Keywords

1 User Experience Theory in Human-Vehicle Interaction

1.1 User Experience Needs in Human-Vehicle Interaction

Based on Maslow’s hierarchy of needs [1], Ren divides the user experience into five levels of needs, which are sensory experience, interactive experience, emotional experience, social experience and personalized experience, from the lowest level to the highest [2]. According to this classification, the following five levels of needs are necessarily to be considered to plan the blueprint of the user experience in the driving process.

Sensory Experience Needs.

When interacting with cars, the most intuitive and perceptible information is expected by the drivers, including visual information, auditory information, tactile information, and even olfactory and taste information through multiple channels.

Interactive Experience Needs.

High availability, ease of use, learnability, fault tolerance and other properties of driving system is expected, because it is related to whether the functions and contents of the system can be correctly transmitted to the driver.

Emotional Experience Needs.

When interacting with cars, more driving pleasure are needed by the drivers, and emotional comfort are needed by the drivers when frightened during driving process.

Social Experience Needs.

When the driver interacts with the car, they hope to gain recognition and respect from others for his driving performance and car brand.

Personalized Experience Needs.

Driving system is expected to meet the individual needs by the drivers.

1.2 User Experience Elements of Human-Vehicle Interaction

The user experience element mainly refers to the factors that affect the driver’s experience during the interaction between the car and the driver. Garrett [3] divided the user experience of information products into five levels in the “Elements of User Experience”: strategic layer, scope layer, structure layer, framework layer and presentation layer. The above five user experience elements are applied in the process of interaction between people and cars.

Huanle Zhang, Tianqiu Huang and others, divide design knowledge into three categories: user, design object and situation, according to the characteristics of automotive user research data [4]. The design process is in fact the process by which the designer transforms the design knowledge into specific and external product-related attributes through design behavior. Therefore, the new research results of the human-computer interaction interface are proposed based on the existing research results related to the three elements.

1.3 Users

Different users have different user information, which can be divided into three categories: basic information, life form information and personal situation information, covering economic status, living environment, living habits, personality hobbies and consumption concepts. The differences of these user information reflect the difference in user experience requirements of various users [5].

1.4 Design Object

The design object is essentially the product, interface, interaction and other objects in the design of the human-vehicle interaction interface. There are concrete parts and visual interfaces, as well as abstract interaction and interaction strategies. The design object contains design factors, design carriers and design concepts, and the organizational relationship is shown in Fig. 1.

Fig. 1.
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The organizational relationship of design object

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1.5 Situation

The situation is the bridge connecting users and design objects. Each situation has corresponding users behind it. Each user has different performances in the same situation. The situation is important for studying user behavior and psychology [1]. There are N situation categories in each driving situation, and multiple sub-contexts in each context. Each sub-context has its own situational features. The key points in the design goals are the situational problems that users encounter under contextual characteristics. The framework for the classification of situations is shown in Table 1.

Table 1. The framework for the classification of situations
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2 Design Factors of the Interface of Automatic-Driving Takeover System

The interaction design strategy in the automatic-driving takeover process can affect the safety [6]. First of all, in the automatic driving state, if the driving task is too easy, the driver can easily enter the passive fatigue due to the low cognitive burden, and the boring driving process also lead the driver to participate more in non-driving main tasks such as social entertainment. In this way, driving distraction is caused. Secondly, since the main attention resources in the automatic driving process are not concentrated in the vehicle state and the road condition, the situational awareness is lowered, so that when the automatic system exits and the takeover request is issued, the driver may be shocked by unexpected state changes or prompts. At the same time, insufficient situational awareness may cause confusion about the driving mode. In addition, the driver may develop over dependence on the automatic driving system or decreased trust on automatic-driving due to frequent warning messages. And the trust in autonomous driving is reduced [7].

2.1 Interaction Problem of Takeover Switching in Level 3 Automatic Driving

For HAD (Highly Automated Driving) vehicles, the interactive interface design of the automatic-driving takeover system based on user experience is very important for driving safety. The design of the takeover system should plan a better way for the driver to be more involved in the driving mission, paying attention to the vehicle status and traffic situation in order to maintain a good situational awareness [8]; At the same time, it is necessary to plan a better warning mode, indicating the current automatic driving status and its restrictions, transmitting information appropriately, clearly and efficiently, and makes it easily accessible by the driver, avoiding the driver’s detachment beyond the human-vehicle-environment system. Therefore, the takeover request method conveyed by the automatic-driving takeover system should balance the workload and urgency well, neither too early (may be interpreted by the driver as a false positive) nor too late (may result in loss of access to the artificially driven vehicle). At the same time, in the context of connected driving, the interactive interface design of the automatic-driving takeover system should also help the driver to get certain economic and entertainment experience, that is, the balance between safety and experience [9].

