Right on Time: Required Time of Arrival (RTA) to Anticipate Human factors Issues with Trajectory Based Operations (TBO)
Bibliographic record
Abstract
The future Trajectory-Based Operation (TBO) management method aims to increase the efficiency and predictability of flight operations. The use of time constraints, such as Required Time of Arrival (RTA) at specific points throughout the flight, enables flight trajectories to be better controlled. In this study, we conducted seven interviews with air traffic controllers, pilots, and civil aviation engineers to analyze the RTA management in the current airspace and to identify differences expected with its use in TBO. We found that in the current airspace, RTAs are used tactically to resolve short-term conflicts, which limits their benefits compared to a more strategic approach. From the pilots’ perspective, accepting RTAs requires an in-depth analysis of its impacts on the mission. Temporal information displayed in the cockpit is limited to support pilots’ decision-making. These results highlight the importance of studying human factors for RTA management in current airspace to address the challenges and limitations expected within TBO.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".