Vehicle-mounted light show control method and device, electronic equipment and storage medium

Abstract

The invention provides a vehicle-mounted light show control method and device applied to an intelligent terminal, electronic equipment and a storage medium. According to the embodiment of the invention, an operation control instruction for a vehicle-mounted machine system is obtained, and a vehicle control flow for the operation control instruction is obtained; the vehicle control process can be generated by a generative pre-training model according to an operation control instruction, then a script file executable by the vehicle machine system can be generated according to the vehicle control process, and then the script file is provided for the vehicle machine system, so that the vehicle machine system controls one or more vehicle machine parts to execute the vehicle control process according to the script file. Through the above scheme, the information related to the operation of the plurality of vehicle machine parts of the vehicle can be accurately extracted from the operation control instruction based on the operation control instruction input by the user, and the corresponding vehicle control flow is generated, so that the intelligent and personalized control of the vehicle is realized, and the vehicle use experience of the user is improved.

Description

Technical Field

[0001] The present application relates to the field of automobile technology, and in particular to a control method, device, electronic device and storage medium for a vehicle light show applied to a smart terminal. Background Art

[0002] As the level of automobile electrification, networking and intelligence continues to improve, vehicle users have increasing demands for diversified and personalized human-vehicle interaction scenarios during vehicle use. However, existing human-vehicle interaction technologies are generally limited to certain specific scenarios, performing simple interactions based on specific user instructions, and are unable to integrate the meaning of user instructions for personalized interactions. Summary of the invention

[0003] The embodiments of the present application provide a control method, device, electronic device and storage medium for a vehicle light show applied to a smart terminal to solve one or more of the above-mentioned technical problems.

[0004] In a first aspect, an embodiment of the present application provides a method for controlling a vehicle light show, which is applied to a smart terminal, and the method includes:

[0005] Obtain operation control instructions for the vehicle system;

[0006] Acquire a vehicle control process for the operation control instruction, where the vehicle control process is generated by a generative pre-trained model according to the operation control instruction;

[0007] Generate a script file executable by the vehicle system according to the vehicle control process;

[0008] The script file is provided to the vehicle system so that the vehicle system controls one or more vehicle components to execute the vehicle control process according to the script file.

[0009] In a second aspect, an embodiment of the present application provides a control device for a vehicle-mounted light show, which is applied to a smart terminal, and the device includes:

[0010] An operation control instruction acquisition module is used to acquire operation control instructions for the vehicle computer system;

[0011] A vehicle control process acquisition module, used to acquire a vehicle control process for the operation control instruction, wherein the vehicle control process is generated by a generative pre-trained model according to the operation control instruction;

[0012] A script file generation module, used to generate a script file executable by the vehicle system according to the vehicle control process;

[0013] The vehicle control process execution module is used to provide the script file to the vehicle system, so that the vehicle system controls one or more vehicle components to execute the vehicle control process according to the script file.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor implements any of the above methods when executing the computer program.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the above is implemented.

[0016] Compared with the related art, this application has the following advantages:

[0017] According to the embodiment of the present application, the vehicle control process for the operation control instruction can be obtained by first obtaining the operation control instruction for the vehicle system. The vehicle control process can be generated by the generative pre-trained model according to the operation control instruction, and then a script file executable by the vehicle system can be generated according to the vehicle control process, and then the script file can be provided to the vehicle system so that the vehicle system can control one or more vehicle components to execute the vehicle control process according to the script file. Through the above scheme, based on the operation control instruction input by the user, the information related to the operation of multiple vehicle components of the vehicle can be accurately extracted from the operation control instruction, and the corresponding vehicle control process can be generated to realize intelligent and personalized control of the vehicle and improve the user's car experience.

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments according to the present application and should not be regarded as limiting the scope of the present application.

[0020] Figure 1 A schematic diagram showing a processing flow of an application example of a control solution for a vehicle-mounted light show applied to a smart terminal provided in an embodiment of the present application;

[0021] Figure 2A schematic diagram of a process of generating a vehicle control process using a generative pre-trained model in an application example of a control solution for a vehicle light show applied to a smart terminal provided in an embodiment of the present application is shown;

[0022] Figure 3 A flow chart of a method for controlling a vehicle light show applied to a smart terminal provided in an embodiment of the present application is shown;

[0023] Figure 4 A structural block diagram of a control device for a vehicle light show applied to a smart terminal provided in an embodiment of the present application is shown; and

[0024] Figure 5 A block diagram of an electronic device used to implement an embodiment of the present application is shown. DETAILED DESCRIPTION

[0025] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the concept or scope of the present application. Therefore, the drawings and descriptions are considered to be exemplary in nature and not restrictive.

[0026] To facilitate understanding of the technical solutions of the embodiments of the present application, the following describes the related technologies of the embodiments of the present application. The following related technologies can be combined with the technical solutions of the embodiments of the present application as optional solutions, and they all belong to the protection scope of the embodiments of the present application.

[0027] In a related technology before this application, the way to realize the vehicle light show is to install the corresponding software on the user's personal computer, save the software for making the light show plan to an external device, and then connect the external device to the vehicle system to realize the display of the pre-saved light show plan. It has high system requirements and only has a few specific plans that can be interactive, which is inconvenient to use. In another related technology before this application, only a specific light show plan can be displayed according to the music selected by the user, and it is impossible to make personalized settings according to the user's needs, and it is also impossible to mobilize more vehicle components to join the light show display, and the interactivity is not strong.

[0028] The embodiment of the present application provides a control scheme for an in-vehicle light show applied to an intelligent terminal. In this scheme, based on the operation control instructions input by the user, information related to the operation of multiple vehicle components can be accurately extracted from the operation control instructions, and a corresponding vehicle control process can be generated. Among them, the vehicle control process can be generated by a generative pre-trained model according to the operation control instructions. It can be generated in real time or by calling a pre-stored vehicle control process. The present application does not impose any restrictions on this. The generative pre-trained model can be deployed in the cloud or on the vehicle side. The present application does not impose any restrictions on this. The use of a generative pre-trained model can automatically compile the vehicle control process and generate a script file executable by the vehicle system, and instantly display the in-vehicle light show, allowing the user to control the vehicle in a way of "talking" with the car, so as to achieve intelligent and personalized control of the vehicle and improve the user's car experience.

