Guest greeting lamp control method and device for vehicle, vehicle, medium and program

Abstract

The invention relates to the technical field of vehicles, in particular to a welcome lamp control method and device of a vehicle, the vehicle, a medium and a program.The method comprises the steps that environment data, vehicle state data, a user face recognition result and user behavior data at the current moment are obtained; the environment data, the vehicle state data, the user face recognition result and the user behavior data are input into a neural network model, and the neural network model outputs target control parameters of the welcome lamp; and controlling the vehicle to welcome according to the target control parameter of the welcome lamp. Therefore, the problem that the user experience feeling is poor due to the fact that the greeting mode is single in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a method, device, vehicle, medium and program for controlling a welcome light of a vehicle. Background Art

[0002] With the rapid development of smart cars, vehicle lighting systems are gradually shifting from traditional mechanical control to intelligent control.

[0003] In the related art, the welcome light of the vehicle mainly relies on manual switch or simple automatic sensing function. However, this simple control system cannot be flexibly adjusted according to the specific behavior of the owner, environmental changes and vehicle status, and the welcome mode is single, resulting in limited user experience. Summary of the invention

[0004] The present application provides a vehicle welcome light control method, device, vehicle, medium and program to solve the problems in the related art such as a single welcome mode resulting in a poor user experience.

[0005] The first aspect of the present application provides a method for controlling a welcome light of a vehicle, comprising the following steps: acquiring environmental data, vehicle status data, user facial recognition results and user behavior data at the current moment; inputting the environmental data, the vehicle status data, the user facial recognition results and the user behavior data into a neural network model, and the neural network model outputs target control parameters of the welcome light; and controlling the vehicle to welcome guests according to the target control parameters of the welcome light.

[0006] Optionally, the environmental data includes ambient brightness, distance between the user and the vehicle, and weather conditions information; the vehicle status data includes door switch information; the user facial recognition result includes user mood data; the user behavior data includes the user's favorite music type; the target control parameters include the switch of the welcome light, light brightness, color and display image.

[0007] Optionally, the processing process of the neural network model includes: determining the light brightness of the target control parameter of the welcome light according to the environmental data; determining the switch of the target control parameter of the welcome light according to the vehicle status data; determining the color and display image of the target control parameter of the welcome light according to the user facial recognition result and the user behavior data.

[0008] Optionally, determining the light brightness of the target control parameter of the welcome light according to the environmental data includes: identifying the ambient brightness, the distance between the user and the vehicle, and weather conditions in the environmental data; determining the light brightness of the target control parameter of the welcome light according to the ambient brightness, the distance between the user and the vehicle, and weather conditions in the environmental data.

[0009] Optionally, the switch for determining the target control parameters of the welcome light according to the vehicle status data includes: identifying the door switch information in the vehicle status data; if the door is closed at the current moment, the welcome light is turned off; if the door is open at the current moment, the welcome light is automatically controlled to turn on.

[0010] Optionally, determining the color and display image of the target control parameters of the welcome light based on the user facial recognition result and the user behavior data includes: if the user facial recognition shows that the mood is good, querying a preset database to match the color and display image of the target control parameters of the welcome light based on the user portrait; identifying the type of music liked by the user behavior data, and querying a preset database to match the color and display image of the target control parameters of the welcome light based on the music type.

[0011] The second aspect of the present application provides a welcome light control device for a vehicle, comprising: an acquisition module for acquiring environmental data, vehicle status data, user facial recognition results and user behavior data at the current moment; an input module for inputting the environmental data, the vehicle status data, the user facial recognition results and the user behavior data into a neural network model, and the neural network model outputs target control parameters of the welcome light; a control module for controlling the vehicle to welcome guests according to the target control parameters of the welcome light.

[0012] A third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to execute the vehicle welcome light control method as described in the above embodiment.

[0013] The fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored. The program is executed by a processor to perform the vehicle welcome light control method as described in the above embodiment.

[0014] The fifth aspect of the present application provides a computer program product, including a computer program or instructions, characterized in that when the computer program or instructions are executed, the vehicle welcome light control method as described in the above embodiment is implemented.

