详细信息
- 来源站点
- ArXiv CS.CV
- 作者
- Muhammad Sulthan Adhipradhana, Ehsan Javanmardi, Naren Bao, Manabu Tsukada
- 文章类型
- PAPER
- 语言
- en
- 发布日期
- 2026-07-28
摘要
arXiv:2607.23132v1 Announce Type: new Abstract: Assessing the severity of a traffic accident scenario is important to decide which emergency service to dispatch. Missing an ambulance dispatch on a pedestrian accident is a fatal issue that can lead to death. Recently, Vision-Language Models (VLMs) have been a promising tool for accident reasoning, yet many VLMs are not grounded in real-life accident response protocols, making them not usable in accident severity assessment off-the-shelf. We introduced DispatchRAG, an accident assessor and dispatcher framework grounded in real-life Japanese traffic-accident response protocols, designed to enhance VLMs to generate an appropriate emergency response during an emergency scenario. Utilizing a RAG-based retrieval mechanism to retrieve the most relevant accident protocol and an LLM-powered reasoner to suggest the most proper response.
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