[0029] Figure 1 A schematic diagram showing a processing flow of an application example of a control solution for a vehicle light show applied to a smart terminal provided in an embodiment of the present application is shown, Figure 1 As shown, the control scheme for the vehicle-mounted light show applied to the smart terminal involved in the embodiment of the present application may include two processes, namely, process A1-A9 "human-computer interaction generates script files through voice or text" and process B1-B5 "script files are sent to the whole vehicle".

[0030] First, the vehicle control process for the operation control instructions can be obtained by obtaining the operation control instructions for the vehicle system, wherein the vehicle control process can be generated by the generative pre-trained model according to the operation control instructions. Figure 1In the process A1-A9, the user can first access the human-computer interaction interface (A1) through a mobile smart terminal, where the smart terminal can be a smart terminal of a vehicle cockpit system, a mobile phone application (APP), a tablet computer (Pad), a personal computer (PC), etc. Then, the user can describe the operation control instructions in the human-computer interaction interface of the smart terminal by inputting voice or text, that is, A2: the user narrates the light show in the form of voice or text, for example, the user inputs the voice "Please help me create a birthday atmosphere". Of course, the content that the user can input in the human-computer interaction interface of the smart terminal includes but is not limited to text, voice, pictures, audio (such as music), video and other types, and this application does not impose any restrictions on this. Next, the human-computer interaction interface can report the received voice or text information to the human-computer interaction interface (H5 HMI) through the mobile gateway (Mobile Gateway), that is, A3: the voice or text information is reported through the gateway, and then the received voice or text information can be voice & text parsed. In the process of speech & text parsing, the human-computer interaction interface can first perform a preliminary analysis of the speech or text (A4), for example, the speech can be converted into text form, and then the text content can be sent to the generative pre-trained model (HiPhi GPT Service), and the generative pre-trained model can further parse the speech or text (A5) to generate a script file corresponding to the operation control instruction, that is, a script file used to represent the vehicle control process in the computer system (A7). Among them, the generative pre-trained model can be a script model that has been pre-trained by a big data model (A6). After the generative pre-trained model generates a vehicle control process in the form of a computer script file corresponding to the operation control instruction, the vehicle control process in the form of a computer script file can be returned to the human-computer interaction interface (A8), and the human-computer interaction interface returns the script file (vehicle control process) to the smart terminal through the mobile gateway (A8). The computer script file is then converted into a vehicle control process that can be viewed by the terminal, and the vehicle control process corresponding to the script file is displayed on the smart terminal (A9).

[0031] The vehicle control process generated according to the operation control instruction input by the user in the intelligent terminal may include one or more of the control sequence, control mode and / or control time of one or more vehicle machine components, and the vehicle control process of the vehicle machine components matching the type of the operation control instruction may be obtained according to the type of the operation control instruction. For example, if the user inputs the voice control instruction "Please help me create a birthday atmosphere", the voice control instruction may be first converted into a text control instruction through the human-computer interaction interface, and then the semantic information in the converted text may be extracted using the generative pre-training model, and the vehicle control process of one or more corresponding vehicle machine components may be matched according to the semantic information, for example, it may be: turn on the front lights and project a cake picture onto the ground; turn on the music and play the Happy Birthday song of Baby Bus once; volume value: 60-80; the range is within the most commonly used volume range of the car outdoors; extract the rhythm of the song, and open the front and rear doors on both sides synchronously according to the rhythm, at each rhythm point, the doors are opened 15 degrees, and opened in sequence, when opened to the maximum angle, at each rhythm point, the doors are closed 15 degrees; repeat in sequence until the song ends.

[0032] Next, the smart terminal can generate a script file executable by the vehicle system according to the vehicle control process. For example, when the confirmation instruction for the vehicle control process input by the user in the smart terminal is obtained, the script file executable by the vehicle system can be generated according to the vehicle control process; or when the modification instruction for the vehicle control process input by the user in the smart terminal is obtained, the script file executable by the vehicle system can be generated according to the modified vehicle control process. For example, continuing with the above example, the user can enter the modification instruction "change the volume value to 50, sing Jay Chou's Sunny Day for me, and don't move the back door" in the smart terminal. After obtaining the modification instruction input by the user, the vehicle control process generated by the generative pre-trained model according to the modified operation control instruction can be obtained. For example, the vehicle control process can be modified as follows: turn on the headlights and project a cake image onto the ground; turn on the music and play Jay Chou's song Sunny Day once; volume value: 50; extract the rhythm points of Sunny Day and open both front doors synchronously according to the rhythm. At each rhythm point, the doors open 15 degrees, and then open in sequence. When opened to the maximum angle, the doors close 15 degrees at each rhythm point; repeat in sequence until the song ends.

[0033] Finally, the intelligent terminal can provide the vehicle system with a script file executable by the vehicle system, so that the vehicle system can control one or more vehicle components to execute the vehicle control process according to the script file. This process can correspond to Figure 1In the process B1-B5, the smart terminal can first send the script file executable by the vehicle system to the vehicle through the mobile gateway (B1), and then the mobile gateway sends the relevant data of sending the script file executable by the vehicle system to the whole vehicle to the Internet of Things / Sensor Gateway (MQTT Gateway) where the vehicle system is located (B3), and then the Internet of Things / Sensor Gateway transmits the above-mentioned relevant data to the vehicle system, so that the whole vehicle receives the script file executable by the vehicle system and executes it (B5). Optionally, after step B1, the script file executable by the vehicle system can be sent to the open cloud computing service (Open Cloud Service) deployed in the cloud or the local vehicle system through the mobile gateway (B2), and the open cloud computing service can store the script file sending record in the corresponding cloud or local storage space (B4: store script file sending record), wherein the corresponding storage space can be in the form of an online database or an offline data warehouse. By storing the script file distribution record, when the smart terminal obtains the same operation control instruction input by the user for the vehicle system again, it can directly call the stored script file from the open cloud computing service. After the user confirms, the script file executable by the vehicle system is sent to the IoT / sensor gateway through the open cloud computing service and then distributed to the whole vehicle (B3) to save computing power. In other words, B1, B3, and B5 in the above process are necessary steps for the vehicle system to execute the executable script file, and B2 and B4 are optional steps. In the actual application process, steps B2 and B4 can be omitted.

