Performance Modeling of Agent-Aided Operator-Interface Interaction for the Control of Multiple UAVs
Bibliographic record
Abstract
The control of multiple uninhabited air vehicles (UAVs) is operator intensive and can involve high levels of workload. Feedback from operators indicates that improvements in operator interfaces would reap significant gains in system performance and effectiveness. Incorporating automation agents in UAV control stations has been proposed as a solution to reduce workload and improve overall human-machine performance. This research investigated the efficacy of agent-aided operator interfaces in a scenario that involved multiple UAVs with the interfaces modeled as part of the UAV tactical workstations of a maritime patrol aircraft. A performance model was developed to compare the difference between mission activities with and without agent aids that was reflected in task conflict frequency, number of ongoing tasks, and task completion time. The simulation results revealed that agent-aided interfaces permitted operators to continue working under high time pressure, resulting in critical tasks being achieved in reduced time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".