A virtual vehicle guidance processing method, system, device and medium

Abstract

This application provides a virtual vehicle guidance processing method, system, device, and medium. The method includes: acquiring vehicle configuration information; constructing a vehicle virtual model based on the vehicle configuration information; classifying executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple function sets of categories, and establishing a mapping relationship between the corresponding function sets of categories and guidance voice; responding to user interaction with the vehicle virtual model, invoking the mapping relationship to determine the guidance voice corresponding to the interaction, and guiding the user to learn the functions of the corresponding functional areas based on the guidance voice. This application uses a vehicle virtual model for interaction, making it easier for users to understand various vehicle functions and effectively enhancing the user experience.

Description

Technical Field

[0001] This application relates to the field of intelligent vehicle applications, and in particular to a virtual vehicle guidance processing method, system, device, and medium. Background Technology

[0002] Today's cars boast an ever-increasing array of functions, and users accustomed to traditional car models don't actively seek out these features, leading to the idleness and waste of many resources that could enhance the user experience. Past technologies relied solely on photos, videos, or audio clips in the user manual to introduce car functions, storing the manual's content in a question-and-answer format. The system then used voice recognition to determine the user's question and displayed the answer via voice or screen. However, voice prompts or simple text displays cannot meet the evolving user experience demands of increasingly intelligent vehicles. The text-and-voice question-and-answer approach is unsuitable for the new intelligent modules in modern cars, failing to intuitively express and utilize existing vehicle functions. Summary of the Invention

[0003] In view of the problems existing in the prior art, this application proposes a virtual vehicle guidance processing method, system, device and medium, which mainly solves the problem that the existing question-and-answer based vehicle function introduction method is prone to some functions being idle, not intuitive enough, and thus affecting the user experience.

[0004] To achieve the above and other objectives, the technical solution adopted in this application is as follows.

[0005] This application provides a virtual vehicle guidance processing method, including:

[0006] Obtain vehicle configuration information and construct a virtual vehicle model based on the vehicle configuration information;

[0007] The executable functions corresponding to multiple preset functional areas in the vehicle virtual model are classified to obtain multiple categories of function sets, so as to establish a mapping relationship between the corresponding category of function sets and the guidance voice.

[0008] In response to the user's interaction with the vehicle virtual model, the mapping relationship is invoked to determine the guiding voice corresponding to the interaction, so as to guide the user to learn the functions of the corresponding functional area according to the guiding voice.

[0009] In one embodiment of this application, after constructing a virtual vehicle model based on the vehicle configuration information, the method further includes:

[0010] Operable identifiers are provided for each of the preset functional areas of the vehicle virtual model to guide the user to locate the preset functional areas through the operable identifiers;

[0011] After the user completes the learning of the corresponding preset function area, the operable identifier is updated to distinguish the learning progress of the preset function area.

[0012] In one embodiment of this application, the executable functions corresponding to multiple preset functional areas in the vehicle virtual model are classified to obtain multiple sets of functions, including:

[0013] Each of the preset functional areas is configured with at least one executable function and a corresponding function code;

[0014] Obtain the category identifier bit in the function code, and merge the executable functions with the same category identifier bit into the same set to obtain the function set of the corresponding category.

[0015] In one embodiment of this application, establishing a mapping relationship between corresponding function sets and guiding voice includes:

[0016] Obtain key features of each voice information in a preset voice database, and perform clustering based on the key features to obtain the voice category corresponding to each voice information;

[0017] The categories of the function set are compared with the voice categories to obtain the matching voice categories;

[0018] Based on the matched voice category, voice information from the preset voice database is invoked as guiding voice to establish a mapping relationship between the corresponding category's function set and the guiding voice.

[0019] In one embodiment of this application, in response to an interaction between a user and the vehicle virtual model, the mapping relationship is invoked to determine the guidance voice corresponding to the interaction, including:

[0020] The target functional area selected by the user is determined based on the interactive operation, and the set of functions contained in the target functional area is taken as the target functional set.

[0021] Based on the category of the target function set, the mapping relationship is invoked to obtain all the guiding voices corresponding to the target function set as the guiding voices corresponding to the interactive operation;

[0022] Obtain the key features of each guiding voice corresponding to the interactive operation, and combine all the key features into a feature sequence;

[0023] Based on the feature sequence, a function introduction voice is generated for the target function area to guide the user in selecting functions.

[0024] In one embodiment of this application, guiding the user to learn the functions of a corresponding functional area according to the guiding voice includes:

[0025] After the user completes the operation specified by the guiding voice, the corresponding functional effect screen is generated;

[0026] In response to the user's confirmation based on the function effect screen, the function corresponding to the function effect screen is executed on the vehicle.

[0027] In one embodiment of this application, after guiding the user to learn the functions of the corresponding functional areas according to the guiding voice, the method further includes:

[0028] Obtain the current user's identity information, mark the current user's learning progress in the vehicle virtual model, and associate and store the marked vehicle virtual model with the current user's identity information;

[0029] When switching users, the associated vehicle virtual model is invoked based on the identity information of the new user.

[0030] In one embodiment of this application, after constructing a virtual vehicle model based on the vehicle configuration information, the method further includes:

[0031] Establish a communication connection between the virtual vehicle model and the corresponding vehicle;

[0032] When the vehicle starts, abnormal areas are marked in the vehicle virtual model based on the vehicle's self-check information.

[0033] In one embodiment of this application, after marking the abnormal areas in the vehicle virtual model, the method further includes:

[0034] If the anomaly corresponding to the anomaly region meets the user's self-handling conditions, then the corresponding anomaly handling steps will be output.

[0035] If the anomaly corresponding to the abnormal area does not meet the user's character processing conditions, then a repair shop search is performed based on the vehicle's location, and recommended repair shop address information is output; or, emergency rescue or towing phone numbers are output.