2.2 User Research of Automatic-Driving System

Norman [10] proposed user-centered design principles, and advocated design to focus on the needs and interests of users to ensure the comprehensibility and usability of the product. In the process of automatic driving, a car will face unexpected situation that various systems can’t solve or can’t completely solve, which is random. Therefore, when conducting user research, it is necessary to select typical users according to certain conditions and obtain different types and degrees of user information in order to discover differences between different users.

The scope of this study is defined in all driving operations performed by the automatic-driving system of L3 driving. Human need to respond to certain request. And the main body of the operation is humans and systems, that is, the automatic driving background with restrictions. The research subjects of this study are not universal, so they can not be classified according to the conventional driving proficiency, but according to the user’s proficiency and understanding of the automatic-driving system, the users are divided into three categories: novice users, intermediate users and expert users.

Novice Users.

Users who have certain driving experience and have used automatic-driving or assisted driving functions. The automatic driving here is not limited to L3 driving and above. Such users have weak auto-driving experience and less knowledge of takeover system.

Intermediate Users.

Users who have rich driving experience and have more auto-driving experience, including automatic driving experience of L3 or above. Such users are more familiar with the knowledge of automatic driving, their functions and operation methods.

Expert Users.

Users who have rich driving experience and have a deep understanding and experience of L3 automatic-driving cars. Such users are very familiar with the automatic vehicle human-vehicle interaction system, and study more on applications of various new technology inside the car.

Three typical users are interviewed in this article, who represent their respective groups. Let the user describe the situation in which the automatic driving system is used, especially in the situation of takeover operations. Three user-specific individual situational issues and needs are documented and analyzed, and the situational characteristics are summarized based on the research of integrated relevant document. The user information is divided into three dimensions: basic information, life form information, and personal situation information of users. The basic information of and life form information of users are shown in Tables 2 and 3.

Table 2. Basic information of users
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Table 3. Life form information
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The specific personal situation problems and needs of the three users are recorded and analyzed, through Interview and survey, allowing users to describe the situation of using the autopilot system, especially the situation relevant to takeover operation. Personal situational interviews provide designers with an overview of the user, help to find problems and discover needs. However, it should be noticed that during the interview process, the users describe the personal situation without much thought. The information obtained by the interview is usually incomplete, which may include the users’ personal emotion color or even error. It is the best way to find more missing content and error information to interview multiple objects, but for the limit of conditions, the author will integrate relevant literature research and summarize the situational features.

2.3 Study of Auto-driving Takeover Situation Study

The above personal situation of three typical users, combined with the results of the existing auto-driving situation-related literature research [11,12,13,14,15], the features of the auto-driving takeover situation include:

Diversity of Takeover Situations.

Due to the cars are constantly moving objects in the driving process, and the complexity of the traffic situation in real world traffic, the ADAS (Advanced Driver Assistant System) of the self-driving car will receive the situation information from different directions, including roads, environment, pedestrians, signs, equipment and other information. The system makes a takeover request when ADAS can’t recognize the current situation information or the situational information exceeds the auto-driving condition. Secondly, when the driver controls the car, the state is also uncertain, they would do sub-tasks such as listening to songs, playing mobile phones, reading newspapers, and so on. Therefore, the takeover situation is also diverse. This requires that the interface design of the takeover system should be adapted to different situations.

Dynamics of the Takeover Situation.

Because the car is constantly moving during the driving process, the surrounding situation is in the process of changing, including location, weather, time and so on. When the auto-driving function is activated, the driver also has more time and space to do non-driving tasks. At this time, the driver is in a distraction state, affecting the perception of the changing situation, and resulting in a decline in situational awareness. This requires that when the situation changes significantly, the driver should be informed immediately that the driver cannot be completely separated from the driving situation.

The Randomness of the Takeover Situation.

