Effects of a color gradient and emoji in AR-HUD warning interfaces in autonomous vehicles on takeover performance and driver emotions.

OBJECTIVE: This study examined the effects of color gradients and emojis in an augmented reality-head-up display (AR-HUD) warning interface on driver emotions and takeover performance. METHODS: A total of 48 participants were grouped into four different warning interfaces for a simulated self-driving takeover experiment. Two-way analysis of variance and the Kruskal-Wallis test was used to analyze takeover time, mood, task load, and system availability. RESULTS: Takeover efficiency and task load did not significantly differ among the interfaces, but the interfaces with a color gradient and emoji positively affected drivers' emotions. Emojis also positively affected emotional valence, and the color gradient had a high emotional arousal effect. Both the color gradient and the emoji interfaces had an inhibitory effect on negative emotions. The emoji interface was easier to learn, reducing driver learning costs. CONCLUSIONS: These findings offer valuable insights for designing safer and more user-friendly AR-HUD interfaces for self-driving cars.

Microchannels Formed Using Metal Microdroplets.

The metal microdroplet deposition manufacturing technique has gained extensive attention due to its potential applications in microstructure fabrication. In order to fabricate components such as microchannel heat sinks and microchannel reactors, this paper investigates the interactions and influences between microdroplets and substrates, as well as between microdroplets themselves. The transient phenomena during the fusion of metal microdroplets in contact with the substrate and the formation of inclined columns, as well as the solid-liquid coupling and morphology formation processes during the collision between microdroplets, are analyzed. The influence of microdroplet spacing on the morphology of microchannels during their formation is specifically studied. A three-dimensional finite element numerical model for the deposition of metal microdroplets forming inclined pillars is established based on the volume of fluid (VOF) method. The model treats the protective gas around the microdroplet as an empty zone and the microdroplet as a single-phase fluid. Simulation analysis is conducted to investigate the forming patterns of unsupported microdroplets at different spacing and their impact on the fusion morphology of microchannel components. Building upon this, a series of validation experiments are conducted using a piezoelectric microdroplet generator to produce uniform aluminum alloy microdroplets with a diameter of approximately 600 µm. A method for fabricating metal microchannel structures is obtained, which is expected to be applied in fields such as scattering structures for high-power electronic devices and microreactors in microchemical fields.

The impact of different AR-HUD virtual warning interfaces on the takeover performance and visual characteristics of autonomous vehicles.

OBJECTIVE: The objective of this study was to determine the different effects of the arrow-pointing augmented reality head-up display (AR-HUD) interface, virtual shadow AR-HUD interface, and non-AR-HUD interface on autonomous vehicle takeover efficiency and driver eye movement characteristics in different driving scenarios. METHODS: Thirty-six participants were selected to carry out a simulated driving experiment, and the eye movement index and takeover time were analyzed. RESULTS: The arrow pointing AR-HUD interface and the virtual shadow AR-HUD interface could effectively reduce the driver's visual distraction, improve the efficiency of obtaining visual information, reduce the number of times the driver's eyes leave the road, and improve the efficiency of the takeover compared with the non-AR-HUD interface, but there was no significant difference in eye movement indexes between the arrow pointing AR-HUD interface and the more eye-catching virtual shadow AR-HUD interface. When specific scenarios were considered, it was found that in the scenario of emergency braking of the vehicle in front, the arrow pointing AR-HUD interface and the virtual shadow AR-HUD interface had more advantages in takeover efficiency than the non-AR-HUD interface. However, in the scenarios of a rear vehicle overtaking the vehicle ahead and non-motor vehicles running red lights, there was no significant difference in takeover efficiency. For the non-motor vehicle invading the line, emergency U-turn of the vehicle in front, and pedestrian crossing scenarios, the virtual shadow AR-HUD interface had the highest takeover efficiency. CONCLUSIONS: These research results can help improve the active safety of autonomous vehicle AR-HUD interfaces.

Influence of Multi-Modal Warning Interface on Takeover Efficiency of Autonomous High-Speed Train.

As a large-scale public transport mode, the driving safety of high-speed rail has a profound impact on public health. In this study, we determined the most efficient multi-modal warning interface for automatic driving of a high-speed train and put forward suggestions for optimization and improvement. Forty-eight participants were selected, and a simulated 350 km/h high-speed train driving experiment equipped with a multi-modal warning interface was carried out. Then, the parameters of eye movement and behavior were analyzed by independent sample Kruskal-Wallis test and one-way analysis of variance. The results showed that the current level 3 warning visual interface of a high-speed train had the most abundant warning graphic information, but it failed to increase the takeover efficiency of the driver. The visual interface of the level 2 warning was more likely to attract the attention of drivers than the visual interface of the level 1 warning, but it still needs to be optimized in terms of the relevance of and guidance between graphic-text elements. The multi-modal warning interface had a faster response efficiency than the single-modal warning interface. The auditory-visual multi-modal interface had the highest takeover efficiency and was suitable for the most urgent (level 3) high-speed train warning. The introduction of an auditory interface could increase the efficiency of a purely visual interface, but the introduction of a tactile interface did not improve the efficiency. These findings can be used as a basis for the interface design of automatic driving high-speed trains and help improve the active safety of automatic driving high-speed trains, which is of great significance to protect the health and safety of the public.