The Effect of Visual System Time Delay on Helicopter Control
Bibliographic record
Abstract
There is interest in the development of synthetic visual systems to improve the capability of aircraft to takeoff and land in poor visibility. These systems often have inherent processing delays that can affect a pilot's ability to control an aircraft and a pilot's sense of orientation. The goal of the current study was to determine how much time delay a pilot could tolerate before control was affected, and whether physiological effects would be apparent at the same point. Pilots hovered at a predetermined position in a full flight simulator equipped with a Computer Image Generation (CIG) system and a helmet mounted display. The pilot's visual image was delayed by 67 to 334 milliseconds and varying levels of turbulence were applied to increase the task difficulty. Pilot performance was assessed by collecting objective data on aircraft position error. Handling qualities ratings and reports of physiological symptoms were collected by questionnaire. The results showed that visual time delay increased the variability of position error when as little as 134 ms of delay was encountered. At long delays, sickness symptoms were reported in addition to handing qualities decrements. Turbulence had a minimal effect on performance with long time delays, however it resulted in increased station keeping errors and degraded handling qualities at low delays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| 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 source (direct Gemma or distilled Codex), 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".