During the driving process, the driving environment is constantly changing, and the content of the takeover situation changes with time and place, showing the characteristics of randomness. The driver cannot predict when the system will make a takeover request, and the sudden appearance of the request may cause the driver’s psychological panic, affecting the efficiency and quality of the takeover. Taking the randomness of the situation, the timing and method of requiring the takeover system to make a warning should balance the urgency well, neither too early (may be interpreted by the driver as a false positive) nor too late (may lead to loss of access to the artificially driven vehicle). The human factors that affect the time of auto-driving takeover include:

Driving Distraction.

Driving distraction is a problem of attention resource allocation during driving. During the automatic driving process, the boring feeling result in low workload. So the driver wants to participate in more interesting tasks instead of monitoring and supervising autonomous driving. Although the system has a warning function, such long-term distraction still poses a threat to the safety of automatic driving.

Passive Fatigue.

In the process of automatic driving, the driver’s workload is too small. Lacking of direct control of the task in hand, the driver will fall into passive fatigue because the cognitive load is too low. Passive fatigue can reduce overall performance of the driver.

Situational Awareness.

When the major task is handed over to the system, the driver’s attention is diverted from the driving task, and less attention resources are used to maintain an understanding of the vehicle state and road conditions, the level of attention to the situation is reduced at the same time. When the situation changes significantly but doesn’t need to be taken over, the driver also needs the system to mainly inform the change of situation, or to improve the driver’s takeover motivation through some mechanism to ensure the maintenance of good situational awareness.

Excessive Trust.

Because the automatic driving system takes over most of the driving tasks, after a period of time, the driver overestimates and relies too much on the autopilot function, and doesn’t doubt whether the auto-driving system can really detect all the dangers. The problem with over-reliance and trust in auto-driving systems is that the driver may mistakenly believe that the technology can accurately warn them every time when necessary. These consequences of over-reliance on autonomous driving are known as negative behavioral adaptation effects and may be detrimental to safe driving.

Skills Degradation.

Drivers who rely heavily on highly automated driving systems may not be able to use their manual driving skills for long periods of time. Conversely, ignoring manual driving skills may reduce the flexibility and driving cognitive skills required to manually complete the task successfully and safely. Therefore, in an automatic driving system, it is necessary to encourage the use of a manual driving mechanism.

In the real driving process, the human factor affects the driver’s autopilot takeover performance, and the factors also affect each other. To reduce the impact of human factors on driving efficiency and quality, a good human-vehicle interface design for auto-driving takeover systems is indispensable.

3 Human-Machine Interface Design Model of Automatic Driving Takeover System Based on User Experience

Through the research on user experience and automobile human-vehicle interface, the user and the situation are analyzed separately, and the situational characteristics of the auto-driving takeover situation and the human factors affecting the takeover process are summarized. Based on the above conclusions, the user needs under the takeover scenario are listed, as shown in Table 4 below:

Table 4. The specific contents of each level that affect the driver experience
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The design of human-vehicle interaction interface should regard safety as the first principle and then meet the needs of users at all levels as much as possible. When multiple needs are not met, low-level needs are more important. The needs of each level are interdependent and overlapping. During the same period, people may have multiple needs, and designers need to think comprehensively to propose specific solutions. Therefore, the design goal is to design an interactive interface that assists the driver to safely complete the takeover of driving control and improve the user experience in the automatic driving mode.

Through the research on the background of the subject, the selected design carrier is the car window and AR-FWSD technology. The characteristics of the large display area and the use of the peripheral field of view can effectively help the driver to understand the situation [15]. The above design factors are introduced into the design model, and the human-vehicle interface design model of the automatic driving takeover system based on the user experience is obtained, as shown in Fig. 2.

Fig. 2.
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Interface design model

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In the human-vehicle interface design of the automatic driving takeover system based on user experience, safety is the first design principle. In general, non-high-frequency operations or non-professional functions often regard visual effects as a priority, within the acceptable range of interactive experience. But for the car, the interactive experience is definitely more important than the visual effect. If there was a problem with car interaction, the cost may be a car crash [16], so in this design model, all design factors must also be designed with safety as the first criterion. In addition, the hum an-vehicle interaction interface needs to be repeatedly verified in the design process, and the emergency plan should be prepared in advance.

User experience elements include strategy layer, scope layer, structure layer, framework layer, and presentation layer. Design factors include design goals, design vectors, and multiple user needs. According to the design model guidance, the design factors of the auto-driving takeover system are introduced into the strategic layer, and the design is layer by layer according to the bottom-up construction principle. Finally, presentation layer expresses the whole design concept through the prototype, interface and story version.

