Vehicle function intelligent recommendation implementation method and device, equipment and storage medium

Abstract

The invention discloses a vehicle function intelligent recommendation implementation method and device, equipment and a storage medium, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining vehicle state information in real time, and transmitting the vehicle state information to a trained neural network model, so as to obtain a current driving scene and a vehicle function which can be matched with the current driving scene; and generating a function use prompt based on the vehicle function obtained through matching, pushing the function use prompt to the vehicle machine, and detecting a vehicle use operation state in real time to judge whether the vehicle function corresponding to the function use prompt is used or not. According to the method and the device, the function use prompt is pushed in the corresponding scene, and whether the corresponding vehicle function is used or not is detected, so that a user is more familiar with each function of the vehicle, and the driving experience is enhanced.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and specifically to a method, device, equipment and storage medium for implementing intelligent recommendation of vehicle functions. Background Art

[0002] With the improvement of vehicle computer capabilities and vehicle intelligence levels, vehicles provide more new functions, such as light shows, fragrance systems, etc. However, since users generally have little knowledge of new vehicle functions, users are currently mainly informed of the use of new or conventional functions through manuals or brochures.

[0003] However, if users look up the manual on their own to understand the functions provided by the vehicle, the following problems will arise: 1. The manual catalog is cumbersome, and most users are unwilling to read the manual, nor can they learn about the vehicle's highlight functions from the manual; 2. When users really need to use certain functions, they cannot obtain the operation method in the first time; 3. There is a lack of a reward mechanism, and users have no motivation to use the special functions developed by car companies; 4. Car companies cannot analyze user habits and cannot clearly understand the specific scenarios in which users use certain functions. Summary of the Invention

[0004] The present application provides a method, apparatus, device and storage medium for implementing intelligent vehicle function recommendation. By pushing function usage prompts in corresponding scenarios and detecting whether the corresponding vehicle functions are used, users can become more familiar with the various vehicle functions and enhance the driving experience.

[0005] In a first aspect, an embodiment of the present application provides a method for implementing intelligent vehicle function recommendation, the method comprising:

[0006] Acquire vehicle status information in real time and send it to the trained neural network model to obtain the current driving scenario and the vehicle functions that can match the current driving scenario;

[0007] Based on the matched vehicle functions, function usage prompts are generated and pushed to the vehicle computer, and the vehicle usage operation status is detected in real time to determine whether the vehicle function corresponding to the function usage prompt is used.

[0008] In conjunction with the first aspect, in one embodiment, for a trained neural network model, the specific construction process includes:

[0009] The vehicle status information of multiple vehicles at different times is collected based on the vehicle-mounted network terminal Tbox, and the collected data is pre-processed;

[0010] The pre-processed data is stored in a real-time cloud database and annotated to form a training set for training the neural network model, so that the trained neural network model can obtain the current driving scenario based on the vehicle status information and generate decision recommendations based on the current driving scenario;

[0011] The decision suggestion is a vehicle operation suggestion, and the decision suggestion corresponds to at least one vehicle function.

[0012] In conjunction with the first aspect, in one embodiment, the real-time acquisition of vehicle status information and sending it to the trained neural network model to obtain the current driving scene and the vehicle functions that can match the current driving scene specifically include:

[0013] Based on the vehicle CAN bus signal and various sensors installed on the vehicle, the vehicle status information is obtained in real time;

[0014] The vehicle status information is sent to the cloud through the on-board connected terminal Tbox. The trained neural network model in the cloud analyzes the vehicle status information to obtain the current driving scenario, and further obtains the vehicle function that matches the current driving scenario.

[0015] In conjunction with the first aspect, in one embodiment, generating a function usage prompt based on the matched vehicle function and pushing it to the vehicle computer specifically includes:

[0016] Generate a function usage prompt based on the matched vehicle function, and send the generated function usage prompt to the vehicle computer and store it;

[0017] Determine whether the vehicle computer is currently logged in to the user account:

[0018] If yes, then if the currently logged-in user account has not pushed the current function usage prompt, push the current function usage prompt to the front end of the vehicle computer;

[0019] If not, then end.

