Understanding pilots’ acceptance to operate in an integrated airspace with crewed and uncrewed aircraft
Bibliographic record
Abstract
The safe integration of new and emerging technologies such as remotely piloted aircraft (RPA) into existing airspace will require pilots’ acceptance of such technology. Therefore, the main aim of the present research is to understand pilots’ willingness to operate with crewed and uncrewed aircraft in an integrated airspace. The research also aims to examine whether factors such as vertical separation, automation levels, and technology acceptance affect pilots’ level of airspace integration acceptance. Eighty-five pilots completed a battery of surveys, comprising a demographics questionnaire, a technology acceptance questionnaire, as well as a newly created Aircraft Separation Questionnaire. The results revealed a clear automation acceptance threshold in acceptance between automation levels 3 and 4, the point at which decision-making transitioned from the human to the automation. The analysis found no significant relationship between vertical separation and technology acceptance. These results illustrate that pilots are more receptive towards integrated airspace operations when controlling decisions are undertaken by a human.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".