ad-foundation-models
OfficialEmpower AD research with advanced foundation models and safety insights.
AuthorRoboSafe-Lab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides comprehensive knowledge on foundation models for autonomous driving, including VLAs, E2E driving, LLM/VLM planning, and safety implications.
Core Features & Use Cases
- Understanding VLAs: Deep dive into Vision-Language-Action models, including RT-2, OpenVLA, and DriveVLM.
- E2E Autonomous Driving: Explore evolution, key methods like UniAD and SparseDrive, and evaluation benchmarks.
- Safety Implications: Grasp critical challenges like hallucination, latency, and distributional shift in foundation models.
- Safety Architecture: Learn about patterns like Foundation Model + Safety Filter and Hierarchical with Safety Monitor.
- Research Frontiers: Identify open problems in scaling laws, pre-training, and compositional generalization.
Quick Start
Use the ad-foundation-models skill to get an overview of the critical safety challenges in deploying foundation models in AD systems.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferencesassets
💻 Claude Code Installation
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Please help me install this Skill: Name: ad-foundation-models Download link: https://github.com/RoboSafe-Lab/ad-safety-research-skills/archive/main.zip#ad-foundation-models Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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