[0034] Figure 2 The following is a flow chart showing a process of using a generative pre-trained model to generate a vehicle control process in an application example of a control solution for a vehicle light show applied to a smart terminal provided in an embodiment of the present application. Figure 2As shown, after the intelligent terminal sends the operation control instruction for the vehicle system to the human-machine interaction interface (H5 HMI), the human-machine interaction interface can send the received operation control instruction to different modules in the generative pre-trained model according to the different types of operation control instructions through the interface service capability (Open HMI Service). Among them, the type of operation control instruction may include at least one of voice control instruction, text control instruction, image control instruction, audio control instruction and / or video control instruction, and each control instruction can be parsed by a processing module in the generative pre-trained model for text meaning. Different methods of text meaning parsing are adopted for different types of control instructions. For example, a voice control command can be input into a voice analysis module for voice analysis (NLP Service), first converting the voice into text, then extracting semantic information from the text, and matching the control flow of the corresponding vehicle-mounted components based on the semantic information; a text control command can be input into a text analysis module for text analysis (Text Service), extracting semantic information from the text and then matching the control flow of the corresponding vehicle-mounted components; an image control command can be input into an image analysis module for image analysis (Image Service), extracting vector features from the image control command, matching images pre-stored in a generative pre-trained model based on the vector features, and then matching the control flow of the corresponding vehicle-mounted components based on the image; an audio control command can be input into an audio analysis module for audio analysis (Audio Service), where the audio can be music, and the rhythm information in the audio control command can be extracted, for example, by first extracting the spectrum information in the audio control command, then using discrete Fourier transform or fast Fourier transform to extract the rhythm information of the audio from the spectrum information, and then matching the control flow of the corresponding vehicle-mounted components based on the rhythm information; a video control command can also be input into a video analysis module for video multi-screen synchronization (Video Service), the video contained in the video control instruction is displayed on multiple screens in the vehicle system, wherein the multi-screen synchronization may include one or more of the instrument screen, the central control screen, and / or the auxiliary screen in the vehicle; the vehicle components may include at least one of the doors, windows, lights, vehicle screens, vehicle speakers, steering wheels, air conditioning, suspensions and / or vehicle seats, and the vehicle components may also be considered as any adjustable components in the vehicle.

[0035] After parsing the above-mentioned different types of operation control instructions respectively, the script file service (HiPhi GPT Script file Service) of the generative pre-trained model can be used to integrate the control process of the vehicle components after parsing into a vehicle control process, and generate a script file corresponding to the vehicle control process. Among them, the script file service of the generative pre-trained model can be obtained by pre-training the generative pre-trained model by the script model training (Script file Model training). Furthermore, the script file corresponding to the generated vehicle control process can be uploaded to the human-computer interaction interface (upload script file) through the script file service (Script file Service) through the interface service capability, and the human-computer interaction interface can display the vehicle control process corresponding to the script file to the user of the smart terminal for viewing (information display) through the interface service capability. Accordingly, before providing the above-mentioned control service of the vehicle light show applied to the smart terminal to the user, the configuration information can be synchronized in the interface service capability of the human-computer interaction interface through the cloud message communication protocol and notification function (MQT&HTTP), and the account information can be synchronized in the interface service capability of the human-computer interaction interface through the cloud account service function (Account Service), so as to better provide users with personalized vehicle light show control services.

[0036] The execution subject of the embodiment of the present application may be an application, service, instance, software-based functional module, virtual machine (VM), container or cloud server, etc., or a hardware device (such as a server or terminal device) or hardware chip (such as CPU, GPU, FPGA, NPU, AI acceleration card or DPU) with data processing function. The device for implementing the control scheme of the vehicle light show can be deployed on the computing device of the application party that provides the corresponding service or on the cloud computing platform that provides computing power, storage and network resources. The mode of providing services to the outside world by the cloud computing platform may be IaaS (Infrastructure as a Service), PaaS (Platform as a Service), SaaS (Software as a Service) or DaaS (Data as a Service). Taking the platform providing SaaS software as a service (Software as a Service) as an example, the cloud computing platform can use its own computing resources to provide the training of the generative pre-trained model in the control scheme of the vehicle light show or the functional execution of the control module of the vehicle light show. The specific application architecture can be built according to the service requirements. For example, the platform can provide construction services based on the above model to application parties or individuals who use platform resources, and further call the above model and implement the control functions of online or offline vehicle light shows based on vehicle light show control requests submitted by related clients or servers and other devices.

[0037] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0038] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The several specific embodiments listed can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0039] The present application embodiment provides a method for controlling a vehicle light show applied to a smart terminal, such as Figure 3 The flowchart of a control method 300 of a vehicle light show applied to a smart terminal according to an embodiment of the present application is shown. The method 300 may include:

[0040] In step S301, an operation control instruction for the vehicle system is obtained.

[0041] The acquisition of operation control instructions for the vehicle system involved in the embodiments of the present application may be instructions input by the vehicle user through a smart terminal, such as text, voice, image, audio (such as music), video and other content input through smart terminals such as vehicle cockpit systems, mobile phone applications (APP), tablet computers (Pad), personal computers (PCs), etc. The present application has no restrictions on the type of smart terminals and the type of input operation control instructions. Depending on the type of content input by the user into the smart terminal, the type of operation control instructions can be divided into text control instructions, voice control instructions, image control instructions, audio control instructions or video control instructions. For different types of operation control instructions, they can be parsed in different ways to obtain the vehicle control process of the vehicle components that match the type of operation control instructions, and then the vehicle control processes of all the vehicle components obtained are integrated to form an overall vehicle control process.

[0042] In step S302, a vehicle control process for the operation control instruction is obtained, and the vehicle control process is generated by a generative pre-trained model according to the operation control instruction.

[0043] The generative pre-trained model involved in the embodiments of the present application can be a generative pre-trained model obtained after pre-training artificial intelligence models such as a stable-diffusion network model, an autoregressive network model, and a generative adversarial network model (GANs network model). The present application does not impose any restrictions on the type of generative pre-trained model. The generative pre-trained model can be deployed in the cloud or on the vehicle side, and the present application does not impose any restrictions on this.

