| --- |
| language: |
| - en |
| license: mit |
| pretty_name: Pilot–Vehicle Loop Coherence State Estimation v0.1 |
| dataset_name: aviation-pilot-vehicle-loop-coherence-state-estimation-v0.1 |
| tags: |
| - clarusc64 |
| - aviation |
| - flight-safety |
| - human-machine |
| - control-loop |
| task_categories: |
| - tabular-regression |
| - tabular-classification |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train.csv |
| - split: test |
| path: data/test.csv |
| --- |
| |
| What this dataset tests |
|
|
| Whether a system can estimate the coherence |
| of the pilot–aircraft control loop |
| during abnormal phases. |
|
|
| Key insight |
| Loss of control begins |
| with loop misalignment |
| before any hard limits are exceeded. |
|
|
| Required outputs |
|
|
| - loop_coherence_index |
| - resonance_stability_band |
| - control_lag_profile |
| - correction_efficiency_score |
| - baseline_deviation |
| |
| Use case |
| |
| Layer one of Pilot–Vehicle Loop Coherence Under Stress. |
| Feeds attribution and adaptive intervention systems. |
| |
