Multimodal LLMs with well-designed prompts can partially match human judgments of driving-scene risk factors, but their performance depends heavily on prompt design and remains unreliable for safety-critical detection.
The long-term effects of active training strategies on improving older drivers’ scanning in intersections: a two-year follow- up to romoser and fisher (2009),
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Understanding Driving Risks using Large Language Models: Toward Elderly Driver Assessment
Multimodal LLMs with well-designed prompts can partially match human judgments of driving-scene risk factors, but their performance depends heavily on prompt design and remains unreliable for safety-critical detection.