Anthropomorphic robots need to maintain effective and emotive communication with humans as automotive agents to establish and maintain effective human–robot performances and positive human experiences. Previous research has shown that the characteristics of robot communication positively affect human–robot interaction outcomes such as usability, trust, workload, and performance. In this study, we investigated the characteristics of transparency and anthropomorphism in robotic dual-channel communication, encompassing the voice channel (low or high, increasing the amount of information provided by textual information) and the visual channel (low or high, increasing the amount of information provided by expressive information). The results showed the benefits and limitations of increasing the transparency and anthropomorphism, demonstrating the significance of the careful implementation of transparency methods. The limitations and future directions are discussed.

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.

Both physical and cultural aspects are important for urban areas. In the context of urban space involving cultural resources, the application of augmented reality (AR) could physically integrate cultural resources into the physical facilities of the city. In this paper, the narrative approach is introduced to the construction of an urban cultural scene based on AR technology. Following the collection of historical materials about the Bund in Shanghai in the 1920s and 1930s, this study creates the characters and events in a non-fictional way, organizing a series of narrative elements around themes based on real historical contexts. This is in line with AR, a technology that superimposes virtual information in the real world. As part of this non-fictional narrative design, the author has chosen suitable characters as ‘avatars’ to observe and experience the development of the narrative from a first-person perspective. A participatory viewing can be brought about by adopting a non-fictional approach, rather than a simple information transfer and passive reception. The result is that instead of the traditional guide centric model, a multi-path tour model is created. In conclusion, this paper believes that the use of AR technology can link the narrative to the region more directly and closely. Further, a new cultural scene is created that allows visitors to have an immersive experience. AR technology provides a narrative perspective based on regional knowledge that reinforces and represents the image of the region in a cohesive way.

With the continuous development of intelligent product interaction technology, the facial expression design of virtual images on the interactive interface of intelligent products has become an important research topic. Based on the current research on facial expression design of existing intelligent products, we symmetrically mapped the PAD (pleasure–arousal–dominance) emotion value to the image design, explored the characteristics of abstract expressions and the principles of expression design, and evaluated them experimentally. In this study, the experiment of PAD scores was conducted on the emotion expression design of abstract expressions, and the data results were analyzed to iterate the expression design. The experimental results show that PAD values can effectively guide designers in expression design. Meanwhile, the efficiency and recognition accuracy of human communication with abstract expression design can be improved by facial auxiliary elements and eyebrows.

In case of dangerous driving, the in-vehicle robot can provide multimodal warnings to help the driver correct the wrong operation, so the impact of the warning signal itself on driving safety needs to be reduced. This study investigates the design of multimodal warnings for in-vehicle robots under driving safety warning scenarios. Based on transparency theory, this study addressed the content and timing of visual and auditory modality warning outputs and discussed the effects of different robot speech and facial expressions on driving safety. Two rounds of experiments were conducted on a driving simulator to collect vehicle data, subjective data, and behavioral data. The results showed that driving safety and workload were optimal when the robot was designed to use negative expressions for the visual modality during the comprehension (SAT 2) phase and speech at a rate of 345 words/minute for the auditory modality during the comprehension (SAT 2) and prediction (SAT 3) phases. The design guideline obtained from the study provides a reference for the interaction design of driver assistance systems with robots as the interface.

Based on the transparency theory, this study investigates the appropriate amount of transparency information expressed by the in-vehicle robot under two channels of voice and visual in a proactive interaction scenario. The experiments are to test and evaluate different transparency levels and combinations of information in different channels of the in-vehicle robot, based on a driving simulator to collect subjective and objective data, which focuses on users’ safety, usability, trust, and emotion dimensions under driving conditions. The results show that appropriate transparency expression is able to improve drivers’ driving control and subjective evaluation and that drivers need a different amount of transparency information in different types of tasks.