[0020] In conjunction with the first aspect, in one embodiment, when the currently logged-in user account has not pushed the current function usage prompt, pushing the current function usage prompt to the front end of the vehicle computer specifically includes:

[0021] Determine whether the current function usage prompt is a single push prompt:

[0022] If not, monitor the usage status of the vehicle function corresponding to the current function usage prompt in real time, and after the vehicle function corresponding to the current function usage prompt is used, record that the vehicle function corresponding to the current function usage prompt has been triggered;

[0023] If so, search the push history to determine whether the currently logged-in user account has ever received a prompt for the current function:

[0024] -If it has been pushed before, it ends;

[0025] - If not pushed before, the current function usage prompt will be pushed to the front end of the vehicle when the vehicle is powered on next time.

[0026] In conjunction with the first aspect, in one embodiment, the real-time detection of the vehicle usage operation status to determine whether the vehicle function corresponding to the function usage prompt is used, wherein, after the vehicle function corresponding to the function usage prompt is used, the method further includes:

[0027] The completion status of each vehicle function is recorded in real time and compared with the previously constructed vehicle function task list to determine in real time whether the vehicle function completion status meets the preset multi-stage task completion goals.

[0028] In conjunction with the first aspect, in one embodiment, the method for implementing intelligent vehicle function recommendation further includes:

[0029] Monitor the usage of vehicle functions in real time and send the usage information to the cloud to analyze the usage scenarios and frequency of each vehicle function.

[0030] In a second aspect, an embodiment of the present application provides a device for implementing intelligent vehicle function recommendation, the device comprising:

[0031] A data acquisition module, which is used to obtain vehicle status information in real time and send it to the trained neural network model to obtain the current driving scenario and the vehicle functions that can match the current driving scenario;

[0032] The push implementation module is used to generate function usage prompts based on the matched vehicle functions and push them to the vehicle computer, and to detect the vehicle usage operation status in real time to determine whether the vehicle function corresponding to the function usage prompt is used.

[0033] In a third aspect, an embodiment of the present application provides a device for implementing intelligent vehicle function recommendations, characterized in that the device comprises a processor, a memory, and a program for implementing intelligent vehicle functions stored in the memory and executable by the processor, wherein when the program for implementing intelligent vehicle functions is executed by the processor, the steps of the above-mentioned method for implementing intelligent vehicle functions are implemented.

[0034] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a vehicle function intelligent recommendation implementation program is stored. When the vehicle function intelligent recommendation implementation program is executed by a processor, the steps of the above-mentioned vehicle function intelligent recommendation implementation method are implemented.

[0035] The beneficial effects of the technical solutions provided in the embodiments of the present application include:

[0036] By acquiring vehicle status information in real time and sending it to the trained neural network model, the current driving scenario and vehicle functions that can match the current driving scenario are obtained, and function usage prompts are generated based on the matched vehicle functions and pushed to the vehicle computer. Through intelligent recommendations, users are guided to use vehicle functions, which helps users to master vehicle functions more accurately and enhance vehicle driving experience. User habits can be analyzed based on the use of vehicle functions to facilitate understanding of specific scenarios of vehicle functions for subsequent vehicle development. At the same time, a reward mechanism can be set up based on the use of vehicle functions to increase user enthusiasm for using vehicle functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flowchart of the method for implementing intelligent vehicle function recommendations in this application;

[0038] Figure 2 This is a schematic diagram of the functional modules of the device for implementing intelligent vehicle function recommendation in this application;

[0039] Figure 3 This is a schematic diagram of the hardware structure of the equipment recommended for implementing intelligent vehicle functions in this application. DETAILED DESCRIPTION

[0040] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0041] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0042] On the first aspect, an embodiment of the present application provides a method for implementing intelligent recommendation of vehicle functions. By pushing function usage prompts in corresponding scenarios and detecting whether the corresponding vehicle functions are used, users can become more familiar with the various vehicle functions and enhance the driving experience.

[0043] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of the method for implementing intelligent vehicle function recommendation in this application. Figure 1 As shown, the method for implementing intelligent vehicle function recommendation includes:

[0044] S1: Real-time acquisition of vehicle status information and sending it to the trained neural network model to obtain the current driving scenario and the vehicle functions that match the current driving scenario;

[0045] S2: Generate a function usage prompt based on the matched vehicle function and push it to the vehicle computer, and detect the vehicle usage operation status in real time to determine whether the vehicle function corresponding to the function usage prompt is used.

