Intelligent cabin interaction mode determination method, system and device and storage medium

Abstract

The invention relates to the field of intelligent cabins, and discloses an intelligent cabin interaction mode determination method, system and device and a storage medium, and the method comprises the steps: judging whether a user drives a vehicle alone or not; when the user drives the vehicle alone, the interaction mode of the intelligent cabin is determined according to the expression information of the user; and when other persons exist in the vehicle, determining an interaction mode of the intelligent cabin according to the user voice information. When the user drives alone, the expression recognition function is adopted, the expression of the driver is recognized, and the interaction mode of the intelligent cabin is adjusted according to the recognized expression. When other passengers exist in the vehicle except for the driver, a speech speed recognition function is adopted, and the emotion state of the user is recognized more accurately, so that a matched interaction mode is adopted. According to the invention, a more accurate emotion recognition method is adopted according to different scenes, so that the interaction mode of the intelligent cabin is adjusted according to the recognized emotion state.

Description

Technical Field

[0001] The present disclosure relates to the technical field of automobile intelligent cockpits, and in particular to a method, system, device and storage medium for determining an interaction mode of an intelligent cockpit. Background Art

[0002] Technology has promoted the development of the automotive industry. Intelligent connected vehicle technology has gradually entered the public's field of vision. At present, large-scale research and development of intelligent connected vehicle technology has begun to promote the development of the intelligent vehicle industry chain. With the growing demand for intelligence and personalization, the advantages of user expression recognition functions in cars are significant. However, the current interaction method does not take into account the actual scene conditions in the car, and the interaction method is not accurate enough. Summary of the invention

[0003] The embodiments of the present disclosure provide a method, system, device and storage medium for determining an intelligent cockpit interaction mode to solve or alleviate one or more of the above technical problems in the prior art.

[0004] According to one aspect of the present disclosure, a method for determining an intelligent cockpit interaction mode is provided, comprising: determining whether a user is driving a vehicle alone;

[0005] When the user is driving the vehicle alone, the interaction mode of the smart cockpit is determined based on the user's facial expression information;

[0006] When there are other people in the car, the interaction mode of the smart cockpit is determined based on the user's voice information.

[0007] In a possible implementation, determining the interaction mode of the smart cockpit according to the user expression information includes:

[0008] Get user facial expression information;

[0009] Determine the corresponding category of the expression according to the user's facial expression;

[0010] Determine the expression level corresponding to the current user's expression category according to the relationship between the expression corresponding category and the expression level;

[0011] Determine the interaction mode of the smart cockpit based on the expression level.

[0012] In a possible implementation, determining the interaction mode of the smart cockpit according to the user voice information includes:

[0013] Get user voice information;

[0014] Extracting speech text features according to user speech information, wherein the speech text features include intonation text information and speech speed text information;

[0015] Identify the user's emotional state level based on voice and text features;

[0016] The interaction mode of the smart cockpit is determined according to the user's emotional state level.

[0017] In a possible implementation, the method for determining the intelligent cockpit interaction mode includes:

[0018] Form a character portrait based on user expression information;

[0019] Integrate the role portrait into the interaction mode of the smart cockpit.

[0020] In a possible implementation, the method for determining the intelligent cockpit interaction mode includes:

[0021] Identifying a user's fatigue state based on user facial expression information and / or user voice information;

[0022] Determine the interaction mode of the smart cockpit based on the user's fatigue status.

[0023] According to one aspect of the present disclosure, a smart cockpit interaction mode determination system is provided, comprising:

[0024] A determination unit, used to determine whether the user is driving the vehicle alone;

[0025] A first determining unit, configured to determine an interaction mode of the smart cockpit according to user expression information when the user is driving the vehicle alone;

[0026] The second determination unit is used to determine the interaction mode of the smart cockpit according to the user voice information when there are other people in the car.

[0027] In a possible implementation manner, the first determining unit includes:

[0028] A first acquisition module is used to acquire user facial expression information;

[0029] A first determination module, used to determine a corresponding category of an expression according to a user's facial expression;

[0030] A second determination module is used to determine the expression level corresponding to the current user's expression category according to the relationship between the expression corresponding category and the expression level;

[0031] The third determination module is used to determine the interaction mode of the smart cockpit according to the expression level.

[0032] In a possible implementation manner, the second determining unit includes:

[0033] The second acquisition module is used to acquire user voice information;

[0034] An extraction module, used for extracting speech text features according to user speech information, wherein the speech text features include intonation text information and speech speed text information;

[0035] A recognition module, used to recognize the user's emotional state level based on speech and text features;

[0036] The fourth determination module is used to determine the interaction mode of the smart cockpit according to the user's emotional state level.