[0036] This application also provides a virtual vehicle guidance processing system, including:

[0037] The model building module is used to obtain vehicle configuration information and build a virtual vehicle model based on the vehicle configuration information.

[0038] The function and voice association module is used to classify the executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple function sets of categories, so as to establish a mapping relationship between the corresponding function sets and the guidance voice.

[0039] The guidance module is used to respond to the user's interaction with the vehicle virtual model, call the mapping relationship to determine the guidance voice corresponding to the interaction, and guide the user to learn the functions of the corresponding functional area according to the guidance voice.

[0040] This application also provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the virtual vehicle guidance processing method.

[0041] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the virtual vehicle guidance processing method described above.

[0042] As described above, this application provides a virtual vehicle guidance processing method, system, device, and medium, which have the following beneficial effects.

[0043] This application constructs a virtual vehicle model, allowing users to quickly and intuitively understand the vehicle's functions simply by interacting with the virtual model. It provides users with an intuitive visual display and voice guidance, making it easy for users to quickly master the use of the relevant functions. Attached Figure Description

[0044] Figure 1 This is a schematic diagram illustrating an application scenario of the virtual vehicle guidance processing method in one embodiment of this application.

[0045] Figure 2 This is a schematic diagram of the structure of a terminal provided in an embodiment of this application.

[0046] Figure 3 This is a flowchart illustrating a virtual vehicle guidance processing method in one embodiment of this application.

[0047] Figure 4 This is a block diagram of a virtual vehicle guidance processing system in one embodiment of this application.

[0048] Figure 5 This is a schematic diagram of the device in one embodiment of this application. Detailed Implementation

[0049] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0050] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0051] The embodiments of this application can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, smart transportation, assisted driving, and intelligent vehicles. The following describes exemplary applications of the devices provided in the embodiments of this application. These devices can be implemented as various types of user terminals such as smartphones, smartwatches, laptops, tablets, desktop computers, set-top boxes, mobile devices (e.g., mobile phones, portable music players, personal digital assistants, dedicated messaging devices, portable gaming devices), intelligent voice interaction devices, smart home appliances, and in-vehicle terminals, or as servers. The following describes exemplary applications when the device is implemented as a server.

[0052] In one embodiment, a virtual model corresponding to the vehicle can be constructed. This virtual model achieves a one-to-one reproduction of the vehicle's internal and external structure and functions. When the user opens the virtual vehicle interface, the operable parts are circled with small dots. The functions of each module are coded according to their functional modules. The left side displays zoomed-in operations, and the right side can simulate animated effects. 360-degree dragging and rotation around the center are supported. Based on the offline configuration, an internal virtual vehicle model is created, and the vehicle model configuration is read from the offline configuration to achieve a one-to-one reproduction of the interior and control system. For the external virtual vehicle interface, the vehicle model configuration is read from the offline configuration, and an external virtual vehicle model is created. The layout of components on the vehicle body is shown, along with the current energy flow status of the vehicle body modules and the overall energy flow path. The user can also request other interaction methods through human-computer interaction, such as single-click or double-click to zoom in, and subsequent clicks or double-clicks to zoom out.

[0053] Please see Figure 1 , Figure 1This is a schematic diagram illustrating an application scenario of the virtual vehicle guidance processing method in one embodiment of this application. Terminal 400 can connect to server 200 via network 100 to obtain the configuration information of the corresponding vehicle model stored on server 200. Server 200 can also connect to the system of vehicle terminal 300 via network 100 to read the configuration information of vehicle terminal 300 and store it in the database of server 200. Terminal 400 performs a one-to-one modeling of the vehicle based on the configuration information to obtain a virtual vehicle model. Users can interact with the virtual vehicle model set by vehicle terminal 400 to understand the various functions of the corresponding vehicle. Terminal 400 can also establish a connection with the vehicle system of vehicle terminal 300 via network 100 to obtain the vehicle's operating status and mark any faults in vehicle terminal 300 in the virtual vehicle model to remind users to handle them promptly. Simultaneously, information such as the vehicle's energy flow path can be obtained and synchronized to the virtual vehicle model for intuitive display, allowing designers to understand the energy consumption of various vehicle components and providing data reference for subsequent vehicle design.

[0054] In one embodiment, server 200 may be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0055] In one embodiment, vehicle configuration information can also be entered on terminal 400, and a virtual vehicle model can be constructed based on the entered vehicle configuration information. After the terminal 400 completes the construction of the virtual vehicle model, it sends the model to vehicle 300 so that the user can try interacting with the virtual vehicle model and understand the various functions of the vehicle during vehicle use. In another embodiment, the terminal can be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, smart voice interaction device, smart home appliance, or in-vehicle terminal, etc., but is not limited to these.

[0056] See Figure 2 , Figure 2 This is a schematic diagram of the structure of the terminal 400 provided in the embodiment of this application. Figure 2 The terminal 400 shown includes at least one processor 410, a memory 450, at least one network interface 420, and a user interface 430. The various components in the terminal 400 are coupled together via a bus system 440. It is understood that the bus system 440 is used to implement communication between these components. In addition to a data bus, the bus system 440 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 2 The general labeled all buses as Bus System 440.

[0057] The processor 410 can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0058] User interface 430 includes one or more output devices 431 that enable the presentation of media content, including one or more speakers and / or one or more visual displays. User interface 430 also includes one or more input devices 432, including user interface components that facilitate user input, such as a keyboard, mouse, microphone, touch screen display, camera, other input buttons and controls.

[0059] Memory 450 may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state storage, hard disk drives, optical disk drives, etc. Memory 250 may optionally include one or more storage devices physically located away from processor 410.

[0060] The memory 450 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), and the volatile memory may be random access memory (RAM). The memory 450 described in this application embodiment is intended to include any suitable type of memory.

[0061] In some embodiments, memory 450 is capable of storing data to support various operations, examples of which include programs, modules, and data structures or subsets or supersets thereof, as illustrated below.