[0046] Furthermore, in one embodiment, the specific construction process of the trained neural network model includes:

[0047] S101: Vehicle status information of multiple vehicles at different times is collected based on the vehicle-mounted network terminal Tbox, and the collected data is pre-processed; the vehicle status information includes vehicle surrounding environment information (such as external temperature, weather, surrounding obstacles, etc.) and vehicle information (such as location, speed, driving mode, function switch status, internal temperature, number of passengers, etc.);

[0048] S102: Storing the preprocessed data in a real-time cloud database and annotating it to form a training set to train a neural network model, so that the trained neural network model can obtain the current driving scenario based on the vehicle status information and generate decision recommendations based on the current driving scenario; wherein the decision recommendations are vehicle operation recommendations, and the decision recommendations correspond to at least one vehicle function.

[0049] Specifically, based on the vehicle status information of multiple vehicles at different times collected by the on-board connected terminal Tbox of each vehicle, the collected data is preprocessed, and the preprocessing includes data cleaning and denoising to ensure data quality and consistency; the preprocessed data is then stored in a real-time cloud database, and the data is regularly converted into historical data for archiving in order to conduct long-term trend analysis and model training. The data stored in the real-time cloud database is labeled to form a training set. For example, the OMS camera recognizes that the user is sweating profusely, the outdoor temperature exceeds 30°, the user adjusts the air conditioning temperature to the lowest, the air volume to the maximum, and the seat ventilation air volume to the maximum. This scene and the user's air conditioning operation function are repeated many times. In this scenario, the user's sweating and the lowering of the air conditioning temperature can be associated; for example, if the user drives to the same underground garage many times and parks the car in the parking space, the scene can be associated with reversing into the garage.

[0050] The neural network model constructed by training the training set can be used to determine the current driving scenario based on vehicle status information and generate decision suggestions based on the current driving scenario (for example, if the driving scenario is entering a specific underground garage, the decision suggestion generated is to initiate automatic parking); wherein the decision suggestion is a vehicle operation suggestion, and the decision suggestion corresponds to at least one vehicle function (such as turning on the wipers, adjusting the air conditioning status, initiating automatic parking, etc.). Of course, the neural network model and related algorithms can also be continuously improved by actively collecting user feedback and the operation of the neural network model.

[0051] Furthermore, in one embodiment, vehicle status information is acquired in real time and sent to a trained neural network model to obtain the current driving scenario and vehicle functions that can match the current driving scenario, specifically including:

[0052] S111: Based on the vehicle CAN bus signal and various sensors installed on the vehicle, obtain vehicle status information in real time;

[0053] S112: The vehicle status information is sent to the cloud through the on-board network terminal Tbox. The trained neural network model in the cloud analyzes the vehicle status information to obtain the current driving scenario, and further obtains the vehicle function that matches the current driving scenario.

[0054] Specifically, the collected vehicle status information is aggregated and pre-processed before being sent to the cloud via the vehicle's connected terminal, the Tbox. A trained neural network model in the cloud analyzes the vehicle status information to determine the current driving scenario and further derives vehicle functions that match the current driving scenario. For vehicle functions that match the current driving scenario, these functions are prompted for use in certain specific scenarios or when preconditions are met.

[0055] Furthermore, in one embodiment, generating a function usage prompt based on the matched vehicle function and pushing it to the vehicle computer specifically includes:

[0056] S201: Generate a function usage prompt based on the matched vehicle function, send the generated function usage prompt to the vehicle computer and store it;

[0057] S202: Determine whether the vehicle computer is currently logged in to the user account:

[0058] If yes, then if the currently logged-in user account has not pushed the current function usage prompt, push the current function usage prompt to the front end of the vehicle computer;

[0059] If not, then end.

[0060] Furthermore, in one embodiment, when the currently logged-in user account has not pushed the current function usage prompt, the current function usage prompt is pushed to the front end of the vehicle computer, specifically including:

[0061] Determine whether the current function usage prompt is a single push prompt:

[0062] If not, monitor the usage status of the vehicle function corresponding to the current function usage prompt in real time, and after the vehicle function corresponding to the current function usage prompt is used, record that the vehicle function corresponding to the current function usage prompt has been triggered;

[0063] If so, search the push history to determine whether the currently logged-in user account has ever received a prompt for the current function:

[0064] -If it has been pushed before, it ends;

[0065] - If not pushed before, the current function usage prompt will be pushed to the front end of the vehicle when the vehicle is powered on next time.