3.1 Strategy Layer Design

The strategic layer consists of “design goals” and “user needs”, so that design factors can be imported directly. The goal is to design an automatic driving takeover system interface that assists the driver in safely completing the control switching and improves the driver’s user experience. Quantifying this design goal into three specific metrics of design success: through the interaction strategy design of the takeover system. ① When the takeover warning is issued, the driver successfully takes over the vehicle in a safe time, or takes over faster, which improve the efficiency of takeover and quality; ② The driver’s distraction is reduced, the situational awareness is improved; ③ Improves the driver’s user experience in the automatic driving mode. In the design process, the specific user needs are placed in the dominant position to dominate the design direction.

3.2 Scope Layer Design

The scope layer design of the automatic driving takeover system is to design appropriate strategies and functions for the user according to the needs and objectives of the strategic layer. There are two kinds of strategies according to the functional attributes, situation information notification strategy and game incentive strategy.

The Situation Information Notification Strategy.

It is the main function of the takeover system, which is mainly used to improve the driver’s situational awareness, reduce distraction, and enhance driving load. The user experience mainly meets the user’s sensory experience needs and interactive experience needs.

The Game Incentive Strategy.

It is a secondary function of the takeover system. It is mainly used to improve the driver’s takeover motivation and increase the driving load to improve the situational awareness. At the same time, the game incentive can also meet the high level of user experience. The user experience mainly meets the user’s emotional experience needs, social experience needs and personality experience needs.

After determining the two strategies, combined with the highly automatic driver’s takeover process model [16], as shown in Fig. 3, the autopilot takeover is divided into two sections: the waiting time and the takeover time, and the functional scope is separately set for the two processes.

Fig. 3.
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Highly automatic driver’s takeover process model

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Notification Strategy of Situational Information

Waiting Time to Takeover.

In the waiting time, the driver’s situational awareness is low, and the system recognizes the change of the external situation. In highly automatic driving, most of the changes do not meet the takeover conditions, such as parallel cars, following cars or entering the tunnel. In order for the driver to maintain a certain situational awareness, the system needs to actively inform the driver of these situational information. The system informs the driver of the information visually and audibly, and the driver needs to look up and understand the information. This process increases the driving load during the autonomous driving process and reduces driving distraction. At the same time, maintaining a certain level of situational awareness is more conducive to responding to takeover requests more quickly.

Takeover Time.

When the takeover condition is triggered, the automatic driving takeover system issues a visual and audible alert request to the pilot to take over. The situation is constantly changing and the road load is not the same. For the driver, it may be necessary to know more quickly the criticality and information of the current takeover situation in order to make the appropriate response faster. This requires that the risk of the takeover warning message be consistent with the takeover scenario. Lerner proposes a multi-level alert, in the highest level of warning, criticality is very important to ensure full warnings are achieved [17]. Road load degree refers to the ratio of the actual traffic flow of the road section to the traffic capacity of the road section, which can be used for dynamic analysis of traffic operation status [17]. The high-risk takeover scenarios are more likely to occur when using automatic driving in high-load roads. Therefore, in the automatic driving takeover system, it is necessary to classify the urgency of the takeover according to the road load, and convey the information to the driver through a multi-level warning method.

The layered warning method can predict the importance of the event in advance and make a takeover warning when the driver hears the warning sound or looks up the warning icon. Multi-layered warnings can alleviate the aversion that is caused by duplicate information and improve the quality of takeovers compared to single-level warnings. But it is important that the multi-layered warning method will also bring a new cognitive burden to the driver. When the driver hears the warning sound or looks up at the warning icon, it takes time to understand the meaning of the information. Therefore, how many levels are most suitable, and what are the characteristics of multiple layers of hearing and vision, this problem is brought into the experiment and the best solution is got.

The peripheral vision of a person has a feature of recognizing a fast moving or sudden appearance more quickly than a foveal field of view. Therefore, in the mood of the autonomous driving driver, the display manner of the warning information can combine the foveal field of view with the peripheral field of view. The peripheral view helps the driver to perceive the presence of information, while the foveal view helps the driver understand the content of the message.

Game Incentive Strategy.

