Affordance-based design (ABD) plays an important role in identifying interactions, especially effortless ones, between users and artifacts. Cognitive ergonomics extends our understanding of this effortless interaction. This study combines the two design methodologies together in order to reduce cognitive friction in using digital products. The design process of a compact digital camera is selected as a case study that includes the design of the physical shape for a camera and of its user interface. In designing a product shape, a design toolbox was developed that integrated a modified multi-objective genetic algorithm and the ABD, which was named as affordance-based interactive genetic algorithm. Using this toolbox and interactive user feedback, the camera design evolves toward a product that better satisfies the users. User interfaces (UIs) including linear and elliptic layouts were subsequently designed based on cognitive ergonomics. A predictive tool of UI, the Cog Tool, was used to evaluate the performance of skilled users on a given task by correlating the overall task completion time. Finally, this research has the potential to not only effectively address the shortcomings of the design of consumer electronics but also enrich the generation of design solutions during the preliminary design phase of such products.

Based on the individual traits of the user’s construal level differences, this study examines the visual cognition differences of graphic–text combined icon concreteness in the interface between users with high and low construal levels. We classified four types of graphic–text combined icons, which are as follows: concrete graphic + concrete text (Ci + Ct), concrete graphic + abstract text (Ci + At), abstract graphic + concrete text (Ai + Ct), and abstract graphic + abstract text (Ai + At). According to the behavioral experiment results, there is no visual cognitive difference between the two types of traits users in Ci + Ct. In terms of Ci + At and Ai + Ct, the visual cognitive performance of high construal level users is slightly better than that of low construal level users. In Ai + At, there are obvious visual cognitive differences between the two types of users. Visual cognitive fluency plays a mediating role in response time and matching rates of the two types of users. Based on the construal level perspective, this study considers the visual cognitive differences based on the user’s stable traits. It provides a certain reference for the graphic–text combined icons’ design in the adaptive human–computer interaction interface.

The identification, selection, and consideration of appropriate affordances during the preliminary design phase of a product play a critical role in the process of Affordance Based Design (ABD). A design tool named Affordance Based Interactive Genetic Algorithm (ABIGA) evolves products by having designers identify, and then users assess the affordance qualities of virtual prototypes. Affordances are defined to be perceived interactions, both positive and negative, primarily between the user and the artifact. In order to achieve a successful product evolution, guidelines are proposed to help designers in the setting up of experiments related to user-centered design and ABD specifically. It was found that the existence of conflicting affordances would result in a slower evolution when compared with one that did not have such conflicts. Meanwhile, it was observed that virtual presentation does influence the users’ judgments. From these observations, hypotheses and multiple experiments, these guidelines are discussed and critiqued to provide designers with insight into how to control user-centered experiments.

Intentional or unintentional littering, especially among young people, poses a threat to the marine environment. It is, therefore, necessary to enhance awareness of marine environmental protection among youth groups. This study explored the interaction between visual image types (photograph vs. cartoon), message framing (positive vs. negative), and psychological distance (human vs. turtle). A three-way analysis of variance (ANOVA) and regression analysis were used to verify the hypotheses. The key findings of the research were as follows: (1) Among the eight information construction methods, cartoons combined with turtles and presented with positive outcomes were the best way to communicate, i.e., cartoons showing animals in a friendly and positive way were the most effective form of marine garbage recycling for young people, and (2) Young people's preference for information will promote their self-efficacy in marine garbage recycling. The implications of these findings for developing marine protection information communication education for youth groups are also proposed.

Adverse road conditions, particularly foggy weather, significantly impair drivers’ abilities to gather information and make judgments in response to unexpected events. To investigate the impact of different Augmented Reality-Head-Up Display (AR-HUD) interfaces (words-only, symbols-only, and words + symbols) on driving behavior, this study simulated driving scenarios under varying visibility and risk levels in foggy conditions, measuring reaction time (RT), time-to-collision (TTC), the maximum lateral acceleration, the maximum longitudinal acceleration, and subjective data. The results indicated that risk levels significantly affected drivers’ RT, TTC, and maximum longitudinal and lateral accelerations. The three interfaces significantly differed in RT and TTC across different risk levels in heavy fog. In light fog, words-only and redundant interfaces significantly affected RT across different risk levels; words-only and symbols-only interfaces significantly affected TTC across different risk levels. In addition, participants responded faster when using text-related interfaces in the subject’s native language. After analyzing data on perceived usability across the three interfaces, the results indicated that under high-risk conditions, both in light fog and heavy fog, participants rated the redundant interface as having higher usability and preferred the redundant interfaces. Based on these findings, this paper proposes the following design strategies for AR-HUD visual interfaces: (1) Under low-risk foggy driving conditions, all three interface types are effective and applicable. (2) Under high-risk foggy driving conditions, redundant interface design is recommended. Although it may not significantly improve driving performance, this interface type was subjectively perceived as more useful and preferred by the subjects. The findings of this study provide support for design of AR-HUD interfaces, contributing to enhanced driving safety and human–machine interaction experience under complex meteorological conditions. This offers practical implications for the development and optimization of intelligent vehicle systems.