目的 在新一代汽车数字座舱的设计中，准确、可靠地获取目标用户的主观评价数据是提升座舱设计水平的重要依据。以量表为主要工具的主观测量法就是就是常用的测量用户主观评价的方法之一，有着不可替代性及广泛的应用价值，然而该方法存在可靠性较低、小样本容量测量结果聚合不够准确的缺点。方法 采用模糊集理论构建模糊量表，解决量表信息转译过程中的信息遗失问题，使测量结果更贴近人真实的主观意见;采用一种线性反馈迭代算法优化权重分配，使小样本容量的个体意见与聚合意见实现最大限度的重合。结果 得到了构建模糊量表的系统性方法，由此提升主观测量法的可靠性;提出了最大同意度意见聚合方法，改善了主观测量法结果聚合的准确性。结论 通过主观测量方法的优化，为提升汽车数字座舱的设计水平提供了新的路径。

In the design of automotive digital cockpit, it is an important basis for improving the design level of the cockpit by obtaining the subjective data of users with accuracy and reliability. The subjective measurement method with its scale as tools is commonly used, which is irreplaceable and has a wide application. However, this method has the disadvantages of low reliability and inaccurate aggregation when the sample size is small. The fuzzy set theory was taken to construct a fuzzy scale to avoid the information loss during the rating, so that the measurement could be much closer to people's real subjective opinions. Meanwhile, a linear feedback iterative algorithm was used to optimize the weight allocation, so that the individual opinions in a small sample size and their aggregated opinions could overlap to the greatest extent. As a result, a systematic method for constructing a fuzzy scale was obtained, which improved the reliability of subjective measurement. A maximum agreement method was proposed, which improved the accuracy of subjective measurement aggregation. The optimization of subjective measurement method provides a new way for improving the design of automotive digital cockpit.