[0062] Operating system 451 includes system programs for handling various basic system services and performing hardware-related tasks, such as the framework layer, core library layer, driver layer, etc., for implementing various basic business functions and handling hardware-based tasks;

[0063] The network communication module 452 is used to reach other computing devices via one or more (wired or wireless) network interfaces 420, exemplary network interfaces 420 including: Bluetooth, WiFi, and Universal Serial Bus (USB), etc.

[0064] Presentation module 453 is configured to enable the presentation of information (e.g., a user interface for operating peripheral devices and displaying content and information) via one or more output devices 431 (e.g., a display screen, a speaker, etc.) associated with user interface 430;

[0065] The input processing module 454 is used to detect and translate one or more user inputs or interactions from one or more input devices 432.

[0066] In some embodiments, the apparatus provided in this application can be implemented in software. Figure 2 A virtual vehicle guidance processing system 455 stored in memory 450 is shown. It can be software in the form of programs and plug-ins, including the following software modules: model building module 4551, function and voice association module 4552, and guidance module 4553. These modules are logical and can therefore be arbitrarily combined or further split according to the functions implemented.

[0067] The functions of each module will be explained below.

[0068] In other embodiments, the system provided in this application can be implemented in hardware. As an example, the system provided in this application can be a processor in the form of a hardware decoding processor, which is programmed to execute the virtual vehicle guidance processing method provided in this application. For example, the processor in the form of a hardware decoding processor can be one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0069] In some embodiments, the terminal or server can implement the virtual vehicle guidance processing method provided in this application by running a computer program. For example, the computer program can be a native program or software module in an operating system; it can be a native application (APP), that is, a program that needs to be installed in the operating system to run, such as a social application APP or a messaging APP; it can also be a mini-program, that is, a program that only needs to be downloaded to a browser environment to run; or it can be a mini-program or web client program that can be embedded in any APP. In short, the above-mentioned computer program can be any form of application, module or plugin.

[0070] The following will describe the virtual vehicle guidance processing method provided in this application embodiment, with reference to the exemplary application and implementation of the device provided in the embodiments of this application.

[0071] Please see Figure 3 This application provides a virtual vehicle guidance processing method, which includes the following steps.

[0072] Step S300: Obtain vehicle configuration information and construct a vehicle virtual model based on the vehicle configuration information.

[0073] In one embodiment, corresponding vehicle models can be constructed for different vehicle configurations, and a one-to-one reconstruction model of the vehicle can be performed based on the vehicle configuration to obtain a virtual vehicle model.

[0074] In one embodiment, the vehicle virtual model may include an interior virtual model and an exterior virtual model. The interior and control systems are replicated one-to-one based on the vehicle's internal configuration. The interior configuration includes: seats, seat cushions, audio system, speaker distribution, steering wheel, turn signal control stalks, wiper control stalks, and air conditioning vents. The exterior virtual model is constructed based on the layout of the vehicle's components. These components include doors, turn signals, chassis, tires, rearview mirrors, and wipers. The energy flow and overall energy flow path of the vehicle can be displayed in the exterior virtual model to determine the energy consumption of various parts of the vehicle, thus providing designers with improvement references.

[0075] In one embodiment, after constructing a virtual vehicle model based on the vehicle configuration information, the following steps are further included:

[0076] Step S301: Provide operable identifiers for each of the preset functional areas of the vehicle virtual model, so as to guide the user to locate the preset functional areas through the operable identifiers.

[0077] In one embodiment, functional areas can be divided on the vehicle virtual model, establishing multiple preset functional areas. These areas are user-operable and can perform corresponding functions based on user actions, such as turning on the turn signals, turning on the audio system, turning on the air conditioning, adjusting the seat back, and adjusting the rearview mirror angle. Based on the divided preset functional areas, corresponding operable icons are set. These icons facilitate user location of the functional areas, preventing users from blindly operating without understanding the vehicle's structure and functions, thus enhancing the user experience. For example, preset functional areas can be circled. The vehicle virtual model supports switching between 3D and 2D views, 360-degree dragging and rotation, and zooming in and out in any way. For example, two-finger swipes or double-clicks can zoom in and out. After zooming in on a specific component, such as selecting the turn signal, a light control handle is displayed on the left, which can be scrolled up and down with a finger. The right side displays a 3D or 2D vehicle virtual model, which follows the left-side scrolling and rotating light position. Simultaneously, the voice module plays the specific operation result, such as indicating that the current function is to turn on the front fog lights. In addition to swiping components, the virtual car also supports click operations, such as turning on the air conditioning and adjusting the temperature. Clicking on a component triggers a simulated animation effect on the right. Different functional areas and points are coded, with identical function sets identified by letters and different set elements by numbers. This alphanumeric coding system records each function set and point. Clicking on a component activates the simulated animation effect on the right. For example, clicking the headrest mode will split the virtual car animation on the right into two sound sources: one from the driver's side and one from the control panel. This, combined with text and voice prompts, provides the user with the current application scenario. Music playback originates from one sound source, while navigation and voice calls originate from the headrest direction, effectively separating the sound field for the driver and other passengers to enhance the audio experience.

[0078] Step S302: After the user completes the learning of the corresponding preset functional area, update the operable identifier to distinguish the learning progress of the preset functional area.

[0079] In one embodiment, a user can learn new vehicle functions based on preset functional areas within a virtual vehicle model. After completing the learning of each vehicle function, the user can fill the corresponding functional area with color, or display the learning progress through the fill ratio. For example, if a user has completed 50% of the learning of a preset functional area, they can choose a color different from the vehicle's actual color to fill that area, filling a portion of the area to indicate the current learning accuracy. Alternatively, two different colors can be used to represent the learning completion and incomplete states, respectively. The choice of color can be made according to actual application needs and is not limited here.