[0015] Therefore, this application has at least the following beneficial effects:

[0016] The embodiments of the present application can obtain environmental data, vehicle status data, user facial recognition results and user behavior data at the current moment; input the environmental data, vehicle status data, user facial recognition results and user behavior data into a neural network model, and the neural network model outputs the target control parameters of the welcome light; control the vehicle welcome according to the target control parameters of the welcome light, so as to be able to analyze the owner's behavior, environmental status and vehicle status in real time, ensure that the control of the welcome light always matches the current situation, realize the personalized customization of the welcome light, and enhance the user experience.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 A flowchart of a vehicle welcome light control method provided according to an embodiment of the present application;

[0020] Figure 2 It is a diagram of the overall technical framework provided according to the embodiments of the present application;

[0021] Figure 3 A flowchart of uploading the owner's behavior information to the cloud according to an embodiment of the present application;

[0022] Figure 4 A flowchart for parsing the owner's behavior information and generating a welcome light style in the cloud according to an embodiment of the present application;

[0023] Figure 5 A flowchart of returning the generated welcome light style to the owner's behavior data in the cloud according to an embodiment of the present application;

[0024] Figure 6 This is an example diagram of a welcome light control device for a vehicle provided according to an embodiment of the present application;

[0025] Figure 7 It is a schematic diagram of the structure of a vehicle provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0027] Big models are built from deep neural networks and usually have billions or even hundreds of billions of parameters. They are designed to improve the expressiveness and predictive performance of the model to handle more complex tasks and data. The application of big intelligent models in the automotive industry is gradually deepening. These models provide strong support for automotive design, R&D, production, autonomous driving and other aspects by processing and analyzing massive amounts of data.

[0028] Therefore, it is an urgent problem to provide an intelligent welcome light control method and system based on a large model to lower the threshold of vehicle-mounted intelligent welcome lights, so that vehicles equipped with welcome lights can generate personalized welcome lights through large models, thereby improving the popularity of vehicle-mounted intelligent welcome lights.

[0029] This application can analyze the owner's behavior, environmental status and vehicle status in real time, and control the switch, brightness, color, image and other parameters of the car's welcome lights accordingly to achieve intelligent lighting.

[0030] The following describes the vehicle welcome light control method, device, vehicle, storage medium and program of the embodiments of the present application with reference to the accompanying drawings.

[0031] Specifically, Figure 1 A flowchart of a vehicle welcome light control method provided in an embodiment of the present application.

[0032] like Figure 1 As shown, the vehicle welcome light control method includes the following steps:

[0033] In step S101, the current environmental data, vehicle status data, user face recognition results and user behavior data are obtained.

[0034] Among them, environmental data includes ambient brightness, distance between user and vehicle, and weather conditions; vehicle status data includes door switch information; user facial recognition results include user mood data; user behavior data includes user's favorite music type; target control parameters include the welcome light switch, light brightness, color, and display image.

[0035] It can be understood that the embodiments of the present application can obtain the current environmental data, vehicle status data, user facial recognition results and user behavior data, so as to facilitate the subsequent determination of the target control parameters of the welcome light.

[0036] It should be noted that the present application can collect current environmental data, vehicle status data, user facial recognition results, user behavior data and other data through sensors (such as infrared sensors, light sensors, vehicle status sensors, etc.), facial recognition systems, and owner behavior collection systems (recently listened to music types).

[0037] In step S102, environmental data, vehicle status data, user facial recognition results and user behavior data are input into a neural network model, and the neural network model outputs target control parameters of the welcome light.

[0038] It can be understood that the embodiments of the present application can input environmental data, vehicle status data, user facial recognition results and user behavior data into the neural network model, and the neural network model outputs the target control parameters of the welcome lights, thereby improving the accuracy of the target control parameters without the need for manual operation by the user, meeting the user's personalized needs and improving the user experience.

[0039] It should be noted that the present application can use a neural network model to learn and recognize the owner's mood, status (approaching, leaving, staying, etc.), environmental brightness, weather conditions, holidays, and even birthdays, as well as the vehicle's door status, position and other information; based on this information, the best lighting strategy can be predicted, and the switch, brightness, color, image and other parameters of the car's welcome lights can be controlled.

[0040] In an embodiment of the present application, the processing process of the neural network model includes: determining the light brightness of the target control parameters of the welcome light based on environmental data; determining the switch of the target control parameters of the welcome light based on vehicle status data; determining the color and display image of the target control parameters of the welcome light based on user facial recognition results and user behavior data.

[0041] It can be understood that the embodiments of the present application can determine the light brightness of the target control parameters of the welcome light based on environmental data; determine the switch of the target control parameters of the welcome light based on vehicle status data; determine the color and display image of the target control parameters of the welcome light based on user facial recognition results and user behavior data, thereby controlling the switch, brightness, color, image and other parameters of the car welcome light in all directions to enhance the user experience.

