Taking female driver as the research object,eye tracking device and BP(Back Propagation)neural network algorithm model are used to evaluate the design of the center control console of new energy vehicles,and image evaluation model is established to provide data and program support for automobile designers.The center console design schemes of new energy vehicles of different brands and styles are collected,and 28 female new energy vehicle drivers of different ages are selected to wear eye tracker to make image scoring and evaluation on different test areas of the center console.Then,mathematical evaluation models are established based on the data of eye tracker and user scoring and evaluation data respectively.Among them,the data source of the eye tracker is the input value of the BP neural network model.The average absolute deviation between the actual score and the predicted score in the calculated results shows that the established neural network model can effectively predict the image score of female drivers on the center console design,which provides a user evaluation index for automobile designers in interior design,and thus provides theoretical support for continuously optimizing the automobile product market and providing more personalized automobile products.
关键词
感性工学/新能源汽车中控/设计意象/BP神经网络/眼动追踪
Key words
kansei engineering/new energy vehicle center console/design imagery/BP neural network/eye tracking
维普
万方数据