[0080] Step S310: Classify the executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple function sets of categories, so as to establish a mapping relationship between the corresponding function sets of categories and the guidance voice.

[0081] In one embodiment, different functional areas and functional points can be encoded. The same functional units are represented by letters, and different set elements are represented by numbers. In this way, each functional set and functional point can be recorded by a combination of letters and numbers.

[0082] In one embodiment, the executable functions corresponding to multiple preset functional areas in the vehicle virtual model are classified to obtain multiple sets of functions, including the following steps:

[0083] Step S321: Configure at least one executable function and corresponding function code for each of the preset functional areas.

[0084] In one embodiment, when designing the corresponding vehicle, at least one executable function can be configured for each preset functional area of ​​the vehicle. For example, when the preset functional area is the steering wheel area, the executable functions include: honking the horn, turning on the left turn signal, turning on the right turn signal, turning on the high beam headlights, turning on the low beam headlights, and turning on the reversing lights. When designing the corresponding executable function, the executable function is encoded according to the preset functional area corresponding to the executable function. The encoding may include the category code corresponding to the preset functional area and the function code of the executable function. The aforementioned combination of letters and numbers can be used to represent the corresponding executable function. The specific encoding method can be selected and adjusted according to actual application needs, and is not limited here. Of course, users can also customize executable functions. When customizing executable functions, users can select the corresponding preset functional area, obtain the category code of the preset functional area, and after completing the customization, the function code of the customized executable function is automatically generated based on the category code. For example, a customizable work attendance tracking function can be implemented, with voice reminders to clock in upon arrival at the company in the morning and to clock out upon boarding the vehicle in the evening. The current time is obtained by calling a function code that queries the time and date, and the system uses the previous parameter to determine if arrival at the company location is on a workday. If the conditions are met, a reminder is issued to clock in promptly. The same logic applies to clocking out. Custom events can also be defined, such as automatically activating the air purifier when PM2.5 concentration reaches an unacceptable level. This can be achieved by calling a PM2.5 function code to detect the current PM2.5 concentration; once a preset value is reached, the air purifier activation function code is invoked to start the air purifier. Specific custom function settings can be defined and adjusted according to actual needs; no restrictions are imposed here.

[0085] Step S322: Obtain the category identifier bit in the function code, and merge the executable functions with the same category identifier bit into the same set to obtain the function set of the corresponding category.

[0086] In one embodiment, based on the category identifier bit in the function code corresponding to each executable function, such as the category code of a preset function area, the pre-designed or customized executable functions can be automatically classified into the function set corresponding to the preset function area, thus completing the function classification.

[0087] In one embodiment, establishing a mapping relationship between the corresponding function set and the guiding voice includes the following steps:

[0088] Step S323: Obtain the key features of each voice information in the preset voice database, and perform clustering based on the key features to obtain the voice category corresponding to each voice information.

[0089] In one embodiment, it is conceivable to store the voice information used to introduce various vehicle functions into a voice database. Feature extraction is performed on the text data corresponding to each voice message to obtain corresponding key features. Feature extraction can employ conventional methods such as neural networks, and there are no limitations here. The corresponding voice information is labeled using these key features. Clustering is performed based on the similarity between the key features of each voice message. Voice messages with similarity reaching a set threshold are grouped into one category. The key features corresponding to the cluster centers can be selected to label the voice categories, thus completing the voice classification in the voice database.

[0090] Step S324: Compare the category of the function set with the voice category to obtain the matching voice category.

[0091] In one embodiment, after obtaining the function set corresponding to the preset functional area according to the aforementioned steps, the matching speech category is retrieved from the speech database based on the category of the function set. The normal distance or cosine distance between the categories can be calculated to obtain the matching speech category.

[0092] Step S325: Based on the matched voice category, call the voice information in the preset voice database as the guiding voice to establish a mapping relationship between the corresponding category's function set and the guiding voice.

[0093] In one embodiment, after identifying the differentiated voice category, all voice information under that category is used as guiding voice and associated with the corresponding function set. For example, the associated information, such as function numbers and voice category keywords, can be mapped to a one-dimensional array to establish a mapping relationship between the function set and the guiding voice. Retrieving the guiding voice corresponding to the user's interaction from the mapping relationship can significantly reduce the amount of data retrieved and improve processing efficiency.

[0094] Step S330: In response to the user's interaction with the vehicle virtual model, the mapping relationship is invoked to determine the guidance voice corresponding to the interaction, so as to guide the user to learn the functions of the corresponding functional area according to the guidance voice.

[0095] In one embodiment, users can interact with a virtual vehicle model. Taking the external virtual vehicle model as an example, clicking the hood opens it, displaying information about various vehicle components, the energy flow of the current vehicle modules, and the energy flow path of the entire vehicle, including the direction and energy consumption during the transfer process. This helps to clarify the energy consumption of each part, allowing for targeted design improvements and increased energy efficiency. For individual vehicle components, the locations of the engine, battery, brake fluid, and most user-concerned items such as the oil filler cap, windshield washer fluid, and dipstick are all clearly marked. Users can zoom in with two fingers. When a component is clicked, voice prompts and virtual vehicle animation modeling provide information about its function. For user-operable components, simulated instructions on how to operate them are also available. When a user clicks on a corresponding preset function area, navigation announcements for that area are triggered, with voice prompts broadcasting a list of executable functions within that preset function area.

[0096] In one embodiment, in response to an interaction between a user and the virtual vehicle model, the mapping relationship is invoked to determine the guidance voice corresponding to the interaction, including the following steps:

[0097] Step S331: Determine the target functional area selected by the user based on the interactive operation, and take the set of functions contained in the target functional area as the target functional set.

[0098] In one embodiment, after determining the target functional area based on user interaction operations such as clicking or swiping, all function sets contained in the target functional area can be invoked. For example, the function sets include lighting sets, turn indicator sets, etc.