[0042] In an embodiment of the present application, the light brightness of the target control parameter of the welcome light is determined according to the environmental data, including: identifying the ambient brightness, the distance between the user and the vehicle, and the weather conditions in the environmental data; determining the light brightness of the target control parameter of the welcome light according to the ambient brightness, the distance between the user and the vehicle, and the weather conditions in the environmental data.

[0043] It can be understood that the embodiments of the present application can identify the ambient brightness, the distance between the user and the vehicle, and the weather conditions in the environmental data; determine the light brightness of the target control parameters of the welcome light based on the ambient brightness, the distance between the user and the vehicle, and the weather conditions in the environmental data, so as to comprehensively consider the environment surrounding the vehicle and enhance the user experience.

[0044] In an embodiment of the present application, the switch of the target control parameters of the welcome light is determined according to the vehicle status data, including: identifying the door switch information in the vehicle status data; if the door is closed at the current moment, the welcome light is turned off; if the door is open at the current moment, the welcome light is automatically controlled to turn on.

[0045] It can be understood that the embodiment of the present application can identify the door switch information in the vehicle status data; if the door is closed at the current moment, the welcome light is off; if the door is open at the current moment, the welcome light is automatically controlled to turn on, making the vehicle more intelligent, able to meet the user's personalized needs, and enhance the user experience.

[0046] In an embodiment of the present application, the color and display image of the target control parameters of the welcome light are determined based on the user facial recognition results and the user behavior data, including: if the user's facial recognition shows that he is in a good mood, then querying the preset database according to the user portrait to match the color and display image of the target control parameters of the welcome light; identifying the type of music liked in the user's behavior data, and querying the preset database according to the music type to match the color and display image of the target control parameters of the welcome light.

[0047] Among them, the preset database can be set according to actual needs without specific limitation.

[0048] It can be understood that the embodiment of the present application can control the color and display image of the target control parameters of the welcome light according to the user's mood and favorite music type, making the vehicle more intelligent, able to meet the user's personalized needs, and enhance the user's experience.

[0049] In step S103, the vehicle is controlled to welcome guests according to the target control parameters of the welcome light.

[0050] It can be understood that the embodiment of the present application can control the vehicle welcome according to the target control parameters of the welcome light, so that the owner's behavior, environmental status and vehicle status can be analyzed in real time, ensuring that the control of the welcome light always matches the current situation, realizing the personalized customization of the welcome light, and enhancing the user experience.

[0051] According to the vehicle welcome light control method proposed in the embodiment of the present application, the current environmental data, vehicle status data, user facial recognition results and user behavior data are obtained; the environmental data, vehicle status data, user facial recognition results and user behavior data are input into a neural network model, and the neural network model outputs the target control parameters of the welcome light; the vehicle welcome is controlled according to the target control parameters of the welcome light, so that the owner's behavior, environmental status and vehicle status can be analyzed in real time to ensure that the control of the welcome light always matches the current situation, realize the personalized customization of the welcome light, and enhance the user experience.

[0052] The following will be combined Figure 2-Figure 5 The vehicle welcome light control method of the present application is described in detail as follows:

[0053] This application includes two parts: hardware and software. The hardware part mainly includes sensors, controllers, facial recognition systems, car welcome lights and other components, such as Figure 2 As shown in the figure, the overall system consists of 1 car owner, 2 sensor module, 3 facial recognition system, 4 car music software, 5 database, 6 car host system, 7 communication module, 8 cloud server, 9 welcome light module; among them, the sensor and facial recognition system are used to collect data on the owner's behavior, environmental status and vehicle status, and transmit the data to the controller; the controller is responsible for receiving data and calling the trained large model for analysis and processing. According to the output results of the model, the controller controls the switch, brightness, color, image and other parameters of the car welcome light; the software part mainly includes the training and deployment of the large model and the formulation of the control strategy.

[0054] Based on the above software and hardware, this application has a wide range of application scenarios, including but not limited to the following scenarios:

[0055] (1) When the owner approaches the vehicle, the car welcome light automatically lights up and automatically adjusts the brightness according to the ambient brightness to provide a comfortable lighting environment;

[0056] (2) When the owner leaves the vehicle, the car welcome light automatically turns off to save energy;

[0057] (3) At night or in dimly lit environments, the car's welcome lights can automatically switch to high beam mode based on the driver's behavior, improving driving safety;

[0058] (4) In rainy and snowy weather, the car's welcome lights can automatically adjust their brightness according to environmental conditions to improve visibility.