[0044] Specifically, a large language model (LLM) can be used to train a language model containing tens of billions (or more) of parameters on a large text corpus, such as GPT-3 (a natural language processing model based on deep learning), PaLM (Pathways Language Model, a large natural language pre-training model), LLaMA (Large Language Model Meta AI, a training language model) and other large prediction models as the basis, and such large language models are trained on large text corpora to obtain a generative pre-trained model that matches the recognition target. During the training process, a Transformer architecture and pre-training objectives (such as Language Modeling) similar to those of a small model can be used to train a large language model on the basis of increasing the model size, training data and computing resources, so that such a large language model acquires capabilities such as contextual learning, instruction following, and step-by-step reasoning. This application does not impose any restrictions on the training method of the generative pre-training model.

[0045] In one possible implementation, the vehicle control process may include one or more of the control sequence, control method and / or control time of one or more vehicle-machine components. The above-mentioned acquisition of the vehicle control process for the operation control instruction may be based on the type of the operation control instruction, and the vehicle control process of the vehicle-machine component matching the type of the operation control instruction is acquired.

[0046] Among them, the control sequence of the vehicle computer components may include the display sequence and closing sequence of the vehicle computer components; the control method may be the action (such as opening and closing), angle (such as the opening and closing angle of the car door), volume (such as the volume of the music played by the speaker), brightness, color, pattern (such as light brightness, color, projected pattern), frequency (such as the opening and closing frequency of the car door), etc. of the vehicle computer components; the control time may be the start time and end time of the vehicle control process, the display time of each vehicle computer component (such as the opening and closing time of the car door), etc.

[0047] According to the type of the operation control instruction, the vehicle control process of the vehicle machine component matching the type of the operation control instruction is obtained, which may mean that different types of operation control instructions may correspond to controlling different vehicle machine components. Of course, different types of operation control instructions may also correspond to controlling the same vehicle machine component, and the present application does not impose any restrictions on this. For example, the type of the operation control instruction may include at least one of a text control instruction, a voice control instruction, an image control instruction, an audio control instruction, and / or a video control instruction. Among them, text control instructions can correspond to controlling the intelligent interactive lights (ISD, Intelligent Signal Display), digital headlights (DLP, Digital Light Processing) and / or multiple screens in the vehicle, such as the instrument screen, central control screen, sub-screen, etc. in the vehicle; voice control instructions can correspond to controlling the doors, windows, lights, vehicle screens, vehicle speakers, steering wheels, air conditioners, suspensions and / or vehicle seats in the vehicle; image control instructions can correspond to controlling the intelligent interactive lights in the vehicle (for example, projecting an image on the ground), digital headlights and / or screens in the vehicle; audio control instructions can correspond to controlling the lights, windows, ambient lights, doors, vehicle speakers, steering wheels and / or vehicle seats in the vehicle; video control instructions can correspond to controlling the digital headlights in the vehicle and / or multiple screens in the vehicle.

[0048] Based on the control methods for different vehicle components, the linkage control scenarios of vehicle components used for the vehicle light show can be standardized and abstracted to create linkage control rules for vehicle components for training. This linkage control rule can include linkage trigger conditions and control instruction sequences. The control instruction sequence can include one or more control instructions. The control instructions are used to instruct or notify the controlled components or intelligent terminals of the vehicle to complete corresponding actions. Each control instruction can correspond to an atomic function of the controlled components or intelligent terminals of the vehicle. This atomic function can be a functional module of the smallest unit of the vehicle. For example, for the air conditioner in the car, its opening, closing, adjusting the temperature, and adjusting the wind speed can all be atomic functions. "Turn on the air conditioner in the car to 24 degrees Celsius" can include at least two atomic functions: turning on the air conditioner and adjusting the temperature. In order to achieve refined control of different types of vehicle components, the atomic functions of different types of vehicle components can be encapsulated into a unified state and operation interface for the vehicle system to call, so as to control the vehicle to execute the vehicle control process. Specifically, the atomic rule information can be filled into a pre-set rule template, and the atomic rule information can be arranged and processed according to the rule template to obtain atomic rule information suitable for the input specification of the large language model, and the atomic rule information can be input into the large language model to obtain the vehicle control process.

[0049] In a possible implementation, the generative pre-trained model can generate a vehicle control process through the following steps: first, the text meaning of the operation control instruction can be parsed, and then the vehicle control process for one or more vehicle components can be generated according to the parsed text meaning. The one or more vehicle components can include at least one of a vehicle door, a vehicle window, a vehicle light, a vehicle screen, a vehicle speaker, a steering wheel, an air conditioner, a suspension, and / or a vehicle seat.

[0050] In the embodiment of the present application, before training the generative pre-training model, a rule database can be constructed based on elements such as vehicle components. The vehicle components, the operation control instructions (such as keywords, music, etc.) that the user may input into the generative pre-training model, and the semantic information that the generative pre-training model may extract from the operator control instructions input by the user can be pre-encoded as vectors, and the above materials are vector modeled using a large language model and a database is established so that the large language model "learns" the knowledge in this field. The process of the large language model receiving the semantic recognition results and searching for similar results in the rule database is the process of the large language model using the learned knowledge to deal with new problems. Correspondingly, the linkage control rules of the vehicle components that can be obtained based on the above materials can also be pre-stored in the rule database. Such linkage control rules can be standardized descriptions of vehicle functions that are designed in advance by professionals and determined based on the official configuration files or user manuals of vehicles or smart terminals provided by manufacturers. The terms are relatively standardized and unified, and can include all the atomic functions supported by the product. Therefore, they can be used as a sample source of the rule database for matching with the operation control instructions input by the user.

[0051] In the constructed rule database, the trigger conditions and control instructions of the atomized vehicle components in non-natural language form can be stored, which can be the trigger conditions and control instructions of the vehicle components expressed in vector form. Specifically, the linkage control rules in natural language form can be segmented and encoded into vectors through vector feature extraction using a neural network model, and then stored in the rule database. Through the above-mentioned pre-designed relevant knowledge in the field of vehicle control, the generative pre-training model can extract vector features from the above-mentioned knowledge, elements or materials, obtain atomized rule information and store it in the rule database, and then match the operation control instructions input by the user with the data pre-stored in the rule database, that is, the unique knowledge in this field "learned" by the large language model, and then generate a vehicle control process that matches the user's vehicle control instructions. For example, the cosine similarity between the text vector corresponding to the semantic recognition result of the operation control instruction input by the generative pre-trained model and the text vector of the atomized linkage trigger conditions and control instructions in the rule database can be calculated respectively, and the atomized linkage trigger conditions and control instructions corresponding to the text vector in the standard rule library with the highest cosine similarity with the text vector corresponding to the semantic recognition result are determined as the atomized rule information matching the semantic recognition result. The atomized rule information can essentially be consistent with the content to be expressed by the vehicle control instruction input by the user, and can include multiple vectors, each of which can be used to represent the atomized linkage trigger condition or control instruction.

