汽車輪廓形態特徵關係之研究

A Study on the Feature Relationship of Automobile Contour

產品的趨勢由單純以機能考量的觀點轉變為融入產品語意，以期能創造出更符合消費者感性的產品。為達到這個目的，設計者運用系統化的設計方法，經由資料收集、分析、綜合及決策等程序，以求得合適的解答，而感性工學即針對此議題所發展出來的一門學問。本研究嘗試以感性工學的觀點，運用相對座標之形態定義與多變量統計分析的方式，以期在其設計研究領域中作更深入的探討。本研究實驗之初，廣泛的收集汽車樣本資與語彙，整理後並運用造形均化法的概念加以運算汽車輪廓樣本，然後利用相對標的方式及貝茲曲線加以對輪廓形態做出定義並運用多變量分析方法進行探討。實驗結果顯示：實驗語彙初步可依其汽車輪廓歸納成三個不同意象。而在意象特徵實驗結果方面，所屬各個意象的樣本群，皆各有其影響意象的特且有所差異，其特徵並形成明顯區別群與群之間的差異。另外，在相似意象群體中區別出個體之差異亦有其區分特徵存在。在本研究實驗分析結果的歸納下，其區分相似意象群體的共同特徵之處為前、後保險桿線段及後車燈線段，皆有其區分似意象群的影響力。至於影響意象的特徵與區別類似意象群體中個體的區分特徵之間的關係，結果顯示，其兩者之特徵並未有絕對的關係存在。

The current trend in product design has shifted from functionalism to product semantics. In order to create the products that are suitable for and satisfied with consumers. The designers often take the systematized design methods, which collecting data, analysis, synthesis, and decision etc, expect to reach the purpose and get the suitable answers. Kansei Engineering is a kind of knowledge that was developed for this issue. In order to study deeply in its design research field, this study tries to use the way of relative coordinates to define the contour of form and Multivariate Analysis to compute data based on the viewpoint of Kansei Engineering. In the early of the study, we collect that automobile samples and perceptual lexicon about automobile contour widely, after outlining the automobile samples and perceptual lexicon about automobile contour we use the concept of form average to compute these sample of automobile contour. Then we use the way of relative coordinates and define sample of automobile contour by Bezier Curve, and use Multivariate Analysis to explore the relationship between automobile samples and perceptual lexicon. The results show that experimental lexicons can be included roughly to three different images form the viewpoint of automobile contour. The experimental result of image feature also reveals that there are different image feature in each image groups and the image features causes the obvious difference among the different imager groups. Furthermore, distinguishing the difference of individual in each similar image group also have discrimination feature. After inducing, the common features that distinguished from individual in similar image groups are the front; rear bumper curve and the rear lamps curve. As to the relationship that image features and discrimination feature that distinguish the individual in similar image groups. The result shows that the relationship between image features and discrimination feature are not absolute.