[0059] Based on the above-mentioned software and hardware, the specific implementation process of this application includes: the process of uploading the owner's behavior information to the cloud, the process of the cloud system constructing the owner's behavior data to generate the welcome light process, and the process of the cloud system constructing the owner's behavior data and other data to generate the welcome light data and sending it to the welcome light module, which are as follows:

[0060] like Figure 3 As shown in the figure, the process of uploading the owner's behavior information to the cloud is as follows:

[0061] Step 301 is to collect the recent behavior data of the car owner through sensors, facial recognition systems, car music software, etc.

[0062] In step 302, after the biometric module sends the vehicle owner information to the vehicle host system, the host system converts the vehicle owner information into data in String format, and uploads the vehicle owner behavior information data to the cloud server through the vehicle TBOX module and the HTTP interface.

[0063] Step 303 uses a large model architecture to analyze the owner's data behavior, determine the owner's mood, build a portrait of the owner, and generate the corresponding welcome light image, words, color, etc. by matching with the cloud database.

[0064] Step 304 is a cloud data comparison. If no such image exists, a new image is created. If a current image already exists, the image content is updated.

[0065] like Figure 4 As shown in the figure, the cloud system constructs the welcome light process based on the owner's behavior data, as follows:

[0066] Step 401 is for the cloud to obtain the initial data of the car owner through the interface.

[0067] Step 402 is data on the vehicle owner's approach, departure, environment, weather and other dimensions.

[0068] Step 403 is the process of matching the reported data with the brightness database. The brightness database contains pre-set data, which is a mapping table of environmental data and brightness values. The brightness value range is an integer from 1 to 3, and the default brightness value is 2 (1 is slightly bright, 2 is normal bright, and 3 is the brightest).

[0069] As the owner approaches the vehicle, the sensor reports different data types A, B, and C according to the distance (A is ten meters away, B is within 2 to 10 meters, and C is within 2 meters). The corresponding brightness values ​​in the database are matched to different brightness values ​​1, 2, and 3, and the mapping relationship is A corresponds to 1, B corresponds to 2, and C corresponds to 3. As the owner moves away from the vehicle, the sensor reports different data types C, B, and A according to the distance, and the corresponding brightness values ​​in the database are matched to different brightness values ​​3, 2, and 1.

[0070] The light sensor also uploads corresponding data according to the brightness of the environment. The data types are divided into a, b, and c. a is a dim environment, b is a normal environment, and c is a strong light environment. The mapping relationship is a corresponds to 1, b corresponds to 2, and c corresponds to 3. The sensor has different data types a, b, and c according to the brightness, and the database matches the corresponding brightness values ​​to different brightness values ​​1, 2, and 3.

[0071] In rainy and snowy outdoor conditions, the vehicle body sensor uploads data x, corresponding to a brightness of 3, and in other weather conditions, it transmits data y, corresponding to a brightness of 2.

[0072] The brightness setting value rule prioritizes weather the most, followed by the environment, and then the distance. For example, when it is rainy or snowy outdoors, pass x, the corresponding brightness is 3, and it is assumed that the welcome light starts to turn on at a distance of 15 meters, and the subsequent brightness values ​​will not change. If it is not rainy or snowy outdoors, if it is a strong light environment, then the setting value is 3, and the privacy of distance is not considered. If it is normal brightness, only the distance B and C are considered, and the brightness value corresponding to the distance is greater than the brightness value corresponding to the environment to have a gradual effect. If it is a dim environment, the corresponding brightness value is 1, and the distance parameter takes effect at this time, and the brightness will gradually change with the distance.

[0073] Step 404 is to generate the final brightness value.

[0074] Step 405 is data on the dimensions of the car owner's behavior, mood, etc. The car owner's facial expression data is recognized by the DMS and can be divided into three categories: happy, sad (painful), and expressionless.

[0075] Step 406 is the process of matching the reported data with the image database.

[0076] The database will preset the corresponding dynamic material pictures. For example, the gif picture materials mapped to happiness include happy little people dancing, smiling faces, and scattering flowers. The gif picture materials mapped to sadness (pain) include a dog wagging its tail, a beautiful natural environment, two little people hugging, rainbows and sunshine, etc. The gif picture material mapped to expressionless faces is a car logo. The display items are randomly selected from the corresponding resources according to the mood type.

