## 1 Introduction  
In recent years, the applications of augmented reality (AR) technologies have been rapidly developed to make our lives more intelligent. The head-up display (HUD) had faster response times to urgent events compared to the head-down display (HDD) [1]. Thus, the HUD is considered one of the most representative interaction devices applied in the vehicle to assist the driver [2]. It was beneficial to display visual information (i.e., speed, navigation cues, safety warnings, environment, traffic, travel conditions) on the windshield with a projector when the driver simultaneously views the driving environment. However, there were still some issues that should be further studied to evaluate its practicality and safety [3]. Due to the intensive variance of the environmental illumination when driving, which has a high dynamic range for human vision, ensuring appropriate visual clarity was the primary purpose of optimizing the HUD. Furthermore, the user experience of the HUD was discussed in lots of research to achieve a better HUD design. The HUD was a type of see-through display in which the ambient lighting would significantly influence the visual perception of the displayed content. When projecting the information with a lower contrast against the background, it might lead to a higher driving risk. Hence, some studies contributed to enhancing the visibility of the HUD for easier recognition. Previous research suggested that the background transparency levelsshould be adjusted adaptively based on the illuminance of the outside environment [4]. With a higher illuminance condition, the visibility of the text could be increased when the transparency of the background was lower, whereas becoming more transparent is applied to the dark or shadow area. Additionally, [PERSON] et al. investigated the visibility of color symbology in high ambient environments. Their results recommended using white, yellow, green, and cyan text [5]. A robust gamut mapping algorithm, including lightness mapping (LM) and chroma reproduction, was proposed by [PERSON] et al. to reduce color distortion for bright ambient light [6]. Moreover, two approaches, the changes of the color symbols and the addition of color outline to symbols for HUD information, were adopted for visibility enhancement determined by the similarity between HUD information and background colors [7]. [PERSON] et al. discussed the influence of three types of HUDs, including a flag, perspective, and flag and perspective, on experienced and inexperienced drivers with subjective and objective measurements. The results showed that both types of drivers were HUD-dependent, and the flag and perspective display performed better in helping drivers execute simple tasks and complex tasks [8]. [PERSON] et al. studied the impacts of visual enhancements for HUDs on the driver's performance and workload. The observers had to track information about driving in an automotive simulation. They found that visual enhancements and task difficulties affect tracking errors and subjective workloads, which provided suggestions for interface designers to take visual enhancement into account for HUDs [9]. [PERSON] et al. investigated if the interface complexity of HUDs would influence drivers' driving performance and self-perception. Their results indicated that too complex and too simple a design of the HUD interface would not provide the best perceived effectiveness and satisfaction for a driver [10]. [PERSON] et al. compared three prototypes of HUD interfaces to improve driver safety. The results presented indicate that familiarity with the interface design is a desirable factor [11]. [PERSON] et al. explored the proper presentation format, including font size and luminance contrast of the text on the dual-plane HUD, to increase the driver's comfort. The results found that the best legibility could be achieved at a luminance contrast of 7:1 [12]. [PERSON] et al. conducted a user survey on the usage contexts and design improvement points of the existing automotive HUD systems.