ad-dataset-analysis
OfficialAnalyze autonomous driving safety data for crash metrics and risk assessment.
AuthorRoboSafe-Lab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill enables comprehensive analysis of crash data and safety metrics in the context of autonomous driving research, offering insights into traffic safety and potential improvements.
Core Features & Use Cases
- Crash Data Analysis: Analyze various crash databases like FARS, CRSS, GIDAS, and SHRP2 for safety metrics and exposure-based risk analysis.
- Surrogate Safety Metrics: Compute Time-to-Collision (TTC), Post-Encroachment Time (PET), and Deceleration Rate to Avoid Crash (DRAC) metrics.
- Safety Claims Statistical Analysis: Provide Poisson tests and required sample size calculations for safety demonstrations in autonomous driving systems.
- Use Case: With the ad-dataset-analysis Skill, you can perform a comparative safety analysis between an autonomous driving system and human driving by inputting crash and disengagement data, followed by matching ODD conditions and calculating relative risk.
Quick Start
Run the analysis on the crash dataset by providing the relevant data and executing the command 'calculate_crash_rates'.
Dependency Matrix
Required Modules
pandasnumpyscipystatsmodelsmatplotlibseabornpyprojgeopandaslifelinespymc3stanscikit-learn
Components
scriptsreferencesassets
💻 Claude Code Installation
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Please help me install this Skill: Name: ad-dataset-analysis Download link: https://github.com/RoboSafe-Lab/ad-safety-research-skills/archive/main.zip#ad-dataset-analysis Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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