[0099] Step S332: Based on the category of the target function set, call the mapping relationship to obtain all the guiding voices corresponding to the target function set as the guiding voices corresponding to the interactive operation.

[0100] In one embodiment, since the aforementioned steps have pre-established a mapping relationship between different function set categories and corresponding guidance voices, the mapping relationship of the corresponding target function set can be called according to the category information of the target function set to obtain the guidance voice corresponding to the target function set. Since each function set may contain multiple function points, the guidance voice may contain multiple functions.

[0101] Step S333: Obtain each key feature of the guiding voice corresponding to the interactive operation, and combine all the key features into a feature sequence;

[0102] In one embodiment, key features corresponding to the guiding voice obtained through interactive operations, such as keywords and key phrases, can be invoked. When there are multiple guiding voices, the key features corresponding to the multiple guiding voices are randomly or in a preset order to form a key feature sequence.

[0103] Step S334: Generate a function introduction voice for the target functional area based on the feature sequence, so as to guide the user to select functions based on the function introduction voice.

[0104] In one embodiment, a function introduction voice for the corresponding target functional area can be generated based on a key feature sequence. This involves converting the key feature sequence into speech and outputting it, resulting in broadcast information for all executable functions within the target functional area. This allows users to select functions based on the function introduction voice. During each function introduction, the corresponding function location in the vehicle virtual model can be highlighted or a corresponding function effect image can be played, allowing users to locate the function and intuitively experience it. After the user completes the function selection based on the function introduction voice, a matching guide voice can be invoked from the preset guide voices corresponding to the selected function area to guide the user in performing the corresponding function operation.

[0105] In one embodiment, guiding the user to learn the functions of the corresponding functional area according to the guiding voice includes the following steps:

[0106] Step S335: After the user completes the operation specified by the guiding voice, the corresponding function effect screen is generated.

[0107] In one embodiment, after the user completes the corresponding function operation according to the guidance voice, the vehicle virtual model can generate a corresponding function effect diagram based on the user's operation. For example, when the user moves the left turn lever, the function effect diagram shows that the vehicle's left turn light is lit.

[0108] Step S336: In response to the user's confirmation information based on the function effect screen, execute the function corresponding to the function effect screen on the vehicle.

[0109] In one embodiment, users can also customize corresponding functions. The user can judge whether the customized function meets the requirements by the displayed function effect screen. If it does, the customized function can be applied to the vehicle and the corresponding function can be executed on the vehicle.

[0110] In one embodiment, after guiding the user to learn the functions of the corresponding functional areas according to the guiding voice, the method further includes:

[0111] Obtain the current user's identity information, mark the current user's learning progress in the vehicle virtual model, and associate and store the marked vehicle virtual model with the current user's identity information;

[0112] When switching users, the associated vehicle virtual model is invoked based on the identity information of the new user.

[0113] In one embodiment, a multi-user mechanism is employed, allowing different users to be guided through virtualization according to their own progress. Data isolation enhances device security. For automated virtual vehicle script operations, there are also user-defined advanced modes or learned switches for different functions, representing unique user-private settings. Switching between users remembers previous settings. This multi-user mechanism ensures user isolation while strengthening data security. Different users have different privacy settings while sharing other system hardware resources. This multi-user mechanism also perfectly adapts to multi-application cloning and dual-app functionality across different operating platforms.

[0114] In one embodiment, after constructing a virtual vehicle model based on the vehicle configuration information, the method further includes:

[0115] Establish a communication connection between the virtual vehicle model and the corresponding vehicle;

[0116] When the vehicle starts, abnormal areas are marked in the vehicle virtual model based on the vehicle's self-check information.

[0117] In one embodiment, after marking the abnormal areas in the vehicle virtual model, the method further includes:

[0118] If the anomaly corresponding to the anomaly region meets the user's self-handling conditions, then the corresponding anomaly handling steps will be output.

[0119] If the anomaly corresponding to the abnormal area does not meet the user's character processing conditions, then a repair shop search is performed based on the vehicle's location, and recommended repair shop address information is output; or, emergency rescue or towing phone numbers are output.

[0120] In one embodiment, both internal and external virtual vehicle modeling communicate with the vehicle body in a certain way. The vehicle body can use traditional CAN communication or new Ethernet communication to fully scan the wear and tear of the vehicle's internal and external structures. For external virtual vehicle modeling, different components and modules are highlighted in red on the current interface and prompted to the user. If the problem can be handled by the user, the ideal operation steps should be provided to solve the problem. If the user cannot operate independently, such as a damaged brake light requiring a professional repair shop, the address of a nearby 4S shop can be recommended. If the vehicle is malfunctioning to the point of being immobile, emergency rescue or nearby tow truck contact numbers can be displayed. For internal virtual vehicle modeling, communication with internal modules can detect the wear and tear of brake pads and clutches, detect the quality of the in-vehicle audio system, and check the normality of internal communication modules such as Bluetooth and Wi-Fi.

[0121] Based on the above solutions, this application embodiment uses internal and external virtual vehicle modeling to graphically and comprehensively showcase all the functions of the current car model, guiding users to experience a brand-new driving experience. It also features fault detection and rescue functions, enhancing vehicle safety. Through 3D / 2D modeling, it comprehensively improves the user experience, deepens understanding of vehicle usage knowledge, rationally utilizes automotive hardware and software resources, and enhances brand influence.

[0122] Please see Figure 4 , Figure 4 This is a block diagram of a virtual vehicle guidance processing system according to an embodiment of this application. The system includes: a model construction module 4551, used to acquire vehicle configuration information and construct a virtual vehicle model based on the vehicle configuration information; a function and voice association module 4552, used to classify the executable functions corresponding to multiple preset functional areas in the virtual vehicle model to obtain multiple function sets of categories, so as to establish a mapping relationship between the corresponding function sets of categories and the guidance voice; and a guidance module 4553, used to respond to the user's interaction with the virtual vehicle model, call the mapping relationship to determine the guidance voice corresponding to the interaction, so as to guide the user to learn the functions of the corresponding functional areas according to the guidance voice.