[0066] Specifically, first determine whether the current function usage prompt is a single push prompt. For example, for vehicle functions that are completed passively (such as accumulated mileage, accumulated navigation times, accumulated check-in times, etc.), the corresponding function usage prompt is not a single push prompt. For vehicle functions that need to be actively completed (such as starting automatic parking, launch start, opening mechanical child locks, standing sensor tailgate, etc.), the corresponding function usage prompt is a single push prompt; for vehicle functions that are completed passively, it is only necessary to continuously monitor the triggering status of the vehicle function, for example, continuously monitor whether the accumulated mileage reaches a certain mileage target; for function usage prompts corresponding to vehicle functions that need to be actively completed, retrieve the push records to determine whether the current function usage prompt has been pushed before the currently logged-in user account. If it has not been pushed before, the current function usage prompt will be pushed to the front end of the vehicle computer the next time the vehicle is powered on, and the function usage prompt will no longer be pushed subsequently.

[0067] The following is an example of the vehicle functions in this application.

[0068] Vehicle functions include launch control, automatic parking, fragrance system, mechanical child lock, AR tailgate opening system, standing sensor tailgate, front wiper service gear, light show, ASD active sound wave, ADAS, hill descent control, fault prompt, rain and snow mode, etc.

[0069] For launch control, the function usage prompt is a graphic and text method to guide the user to use the launch control function, and the trigger condition is that the specific mileage is met and the function has never been used before; for automatic parking, the function usage prompt is a graphic and text method to guide the user to turn on automatic parking, and the trigger condition is that the automatic parking is turned on; for the fragrance system, the function usage prompt is a graphic and text method to guide the user to turn on the fragrance, and the trigger condition is that it has not been used after the first maintenance; for the mechanical child lock, the function usage prompt is a graphic and text method to introduce the use of the child lock, and the trigger condition is that the OMS recognizes the child passengers in the back row; for the AR tailgate opening system, the function usage prompt is a graphic and text method to introduce the use of the AR tailgate, and the trigger condition is that it has never been used before; for the standing induction tailgate, the function usage prompt is a graphic and text method to introduce the use of the induction tailgate, and the trigger condition is that it has never been used before; for the front wiper maintenance gear, the function usage prompt is a graphic and text method to introduce the method to open the front wiper maintenance gear, and the trigger condition is that the outdoor temperature is low at 0℃ and has never been used; for light show, the function usage prompt is a graphic guide to guide users to use the light show, and the trigger condition is that a specific mileage has been reached and it has never been used; for ASD active sound, the function usage prompt is a graphic guide to guide users to turn on the active sound, and the trigger condition is that a specific mileage has been reached and it has never been used; for ADAS, the function usage prompt is a graphic guide to guide users to turn on ADAS, and the trigger condition is that a specific mileage has been reached and it has never been used at the current location; for steep slope descent, the function usage prompt is a graphic guide to guide users to turn on steep slope descent, and the trigger condition is that it is located at a specific slope and has never been used; for fault prompts, when the vehicle fails, a pop-up window will push a prompt of the electronic manual page of the fault, and the user can click on the pop-up window to view the relevant information in the electronic manual; for rain and snow mode, during driving, when it is recognized that it is raining heavily, the wiper is maintained in high speed gear for more than 5 seconds, prompting the user to turn on rain and snow mode.

[0070] Furthermore, in one embodiment, the vehicle usage operation status is detected in real time to determine whether the vehicle function corresponding to the function usage prompt is used, wherein, after the vehicle function corresponding to the function usage prompt is used, it also includes: real-time recording of the completion status of each vehicle function, and comparing it with the previously constructed vehicle function task list to determine in real time whether the vehicle function completion status meets the preset multi-stage task completion goals.

[0071] Specifically, a vehicle function task list can be written into the vehicle computer to mark the highlight functions of the vehicle. After the user successfully uses the vehicle function, the vehicle function task list will prompt that the task has been completed, and the completion percentage will be used to determine whether the preset multi-stage task completion target has been met. At the same time, after the vehicle function is completed, the user can be awarded corresponding points. The accumulation of points can increase the user's level. Each level increase can earn rewards and titles. The rewards can be virtual items (such as the action expressions, clothing or props of the in-vehicle voice assistant) or physical items (such as car models and mugs customized by the car company). Of course, the tasks in the vehicle function task list can also be refreshed as needed to facilitate the user's point acquisition.

