With the rapid development of automobiles, car cockpits are becoming more and more intelligent and advanced, and the intelligent requirements of automobile cockpits are gradually increasing. However, the real value of intelligence can only be realized when it makes passengers in a cockpit feel comfortable. In this study, seven factors that affect passenger comfort in intelligent cockpits are defined. Under these factors, a total of 33 evaluation indicators were developed. The core of the method was to determine the dissatisfaction indicators and degree of dissatisfaction in the intelligent cockpit by analyzing the relationship between people's perceived performance and their expectations. This method was used to evaluate the Tesla Model 3, and it was found in the results that the higher the degree of dissatisfaction with the indicator, the more subjective feedback it had, which in turn proved the effectiveness of the model. According to the degree of dissatisfaction, the indicators affecting comfort were also divided into three levels. This hierarchical division helps clarify which indicators should be prioritized for improvement. Generally, this method has a certain feasibility, which is helpful for the development and redesign of an intelligent car cockpit, and provides some reference strategies for other transportation fields.

中文翻译：

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一种基于智能汽车座舱的舒适性评价方法

随着汽车的高速发展，汽车座舱也越来越智能化和先进化，对汽车座舱的智能化要求也逐渐提高。然而，只有让驾驶舱内的乘客感到舒适，智能的真正价值才能体现出来。在这项研究中，定义了影响智能驾驶舱乘客舒适度的七个因素。在这些因素下，共制定了33项评价指标。该方法的核心是通过分析人们的感知绩效与期望之间的关系，确定智能座舱的不满指标和不满程度。使用该方法对特斯拉Model 3进行评价，结果发现，对指标的不满意程度越高，它获得的主观反馈越多，这反过来又证明了模型的有效性。根据不满意程度，影响舒适度的指标也分为三个等级。这种层次划分有助于明确哪些指标应该优先改进。总的来说，该方法具有一定的可行性，有助于智能汽车座舱的开发和再设计，也为其他交通领域提供了一些参考策略。