[0037] According to one aspect of the present disclosure, there is provided a device, comprising:

[0038] Processor and memory;

[0039] The memory is used to store a computer program, and the processor calls the computer program stored in the memory to execute any one of the above-mentioned methods for determining the smart cockpit interaction mode.

[0040] According to one aspect of the present disclosure, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, the processor is enabled to execute any of the above-mentioned methods for determining an interaction mode of a smart cockpit.

[0041] The present disclosure has the following beneficial effects: When the user is driving alone, the present disclosure uses the expression recognition function to recognize the driver's expression, and adjusts the interaction mode of the smart cockpit according to the recognized expression. When there are other passengers in the car besides the driver, the speech speed recognition function is used to more accurately recognize the user's emotional state and adopt a matching interaction mode. The present disclosure adopts a more accurate emotion recognition method according to different scenarios, so as to adjust the interaction mode of the smart cockpit according to the recognized emotional state.

[0042] The details of one or more embodiments of the present application are presented in the following drawings and descriptions. Other features and advantages of the present application will become apparent from the accompanying drawings. It should be understood that the above general description and the detailed descriptions below are only exemplary and explanatory and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0044] Figure 1 is a flow chart of a method for determining an intelligent cockpit interaction mode of the present exemplary embodiment;

[0045] Figure 2 is a block diagram of a smart cockpit interaction mode determination system of the present exemplary embodiment;

[0046] Figure 3 It is a schematic diagram of the structure of a device of this exemplary embodiment. DETAILED DESCRIPTION

[0047] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the example embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0048] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware units or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0049] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the steps. For example, some steps may be decomposed, while some steps may be combined or partially combined, so the actual execution order may change according to the actual situation.

[0050] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example.

[0051] In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or sub-modules is not necessarily limited to those steps or sub-modules explicitly listed, but may include other steps or sub-modules not explicitly listed or inherent to these processes, methods, products, or apparatuses.

[0052] Figure 1 is a flow chart of a method for determining an intelligent cockpit interaction mode of the present exemplary embodiment. Figure 1 As shown, an exemplary embodiment of the present disclosure provides a method for determining an intelligent cockpit interaction mode, comprising:

[0053] Determine whether the user is driving the vehicle alone;

[0054] When the user is driving the vehicle alone, the interaction mode of the smart cockpit is determined based on the user's facial expression information;

[0055] When there are other people in the car, the interaction mode of the smart cockpit is determined based on the user's voice information.

[0056] It is worth noting that the main operation mode of this embodiment is to call the iFlytek camera interface, collect hundreds of facial image data of users, and determine the level of the target expression according to the relationship between the target expression category and the classification that has been determined, so as to determine the interaction mode of the smart cockpit. The auxiliary operation mode is to convert the collected user voice information into text through the voice recognition module, and use the existing data analysis and processing method to evaluate and determine the user's emotional state level, so as to adopt corresponding different interaction methods. The technology involved is a multi-dimensional scenario composite technology that determines the target expression category through the above two operation methods to determine the interaction mode of the smart cockpit. The interaction method proposed in this embodiment needs to be supported by vehicles with cameras, audio speakers, wireless network cards, car infotainment domain controller modules, and car display screens, and cooperate with user mobile phones and match the connection relationship.

[0057] In voice social scenarios, the car machine increases the flexibility of the interaction method during the voice interaction process by recognizing the user's facial expressions, so as to improve the driver's driving experience and adapt the interaction method to the driver's emotions. At the same time, the change in speech speed is related to the user's emotional state, and the specific increase in speech speed is related to anxiety or excitement. When the user is driving alone, the driver's facial expression information is usually greater than the voice information. When there are other passengers in the user's car, the driver's voice information is usually greater than the facial expression information. Therefore, a multi-dimensional scenario composite technology that combines facial expression recognition and speech speed recognition is used to realize personalized interaction methods. The advantages of installing related technologies in the car are as follows:

[0058] Personalized experience: Customized services, expression recognition and speech speed recognition functions allow users to record their own or their relatives' facial expressions and voices, so as to switch different interaction methods according to their expressions and speech speed changes, making the interaction of the vehicle system more personalized. Emotional connection, by adopting different interaction methods based on user expression recognition and speech speed recognition, the emotional connection between users and vehicles is increased. User preference, users can select or change the interaction method according to different emotional states, and determine the interaction method of the smart cockpit according to the correspondence between the pre-set level and the interaction method.