[0123] In one embodiment, after the model building module 4551 builds a vehicle virtual model based on the vehicle configuration information, it further includes: providing an operable identifier for each of the preset functional areas of the vehicle virtual model, so as to guide the user to locate the preset functional area through the operable identifier; after the user completes the learning of the corresponding preset functional area, updating the operable identifier to distinguish the learning progress of the preset functional area.

[0124] In one embodiment, the function and voice association module 4552 is further configured to classify the executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple sets of functions, including:

[0125] Each of the preset functional areas is configured with at least one executable function and a corresponding function code;

[0126] Obtain the category identifier bit in the function code, and merge the executable functions with the same category identifier bit into the same set to obtain the function set of the corresponding category.

[0127] In one embodiment, the function and voice association module 4552 is further configured to establish a mapping relationship between a function set of a corresponding category and a guiding voice, including: acquiring key features of each voice information in a preset voice database; clustering according to the key features to obtain a voice category corresponding to each voice information; comparing the category of the function set with the voice category to obtain a matching voice category; and calling the voice information in the preset voice database as guiding voice according to the matching voice category to establish a mapping relationship between the function set of a corresponding category and the guiding voice.

[0128] In one embodiment, the guidance module 4553 is further configured to respond to an interaction between a user and the vehicle virtual model by invoking the mapping relationship to determine the guidance voice corresponding to the interaction, including: determining the target functional area selected by the user based on the interaction, and taking the set of functions contained in the target functional area as the target functional set; invoking the mapping relationship based on the category of the target functional set to obtain all guidance voices corresponding to the target functional set as the guidance voices corresponding to the interaction; acquiring key features of each guidance voice corresponding to the interaction, and forming a feature sequence from all the key features; and generating a function introduction voice for the target functional area based on the feature sequence to guide the user to select functions based on the function introduction voice.

[0129] In one embodiment, the guidance module 4553 is further configured to guide the user to learn functions in a corresponding functional area based on the guidance voice, including: generating a corresponding function effect screen after the user completes the operation specified by the guidance voice; and executing the function corresponding to the function effect screen on the vehicle in response to the user's confirmation information based on the function effect screen.

[0130] In one embodiment, the guidance module 4553 is further configured to: after guiding the user to learn the functions of the corresponding functional area according to the guidance voice, it further includes: obtaining the identity information of the current user, marking the learning progress of the current user in the vehicle virtual model, associating and storing the marked vehicle virtual model with the identity information of the current user; and when switching users, calling the associated vehicle virtual model according to the identity information of the switched user.

[0131] In one embodiment, the guidance module 4553 is further configured to, after constructing a vehicle virtual model based on the vehicle configuration information, establish a communication connection between the vehicle virtual model and the corresponding vehicle; and when the vehicle starts, mark abnormal areas in the vehicle virtual model based on the vehicle self-check information.

[0132] In one embodiment, the guidance module 4553 is further configured to, after marking the abnormal area in the vehicle virtual model, include: if the abnormality corresponding to the abnormal area meets the user's self-processing conditions, then output the corresponding abnormality processing steps; if the abnormality corresponding to the abnormal area does not meet the user's self-processing conditions, then search for a repair shop based on the vehicle location and output recommended repair shop address information; or, output emergency rescue phone number or towing phone number.

[0133] The aforementioned virtual vehicle guidance processing system can be implemented in the form of a computer program, and the computer program can be implemented in, for example... Figure 5 The computer device shown runs on the computer. The computer device includes: memory, processor, and computer programs stored in the memory and executable on the processor.

[0134] The modules in the aforementioned virtual vehicle guidance system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the terminal's memory in hardware form, or stored in the terminal's memory in software form, so that the processor can call and execute the corresponding operations of each module. The processor can be a central processing unit (CPU), a microprocessor, a microcontroller, etc.

[0135] like Figure 5 The diagram shown is a schematic representation of the internal structure of a computer device in one embodiment. A computer device is provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it performs the following steps: acquiring vehicle configuration information; constructing a virtual vehicle model based on the vehicle configuration information; classifying executable functions corresponding to multiple preset functional areas in the virtual vehicle model to obtain multiple sets of functions of different categories, and establishing a mapping relationship between the corresponding sets of functions and guiding voice; responding to user interaction with the virtual vehicle model, invoking the mapping relationship to determine the guiding voice corresponding to the interaction, so as to guide the user to learn the functions of the corresponding functional areas based on the guiding voice.

[0136] In one embodiment, after the processor constructs a virtual vehicle model based on the vehicle configuration information, it further includes: providing an operable identifier for each preset functional area of ​​the virtual vehicle model to guide the user to locate the preset functional area through the operable identifier; and updating the operable identifier after the user completes the learning of the corresponding preset functional area to distinguish the learning progress of the preset functional area.

[0137] In one embodiment, when the processor executes the above-mentioned process, it classifies the executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple categories of function sets, including: configuring at least one executable function and a corresponding function code for each preset functional area; obtaining the category identifier bit in the function code; and merging the executable functions with the same category identifier bit into the same set to obtain the corresponding category of function set.

[0138] In one embodiment, when the processor executes the above-mentioned method, the process of establishing a mapping relationship between a set of functions of a corresponding category and the guiding voice includes: acquiring key features of each voice information in a preset voice database; clustering the voice information according to the key features to obtain a voice category corresponding to each voice information; comparing the category of the set of functions with the voice category to obtain a matching voice category; and calling the voice information in the preset voice database as the guiding voice according to the matching voice category to establish a mapping relationship between the set of functions of a corresponding category and the guiding voice.

