Automated vehicles can perceive their environment and control themselves, but how to effectively transfer the information perceived by the vehicles to human drivers through interfaces, or share the awareness of the situation, is a problem to be solved in human–machine co-driving. The four elements of the shared situation awareness (SSA) interface, namely human–machine state, context, current task status, and plan, were analyzed and proposed through an abstraction hierarchy design method to guide the output of the corresponding interface design elements. The four elements were introduced to visualize the interface elements and design the interface prototype in the scenario of “a vehicle overtaking with a dangerous intention from the left rear”, and the design schemes were experimentally evaluated. The results showed that the design with the four elements of an SSA interface could effectively improve the usability of the human–machine interface, increase the levels of human drivers’ situational awareness and prediction of dangerous intentions, and boost trust in the automatic systems, thereby providing ideas for the design of human–machine collaborative interfaces that enhance shared situational awareness in similar scenarios.

While automated driving has attracted more and more attention, human drivers still play an important role. Drivers must be aware of their surroundings and potential danger to take over the vehicle’s control immediately when the automation system cannot function, which could otherwise pose a road safety risk. The transparent design of the human–machine interface can accurately convey the perceived information of the machine to help drivers understand the dynamic environment. We designed the scenario where the rear vehicle is about to overtake the ego vehicle and has a dangerous tendency to collide with the ego vehicle by stepping on the lane line. We analyzed the information shared by the intelligent system in this scenario to make “transparent” the intelligent system. According to the requirements of the task model of transparency and the three stages of situation awareness, we formed three designs. Then we analyzed the availability, situation awareness, and workload of different designs. Results showed that the transparency design according to the shared situation awareness stage can have a positive impact on the usability of the intelligent system. Therefore, the effective transparency-based design in automated driving can enhance the user’s understanding of the system and improve their experience.

In order to ensure the driver’s safe driving, the human–computer interaction interface of an intelligent vehicle needs to convey important information. The text is an important carrier of this kind of information. The design criteria of English characters have been widely discussed, including the color, meaning, size and length. However, design guidelines for Chinese characters in central consoles of vehicles have rarely been discussed from a human–computer interaction perspective. In this paper, we investigated the size and the length of Chinese characters in the intelligent vehicle’s central control screen, based on international design guidelines and standards. The experiment involved 30 participants performing simulated in-vehicle secondary tasks. The result from the experiments shows that the usability of characters increases and the driver’s workload decreases as the characters get larger and shorter. We also propose a set of recommended values for the size and length of Chinese characters in this context. Future work will focus on providing design guidelines for other aspects of HMI design in intelligent vehicles.