[0059] Technical convenience: Easy recording process: The recording process of multiple facial images and voices is simple and fast. Users only need to follow the instructions to complete the video and recording. Fast training: The system takes a short time to recognize and classify user expressions and speech speeds. It takes about 30 minutes to complete the full-function recognition of users. Easy to manage: Users can easily manage and switch different interaction methods according to changes in facial expressions and speech speeds.

[0060] Wide range of application scenarios: Diverse uses. In addition to car systems, expression recognition and speech rate recognition technologies can also be applied to smart homes, smart devices and other fields. Social interaction. In social media or communication applications, using customized user expression recognition can increase the safety and intimacy of interaction. Content creation. Content creators can use expression recognition technology to portray characters and increase the appeal of their works.

[0061] Improve safety: Reduce fatigue driving, identify the user's fatigue state, and avoid safety hazards caused by the user's fatigue driving. In emergency situations, high-volume voice prompts and higher screen brightness may attract the driver's attention.

[0062] Enhanced interactivity: Simulating interpersonal communication, user expression recognition and speech speed recognition technology make the communication between the car system and people closer to real interpersonal communication.

[0063] Improved entertainment: During long-distance driving or traffic jams, interesting user expression recognition and speech speed recognition can improve driving interactivity and safety.

[0064] Improved sense of technology: Demonstrating advanced technology, the expression recognition and speech speed recognition functions demonstrate the advanced technology of vehicle intelligence and enhance the user's technological experience. Brand influence, car brands that provide expression recognition and speech speed recognition functions may thus enhance their competitiveness in the market.

[0065] Enhanced user stickiness: Dependence on personalized settings: Once users use the customized interaction method based on expression recognition and speech speed recognition, they may be more willing to use the vehicle out of habit. Long-term use and personalized interaction method settings may become one of the reasons why users use a certain model for a long time.

[0066] Economic benefits: Value-added services, expression recognition and speech rate recognition can be used as value-added services for vehicles to increase the added value of products. Maintenance costs, compared with traditional voice prompts, digital expression recognition and speech rate recognition technologies may reduce long-term maintenance and update costs.

[0067] In addition, vehicle customization can be enhanced: specifically, car owners can customize the interaction method according to their own voice and facial expressions, so that the personalization of the vehicle is not only reflected in the appearance and configuration, but also in the intelligent interactive experience.

[0068] Specifically, the interaction mode of the smart cockpit is determined according to the user's facial expression information, including:

[0069] Get user facial expression information;

[0070] Determine the corresponding category of the expression according to the user's facial expression;

[0071] Determine the expression level corresponding to the current user's expression category according to the relationship between the expression corresponding category and the expression level;

[0072] Determine the interaction mode of the smart cockpit based on the expression level.

[0073] In this embodiment, the advantage of the expression recognition function on the car is that it provides a more personalized, convenient and safe driving experience. This technology not only enhances the interaction between the vehicle and the user, but also shows a new trend of automobile intelligence. With the continuous development and improvement of technology, expression recognition and speech rate recognition functions are expected to be applied in more scenarios in the future, bringing more surprises and convenience to users.

[0074] Specifically, determining the interaction mode of the smart cockpit according to the user voice information includes:

[0075] Get user voice information;

[0076] Extracting speech text features according to user speech information, wherein the speech text features include intonation text information and speech speed text information;

[0077] Identify the user's emotional state level based on voice and text features;

[0078] The interaction mode of the smart cockpit is determined according to the user's emotional state level.

[0079] In this embodiment, when there are other passengers in the car besides the driver, the speech speed recognition function is used to more accurately identify the user's emotional state and adopt a matching interaction method. This embodiment adopts a more accurate emotion recognition method according to different scenarios, and adjusts the interaction method of the smart cockpit according to the recognized emotional state.

[0080] Specifically, it includes:

[0081] Form a character portrait based on user expression information;

[0082] Integrate the role portrait into the interaction mode of the smart cockpit.

[0083] In this embodiment, content creators can use expression recognition technology to create character portraits and present the character portraits in an interactive way in the smart cockpit to increase appeal.

[0084] Specifically, it includes:

[0085] Identifying a user's fatigue state based on user facial expression information and / or user voice information;

[0086] Determine the interaction mode of the smart cockpit based on the user's fatigue status.

