Implementation method and equipment of vehicle intelligent scene based on simulated voice data

Abstract

The invention discloses an implementation method and device for a vehicle intelligent scene based on simulated voice data, and belongs to the technical field of vehicle scene development, and the method comprises the steps: generating a scene control instruction according to the environment data, user state data and device state data of a vehicle; converting the scene control instruction into simulation voice data based on a preset rule base; and sending the analog voice data to the voice control module, so that the voice control module analyzes the analog voice data and then distributes the analyzed analog voice data to the corresponding function implementation interface. According to the scheme, the intelligent scene of the vehicle is realized by multiplexing the existing voice control module and the function realization interface in the vehicle, so that a special interface is prevented from being independently developed for a function corresponding to each intelligent scene, and the development cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of vehicle scene development, and particularly relates to a method and device for implementing a vehicle intelligent scene based on simulated voice data. BACKGROUND

[0002] With the improvement of the intelligent level of automobiles, users have an increasing demand for intelligent scene functions (such as automatically closing windows and turning on a windscreen wiper in rainy weather, and automatically turning on seat heating in cold weather). In existing vehicles, especially vehicles with a non-service-oriented architecture (SOA) or a partial SOA architecture, in order to implement diversified intelligent scenes, a special interface needs to be developed for each intelligent scene corresponding function, and therefore the development cost is high. SUMMARY

[0003] Embodiments of the present application provide a method and device for implementing a vehicle intelligent scene based on simulated voice data, thereby avoiding the development of a special interface for each intelligent scene corresponding function at least to some extent, and reducing the development cost.

[0004] Other characteristics and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0005] According to a first aspect of embodiments of the present application, a method for implementing a vehicle intelligent scene based on simulated voice data is provided, the vehicle comprising a voice control module and a function implementation interface, and the method comprising:

[0006] generating a scene control instruction based on environment data, user state data and device state data of the vehicle;

[0007] converting the scene control instruction into simulated voice data based on a preset rule library;

[0008] sending the simulated voice data to the voice control module, so that the voice control module distributes the simulated voice data to the corresponding function implementation interface after analyzing the simulated voice data.

[0009] In some embodiments, the preset rule library comprises multiple types of mapping tables, template libraries and natural language generation models, and converting the scene control instruction into simulated voice data based on the preset rule library comprises:

[0010] determining a target rule library from the preset rule library according to the type of the scene control instruction;

[0011] converting the scene control instruction into simulated voice data based on the target rule library.

[0012] In some embodiments, the target rule base is a mapping table, and the scene control instruction is converted into the simulated voice data based on the target rule base, including:

[0013] finding voice data corresponding to the scene control instruction from the mapping table;

[0014] taking the found voice data as the simulated voice data.

[0015] In some embodiments, the target rule base is a template library, and the scene control instruction is converted into the simulated voice data based on the target rule base, including:

[0016] determining a control target and a control mode according to the scene control instruction;

[0017] selecting a template to be filled from the template library according to the control mode;

[0018] filling the control target into the template to be filled to obtain the simulated voice data.

[0019] In some embodiments, the target rule base is a natural language generation model, and the scene control instruction is converted into the simulated voice data based on the target rule base, including:

[0020] inputting the scene control instruction into the natural language generation model to obtain simulated voice data output by the natural language generation model.

[0021] In some embodiments, the scene control instruction is generated according to environmental data of the vehicle, user state data and device state data, including:

[0022] determining a vehicle scene according to the environmental data of the vehicle and the user state data;

[0023] generating the scene control instruction according to the device state data and the vehicle scene.

[0024] In some embodiments, after the scene control instruction is converted into the simulated voice data based on the preset rule base, the implementation method of the vehicle intelligent scene based on the simulated voice data further includes:

[0025] performing semantic consistency verification on the simulated voice data based on the scene control instruction;

[0026] in the case of passing the verification, sending the simulated voice data to the voice control module.