In the process of automatic driving, the driver’s situational awareness is low, and the essential reason is the lack of motivation to look up the road. Motivation refers to behavior characterized by intention and will. It affects whether humans decide to take action and whether it is internal or external. Intrinsic motivation stems from the desire to engage in specific behaviors for their own benefit, with internal rewards such as enjoyment or satisfaction. Extrinsic motivation stems from the desire for specific behaviors caused by external reward commitments or threatened external rewards. These motivations affect the driver’s active acquisition of situational awareness and willingness to take over. Although traffic laws and regulations require each driver to take over, individual factors such as mood, time pressure or social status often lead to disregard and non-cooperation. The concept of gamification, in the background of connected driving, is considered to have the potential to be applied to the driving process and to solve more problems. The table below summarizes some of the game elements that are suitable for an automatic driving takeover system, as shown in Table 5.

Table 5. The specific contents of each level that affect the driver experience
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Waiting Time to Takeover.

During the waiting time, the driver’s driving load is low, and it is necessary to encourage the driver to use artificial driving. On the one hand, it prevents the driver from over-trusting the automatic driving system, and on the other hand, prevents the driver’s driving skills from deteriorating. Second, it can also motivate drivers to participate more in social tasks on the windshield. When the driver interacts with other drivers, cars or the environment on the wind window, he can passively obtain situational awareness, which is benefit for the takeover. Other than that, Social activities themselves can also meet the user’s social experience needs, even personalized needs.

Takeover Time.

At the takeover time, the entire process of taking over the action is “gamed”, so that the takeover task is considered to be “want to take over” rather than “must take over”, which is “interesting” rather than “responsibility.” Adding game factors to the takeover task and setting up a “takeover behavior scoring mechanism”, the fun of which improves the takeover motivation and satisfies the user’s emotional experience needs.

In the true HAD situation, the “game rewards” of the system for the driver may be fulfilled as actual economic benefits. For example, if the driver takes over the score, the corresponding ones may receive real rewards such as free car wash, refueling discount, and free toll. However, if the driver scores poorly, there will be certain penalties, such as limiting the speed of self-driving and the length of use. The game incentive strategy may involve more advanced business strategies in the development of connected driving.

The design of the interface layer of the automatic driving takeover system interactive interface is shown in Table 6.

Table 6. The design of the interface layer of the automatic driving takeover system interactive interface
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3.3 Design of Structure Layer

The structural layer design of the automatic driving takeover system is to refine the functional contents of the takeover system, tease out the structure and hierarchical relationship between the interfaces, etc. The design can according to two strategies, which are the situation information classification strategy and the game incentive strategy. Although the function of the takeover system is simple, reasonable content planning, classification, and subdivision can ensure the integrity of the final output, which is very important for the notification strategy of situational information and driving safety. Classification strategy of situation information as follows:

Divide the Situation into the Waiting Time and Takeover Time.

Both time periods need to provide the user with the situation, especially the takeover time.

Notification Policy for Change of the Takeover Time (The Situation Where the Takeover Condition Is Not Reached).

The information of situation change is divided into four categories: road change information (multiple corners, front tunnel), dynamic vehicle change information (with car following, with cars in parallel), traffic congestion information and target distance information, and so on.

Takeover Time (In the Situation of the Takeover Condition) Using the Stratification Strategy of Takeover Warning.

The current situational load is conveyed through multiple levels of warnings. The specific warning information includes visual warning information and audible warning information. The warning layer is divided into three levels, and more than three layers would have significant cognitive. Game incentive strategy as follows:

Scoring Mechanism of Takeover Behavior.

The scoring mechanism takeover behavior is divided into five information elements, including the current takeover status, the current takeover time, the current takeover score, the comprehensive takeover score, and the number of consecutive successful takeovers. The current takeover status represents the success or failure of this takeover, the time from the issuance of the warning message to the successful control of the driver and the score for the efficiency and quality of this takeover. The grade of comprehensive takeover is to calculate the average score of each takeover and give the driver a badge. The badge is graded according to the game routine, and is divided into five colors: gray, green, blue, and purple. The higher the level, the more privilege the driver can have. Permissions, such as unlocking patterns, phrases, etc. available for social features. The number of consecutive successful takeovers is represented by the number of combo times. The higher the number of Combo, the more “achievement” is obtained.

