dataset
autonomous-driving-catastrophic-plausible-alternative-identification-v0.1
ClarusC64
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Overview
Name
autonomous-driving-catastrophic-plausible-alternative-identification-v0.1
Source
ClarusC64
Episodes
0
Robot count
0
Format
csv
Description
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-catastrophic-plausible-alternative-identification-v0.1.
Robots used
null