[0027] According to a second aspect of the embodiments of the present application, an implementation device of a vehicle intelligent scene based on simulated voice data is provided, the vehicle includes a voice control module and a function implementation interface, and the device includes:

[0028] The scene control instruction generation module is configured to generate a scene control instruction according to the environment data of the vehicle, the user state data, and the device state data.

[0029] The simulated voice data generation module is configured to convert the scene control instruction into simulated voice data based on a preset rule library.

[0030] The voice channel multiplexing module is configured to send the simulated voice data to the voice control module, so that the voice control module distributes the simulated voice data to the corresponding function implementation interface after analyzing the simulated voice data.

[0031] According to a third aspect of the embodiments of the present application, an implementation device of a vehicle intelligent scene based on simulated voice data is provided, which comprises a processor and a memory. The memory stores computer program instructions capable of being executed by the processor. When the processor executes the computer program instructions, the steps of the method according to any one of the first aspect are implemented.

[0032] According to a fourth aspect of the embodiments of the present application, a computer readable storage medium is provided, which stores computer program instructions. When the computer program instructions are executed by a processor, the processor is prompted to implement the steps of the method according to any one of the first aspect.

[0033] In the present application, a scene control instruction is generated according to the environment data of the vehicle, the user state data, and the device state data. The scene control instruction is converted into simulated voice data based on a preset rule library. The simulated voice data is sent to the voice control module, so that the voice control module distributes the simulated voice data to the corresponding function implementation interface after analyzing the simulated voice data. This scheme realizes the intelligent scene of the vehicle by multiplexing the existing voice control module and function implementation interface in the vehicle, avoids developing a special interface for each corresponding function of the intelligent scene, and reduces the development cost.

[0034] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0035] The drawings incorporated into the specification and forming a part thereof, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. In the drawings:

[0036] Figure 1 A flowchart of an implementation method of a vehicle intelligent scene based on simulated voice data according to some embodiments of the present application is shown;

[0037] Figure 2 A block diagram of an implementation apparatus of a vehicle intelligent scenario based on analog voice data according to some embodiments of the present application is shown;

[0038] Figure 3 A structural schematic diagram of an implementation device of a vehicle intelligent scenario based on analog voice data according to some embodiments of the present application is shown. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0040] In addition, the described features, structures or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to give a sufficient understanding of the embodiments of the present application. However, those skilled in the art will realize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other cases, well-known methods, devices, implementations or operations are not shown or described in detail to avoid obscuring the aspects of the present application.

[0041] The block diagrams shown in the drawings are only functional entities, which do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0042] The flowcharts shown in the drawings are only exemplary illustrations, which do not necessarily include all contents and operations / steps, and are not necessarily executed in the described order. For example, some operations / steps can be further decomposed, and some operations / steps can be combined or partially combined, so that the actual execution order can be changed according to the actual situation.

[0043] In order for those skilled in the art to better understand the present application, first, the application scenarios involved in the present application are briefly described.

[0044] The traditional vehicle-mounted voice control module directly binds the preset voice commands to the vehicle functions. After the user issues a voice command, the voice control module parses the voice command and then directly calls the corresponding function implementation interface. The triggering of the traditional vehicle-mounted voice control module depends on the voice commands actively issued by the user, and cannot directly support vehicle scenes actively triggered by the system. In order to realize diverse vehicle scenes, it is necessary to develop a dedicated interface for the function corresponding to each vehicle scene, so the development cost is relatively high. In the embodiment of the present application, the scene control command is innovatively converted into simulated voice data similar to the user's voice command, and then the simulated voice data is sent to the voice control module. The existing voice control module and function implementation interface in the vehicle are used to realize the functions corresponding to the vehicle's intelligent scenes, avoiding the development of a dedicated interface for the function corresponding to each intelligent scene, thereby reducing development costs.