[0072] Furthermore, the method for implementing intelligent vehicle function recommendation in this application also includes: real-time monitoring of vehicle function usage and sending the vehicle function usage information to the cloud to analyze the usage scenarios and frequency of each vehicle function. That is, after a user uses a vehicle function, the vehicle computer sends embedded data (such as user registration information, location information, cabin temperature, vehicle speed, etc.) to the cloud to determine whether the corresponding task has been completed. The user's habits can be analyzed based on the usage of the vehicle function, and the usage scenarios and frequency of the vehicle functions can be comprehensively analyzed to facilitate subsequent vehicle development.

[0073] The method for implementing intelligent vehicle function recommendation in the embodiment of the present application obtains vehicle status information in real time and sends it to a trained neural network model to obtain the current driving scenario and vehicle functions that can match the current driving scenario, and generates function usage prompts based on the matched vehicle functions and pushes them to the vehicle computer. It guides users to use vehicle functions through intelligent recommendations, which helps users to master vehicle functions more accurately and enhance vehicle driving experience. It can also analyze user habits based on the use of vehicle functions to facilitate understanding of specific scenarios of vehicle functions for subsequent vehicle development. At the same time, it can also increase users' enthusiasm for using vehicle functions by setting up a reward mechanism based on the use of vehicle functions.

[0074] In a second aspect, an embodiment of the present application also provides a device for implementing intelligent vehicle function recommendations.

[0075] In one embodiment, referring to Figure 2 , Figure 2 This is a functional module diagram of the vehicle function intelligent recommendation implementation device of this application. Figure 2 As shown, the vehicle function intelligent recommendation implementation device includes: a data acquisition module and a push implementation module.

[0076] The data acquisition module is used to obtain vehicle status information in real time and send it to the trained neural network model to obtain the current driving scene and the vehicle functions that can match the current driving scene; the push implementation module is used to generate function usage prompts based on the matched vehicle functions and push them to the vehicle computer, and to detect the vehicle usage operation status in real time to determine whether the vehicle function corresponding to the function usage prompt is used.

[0077] On the third aspect, an embodiment of the present application provides a device for implementing intelligent vehicle function recommendation. The device for implementing intelligent vehicle function recommendation can be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0078] Reference Figure 3 , Figure 3 Schematic diagram of the hardware structure of the vehicle function intelligent recommendation implementation device involved in the embodiment of the present application. In the embodiment of the present application, the vehicle function intelligent recommendation implementation device may include a processor, a memory, a communication interface and a communication bus.

[0079] The communication bus may be of any type and is used to interconnect the processor, memory, and communication interface.

[0080] Communication interfaces include input / output (I / O), physical, and logical interfaces, which interconnect components within the vehicle function intelligent recommendation device and other devices (such as other computing devices or user devices). Physical interfaces can include Ethernet, fiber optic, and ATM interfaces; user devices can include displays and keyboards.

[0081] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0082] The processor may be a general-purpose processor that can call a program for implementing intelligent vehicle function recommendations stored in a memory and execute the method for implementing intelligent vehicle function recommendations provided in the embodiments of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the program for implementing intelligent vehicle function recommendations is called may refer to the various embodiments of the method for implementing intelligent vehicle function recommendations of the present application and will not be further described here.

[0083] Those skilled in the art will understand that Figure 3 The hardware structure shown in the figure does not constitute a limitation to the present application and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0084] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0085] The computer-readable storage medium of the present application stores a vehicle function intelligent recommendation implementation program, wherein when the vehicle function intelligent recommendation implementation program is executed by a processor, the steps of the vehicle function intelligent recommendation implementation method as described above are implemented.

[0086] Among them, the method implemented when the vehicle function intelligent recommendation implementation program is executed can refer to the various embodiments of the vehicle function intelligent recommendation implementation method of this application, and will not be repeated here.

[0087] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit the "first", "second" and "third" to different types.

[0088] In the description of the embodiments of this application, the words "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0089] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0090] In some processes described in the embodiments of the present application, multiple operations or steps are included that appear in a specific order. However, it should be understood that these operations or steps may not be performed in the order in which they appear in the embodiments of the present application or may be performed in parallel. The sequence numbers of the operations are only used to distinguish between different operations, and the sequence numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations or steps may be performed in sequence or in parallel, and these operations or steps may be combined.

[0091] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to execute the methods described in each embodiment of the present application.

