A Design Method for Automotive Interior Textures Based on Cultural Semantic Modeling and Generative Design

Abstract

This study proposes a methodological framework for automotive interior texture design that integrates cultural semantic modeling with generative design techniques. The approach involves collecting relevant cultural imagery materials, extracting high-frequency cultural imagery vocabulary, and constructing a cultural semantic network through keyword co-occurrence analysis. In the semantic modeling phase, the “Entity–Event–Context” paradigm of the CIDOC CRM model is adopted to structurally represent representative cultural elements, thereby forming a semantic model with contextual association capabilities. A semantic-to-design mapping matrix is then established to translate cultural semantics into controllable design prompts. Finally, with the aid of generative design tools such as diffusion models, the semantic information is transformed into interior texture patterns that embody both cultural connotation and visual aesthetics. A design practice based on Han culture demonstrates that this method effectively enhances the cultural expressiveness and emotional recognizability of automotive interior design, offering a feasible path for culture-driven intelligent design.