[0052] Correspondingly, the atomic elements that can be stored in the rule database may include: Element 1: the atomic capabilities of different parts of the whole vehicle after disassembly. The vehicle components corresponding to these atomic capabilities can be considered as any adjustable parts in the car, including but not limited to doors, windows, lights, large screens in the cockpit, speakers, ambient lights, robotic arms, smart interactive lights, digital headlights, steering wheels, seats, air conditioning, suspension, etc.; Element 2: the material service engine for different types of input vehicle control instructions, which may include text, audio, pictures, videos, etc. For audio files, the rhythm, drum beats, relative time, etc. of popular song libraries can be pre-extracted to make the different parts of the whole vehicle Atomic capabilities can execute vehicle control processes based on rhythmic drum beats and relative time; Element 3: a word segmentation library, which can be a word segmentation library for pre-speech decomposition and recognition classification of human natural language. For example, the classification types can include "human", "festival", "science fiction", "fashion" and other types, and the vocabulary included in each type can be: "Human" can include gender, age, city, place of origin, etc.; "Festival" can include birthdays, international festivals, domestic festivals, anniversaries, etc.; "Science fiction" can include "universe", "quantum", "Ultraman", etc.; "Fashion" can include "games", "football", "auto shows", etc., and this application does not impose any restrictions on this. The above-mentioned different types of atomic elements can be combined into different atomic rule information. When training the generative pre-training model, different atomic rule information is used for training (for example, input a specific scene + atomic rule information composed of element 1 + element 2 + element 3), and then output the execution command according to the input target, prompt word (Prompt) and fine-tuning of the model parameters. Among them, the prompt word is input into the model because the prompt word is clear, specific and can provide sufficient contextual information or background information. The prompt word can be used to guide the generative pre-trained model to generate a text segment of natural language text to produce a vehicle control process that meets the expectations. Finally, if the training accuracy of the model is higher than 60%, the model training can be considered complete.

[0053] The way to disassemble the atomic capabilities of different parts of the whole vehicle can be to combine the vehicle machine parts with their adjustable ranges, etc., to form the atomic capabilities of the vehicle machine parts after disassembly. For example, for the "right rear window" in the vehicle machine parts, when disassembling the atomic capabilities, we can consider the adjustment range of the rear right window position, what the different optional adjustment gears in the adjustment range represent, and what the interval selection span is, and then disassemble the atomic capabilities. The atomic capabilities of the "right rear window" in the vehicle machine parts obtained after disassembly can be: the adjustment range of the "right rear window" is between 0 and 100; the adjustment gear 0 represents that the rear right window is completely closed, the adjustment gear 100 represents that the rear right window is fully opened, and the adjustment gear from 0 to 100 represents the process of the window from closing to opening; the interval selection span is 10.

[0054] In some embodiments, the types of operation control instructions may include at least one of text control instructions, voice control instructions, image control instructions and / or audio control instructions. The method of parsing the text meaning of the operation control instructions can be by extracting semantic information from the text control instructions and matching the control flow of one or more corresponding vehicle-machine components according to the semantic information, wherein the text control instructions can be converted from voice control instructions or directly obtained through an intelligent terminal; or by extracting vector features from image control instructions, matching images pre-stored in a generative pre-trained model according to the vector features, and matching the control flow of one or more corresponding vehicle-machine components based on the pre-stored images; and also by extracting rhythm information from audio control instructions and matching the control flow of one or more corresponding vehicle-machine components according to the rhythm information.

[0055] In the process of executing the above-mentioned text parsing, the process of the above-mentioned text meaning parsing can be executed in parallel or in series, and the present application does not impose any restrictions on this. The parsing can be performed through the cloud or on the vehicle side, and the present application does not impose any restrictions on this. For different types of operation control instructions, the method used to parse the operation control instructions can be determined according to the type of one or more operation control instructions input by the user, and the present application does not impose any restrictions on this. For example, if the user only inputs text control instructions and voice control instructions, the operation control instructions can be parsed only by extracting the semantic information in the text control instructions. For another example, if the user inputs voice control instructions and image control instructions, the text control instructions converted from the voice control instructions are used to extract the semantic information therein; for the image control instructions, the vector features in the image are extracted. Furthermore, according to the data obtained by extracting the text semantic information and extracting the image vector features, the control process of the corresponding one or more vehicle components is matched, and the vehicle control processes obtained by the two methods are integrated and output.

[0056] In the embodiment of the present application, the voice control instructions are converted into text control instructions by using speech recognition technologies such as Automatic Speech Recognition (ASR) to convert the voice control instructions into corresponding text data (text control instructions), and then input them into a neural network model for semantic recognition. Automatic speech recognition technology can convert the vocabulary content in human speech into computer-readable input, such as keys, binary codes, or character sequences. Automatic speech recognition only converts voice data into corresponding text, and does not involve semantic changes. Therefore, the voice control instructions converted into text can be parsed in text form. Optionally, the user's smart terminal or the vehicle control system in the vehicle can upload the voice control instructions input by the user to the cloud server, and the cloud server inputs the received voice data into the neural network model to obtain the semantic recognition results corresponding to the voice data.

[0057] The method of extracting semantic information from text control instructions can use NLU (Natural Language Understanding) neural network model for semantic recognition. NLU is a general term for all methods, models or tasks that support machine understanding of text content, which enables computer systems to read user input information, understand text, language and extract information to help perform downstream tasks such as text classification, grammatical analysis and information search. In the field of artificial intelligence NLU, a commonly used semantic recognition method is to classify based on domain (Domain)-intent (Intent), which can pre-divide multiple domains and intent categories, and domains and different intents can be orthogonal. For example, the instruction "Please help me turn on the air conditioner in the car" can be classified into the "air conditioning" domain and further classified into the intent category of "turn on the car air conditioning"; while "Please help me turn on the air conditioner at home in advance" still belongs to the "air conditioning" domain, but the intent is completely different, involving the control of the air conditioner at home.

