DriveSafe: A Framework for Risk Detection and Safety Suggestions in Driving Scenarios

ArXi:2605.16892v1 Announce Type: cross Comprehensive situational awareness is essential for autonomous vehicles operating in safety-critical environments, as it enables the identification and mitigation of potential risks. Although recent Multimodal Large Language Models (MLLMs) have shown promise on general vision-language tasks, our findings indicate that zero-shot MLLMs still underperform compared to domain-specific methods in fine-grained, spatially grounded risk assessment.