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• The paper proposes C-TRAIL, a multimodal legal dataset that aligns dashcam videos and textual descriptions with responsibility modes and Chinese traffic statutes.method 95%
• Existing ego-view traffic accident studies mainly focus on perception and semantic understanding, while LLM-based legal methods rarely incorporate video evidence.limitation 90%
• The paper introduces a two-stage framework with a traffic accident understanding module and a legal multi-agent framework.method 95%
• The method provides a transparent and interpretable legal reasoning process.technical 90%
• The proposed method outperforms general and legal LLMs on C-TRAIL and MM-AU datasets.result 85%
• The legal multi-agent framework outputs responsibility modes, statute sets, and complete judgment reports.method 90%
• The framework addresses the gap between video evidence analysis and legal responsibility determination.technical 80%
• The method outperforms existing agent-based approaches on the evaluated datasets.result 85%

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