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基于眼动追踪的女性用户新能源汽车中控设计意象研究

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以女性驾驶员为研究对象,在新能源汽车中控台设计中采用眼动设备和BP(Back Propagation)神经网络算法模型展开评价,建立意象评价模型,为汽车设计师提供数据与方案支持.搜集不同品牌风格的新能源汽车中控台设计方案,选择28名不同年龄层次的女性新能源汽车驾驶员佩戴眼动仪对中控台不同的测试区作出意象打分评价,再分别以眼动仪的数据和用户打分评价数据为基础建立数学评价模型,其中,眼动仪的数据来源是BP神经网络模型的输入值.计算结果中实际分值与预测分值的平均绝对偏差值表明:建立的神经网络模型能够有效预测女性驾驶员对中控台设计的意象评分.这给汽车设计师在进行内饰设计时提供了用户评价指标,从而为不断优化汽车产品市场、提供更多个性化汽车产品提供了理论支撑.
Research on image of central control design of new energy vehicles for female users based on eye tracking
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.

kansei engineeringnew energy vehicle center consoledesign imageryBP neural networkeye tracking

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韩国全北国立大学,韩国全州54896

感性工学 新能源汽车中控 设计意象 BP神经网络 眼动追踪

2024

江苏理工学院学报
江苏技术师范学院

江苏理工学院学报

CHSSCD
影响因子:0.369
ISSN:2095-7394
年,卷(期):2024.30(6)