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Record W4412788123 · doi:10.1139/dsa-2024-0070

Understanding pilots’ acceptance to operate in an integrated airspace with crewed and uncrewed aircraft

2025· article· en· W4412788123 on OpenAlexvenueno aff
D. Vinod, Brett R. C. Molesworth

Bibliographic record

VenueDrone Systems and Applications · 2025
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsAeronauticsAir traffic controlComputer scienceEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.359
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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