[0045] Figure 1 The flowchart of the method for realizing vehicle intelligent scene based on simulated voice data according to some embodiments of the present application is shown. Figure 1 As shown, a method for implementing a vehicle intelligent scenario based on simulated voice data is provided. The vehicle includes a voice control module and a function implementation interface. The function implementation interface is the vehicle underlying interface exposed to the outside by each underlying control module of the vehicle (such as the window electronic control unit (ECU), wiper ECU, air conditioning ECU, body control module (BCM) domain controller, in-vehicle infotainment (IVI) domain controller, etc.). The function implementation interface can receive the underlying function instructions parsed by the voice control module and send the underlying function instructions to the corresponding underlying control module to enable the underlying control module to perform the corresponding vehicle function (such as closing the window, starting the wiper, etc.). The method may include the following steps 101 to 103.

[0046] In step 101, a scene control instruction is generated based on vehicle environment data, user status data, and device status data.

[0047] The vehicle's environmental data may include environmental data inside the vehicle (such as the temperature and humidity inside the vehicle) and environmental data outside the vehicle (such as the temperature, rainfall, light, traffic environment, etc. outside the vehicle).

[0048] User status data may include user fatigue, preference settings, and other data, and device status data may include whether the car windows are open, whether the wipers are turned on, and so on.

[0049] In some embodiments, the vehicle scene can be determined according to the environment data and the user state data of the vehicle; and the scene control instruction can be generated according to the device state data and the vehicle scene.

[0050] In the implementation process, the vehicle scene involved in the environment data and the user state data can be identified and judged in combination with a pre-set rule or a machine learning model, and then the scene control instruction is generated. For example, if the rainfall of the environment where the vehicle is located at the current time is greater than the pre-set rainfall, the vehicle scene is determined to be "rainy day mode"; for example, if the fatigue degree of the driver at the current time is greater than the pre-set fatigue degree, the vehicle scene is determined to be "fatigue driving mode"; for example, if the device state data is that the window is opened, after the vehicle scene is determined to be "rainy day mode", the scene control instruction "execute rainy day mode" can be generated to close the window in the subsequent control process.

[0051] In step 102, the scene control instruction is converted into simulated voice data based on a pre-set rule library.

[0052] The simulated voice data refers to data that can be recognized by an existing voice control module in the intelligent cabin of the vehicle and is equivalent to a voice instruction of the user. The simulated voice data can be text, semantic frame, etc. The specific data form of the simulated voice data is not limited in the present application.

[0053] The pre-set rule library includes the corresponding relationship between the scene control instruction and the simulated voice data, and can support multiple scene modes (such as rainy day mode, night mode, energy saving mode, etc.). The pre-set rule library can include multiple forms such as a mapping table, a template library and a natural language generation model.

[0054] In some embodiments, a target rule library can be determined from the pre-set rule library according to the type of the scene control instruction; and the scene control instruction is converted into simulated voice data based on the target rule library.

[0055] The type of the scene control instruction can include instructions with simple mapping relationship, instructions that can be parameterized, instructions with complex mapping relationship, etc. For different types of scene control instructions, different target rule libraries can be selected for the conversion of the scene control instruction to improve the conversion efficiency.

[0056] In some embodiments, for instructions with simple mapping relationship, a mapping table can be selected as the target rule library, and the scene control instruction is converted into simulated voice data based on the target rule library, including: searching for the voice data corresponding to the scene control instruction from the mapping table; and taking the searched voice data as the simulated voice data.

[0057] In some embodiments, for instructions that can be parameterized, a template library can be selected as a target rule library, and the scene control instruction can be converted into simulated voice data based on the target rule library, including: determining a control target and a control mode according to the scene control instruction; selecting a template library to be filled from the template library according to the control mode; filling the control target into the template library to be filled to obtain the simulated voice data.

[0058] Taking the scene control instruction "execute the rain mode" as an example, according to the scene control instruction "execute the rain mode", it can be determined that the control target is "car window" and "windshield wiper", and the control mode is "close the car window" and "open the windshield wiper", and the template library to be filled is "please close {...} and open {....}", and the control target "car window" and "windshield wiper" is filled into the template library to obtain the simulated voice data "please close the car window and open the windshield wiper".

