Evaluation of Heavy Truck Front Face Styling Imagery Based on a Multiscale Approach

This paper takes the front face styling of heavy trucks as the research object, adopts the multi-scale method to perceptually evaluate the front face of heavy trucks, establishes a semantic perceptual space with user imagery as the core, and explores the perceptual connection between imagery evaluation and styling design. Firstly, 40 samples were obtained based on the front face styling elements of heavy trucks, and 12 sets of representative imagery word pairs were obtained. Then a cognitive similarity matrix was established based on the evaluations of 17 testers, and similarity analysis was performed using the multivariate scale method to obtain seven representative phase samples. Finally, the 93 evaluation questionnaires were analyzed using principal component analysis to obtain four sets of imagery word pairs that are decisive for the front face shape of heavy trucks. With the above approach, this paper provides a strategic approach for the styling development of new products in the heavy truck industry. Its innovation lies in the abandonment of the traditional shape evolution-based or inspiration-driven styling design approach. It adopts the quantification of perceptual evaluation in digital space and transforms it into analyzable data to invert the guiding perceptual semantics. The purpose is to design the product shape that users really like more scientifically.