[0092] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for implementing intelligent vehicle function recommendation, characterized in that: The method for implementing intelligent vehicle function recommendation includes: Acquire vehicle status information in real time and send it to the trained neural network model to obtain the current driving scenario and the vehicle functions that can match the current driving scenario; Based on the matched vehicle functions, function usage prompts are generated and pushed to the vehicle computer, and the vehicle usage operation status is detected in real time to determine whether the vehicle function corresponding to the function usage prompt is used.

2. The method for implementing intelligent vehicle function recommendation according to claim 1, characterized in that: For a trained neural network model, the specific construction process includes: The vehicle status information of multiple vehicles at different times is collected based on the vehicle-mounted network terminal Tbox, and the collected data is pre-processed; The pre-processed data is stored in a real-time cloud database and annotated to form a training set for training the neural network model, so that the trained neural network model can obtain the current driving scenario based on the vehicle status information and generate decision recommendations based on the current driving scenario; The decision suggestion is a vehicle operation suggestion, and the decision suggestion corresponds to at least one vehicle function.

3. The method for implementing intelligent vehicle function recommendation according to claim 2, characterized in that: The real-time acquisition of vehicle status information and sending it to the trained neural network model to obtain the current driving scenario and vehicle functions that can match the current driving scenario specifically include: Based on the vehicle CAN bus signal and various sensors installed on the vehicle, the vehicle status information is obtained in real time; The vehicle status information is sent to the cloud through the on-board connected terminal Tbox. The trained neural network model in the cloud analyzes the vehicle status information to obtain the current driving scenario, and further obtains the vehicle function that matches the current driving scenario.

4. The method for implementing intelligent vehicle function recommendation according to claim 1, characterized in that: The generating of function usage prompts based on the matched vehicle functions and pushing the prompts to the vehicle computer specifically includes: Generate a function usage prompt based on the matched vehicle function, and send the generated function usage prompt to the vehicle computer and store it; Determine whether the vehicle computer is currently logged in to the user account: If yes, then if the currently logged-in user account has not pushed the current function usage prompt, push the current function usage prompt to the front end of the vehicle computer; If not, then end.

5. The method for implementing intelligent vehicle function recommendation according to claim 4, characterized in that: When the currently logged-in user account has not pushed the current function usage prompt, pushing the current function usage prompt to the front end of the vehicle specifically includes: Determine whether the current function usage prompt is a single push prompt: If not, monitor the usage status of the vehicle function corresponding to the current function usage prompt in real time, and after the vehicle function corresponding to the current function usage prompt is used, record that the vehicle function corresponding to the current function usage prompt has been triggered; If so, search the push history to determine whether the currently logged-in user account has ever received a prompt for the current function: -If it has been pushed before, it ends; - If not pushed before, the current function usage prompt will be pushed to the front end of the vehicle when the vehicle is powered on next time.

6. The method for implementing intelligent vehicle function recommendation according to claim 1, characterized in that: The real-time detection of the vehicle operation state to determine whether the vehicle function corresponding to the function use prompt is used, wherein after the vehicle function corresponding to the function use prompt is used, the method further includes: The completion status of each vehicle function is recorded in real time and compared with the previously constructed vehicle function task list to determine in real time whether the vehicle function completion status meets the preset multi-stage task completion goals.

7. The method for implementing intelligent vehicle function recommendation according to claim 1, characterized in that: The method for implementing intelligent vehicle function recommendation further includes: Monitor the usage of vehicle functions in real time and send the usage information to the cloud to analyze the usage scenarios and frequency of each vehicle function.

8. A vehicle function intelligent recommendation implementation device, characterized in that: The vehicle function intelligent recommendation implementation device includes: A data acquisition module, which is used to obtain vehicle status information in real time and send it to the trained neural network model to obtain the current driving scenario and the vehicle functions that can match the current driving scenario; The push implementation module is used to generate function usage prompts based on the matched vehicle functions and push them to the vehicle computer, and to detect the vehicle usage operation status in real time to determine whether the vehicle function corresponding to the function usage prompt is used.

9. A vehicle function intelligent recommendation implementation device, characterized in that: The vehicle function intelligent recommendation implementation device includes a processor, a memory, and a vehicle function intelligent recommendation implementation program stored in the memory and executable by the processor, wherein when the vehicle function intelligent recommendation implementation program is executed by the processor, the steps of the vehicle function intelligent recommendation implementation method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a vehicle function intelligent recommendation implementation program, wherein when the vehicle function intelligent recommendation implementation program is executed by the processor, the steps of the vehicle function intelligent recommendation implementation method as described in any one of claims 1 to 7 are implemented.

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