The badges in the comprehensive takeover score have different powers according to the badge level. When the score level is higher than the blue badge, the higher the level, the more real world economic rewards, such as free car wash, free toll, fuel discount, etc. When the rating is lower than the blue badge, the lower the level, the restrictions will be imposed, such as limiting the cruising speed limit or even disabling the autopilot function.

Social Mechanism of Windshield.

The social mechanism of windshield refers to simple interaction with other cars, drivers, environments, etc. on the car window directly through gestures or touch screens. The mechanism is divided into “nearby riders” and “personalization”. “Nearby riders” can identify nearby vehicles and issue daily phrases and patterns. “Personalization” means that the driver can choose and set his or her favorite personality. Icons and titles represent the attributes of yourself and the car. These icons and titles can be obtained by increasing the overall takeover score, or by unlocking achievements by completing the incentive task.

Mission Achievement Mechanism.

There are “Today’s Mission” and “Task Achievement”. “Today’s mission” includes “completed missions” and “unfinished missions”. The mission here is to encourage more drivers to use manual driving and windowing, etc. Completion of tasks can improve the overall score. “Task Achievements” also includes “Achieved Achievements” and “Unfulfilled Achievements”. Achievements can unlock icons and titles in “Personalization”.

3.4 Design of Framework Structure

The windshield may become a new display carrier, and the Augment Reality Full Windshield Display (AR-FWSD) may also play an important role in the future of HAD cars. Unlike ARDs, AR-FWSD can use a large area of windshield as the display area, while a typical HUD is usually only three to five inches. The small display area imposes significant restrictions on driving and safety-related information, because its instrument area is more crowded, giving the driver a cognitive load when performing driving tasks. At the same time, the information prompts are spatially separated from the real world, and the driver needs to distract attention to find the location of the event, such as a pedestrian warning, and the driver still needs time to search for the specific location of the pedestrian.

At the same time, most AR-HUDs currently put information in the driver’s visual center (i.e., the foveal view) because the visual resolution in the center of the field of view is much higher than elsewhere, and the spatial resolution of the human field of view declines sharply from the center to the edge. So the peripheral area except the fovea area (i.e., the peripheral field of view) is considered unsuitable for putting important information. However, the peripheral vision of a person has a feature of recognizing a fast moving or sudden appearance more quickly than a foveal field of view. Therefore, in the automatic driving mode, the driver is distracted and when the system detects a burst of non-fixed information, it won’t work if it is displayed in the peripheral area. AR-FWSD not only provides opportunities for new information presentations and visual experiences, but also integrates automatic driving, car networking and social entertainment applications. AR-FWSD will be the most appropriate interactive window for driving sub-tasks.

Based on AR-FWSD, in the human-computer interaction interface design model based on user experience, design factors include design goals, user experience needs and design carriers. Among them, the design carrier is the front windshield of the car, and the design goals and user experience needs are related to the user information and the current user driving situation.

The main content of the frame layer design is the layout and planning of the information on the AR-FWSD, that is, how to clearly and properly present the contents and functions of the takeover system to the driver. The visual resolution of a person’s central field of view is much higher than elsewhere, and the spatial resolution of a person’s field of view is sharply reduced from the center to the edge [18]. The human peripheral field of view has a feature that can identifies things that move quickly or suddenly more quickly when compared to the foveal field of view. It is necessary to arrange the information in a reasonable position of the AR-FWSD based on the visual characteristics of these two points.

Each layer of the warning information includes auditory information and visual information, and the visual information is simultaneously displayed on different areas of the AR-FWSD through two presentation modes. The first type is a peripheral area for peripheral visual field information display along the edge of the wind window. The flashing information appears in a more favorable manner for the driver to recognize the presence of the warning information in the distracting state. In a highly automated driving situation, the driver’s behavior is uncertain and does not necessarily have to sit in a regular driving position. At the same time, in recent years, more and more autonomous car interior concept design allows the driver to have more space for activities, so the driver’s most central view on the wind window is uncertain. Therefore, the intermediate area except the edge area of the wind window can be used to display specific warning information.

In addition, the information visualization feature in the AR system can solve the user’s attention-guided problem [19]. The dynamic display method the information is superimposed on the road or tracking the target’s activity (world-Fixed) helps the driver find the exact location where the risk exists [20]. Better tracking performance allows the driver to get better driving performance in the right lane. AR information design should aim at enhance tracking of activity symbols [21].