[0058] The method involved in extracting vector features in image control instructions and matching images pre-stored in the generative pre-trained model according to vector features can be to extract feature points in the picture uploaded by the user, such as animal color, size, position, etc., vectorize these feature points, and then perform vectorized similarity search from the image library of the generative pre-trained model to find pictures with features with relatively high similarity.

[0059] In one embodiment, the rhythm information extracted from the audio control instruction may be extracted by first extracting spectrum information from the audio control instruction, and then extracting the rhythm information from the spectrum information using discrete Fourier transform or fast Fourier transform.

[0060] Exemplary methods for extracting spectrum information include converting the input audio control instruction into a spectrum graph by wavelet transform and the like, and then extracting high-frequency information or low-frequency information from the spectrum graph as spectrum information; or obtaining the spectrum information of the audio by MFCC (Mel-frequency cepstral coefficients) and / or FBANK (FilterBank) and the like, through pre-emphasis, framing and windowing, Fourier transform, Mel filter, etc. Further, the rhythm information of the audio is extracted from the spectrum information by using discrete Fourier transform or fast Fourier transform.

[0061] Among them, the discrete Fourier transform can sample the spectrum of a time-domain discrete signal in a finite time length at equal intervals, so that the frequency domain function is discretized, which is convenient for computer processing of the signal; the fast Fourier transform is an efficient and fast algorithm of the discrete Fourier transform. Since the discrete Fourier transform has a large amount of computation, the discrete Fourier transform and the fast Fourier transform algorithms can be combined for audio drum beat recognition and rhythm capture.

[0062] When the input vehicle control instructions include audio control instructions, based on the rhythm information extracted from the audio, some vehicle components can be displayed according to the extracted rhythm information in the vehicle control process and execute corresponding commands; the start time of the entire vehicle control process can also be controlled according to the start and end time in the audio rhythm information. This application does not impose any restrictions on the role of the extracted rhythm information in the audio control instructions in this application.

[0063] In addition, before extracting the rhythm information in the audio control instruction, the music rhythm drum beats of the audio can be extracted in advance through the relevant audio language processing library, and the extracted audio and its rhythm information are used as a knowledge base, and stored offline in the cloud or the storage space in the car system where the generative pre-training model in the embodiment of the present application is located. The generative pre-training model can also be used in advance to perform migration training on the music beats of the audio in the relevant audio language processing library, and the drum beats of the music beat data part are marked and identified. When the audio control instruction input by the user through the smart terminal includes the audio in the relevant audio language processing library, the music rhythm drum beats (drum beat information) of the corresponding audio can be produced by combining the "generative pre-training model for music drum beat recognition after transfer learning" with the "generative pre-training model music drum beat knowledge base", and then the control process of one or more corresponding car machine components is matched according to the extracted rhythm information. The rhythm information in this type of audio can be used for sound door linkage, that is, the doors, windows, etc. in the vehicle perform corresponding actions with the rhythm information in the audio.

[0064] In a possible implementation, the type of operation control instruction may further include a video control instruction, and the above-mentioned acquisition of the vehicle control process for the operation control instruction may be to acquire the vehicle control process including the video displayed on multiple screens when the operation control instruction includes the video control instruction. The multiple screens may include one or more of the instrument screen, the central control screen, and / or the secondary screen in the vehicle.

[0065] That is to say, when the operation control instruction includes a video control instruction, one or several screens in the vehicle can be controlled to play the video simultaneously. These screens can be of the same type, for example, three instrument screens in the vehicle play the video included in the video control instruction simultaneously; they can also be of different types, for example, one instrument screen and one sub-screen in the vehicle play the video included in the video control instruction simultaneously; or they can be all screens in the vehicle, for example, all instrument screens, the central control screen and the sub-screen play the video included in the video control instruction simultaneously, and this application does not impose any restrictions on this.

[0066] The above-mentioned vehicle control process for playing videos on multiple screens at the same time can be combined into the same process with the vehicle control process of the vehicle computer components corresponding to other types of operation control instructions, or it can be divided into different processes for display (for example, the end time of the two processes is different). This application does not impose any restrictions on this.

[0067] Optionally, in the above process, the input operation control instructions, whether they are text control instructions, voice control instructions, image control instructions, audio control instructions or video control instructions, can be generated into a script file in JSON format after the text meaning is parsed by the generative pre-trained model, so as to facilitate data transmission between the Web application and the server.

[0068] In step S303, a script file executable by the vehicle system is generated according to the vehicle control process.

[0069] In the embodiment of the present application, the vehicle control process generated by the generative pre-trained model can be a script file in JSON format; generating a script file executable by the vehicle system according to the vehicle control process can be inputting the vehicle control process in JSON format into a script parser for script parsing to obtain the parsed script file executable by the vehicle system.

[0070] JSON files are files of simple data structures and objects stored in JavaScript Object Notation (JSON) format. They are standard data exchange formats and are mainly used to transfer data between Web applications and servers. JSON files are lightweight, text-based, human-readable files that can be edited using a text editor. In an embodiment of the present application, the generative pre-trained model can output a script file in JSON format based on the input atomized rule information, in which the trigger conditions, start nodes, end nodes, and control instruction sequences of the vehicle control process (which may include the contents of each vehicle control instruction and the sequential relationship between them) can be recorded. The output format of the generative pre-trained model can be limited in advance so that it outputs a JSON format script file, which is easy for developers to understand and process, and it is also easy to convert the JSON format script file into a file format that matches the data protocol of the rule execution component responsible for executing the linkage control rule.

[0071] The generated JSON format script file can also be input into the script parser to obtain a parsed script file that can be executed by the vehicle system. Although the JSON format script file is suitable for data transmission between servers, systems and devices, it is not an executable file itself. Therefore, it is necessary to parse the JSON format script file into a script file format executable by the vehicle system, such as an XML format script file, through a script parser. The XML format script file can match the data protocol of the vehicle's rule execution component, so that the rule execution component can notify the vehicle or smart terminal to execute the corresponding vehicle control process after detecting that the vehicle status meets the corresponding linkage trigger condition.

[0072] In addition, the generated vehicle control process can also be stored in the cloud so that the vehicle-side engine can call it when it is connected to the Internet. The newly created vehicle control process can be further processed and stored in the aforementioned rule database to enrich the corpus data that can be used by the large language model. For example, the cloud server can send the generated vehicle control process to the vehicle-side scenario engine (such as an open cloud computing service deployed in the cloud or the local vehicle system) for storing the vehicle control process. When the rule execution component in the vehicle detects again that the same vehicle control instruction meets the triggering conditions of the vehicle control process, it can send instructions to the vehicle controlled components recorded in the pre-stored vehicle control process to enable them to complete the corresponding actions.