[0087] In this embodiment, the user's fatigue state is identified to avoid the safety hazards caused by the user's fatigue driving. In an emergency, a high-volume voice prompt and a higher screen brightness may attract the driver's attention.

[0088] Figure 2 is a block diagram of a smart cockpit interaction mode determination system of the present exemplary embodiment. Figure 2 As shown, an exemplary embodiment of the present disclosure provides a smart cockpit interaction mode determination system, including:

[0089] A determination unit, used to determine whether the user is driving the vehicle alone;

[0090] A first determining unit, configured to determine an interaction mode of the smart cockpit according to user expression information when the user is driving the vehicle alone;

[0091] The second determination unit is used to determine the interaction mode of the smart cockpit according to the user voice information when there are other people in the car.

[0092] Specifically, the first determining unit includes:

[0093] A first acquisition module is used to acquire user facial expression information;

[0094] A first determination module, used to determine a corresponding category of an expression according to a user's facial expression;

[0095] A second determination module is used to determine the expression level corresponding to the current user's expression category according to the relationship between the expression corresponding category and the expression level;

[0096] The third determination module is used to determine the interaction mode of the smart cockpit according to the expression level.

[0097] Specifically, the second determining unit includes:

[0098] The second acquisition module is used to acquire user voice information;

[0099] An extraction module, used for extracting speech text features according to user speech information, wherein the speech text features include intonation text information and speech speed text information;

[0100] A recognition module, used to recognize the user's emotional state level based on speech and text features;

[0101] The fourth determination module is used to determine the interaction mode of the smart cockpit according to the user's emotional state level.

[0102] In this embodiment, the expression recognition and speech rate recognition systems are usually used in conjunction with intelligent voice recognition technology and intelligent facial image recognition technology to achieve fast and accurate command recognition and feedback, thereby improving operational efficiency. Related components include:

[0103] In a broad sense, a vehicle is a vehicle that is driven by an engine to travel. In a narrow sense, it is a vehicle, including new energy vehicles, sedans, SUVs, MPVs, commercial vehicles, etc. This vehicle needs to be equipped with a product containing a communication module.

[0104] The domain controller module is the core of each functional domain of the car. It is mainly composed of three parts: the domain master processor, the operating system, and the application software and algorithms. It is generally called the "host". In this disclosure, it refers to the infotainment domain controller.

[0105] Voice cloud platform is a technology platform that provides intelligent voice interaction services. This platform integrates advanced artificial intelligence technologies such as speech recognition, speech synthesis, and natural language understanding to quickly generate a usable speech synthesis library and accurately identify the user's voice data.

[0106] In-car audio system: A high-quality audio system is the basis for accurate sound playback. For example, Sony's advanced in-car audio system with 14 speakers can accurately hear the sound and provide the driver with a clear sound quality experience.

[0107] The car's central control screen, the car's central control screen display, can display images and can perform touch screen operations.

[0108] The personalized interaction method is: click the camera in the ALL APP interface to enter, and before entering the main interface of taking pictures, set the camera switch to the on state. Facial image sampling, when the camera and the car computer keep the network unobstructed, you can scan the car computer QR code to enter the mini program. According to the guidance prompts, perform facial image recording and voice recognition in a quiet environment. The driver's facial expression video image data is collected through the DMS (Driver Monitoring System, driver monitoring module), and the collected video image data is transmitted to the main control module. The voice acquisition module is used to collect the voice data of all people in the car, and the collected voice data is transmitted to the voice recognition module. The account in the camera system is bound and synchronized with the mini program account. After the expression and sound recording are displayed on the mobile phone, click the button in the car computer to refresh the current list. Find the system settings in the control panel of the car computer, enter the settings to switch to the personalized interaction mode, and you can start to experience the composite personalized interaction mode service.

[0109] The specific control strategy or control method is as follows: the user downloads and installs the developed APP application or applet on the mobile phone, and the car computer also pre-installs the expression and speech speed recognition APP developed by the car company. The user logs in to the account on the mobile phone, which is consistent with the car computer account. The expression information generated by the user in the car is graded by DMS, and the generated voice information is converted into text through the voice recognition module. After uploading, the cloud will process the video image, such as editing, converting to text, adjusting the image quality, etc., to ensure the accuracy of the analysis and evaluation of the video image information. Then the platform's powerful voice analysis and evaluation capabilities are output into text and fed back to the car computer. The user logs in to the account on the car computer, enters the APP for the first time in the car system, and clicks the refresh control. The car computer recognizes emotions and adjusts the interaction mode function.