3.5 Design of Presentation Layer

The presentation layer visualizes the strategic layer, the scope layer, the structural layer and the framework layer. It is a direct expression of the mechanism of the driver’s takeover system and a carrier that reflects the usability of the interaction strategy design.

To ensure that the symbols of the car’s functions and functions can be (uniquely) identified and their functions are easy to use, ISO 2575 (ISO 2010a) defines symbols and colors that describe the state of the system (e.g., correct operation or failure). DIN EN ISO 15005 (DIN 2012) provides principles for dialogue management and sets standards for compliance. The principles of this standard complement the previous guidelines and address the requirements and compliance procedures for using dialogue while driving. The visual presentation of the IVIS ergonomics direction is covered in EN ISO 15008 (DIN 2011c), for example with regard to the image content and readability of (dynamic) content. To display alphanumeric messages in IVIS, SAE J2831 (SAE n.d.) provides information and design recommendations for OEM and aftermarket systems.

For the use of AR-HUD, Yang [22] and others summarized the existing theoretical results and conclusions of experimental research, and intensively study from the four aspects: road safety prompt information interface layout, information type compatibility, color and quantity. The research proposed the design principle of road safety prompt information interface of the vehicle AR-HUD.

Regarding the design of the voice user interface, the SAE J2988 is a standard being developed that will provide principles and guidance on how to safely use the voice user interface to control the vehicle’s selection functions and functions. The audible output DIN EN ISO 15006 (DIN 2012) provides ergonomic specifications for the design and integration of IVIS using sound and speech output. For example, details regarding sound frequency and loudness, information encoding, and enhancement of information (e.g., additional synchronized visual output).

Based on the above specifications and principles, the author designs the presentation layer of the automatic driving takeover system prototype. The design of situational information notification interface is shown in Figs. 4 and 5, and the design list is shown in Table 7.

Fig. 4.
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Interface design of layering strategy of takeover warning (Color figure online)

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Fig. 5.
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Interface design of notification of situational change information

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Table 7. Design list of situational information notification interface
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In the design of warning information, when designing a logo element, its edges can be enhanced. Use a contrasting color or white that has a high contrast with the environment to set the color edges and increase the contrast between the target color and the background to make it easier to recognize. At the same time, the color principle of importance information is observed, and red is the highest warning color. The warning information is displayed on the wind window in the form of AR. The warning icon would block the driver’s sight to some degree, so it is allowed to reduce the transparency of a certain icon, and the recognition of the warning icon does not completely affect the identification of the real environment information.

Add game elements to the interface design of the game motivation strategy to match the policy function settings. The relevant interface information of the game incentive strategy does not belong to the warning information. In order to avoid excessive occupation of the driver’s attention resources, no enhanced edge processing is performed. The selected color is technology blue, which represents intelligence, technology and security. The interface design of the takeover behavior scoring mechanism is shown in Fig. 7, and the design list is shown in Table 7. The interface design of the interconnection social mechanism is shown in Fig. 6. The interface design of task achievement mechanism is shown in Fig. 7.

Fig. 6.
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Interface design interconnected social mechanism achievement mechanism (Color figure online)

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Fig. 7.
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Interface design of task (Color figure online)

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The simulated automatic driving system developed based on this experimental research can realize the main functions of manual driving, automatic driving and driving control right switching, and can also synchronously record data related to tests, such as the times of collision, takeover time and takeover score. In the simulator, The automatic driving function is implemented by setting a default path in the map. When the car enters the range of collision module, a takeover warning is issued to simulate the takeover situation of the automatic driving, and the simulated road driving is as shown in Fig. 8.

Fig. 8.
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Simulated automatic driving system developed by Unity 3D

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4 Conclusion

Based on the user experience, the human-machine interface design of the automatic driving takeover system must always be user-centered, and deeply analyze user needs and situational features to perform function and content design in order to obtain a perfect user experience. The model is effective for the automatic driving takeover system, and explains the intrinsic connection between the user, the situation and the design object in the human-machine interface design of the system, which is conducive to understanding and integrating the survey information. The model will provide design guidance for the human-vehicle interface designer of the automatic driving takeover system to provide a better driving experience for drivers in an automatic driving situation. At the same time, the human-vehicle interface design model of the automatic driving takeover system based on user experience enriches the theoretical system of interaction design methodology and contributes to the design method of human-vehicle interface for the automatic driving takeover system.