[0059] In some embodiments, for instructions with complex mapping relationships, a natural language generation model can be selected as a target rule library, and the scene control instruction can be converted into simulated voice data based on the target rule library, including: inputting the scene control instruction into the natural language generation model to obtain the simulated voice data output by the natural language generation model.

[0060] It can be understood that the natural language generation model can be obtained by training historical time scene control instructions and labeled simulated voice data as samples, and the natural language generation model can be used to dynamically generate simulated voice data that meets the requirements of grammar and semantics.

[0061] By converting the scene control instruction into simulated voice data that can be recognized by the voice control module, seamless docking of intelligent scene control and existing voice control modules can be achieved, thereby providing a basis for reusing the voice control module.

[0062] In step 103, the simulated voice data is sent to the voice control module, so that the voice control module parses the simulated voice data and distributes it to the corresponding function implementation interface.

[0063] It can be understood that after receiving the simulated voice data, the voice control module processes the simulated voice data as a voice instruction issued by the user. The voice control module parses the simulated voice data through the parser to obtain the underlying function instruction, and then distributes the underlying function instruction to the corresponding function implementation interface, and the corresponding controller of the function implementation interface executes the corresponding function.

[0064] Taking the scene control instruction "execute rain mode" as an example, it is converted into simulated voice data "please close the window and open the wiper", the voice control module parses the simulated voice data into underlying function instructions "close the window" and "open the wiper", and sends the underlying function instruction "close the window" to the window ECU through the function implementation interface of the window ECU, and the window ECU executes the action of closing the window; the underlying function instruction "open the wiper" is sent to the wiper ECU through the function implementation interface of the wiper ECU, and the wiper ECU executes the action of opening the wiper.

[0065] Taking the scene control instruction "execute night mode" as an example, it is converted into simulated voice data "please dim the interior light and adjust the display screen brightness", the voice control module parses the simulated voice data into underlying function instructions "dim the interior light" and "adjust the display screen brightness", and sends the underlying function instruction "dim the interior light" to the BCM domain controller through the function implementation interface of the BCM domain controller, and the BCM domain controller executes the action of dimming the interior light; the underlying function instruction "adjust the display screen brightness" is sent to the IVI domain controller through the function implementation interface of the IVI domain controller, and the IVI domain controller executes the action of adjusting the display screen brightness.

[0066] In some embodiments, after converting the scene control instruction into simulated voice data based on the preset rule library, the simulated voice data can also be subjected to semantic consistency verification based on the scene control instruction; in the case of passing the verification, the simulated voice data is sent to the voice control module.

[0067] The semantic consistency verification can be performed by calculating the semantic similarity of the scene control instruction and the simulated voice data, and in the case that the semantic similarity is greater than a preset similarity, it is determined that the verification passes, otherwise, it is determined that the verification fails.

[0068] In the implementation process, the simulated voice data can also be subjected to syntax rule verification to ensure that the simulated voice data can be recognized by the voice control module.

[0069] In the case that the semantic consistency verification and / or syntax rule verification pass, the simulated voice data is sent to the voice control module, otherwise, log information can be recorded and prompt information for indicating the conversion failure is returned, and further, a default conversion scheme can be provided.

[0070] By verifying the simulated voice data, the success rate of the voice control module is improved, and the smooth implementation of the intelligent scene of the vehicle is ensured.

[0071] The above scheme generates a scene control instruction according to environment data of a vehicle, user state data and device state data; converts the scene control instruction into simulated voice data based on a preset rule library; and sends the simulated voice data to a voice control module, so that the voice control module distributes the simulated voice data to a corresponding function implementation interface after analyzing the simulated voice data. The scheme can at least achieve the following beneficial effects:

[0072] 1. The existing voice control module and function implementation interface in the vehicle are reused to implement the intelligent scene of the vehicle, avoiding the development of a special interface for each corresponding function of the intelligent scene, thereby reducing the development cost and development period.

[0073] 2. The existing voice control module and function implementation interface are used, and the new intelligent scene can be quickly deployed and adapted on various vehicle platforms (especially traditional architecture platforms) at low cost, thereby reducing the development and adaptation difficulty of the intelligent scene function.

