AI review integrates LLMs and ViTs for vulnerable road user safety

A new review paper explores the integration of AI, specifically Large Language Models (LLMs) and Vision Transformers (ViTs), into camera-based systems for enhancing the safety of vulnerable road users (VRUs). The paper organizes existing research into visual perception, motion modeling, and behavior understanding, forming a pipeline for early risk anticipation. It also identifies key challenges such as data scarcity and the need for efficient edge deployment. AI

IMPACT This review highlights the potential for advanced AI models like LLMs and ViTs to significantly improve proactive safety systems for pedestrians and cyclists.

RANK_REASON The cluster contains an academic review paper on AI applications. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Large Language Models
• Vision Transformers
• vulnerable road users
• Yuang Zhang

• paper
• safety

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