AI 中文总结
研究针对现有自动驾驶视觉语言模型忽视情感维度与用户体验的问题，提出KYA系统。它由视觉模块（用YOLOv8变体检测危险行为并提取指标生成日志）和语言模块（依情感基调设置生成回应）组成，经实验评估表现良好，为车载人工智能带来新范式。
AI 中文摘要
本研究引入了一种视觉语言管道，用于检测危险驾驶行为并生成具有情感表达的回应，以支持驾驶员的意识和舒适度。尽管视觉语言模型在自动驾驶中具备先进的感知和推理能力，但现有系统很少考虑情感维度或现实世界用户体验。Keep Yelling Assistant（KYA）实时检测高风险驾驶动作，如突然切入，然后通过根据驾驶员偏好定制的大语言模型产生情感回应。该框架由两个核心模块组成。视觉模块使用YOLOv8变体检测附近车辆并识别危险行为，提取并归一化关键驾驶指标以生成结构化行为日志。语言模块根据用户定义的情感基调设置处理该日志，并使用包括ChatGPT-4o、Claude 3、Gemini 2.5和Copilot等先进大语言模型生成语言反应。通过包含危险驾驶行为的行车记录仪视频和涉及108名参与者的用户研究对所提出的系统进行了评估。所有模型都获得了好评，尽管不同用户的偏好有所不同。值得注意的是，YOLOv8s和ChatGPT-4o的组合在5.00分中获得了最高4.29分。通过将现实世界感知与情感自适应对话相结合，KYA引入了一种用于情感智能车载人工智能的新范式，为提高传统车辆和自动驾驶车辆的安全性、信任度和情感幸福感提供了有前景的方向。
英文摘要
This study introduces a vision-language pipeline that detects risky driving behaviors and generates emotionally expressive responses to support driver awareness and comfort. Although vision-language models have advanced perception and reasoning in autonomous driving, existing systems rarely consider the emotional dimension or real-world user experience. Keep Yelling Assistant (KYA) detects high-risk driving maneuvers in real time, such as sudden cut-ins. It then produces emotional responses through a large language model tailored to driver preferences. The framework comprises two core modules. The vision module uses YOLOv8 variants to detect nearby vehicles and identify risky behaviors such as sudden cut-ins. Key driving metrics, including relative distance, speed, and projected reach time, are extracted and normalized to produce a structured behavior log. The language module processes this log with user-defined emotional tone settings, such as neutral, humorous, and analytical, and generates verbal reactions using state-of-the-art large language models, including ChatGPT-4o, Claude 3, Gemini 2.5, and Copilot. We evaluated the proposed system using dashcam videos containing risky driving behaviors and a user study involving 108 participants. Participants selected preferred response styles, and the large language models were evaluated based on emotional alignment. All models received favorable ratings, although preferences varied across personas. Notably, the combination of YOLOv8s and ChatGPT-4o achieved the highest score of 4.29 out of 5.00. By integrating real-world perception with emotionally adaptive dialogue, KYA introduces a new paradigm for emotionally intelligent in-vehicle artificial intelligence. It offers promising directions for improving safety, trust, and emotional well-being in both conventional and autonomous vehicles.
CommentsTransportation Research Record. Advance online publication (2026)
