metadata
language:
- en
license: mit
pretty_name: Autonomous Driving Human-Vehicle Coupling Coherence Scoring v0.1
dataset_name: autonomous-driving-human-vehicle-coupling-coherence-scoring-v0.1
tags:
- clarusc64
- autonomous-driving
- human-in-the-loop
- coupling
- trust
- driver-state
task_categories:
- tabular-classification
- time-series-forecasting
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 score coherence between driver state, vehicle behavior, and scene context.
This is not crash prediction. It is coupling integrity.
Required outputs
- coupling_coherence_score
- overassertive_flag
- underassertive_flag
- trust_stability_index
- takeover_risk_score
- recovery_margin
Scoring conventions
- all scores range 0 to 1
- flags are 0 or 1
- takeover risk estimates likelihood of manual override in the next window
Use case
Layer two of Driver-State and Vehicle-Response Coupling Manifold.
Supports:
- adaptive policy switching
- takeover risk management
- trust-preserving driving behavior