[0074] 3. Without greatly changing the underlying architecture, more complex and intelligent scene linkage is achieved, breaking through the limitations of the traditional vehicle voice control module in scene intent reasoning and complex function linkage, and improving the richness of the intelligent scene.

[0075] 4. The intelligent scene logic and underlying function call are decoupled through a general voice control channel, improving the maintainability and expansibility of the system.

[0076] The following describes a device embodiment of the present application, which can be used to execute the implementation method of the vehicle intelligent scene based on simulated voice data in the above embodiments of the present application. For details not disclosed in the device embodiment of the present application, refer to the above embodiments of the implementation method of the vehicle intelligent scene based on simulated voice data.

[0077] Referring to Figure 2 , a block diagram of an implementation device of the vehicle intelligent scene based on simulated voice data in an embodiment of the present application is shown.

[0078] As shown in Figure 2 , the implementation device of the vehicle intelligent scene based on simulated voice data in the embodiment of the present application includes a scene control instruction generation module 201, a simulated voice data generation module 202 and a voice channel multiplexing module 203. The scene control instruction generation module 201 is configured to generate a scene control instruction according to environment data of a vehicle, user state data and device state data. The simulated voice data generation module 202 is configured to convert the scene control instruction into simulated voice data based on a preset rule library. The voice channel multiplexing module 203 is configured to send the simulated voice data to a voice control module, so that the voice control module distributes the simulated voice data to a corresponding function implementation interface after analyzing the simulated voice data.

[0079] In some embodiments, based on the foregoing scheme, the preset rule library includes multiple types of mapping table, template library and natural language generation model, and the simulation voice data generation module 202 is further configured to determine a target rule library from the preset rule library according to the type of the scene control instruction; and convert the scene control instruction into simulation voice data based on the target rule library.

[0080] In some embodiments, based on the foregoing scheme, the target rule library is a mapping table, and the simulation voice data generation module 202 is further configured to find voice data corresponding to the scene control instruction from the mapping table; and take the found voice data as the simulation voice data.

[0081] In some embodiments, based on the foregoing scheme, the target rule library is a template library, and the simulation voice data generation module 202 is further configured to determine a control target and a control mode according to the scene control instruction; select a template library to be filled from the template library according to the control mode; and fill the control target into the template library to be filled to obtain the simulation voice data.

[0082] In some embodiments, based on the foregoing scheme, the target rule library is a natural language generation model, and the simulation voice data generation module 202 is further configured to input the scene control instruction into the natural language generation model to obtain simulation voice data output by the natural language generation model.

[0083] In some embodiments, based on the foregoing scheme, the scene control instruction generation module 201 is further configured to determine a vehicle scene according to environmental data and user state data of the vehicle; and generate the scene control instruction according to the device state data and the vehicle scene.

[0084] In some embodiments, based on the foregoing scheme, the voice channel multiplexing module 203 is further configured to perform semantic consistency verification on the simulation voice data based on the scene control instruction; and send the simulation voice data to the voice control module if the verification is passed.

[0085] Based on the same inventive concept, the embodiments of the present application also provide an implementation device of a vehicle intelligent scene based on simulation voice data. Referring to Figure 3 The structure of the implementation device of the vehicle intelligent scene based on simulation voice data in the embodiments of the present application is shown in FIG. 4. The implementation device of the vehicle intelligent scene based on simulation voice data includes one or more memories 304, one or more processors 302, and at least one computer program (computer program instructions) stored in the memory 304 and executable on the processor 302. When the processor 302 executes the computer program, the method as described above is implemented.

[0086] In some embodiments, the implementation device of the vehicle intelligent scene based on simulation voice data includes a scene control instruction generation module 201, a simulation voice data generation module 202 and a voice channel multiplexing module 203. Figure 3In the embodiment of the present invention, a bus architecture (represented by bus 300) is shown. Bus 300 may include any number of interconnected buses and bridges, and bus 300 links together various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same component, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 may be used to store data used by processor 302 when performing operations.

