Situational perception in distracted driving: an agentic multi-modal LLM framework

These findings highlight the potential of LLM-driven, multi-modal reasoning for distracted driving intervention. Integrating specialized agents and structured orchestration improves situational awareness, maintains concise communication, and meets real-time safety requirements. This proof-of-concept establishes a pathway for deploying intelligent, AI-driven driver support systems in safety-critical applications.