A two-stage framework that fuses semantic, kinematic, and contextual features with LLM-generated complexity annotations reaches 90.15% accuracy in predicting crash-density classes, a small but statistically claimed gain over a non-fused baseline.
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The Context of Crash Occurrence: A Complexity-Infused Approach Integrating Semantic, Contextual, and Kinematic Features
A two-stage framework that fuses semantic, kinematic, and contextual features with LLM-generated complexity annotations reaches 90.15% accuracy in predicting crash-density classes, a small but statistically claimed gain over a non-fused baseline.