[0139] In one embodiment, when the processor executes the above-described action, in response to an interaction between the user and the virtual vehicle model, it invokes the mapping relationship to determine the guiding voice corresponding to the interaction, including: determining the target functional area selected by the user based on the interaction, and taking the set of functions contained in the target functional area as a target functional set; invoking the mapping relationship based on the category of the target functional set to obtain all guiding voices corresponding to the target functional set as guiding voices corresponding to the interaction; acquiring key features of each guiding voice corresponding to the interaction, and forming a feature sequence from all the key features; and generating a function introduction voice for the target functional area based on the feature sequence to guide the user to select functions based on the function introduction voice.

[0140] In one embodiment, when the processor is executed, the function learning of the corresponding functional area guided by the guidance voice includes: generating a corresponding function effect screen after the user completes the operation specified by the guidance voice; and executing the function corresponding to the function effect screen on the vehicle in response to the user's confirmation information based on the function effect screen.

[0141] In one embodiment, when the processor executes the above-mentioned functions, after guiding the user to learn the corresponding functional area according to the guidance voice, it further includes: obtaining the current user's identity information, marking the current user's learning progress in the vehicle virtual model, associating and storing the marked vehicle virtual model with the current user's identity information; and when switching users, calling the associated vehicle virtual model according to the identity information of the switched user.

[0142] In one embodiment, after the processor constructs a vehicle virtual model based on the vehicle configuration information, it further includes: establishing a communication connection between the vehicle virtual model and the corresponding vehicle; and marking abnormal areas in the vehicle virtual model based on vehicle self-check information when the vehicle starts.

[0143] In one embodiment, when the processor executes the above-mentioned process, after marking the abnormal area in the vehicle virtual model, it further includes: if the abnormality corresponding to the abnormal area meets the user's self-processing conditions, then outputting the corresponding abnormality processing steps; if the abnormality corresponding to the abnormal area does not meet the user's self-processing conditions, then searching for a repair shop based on the vehicle location and outputting recommended repair shop address information; or, outputting emergency rescue or towing phone numbers.

[0144] In one embodiment, the aforementioned computer device can be used as a server, including but not limited to a standalone physical server or a server cluster consisting of multiple physical servers. The computer device can also be used as a terminal, including but not limited to mobile phones, tablets, personal digital assistants, or smart devices. Figure 5 As shown, the computer device includes a processor, non-volatile storage medium, internal memory, display screen, and network interface connected via a system bus.

[0145] The processor of this computer device provides computing and control capabilities to support the operation of the entire device. The non-volatile storage medium of the computer device stores the operating system and computer programs. These programs can be executed by the processor to implement the virtual vehicle guidance processing method provided in the above embodiments. The internal memory of the computer device provides a cached runtime environment for the operating system and computer programs stored in the non-volatile storage medium. The display interface can display data via a screen. The screen can be a touchscreen, such as a capacitive or electronic screen, and can generate corresponding instructions by receiving click operations on the controls displayed on the touchscreen.

[0146] Those skilled in the art will understand that Figure 5 The structure of the computer device shown in the figure is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0147] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon. When executed by a processor, the computer program performs the following steps: acquiring vehicle configuration information; constructing a vehicle virtual model based on the vehicle configuration information; classifying executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple sets of functions of different categories, thereby establishing a mapping relationship between the corresponding sets of functions of different categories and guiding voice; and, in response to an interaction between a user and the vehicle virtual model, invoking the mapping relationship to determine the guiding voice corresponding to the interaction, thereby guiding the user to learn the functions of the corresponding functional areas based on the guiding voice.

[0148] In one embodiment, when the computer program is executed by the processor, after constructing a virtual vehicle model based on the vehicle configuration information, it further includes: providing an operable identifier for each of the preset functional areas of the virtual vehicle model, so as to guide the user to locate the preset functional area through the operable identifier; after the user completes the learning of the corresponding preset functional area, updating the operable identifier to distinguish the learning progress of the preset functional area.

[0149] In one embodiment, when the computer program is executed by the processor, it classifies the executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple sets of functions of different categories, including: configuring at least one executable function and a corresponding function code for each preset functional area; obtaining the category identifier bit in the function code; and merging executable functions with the same category identifier bit into the same set to obtain a set of functions of the corresponding category.

[0150] In one embodiment, when the computer program is executed by a processor, the process of establishing a mapping relationship between a set of functions of a corresponding category and guiding speech includes: acquiring key features of each voice information in a preset voice database; clustering the voice information according to the key features to obtain a voice category corresponding to each voice information; comparing the category of the set of functions with the voice category to obtain a matching voice category; and calling the voice information in the preset voice database as guiding speech according to the matching voice category to establish a mapping relationship between the set of functions of a corresponding category and the guiding speech.

[0151] In one embodiment, when the computer program is executed by a processor, the implementation of responding to an interaction between a user and the virtual vehicle model by invoking the mapping relationship to determine the guiding voice corresponding to the interaction includes: determining the target functional area selected by the user based on the interaction, and taking the set of functions contained in the target functional area as a target functional set; invoking the mapping relationship based on the category of the target functional set to obtain all guiding voices corresponding to the target functional set as guiding voices corresponding to the interaction; acquiring key features of each guiding voice corresponding to the interaction, and forming a feature sequence from all the key features; and generating a function introduction voice for the target functional area based on the feature sequence to guide the user to select functions based on the function introduction voice.

[0152] In one embodiment, when the computer program is executed by the processor, the function learning of the corresponding functional area guided by the guidance voice includes: generating a corresponding function effect screen after the user completes the operation specified by the guidance voice; and executing the function corresponding to the function effect screen on the vehicle in response to the user's confirmation information based on the function effect screen.

[0153] In one embodiment, when the instruction is executed by the processor, after guiding the user to learn the corresponding functional area according to the guiding voice, it further includes: obtaining the current user's identity information, marking the current user's learning progress in the vehicle virtual model, associating and storing the marked vehicle virtual model with the current user's identity information; and when switching users, calling the associated vehicle virtual model according to the identity information of the switched user.