[0073] In a possible implementation, before the vehicle control process is generated according to the vehicle control process, the vehicle control process can be displayed based on the smart terminal. There are two cases in which the vehicle control process generates a script file executable by the vehicle system: the first case is that when a confirmation instruction for the vehicle control process is obtained, the vehicle control system generates a script file executable by the vehicle system according to the vehicle control process; the second case is that when a modification instruction for the vehicle control process is obtained, the vehicle control system generates a script file executable by the vehicle system according to the modified vehicle control process.

[0074] For example, after the user inputs the voice control command "Please help me create a birthday atmosphere" on the smart terminal, the generative pre-trained model extracts the semantic information in the command "Please help me create a birthday atmosphere" to generate the initial vehicle control process, which can be: turn on the front lights and project a cake picture onto the ground; turn on the music and play the Happy Birthday song of Baby Bus once; volume value: 60-80; the range is within the most commonly used volume range for cars outdoors; extract the rhythm of the song, and open the front and rear doors on both sides synchronously according to the rhythm. At each rhythm point, the doors are opened 15 degrees, and opened in sequence. When opened to the maximum angle, the doors are closed 15 degrees at each rhythm point; repeat in sequence until the song ends. The above initial vehicle control process can be displayed to the user based on the smart terminal. If the user clicks the "Confirm" button on the smart terminal (or confirms the initial vehicle control process in other forms), the smart terminal can obtain the confirmation instruction for the vehicle control process, and then generate a script file executable by the vehicle system according to the vehicle control process and send it to the vehicle system for execution.

[0075] However, if the user needs to modify the above initial vehicle control process, he can click the "Modify" button on the smart terminal (or use other forms to modify the initial vehicle control process), and can further enter the modification command, such as "change the volume value to 50, sing Jay Chou's Sunny Day for me, and don't move the back door", then when the modification command for the vehicle control process is obtained, the smart terminal can send the modification command to the generative pre-trained model through the gateway again, and the generative pre-trained model can extract the semantic information in the modification command again, and regenerate the modified vehicle control process, for example: turn on the front lights and project the cake picture to the ground; turn on the music and play Jay Chou's song Sunny Day once; volume value: 50; extract the rhythm point of Sunny Day, and open the front doors on both sides synchronously according to the rhythm. At each rhythm point, the doors are opened 15 degrees, and opened in sequence. When opened to the maximum angle, the doors are closed 15 degrees at each rhythm point; repeat in sequence until the song ends. The above modified vehicle control process can also be displayed to the user based on the smart terminal. If the user clicks the "Confirm" button on the smart terminal (or confirms the initial vehicle control process in other ways), the smart terminal can obtain the confirmation instruction for the modified vehicle control process, and then generate a script file executable by the vehicle system according to the modified vehicle control process and send it to the vehicle system for execution. Optionally, before the user confirms, if the user replies "Cancel" on the smart terminal, the control operation of the above-mentioned vehicle light show ends; if the user replies "Execute or Confirm" on the smart terminal, the operation can continue.

[0076] In some embodiments, when modification information for a vehicle control process is obtained, a script file executable by the vehicle system is generated according to the modified vehicle control process, by first obtaining a modification instruction for the vehicle control process, then obtaining a modified vehicle control process generated based on the modification instruction, and finally generating a script file executable by the vehicle system according to the modified vehicle control process. The modified vehicle control process can be generated by a generative pre-trained model according to the modification instruction.

[0077] In step S304, the script file is provided to the vehicle system, so that the vehicle system controls one or more vehicle components to execute the vehicle control process according to the script file.

[0078] The script file may be provided to the vehicle system through a gateway, such as a mobile gateway or an IoT / sensor gateway (MQTT Gateway) for execution by the vehicle system; or it may not be provided through a gateway, such as directly calling a script file stored in the local storage space of the vehicle system. Such script files may be script files generated by previously executing the same vehicle control instructions. The vehicle system may execute the same vehicle control process as before for the same vehicle control instructions based on such pre-generated script files. This application does not impose any restrictions on the manner in which the script file is provided to the vehicle system.

[0079] Corresponding to the above examples and method embodiments provided in the embodiments of the present application, the embodiments of the present application also provide a control device for a vehicle light show applied to a smart terminal. Figure 4 The structure block diagram of a control device 400 for a vehicle light show applied to a smart terminal according to an embodiment of the present application is shown. The device 400 may include:

[0080] The operation control instruction acquisition module 401 is used to acquire the operation control instruction for the vehicle system;

[0081] A vehicle control process acquisition module 402 is used to acquire a vehicle control process for the operation control instruction, wherein the vehicle control process is generated by a generative pre-trained model according to the operation control instruction;

[0082] A script file generating module 403, used to generate a script file executable by the vehicle system according to the vehicle control process;

[0083] The vehicle control process execution module 404 is used to provide the script file to the vehicle system, so that the vehicle system controls one or more vehicle components to execute the vehicle control process according to the script file.

[0084] In a possible implementation, before generating a script file executable by a vehicle system according to the vehicle control process, the apparatus may further include:

[0085] A vehicle control process display module, used to display the vehicle control process based on the smart terminal;

[0086] The script file generation module 403 may include:

[0087] A script file generation submodule under confirmation instruction, used to generate a script file executable by the vehicle system according to the vehicle control process when a confirmation instruction for the vehicle control process is obtained;

[0088] The script file generation submodule under the modification instruction is used to generate a script file executable by the vehicle system according to the modified vehicle control process when the modification instruction for the vehicle control process is obtained.

[0089] In some implementations, the script file generation submodule under the modification instruction may include:

[0090] A modification instruction acquisition unit, used to acquire a modification instruction for the vehicle control process;

[0091] A modified vehicle control process generating unit, used for obtaining a modified vehicle control process generated based on the modification instruction, wherein the modified vehicle control process is generated by a generative pre-trained model according to the modification instruction;

[0092] The script file generating unit is used to generate a script file executable by the vehicle system according to the modified vehicle control process.