[0087] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor is prompted to implement the steps of the method as described above.

[0088] Based on the same inventive concept, an embodiment of the present application provides a computer program product, including a computer program. When the computer program product is executed by a processor, it prompts the processor to implement the steps of the method described above.

[0089] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and implementations are within the scope and spirit of this application and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwiring, or a combination of any of these. Furthermore, the functional units may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0090] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between units or modules, which can be electrical or other forms.

[0091] The units described as separate components can or can not be physically separated, and the components of the control device can or can not be physical units, i.e. can be located in one place or can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0092] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of instructions for making a computer device (which can be a personal computer, a server or a network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various computer program instruction storage media.

[0093] The above is only an embodiment of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of claims of the present application.

Claims

1. A method for realizing vehicle intelligent scene based on simulated voice data, characterized in that: The vehicle includes a voice control module and a function implementation interface, and the method includes: Generate scene control instructions based on vehicle environmental data, user status data and device status data; Converting the scene control instructions into simulated voice data based on a preset rule library; The simulated voice data is sent to the voice control module, so that the voice control module analyzes the simulated voice data and distributes it to the corresponding function implementation interface.

2. The method for realizing vehicle intelligent scene based on simulated voice data according to claim 1, characterized in that: The preset rule base includes multiple types of mapping tables, template libraries, and natural language generation models. The converting of the scene control instructions into simulated voice data based on the preset rule base includes: Determining a target rule base from the preset rule base according to the type of the scene control instruction; The scene control instruction is converted into the simulated voice data based on the target rule base.

3. The method for realizing vehicle intelligent scene based on simulated voice data according to claim 2, characterized in that: The target rule base is a mapping table, and converting the scene control instruction into the simulated voice data based on the target rule base includes: Searching for the voice data corresponding to the scene control instruction from the mapping table; The found voice data is used as the simulated voice data.

4. The method for realizing vehicle intelligent scene based on simulated voice data according to claim 2, characterized in that: The target rule base is a template base, and converting the scene control instruction into the simulated voice data based on the target rule base includes: Determine the control target and control method according to the scene control instruction; selecting a template library to be filled from the template library according to the control mode; The control target is filled into the template library to be filled to obtain the simulated voice data.

5. The method for realizing vehicle intelligent scene based on simulated voice data according to claim 2, characterized in that: The target rule base is a natural language generation model, and converting the scene control instruction into the simulated voice data based on the target rule base includes: The scene control instruction is input into the natural language generation model to obtain simulated speech data output by the natural language generation model.

6. The method for realizing a vehicle intelligent scene based on simulated voice data according to any one of claims 1 to 5, characterized in that: The generating of scene control instructions according to the vehicle environment data, user status data and device status data includes: determining a vehicle scenario based on the vehicle environment data and the user status data; The scenario control instruction is generated according to the device status data and the vehicle scenario.

7. The method for realizing a vehicle intelligent scene based on simulated voice data according to any one of claims 1 to 5, characterized in that: After converting the scene control instruction into simulated voice data based on a preset rule library, the method further includes: Performing a semantic consistency check on the simulated voice data based on the scene control instruction; If the verification is passed, the simulated voice data is sent to the voice control module.

8. A device for realizing vehicle intelligent scene based on simulated voice data, characterized in that: The vehicle includes a voice control module and a function implementation interface, and the device includes: A scene control instruction generation module is used to generate scene control instructions based on vehicle environment data, user status data and device status data; A simulated voice data generating module, configured to convert the scene control instructions into simulated voice data based on a preset rule library; The voice channel multiplexing module is used to send the analog voice data to the voice control module, so that the voice control module analyzes the analog voice data and distributes it to the corresponding function implementation interface.

9. An implementation of a vehicle intelligent scene based on simulated voice data, comprising a processor and a memory, characterized in that: The memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, which, when executed by a processor, prompt the processor to implement the steps of the method according to any one of claims 1 to 7.

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