[0154] In one embodiment, when the instruction is executed by the processor, after constructing a vehicle virtual model based on the vehicle configuration information, it further includes: establishing a communication connection between the vehicle virtual model and the corresponding vehicle; and when the vehicle starts, marking abnormal areas in the vehicle virtual model based on the vehicle self-check information.

[0155] In one embodiment, when the instruction is executed by the processor, after marking the abnormal area in the vehicle virtual model, it further includes: if the abnormality corresponding to the abnormal area meets the user's self-processing conditions, then outputting the corresponding abnormality processing steps; if the abnormality corresponding to the abnormal area does not meet the user's self-processing conditions, then searching for a repair shop based on the vehicle location and outputting recommended repair shop address information; or, outputting emergency rescue or towing phone numbers.

[0156] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), etc.

[0157] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A virtual vehicle guidance processing method, characterized in that, include: Obtain vehicle configuration information and construct a virtual vehicle model based on the vehicle configuration information; The executable functions corresponding to multiple preset functional areas in the vehicle virtual model are classified to obtain multiple function sets of categories, so as to establish a mapping relationship between the corresponding function sets and the guiding voice. This includes: obtaining key features of each voice information in a preset voice database; clustering according to the key features to obtain the voice category corresponding to each voice information; comparing the category of the function set with the voice category to obtain the matching voice category; and calling the voice information in the preset voice database as the guiding voice according to the matching voice category to establish a mapping relationship between the corresponding function sets and the guiding voice. In response to the user's interaction with the vehicle virtual model, the mapping relationship is invoked to determine the guiding voice corresponding to the interaction, so as to guide the user to learn the functions of the corresponding functional area according to the guiding voice.

2. The virtual vehicle guidance processing method according to claim 1, characterized in that, After constructing the vehicle virtual model based on the vehicle configuration information, the following is also included: Operable identifiers are provided for each of the preset functional areas of the vehicle virtual model to guide the user to locate the preset functional areas through the operable identifiers; After the user completes the learning of the corresponding preset function area, the operable identifier is updated to distinguish the learning progress of the preset function area.

3. The virtual vehicle guidance processing method according to claim 1, characterized in that, The executable functions corresponding to multiple preset functional areas in the vehicle virtual model are classified to obtain multiple sets of functions, including: Each of the preset functional areas is configured with at least one executable function and a corresponding function code; Obtain the category identifier bit in the function code, and merge the executable functions with the same category identifier bit into the same set to obtain the function set of the corresponding category.

4. The virtual vehicle guidance processing method according to claim 1, characterized in that, In response to a user's interaction with the vehicle virtual model, the mapping relationship is invoked to determine the guidance voice corresponding to the interaction, including: The target functional area selected by the user is determined based on the interactive operation, and the set of functions contained in the target functional area is taken as the target functional set. Based on the category of the target function set, the mapping relationship is invoked to obtain all the guiding voices corresponding to the target function set as the guiding voices corresponding to the interactive operation; Obtain the key features of each guiding voice corresponding to the interactive operation, and combine all the key features into a feature sequence; Based on the feature sequence, a function introduction voice is generated for the target function area to guide the user in selecting functions.

5. The virtual vehicle guidance processing method according to claim 1, characterized in that, The user is guided through the corresponding functional areas by the provided voice prompts, including: After the user completes the operation specified by the guiding voice, the corresponding functional effect screen is generated; In response to the user's confirmation based on the function effect screen, the function corresponding to the function effect screen is executed on the vehicle.

6. The virtual vehicle guidance processing method according to claim 1, characterized in that, After guiding the user through the corresponding functional areas according to the voice prompts, the process also includes: Obtain the current user's identity information, mark the current user's learning progress in the vehicle virtual model, and associate and store the marked vehicle virtual model with the current user's identity information; When switching users, the associated vehicle virtual model is invoked based on the identity information of the new user.

7. The virtual vehicle guidance processing method according to any one of claims 1-6, characterized in that, After constructing the vehicle virtual model based on the vehicle configuration information, the following is also included: Establish a communication connection between the virtual vehicle model and the corresponding vehicle; When the vehicle starts, abnormal areas are marked in the vehicle virtual model based on the vehicle's self-check information.

8. The virtual vehicle guidance processing method according to claim 7, characterized in that, After marking the abnormal areas in the vehicle virtual model, the process also includes: If the anomaly corresponding to the anomaly region meets the user's self-handling conditions, then the corresponding anomaly handling steps will be output. If the anomaly corresponding to the abnormal area does not meet the conditions for user self-handling, then a repair shop search is performed based on the vehicle location, and recommended repair shop address information is output; or, emergency rescue or towing phone numbers are output.

9. A virtual vehicle guidance processing system, characterized in that, include: The model building module is used to obtain vehicle configuration information and build a virtual vehicle model based on the vehicle configuration information. The function and voice association module is used to classify the executable functions corresponding to multiple preset functional areas in the vehicle virtual model to obtain multiple function sets of categories, so as to establish a mapping relationship between the corresponding function sets and the guidance voice. This includes: acquiring key features of each voice information in a preset voice database; clustering based on the key features to obtain the voice category corresponding to each voice information; comparing the category of the function set with the voice category to obtain a matching voice category; and calling the voice information in the preset voice database as the guidance voice according to the matching voice category to establish a mapping relationship between the corresponding function sets and the guidance voice. The guidance module is used to respond to the user's interaction with the vehicle virtual model, call the mapping relationship to determine the guidance voice corresponding to the interaction, and guide the user to learn the functions of the corresponding functional area according to the guidance voice.

10. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the steps of the virtual vehicle guidance processing method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the virtual vehicle guidance processing method according to any one of claims 1 to 8.

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