With the development of intelligence and network connectivity, the development of the automotive industry is also moving toward intelligent systems. For passengers, the utility of intelligence is to achieve more convenience and comfort. The intelligent cockpit is the place where passengers directly interact with the car, which directly affects the experience of passengers in the car. For the intelligent cockpits that have emerged in recent years, a reasonable and accurate comfort evaluation model is urgently needed. Therefore, in this article, from the passenger’s perspective, a subjective evaluation experiment was set up to collect data on four important indicators affecting the comfort of the intelligent cockpit: sound, light, heat, and human–computer interaction. The subjective evaluation weights were derived from a questionnaire, and the entropy weighting method was used to obtain the objective weights. Finally, the two weights were combined using the idea of game theory combination assignment to get the final accurate weights. Using the idea of penalty type substitution, the four index models were then synthesized to get the final evaluation model. The feasibility of the model was verified when measuring the car cockpit. The feasibility of the method means it can evaluate the comfort level of an intelligent cockpit more reasonably, facilitate the enhancement and improvement of the model, and promote the development of the model to achieve maximum passenger comfort.

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.comfort, evaluation method, expectation, intelligent cockpit, the degree of dissatisfactionWith the rapid development of technology, the number of intelligent cars has also increased in recent years (Arena et al., 2020). Related research describes the intelligent car of the future as not only improving traffic safety like a robot but also further meeting people's demands by connecting to the Internet (Huang et al., 2016;James, 2012). Intelligent vehicles have become a trend now. Companies such as Tesla, Jaguar, and Google are now launching more intelligent vehicles from innovative materials and innovative technologies (Sun et al., 2021).However, for the vast majority of consumers, it is not the technology itself that cares about them, but how they feel in the cockpit (Park et al., 2019). The benefits of intelligent cars include increased safety, reduced need for infrastructure investment, improved fuel economy, and reduced congestion. But most importantly, they make passengers more relaxed and comfortable (Jorlöv et al., 2017). The real benefits of intelligent cars can only be realized when the human driver is comfortable in the intelligent cockpit and the interaction between the driver and the automated system is at a reasonable level (Helldin et al., 2013). Beggiato et al. (2019 believe that comfort plays an important role in the wide acceptance of intelligent vehicles. For some products such as smart cars, consumer satisfaction is a factor for business success (Park et al., 2019;Salomo et al., 2003). Industry and research are working to develop systems that can automatically adapt to maximize well-being (Olugbade et al., 2021). Therefore, making people feel comfortable is