ClarusC64/autonomous-driving-catastrophic-plausible-alternative-identification-v0.1

What this dataset tests Whether a system can identify the most dangerous coherent alternative within a counterfactual scenario tree. Danger is defined as: high plausibility high collapse severity short recovery window. Required outputs most_dangerous_branch_id initiating_agent trigger_action time_to_instability_s prevention_leverage_point countermeasure_suggestion Scoring conventions time_to_instability is seconds prevention leverage point names the earliest controllable step… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/autonomous-driving-catastrophi

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