[0110] Figure 3 Schematic diagram of the structure of a device of this exemplary embodiment. Figure 3 As shown, corresponding to the method for determining the interaction mode of the smart cockpit provided above, the present disclosure also provides a device. Since the embodiment of the device is similar to the above method embodiment, the description is relatively simple. Please refer to the description of the above method embodiment for relevant points. The device described below is only schematic. The device may include: a processor 1, a memory 2 and a communication bus (i.e., the above device bus) and a search engine, wherein the processor 1 and the memory 2 communicate with each other through the communication bus and communicate with the outside through the communication interface. The processor 1 can call the logic instructions in the memory 2 to execute the method for determining the interaction mode of the smart cockpit.

[0111] In addition, the logic instructions in the above-mentioned memory 2 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present disclosure. The aforementioned storage medium includes: a storage chip, a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, and other media that can store program codes.

[0112] On the other hand, an embodiment of the present disclosure further provides a processor-readable storage medium, on which a computer program 3 is stored. When the computer program 3 is executed by the processor 1, the method for determining the smart cockpit interaction mode provided in the above embodiments is implemented.

[0113] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor 1, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drive (SSD)), etc.

[0114] The above are only preferred implementations of the present disclosure, and the protection scope of the present disclosure is not limited to the above embodiments. All technical solutions under the concept of the present disclosure belong to the protection scope of the present disclosure. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present disclosure should be regarded as the protection scope of the present disclosure.

Claims

1. A method for determining an intelligent cockpit interaction mode, characterized in that: include: Determine whether the user is driving the vehicle alone; When the user is driving the vehicle alone, the interaction mode of the smart cockpit is determined based on the user's facial expression information; When there are other people in the car, the interaction mode of the smart cockpit is determined based on the user's voice information.

2. The method for determining the intelligent cockpit interaction mode according to claim 1, characterized in that: The interaction modes of the smart cockpit determined based on user expression information include: Get user facial expression information; Determine the corresponding category of the expression according to the user's facial expression; Determine the expression level corresponding to the current user's expression category according to the relationship between the expression corresponding category and the expression level; Determine the interaction mode of the smart cockpit based on the expression level.

3. The method for determining the intelligent cockpit interaction mode according to claim 1, characterized in that: The interaction modes of the smart cockpit determined based on the user's voice information include: Get user voice information; Extracting speech text features according to user speech information, wherein the speech text features include intonation text information and speech speed text information; Identify the user's emotional state level based on voice and text features; The interaction mode of the smart cockpit is determined according to the user's emotional state level.

4. The method for determining the intelligent cockpit interaction mode according to any one of claims 1 to 3, characterized in that: include: Form a character portrait based on user expression information; Integrate the role portrait into the interaction mode of the smart cockpit.

5. The method for determining the intelligent cockpit interaction mode according to any one of claims 1 to 3, characterized in that: include: Identifying a user's fatigue state based on user facial expression information and / or user voice information; Determine the interaction mode of the smart cockpit based on the user's fatigue status.

6. A smart cockpit interaction mode determination system, characterized in that: include: A determination unit, used to determine whether the user is driving the vehicle alone; A first determining unit, configured to determine an interaction mode of the smart cockpit according to user expression information when the user is driving the vehicle alone; The second determination unit is used to determine the interaction mode of the smart cockpit according to the user voice information when there are other people in the car.

7. The intelligent cockpit interaction mode determination system according to claim 6, characterized in that: The first determining unit includes: A first acquisition module is used to acquire user facial expression information; A first determination module, used to determine a corresponding category of an expression according to a user's facial expression; A second determination module is used to determine the expression level corresponding to the current user's expression category according to the relationship between the expression corresponding category and the expression level; The third determination module is used to determine the interaction mode of the smart cockpit according to the expression level.

8. The smart cockpit interaction mode determination system according to claim 6, characterized in that: The second determining unit includes: The second acquisition module is used to acquire user voice information; An extraction module, used for extracting speech text features according to user speech information, wherein the speech text features include intonation text information and speech speed text information; A recognition module, used to recognize the user's emotional state level based on speech and text features; The fourth determination module is used to determine the interaction mode of the smart cockpit according to the user's emotional state level.

9. A device, characterized in that: include: Processor and memory; The memory is used to store a computer program, and the processor calls the computer program stored in the memory to execute the method for determining the smart cockpit interaction mode according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is enabled to execute the method for determining the smart cockpit interaction mode according to any one of claims 1 to 5.

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