[0077] The songs that the car owners have recently listened to can be divided into several types of music, such as rock music, pop music, love songs, cartoon songs or other music, and the types of music that the car owners listen to most frequently are collected.

[0078] The database will preset corresponding dynamic material pictures, such as the drummer's fierce beating scenes, or the bassist swaying to the rhythm, waving arms, flames, etc. mapped to rock music; the latest looks or stage performance animations of idols, singers or band members, waving light sticks, wonderful moments or classic actions in pop music MVs, etc. mapped to love songs are seaside sunsets, falling cherry blossoms, starry skies, heart-shaped balloons, heart-shaped fireworks, etc. mapped to anime songs are well-known anime characters, classic battle scenes, adventure journeys, etc. mapped to other music types. Display items are randomly selected from the corresponding resources according to the music type.

[0079] The priority of image generation is expression data first. When a face is recognized as expressionless, the image resources corresponding to the music data will be used.

[0080] Step 407 is the final generated image.

[0081] Step 408 is the data of the holiday and birthday dimensions.

[0082] Step 409 is a process of matching the reported data with the date database resources.

[0083] The database will preset corresponding date materials. For example, for festivals, the Spring Festival will be mapped with fireworks and the text "Happy Spring Festival", the Mid-Autumn Festival will be mapped with the starry sky and the moon and the text "Happy Mid-Autumn Festival", and birthdays will be mapped with a birthday cake picture and the text "Happy Birthday".

[0084] Step 4010 is the final generated image / text.

[0085] Because there are many parameters, the priority of the final generated content of the welcome light is differentiated, following the following generation logic:

[0086] If the day is a holiday or a birthday, the holiday and birthday dimensions will be used first when the car is used for the first time. The pictures generated by the owner's behavior / mood dimensions will not be used. The pictures generated by the owner's behavior / mood dimensions can be used for subsequent uses of the car on the same day, combined with the brightness generated by the owner's approach / leave / environment / weather dimensions.

[0087] If it is not a holiday or birthday, the picture generated by the owner's behavior / mood dimension is used, and the brightness generated by the owner's approach / leave / environment / weather dimension is combined to finally generate the desired effect picture.

[0088] Step 4011 finally generates the welcome light content.

[0089] like Figure 5 As shown in the figure, the cloud system constructs the owner's behavior data and other data to generate the welcome light data and sends it to the welcome light module. The specific process is as follows:

[0090] Step 501 returns the welcome light data through the interface.

[0091] Step 502 is to send the information to the host system through the vehicle-mounted TBOX module.

[0092] Step 503 is that the host system sends the data to the welcome light control module to display the final effect.

[0093] In summary, the present application has a high degree of intelligence: it can analyze the owner's behavior, environmental status and vehicle status in real time, and control the switch, brightness, color, picture and other parameters of the car's welcome lights accordingly to realize intelligent lighting; realize personalized customization: the large model can automatically generate different types of welcome light patterns according to specific holidays and the owner's personal birthday; energy saving and environmental protection: the lighting parameters are adjusted in real time according to the environmental status and the owner's behavior to avoid unnecessary energy waste; improve driving safety: at night or in dimly lit environments, as well as in rainy and snowy weather, the lighting parameters can be automatically adjusted to improve driving safety.

[0094] Next, a welcome light control device for a vehicle according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0095] Figure 6 It is a block diagram of a welcome light control device for a vehicle according to an embodiment of the present application.

[0096] like Figure 6 As shown, the vehicle welcome light control device 10 includes: an acquisition module 100 , an input module 200 and a control module 300 .

[0097] Among them, the acquisition module 100 is used to obtain the current environmental data, vehicle status data, user facial recognition results and user behavior data; the input module 200 is used to input the environmental data, vehicle status data, user facial recognition results and user behavior data into the neural network model, and the neural network model outputs the target control parameters of the welcome light; the control module 300 is used to control the vehicle to welcome guests according to the target control parameters of the welcome light.

[0098] It should be noted that the above explanation of the embodiment of the vehicle welcome light control method is also applicable to the vehicle welcome light control device of this embodiment, which will not be repeated here.

