, and mitigated in unmanned aerial vehicle (UAV) operations. Key research themes include task complexity, measurement techniques, and operator interface design. The insights from this review are incorporated into a conceptual framework that captures the dynamic interplay between task characteristics, operators' individualistic factors, and environmental influences. This framework provides a foundation for advancing drone operation safety and optimizing operator cognitive workload and performance. The findings highlight critical gaps in current research, particularly in multi-operator scenarios and adaptive automation, offering a roadmap for future studies and practical applications. |
| Poster: | View Poster #67 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |