Pressure distribution of the human-machine interface is a key factor which affects the comfort. Because every part of the human body has different tolerance to pressure, high or low pressure will make the driver feel uncomfortable. Through the virtual simulation method combining 3D modeling and finite element analysis, the human body and seat finite element model is established to simulate the interaction of the contact interface, the human-seat coupling model was constructed and finally imported into ANSYS for finite element analysis and compared with the actual measured pressure distribution. The pressure distribution obtained by this method was proved to be feasible for evaluating driver comfort. When apply on seat back comfort study, the changes in the pressure distribution under various conditions can be observed by changing parameters such as seat inclination. The model can be used as a scientific basis for seat comfort assessment and optimization, and the researchers can understand the pressure on the driver's various parts to guide the seat comfort design.

In this study, the usability evaluation model is constructed for a co-pilot screen, and an analysis of the impact factors and optimization recommendations is made based on the evaluation results. Firstly, based on the usability design principles, interaction ease, interaction efficiency, visual comfort, driving safety, and their corresponding secondary indicators are defined, and the subjective weight of each indicator is determined using the analytic hierarchy process (AHP). Then, usability evaluation is carried out on four vehicles via vehicle driving simulated experiments and driving experiments on the road, and the objective weight of the indicators is determined using the CRITIC method. Finally, the usability evaluation model for co-pilot screens is established by applying the fuzzy comprehensive evaluation method. The results indicate that the overall usability comprehensive score of co-pilot screens is convergent and is mainly concentrated in the range of 50–65 points, with two vehicles having excellent affiliation and two vehicles having average affiliation. However, there is a great distance still to reach when compared to an excellent level. The usability evaluation model of co-pilot screens established in this article can quantify the HMI usability design of co-pilot screens. The results of this study are significant for the four tested vehicles in terms of guiding the usability design of co-pilot screens and in promoting the rapid iteration of co-pilot screen development. And a production vehicle that connects a driving simulation platform and the usability evaluation model can be used to test and evaluate more screen designs, interaction models, tasks, and infotainment applications, thus guiding further user experience designs.

Alarm sounds significantly influence a user’s sensory perception while driving, directly affecting driving judgement and safety. Personal experience and the environment play an important role in information cognition, but they are rarely considered in the current warning design. We propose a methodology enabling engineers and designers to locally optimize the advanced driver-assistance system (ADAS) functions and applied it to the Shanghainese ecosystem to improve performance. The alarm sound content is studied and sorted out to conduct user research and spatial sound collection evaluation. Local optimization and the subdivision of data are carried out to generate a user perception set on which the experimental tests and evaluation analysis are implemented. The framework increases the overall efficiency of auditory warning systems and minimizes Human–Machine Interface misunderstandings, thus providing the optimal security scheme for users.