WarNav: An Autonomous Driving Benchmark for Segmentation of Navigable Zones in War Scenes

This study evaluates the understanding of road safety principles by multi-modal large language models (LLMs), particularly in the context of autonomous vehicles. Using a curated dataset of traffic signs and safety norms from school textbooks, the research reveals that these models struggle with safety reasoning, highlighting significant gaps between human learning and model interpretation. The findings suggest a need for further research to address these performance deficiencies in AI systems governing autonomous vehicles.