[0099] According to the vehicle welcome light control device proposed in the embodiment of the present application, the current environmental data, vehicle status data, user facial recognition results and user behavior data are obtained; the environmental data, vehicle status data, user facial recognition results and user behavior data are input into the neural network model, and the neural network model outputs the target control parameters of the welcome light; the vehicle welcome is controlled according to the target control parameters of the welcome light, so that the owner's behavior, environmental status and vehicle status can be analyzed in real time to ensure that the control of the welcome light always matches the current situation, realize the personalized customization of the welcome light, and enhance the user experience.

[0100] Figure 7 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0101] A memory 701 , a processor 702 , and a computer program stored in the memory 701 and executable on the processor 702 .

[0102] When the processor 702 executes the program, the vehicle welcome light control method provided in the above embodiment is implemented.

[0103] Furthermore, the vehicle also includes:

[0104] The communication interface 703 is used for communication between the memory 701 and the processor 702 .

[0105] The memory 701 is used to store computer programs that can be executed on the processor 702 .

[0106] The memory 701 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0107] If the memory 701, the processor 702 and the communication interface 703 are implemented independently, the communication interface 703, the memory 701 and the processor 702 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0108] Optionally, in a specific implementation, if the memory 701, the processor 702 and the communication interface 703 are integrated on a chip, the memory 701, the processor 702 and the communication interface 703 can communicate with each other through an internal interface.

[0109] The processor 702 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0110] An embodiment of the present application also provides a computer-readable storage medium having a computer program or instruction stored thereon. When the computer program or instruction is executed by a processor, the vehicle welcome light control method as described above is implemented.

[0111] An embodiment of the present application also provides a computer program product, including a computer program or instructions, characterized in that when the computer program or instructions are executed, the above-mentioned vehicle welcome light control method is implemented.

[0112] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0113] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0114] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0115] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0116] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

Claims

1. A method for controlling a welcome light of a vehicle, characterized in that: The following steps are involved: Obtain current environmental data, vehicle status data, user facial recognition results, and user behavior data; Inputting the environmental data, the vehicle status data, the user face recognition result and the user behavior data into a neural network model, and the neural network model outputs a target control parameter of a welcome light; The vehicle welcoming is controlled according to the target control parameter of the welcome light.

2. The vehicle welcome light control method according to claim 1, characterized in that: The environmental data includes environmental brightness, distance between the user and the vehicle, and weather conditions; the vehicle status data includes door switch information; the user facial recognition result includes the user's mood data; the user behavior data includes the user's favorite music type; the target control parameters include the welcome light switch, light brightness, color, and display image.

3. The vehicle welcome light control method according to claim 2, characterized in that: The processing process of the neural network model includes: Determine the light brightness of the target control parameter of the welcome light according to the environmental data; A switch for determining a target control parameter of a welcome light according to the vehicle status data; The color and display image of the target control parameters of the welcome light are determined according to the user facial recognition result and the user behavior data.

4. The vehicle welcome light control method according to claim 3, characterized in that: The step of determining the light brightness of the target control parameter of the welcome light according to the environmental data includes: Identify the ambient brightness, the distance between the user and the vehicle, and the weather condition information in the ambient data; The light brightness of the target control parameter of the welcome light is determined according to the ambient brightness, the distance between the user and the vehicle, and the weather condition information in the environmental data.

5. The vehicle welcome light control method according to claim 3, characterized in that: The switch for determining the target control parameter of the welcome light according to the vehicle status data comprises: Identifying door switch information in the vehicle status data; If the door is closed at the current moment, the welcome light is turned off; If the vehicle door is open at the current moment, the welcome light is automatically turned on.

6. The vehicle welcome light control method according to claim 3, characterized in that: The step of determining the color and display image of the target control parameter of the welcome light according to the user facial recognition result and the user behavior data includes: If the user's facial recognition shows that he is in a good mood, the preset database is queried according to the user's portrait to match the color and display image of the target control parameters of the welcome light; Identify the favorite music types in the user behavior data, and query the preset database to match the color and display image of the target control parameters of the welcome light according to the music type.

7. A vehicle welcome light control device, characterized in that: include: An acquisition module is used to obtain current environmental data, vehicle status data, user face recognition results, and user behavior data; An input module, used for inputting the environmental data, the vehicle status data, the user face recognition result and the user behavior data into a neural network model, and the neural network model outputs a target control parameter of a welcome light; A control module is used to control the vehicle to welcome guests according to the target control parameters of the welcome light.

8. A vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle welcome light control method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, it is used to implement the vehicle welcome light control method as described in any one of claims 1-6.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed, the vehicle welcome light control method as described in any one of claims 1 to 6 is implemented.

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