[0093] In a possible implementation, the vehicle control process acquisition module 402 may include:

[0094] A text meaning parsing submodule, used for parsing the text meaning of the operation control instruction;

[0095] The vehicle control process generation submodule is used to generate a vehicle control process for one or more vehicle components according to the parsed text meaning, and the one or more vehicle components include at least one of vehicle doors, windows, lights, vehicle screens, vehicle speakers, steering wheels, air conditioners, suspensions and / or vehicle seats.

[0096] In some implementations, the type of the operation control instruction includes at least one of a text control instruction, a voice control instruction, an image control instruction and / or an audio control instruction, and the text meaning parsing submodule may include:

[0097] A text semantic information parsing unit, used to extract semantic information from the text control instruction, and match the control flow of one or more corresponding vehicle components according to the semantic information, wherein the text control instruction is obtained by converting the text control instruction or directly obtained through the intelligent terminal;

[0098] An image semantic information parsing unit, configured to extract vector features from the image control instruction, match images pre-stored in the generative pre-trained model according to the vector features, and match control processes of one or more corresponding vehicle components based on the pre-stored images;

[0099] The audio semantic information parsing unit is used to extract the rhythm information in the audio control instruction and match the control flow of one or more corresponding vehicle machine components according to the rhythm information.

[0100] In a possible implementation, the type of the operation control instruction includes a video control instruction, and the vehicle control process acquisition module 402 may include:

[0101] The video vehicle control process acquisition submodule is used to obtain the vehicle control process including the video displayed on multiple screens when the operation control instruction includes a video control instruction. The multiple screens include one or more of the instrument screen, central control screen, and / or auxiliary screen in the vehicle.

[0102] In some embodiments, the audio semantic information parsing unit may include:

[0103] A spectrum information extraction subunit, used to extract spectrum information in the audio control instruction;

[0104] The rhythm information extraction subunit is used to extract the rhythm information from the frequency spectrum information by using discrete Fourier transform or fast Fourier transform.

[0105] In a possible implementation, the vehicle control process includes one or more of a control sequence, a control method and / or a control time of one or more vehicle components. The vehicle control process acquisition module 402 may include:

[0106] The type vehicle control process acquisition submodule is used to acquire the vehicle control process of the vehicle machine component that matches the type of the operation control instruction according to the type of the operation control instruction.

[0107] The functions of each module in each device in the embodiments of the present application can be found in the corresponding description in the above method, and have corresponding beneficial effects, which will not be repeated here.

[0108] Figure 5 FIG. 1 is a block diagram of an electronic device used to implement an embodiment of the present application. Figure 5 As shown, the electronic device includes: a memory 501 and a processor 502. The memory 501 stores a computer program that can be run on the processor 502. When the processor 502 executes the computer program, the method in the above embodiment is implemented. The number of the memory 501 and the processor 502 can be one or more.

[0109] The electronic device also includes:

[0110] The communication interface 503 is used to communicate with external devices and perform data exchange transmission.

[0111] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the memory 501, the processor 502 and the communication interface 503 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 5 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.

[0112] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0113] An embodiment of the present application provides a computer-readable storage medium storing a computer program, which implements the method provided in the embodiment of the present application when the program is executed by a processor.

[0114] An embodiment of the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the method provided in any embodiment of the present application is implemented.

[0115] An embodiment of the present application also provides a chip, which includes a processor for calling and executing instructions stored in the memory from the memory, so that a communication device equipped with the chip executes the method provided by the embodiment of the present application.

[0116] An embodiment of the present application also provides a chip, including: an input interface, an output interface, a processor and a memory, wherein the input interface, the output interface, the processor and the memory are connected via an internal connection path, and the processor is used to execute the code in the memory. When the code is executed, the processor is used to execute the method provided in the embodiment of the present application.

[0117] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor supporting the Advanced RISC Machines (ARM) architecture.

[0118] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of exemplary but not limiting description, many forms of RAM are available. For example, static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (DR RAM).

[0119] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0120] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" 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. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0121] 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, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0122] Any process or method described in the flow chart or otherwise described herein can be understood as a module, fragment or portion of a code representing one or more executable instructions for implementing the steps of a specific logical function or process. And the scope of the preferred embodiment of the present application includes other implementations, in which the functions may not be performed in the order shown or discussed, including in a substantially simultaneous manner or in a reverse order according to the functions involved.

[0123] The logic and / or steps described in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, which can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or used in combination with these instruction execution systems, devices or apparatuses.

[0124] It should be understood that the various parts of the present application can be implemented with hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method can be completed by instructing the relevant hardware through a program, which can be stored in a computer-readable storage medium, and when the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0125] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a disk or an optical disk, etc.

[0126] The above is only an exemplary embodiment of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope recorded in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for controlling a vehicle light show, applied to a smart terminal, the method comprising: Obtain operation control instructions for the vehicle system; Acquire a vehicle control process for the operation control instruction, where the vehicle control process is generated by a generative pre-trained model according to the operation control instruction; Generate a script file executable by the vehicle system according to the vehicle control process; The script file is provided to the vehicle system so that the vehicle system controls one or more vehicle components to execute the vehicle control process according to the script file.

2. The method according to claim 1, wherein: Before generating a script file executable by a vehicle system according to the vehicle control process, the method further includes: Displaying the vehicle control process based on the smart terminal; The step of generating a script file executable by the vehicle system according to the vehicle control process includes: When a confirmation instruction for the vehicle control process is obtained, a script file executable by the vehicle system is generated according to the vehicle control process; When a modification instruction for the vehicle control process is obtained, a script file executable by the vehicle system is generated according to the modified vehicle control process.

3. The method according to claim 2, wherein: When the modification information for the vehicle control process is obtained, generating a script file executable by the vehicle system according to the modified vehicle control process includes: Obtaining a modification instruction for the vehicle control process; Acquire a modified vehicle control process generated based on the modification instruction, wherein the modified vehicle control process is generated by a generative pre-trained model according to the modification instruction; Generate a script file executable by the vehicle system according to the modified vehicle control process.

4. The method according to claim 1, wherein: The generative pre-trained model generates the vehicle control process through the following steps: Performing textual meaning analysis on the operation control instruction; Based on the parsed text meaning, a vehicle control process is generated for one or more vehicle components, wherein the one or more vehicle components include at least one of vehicle doors, windows, lights, vehicle screens, vehicle speakers, steering wheels, air conditioning, suspensions and / or vehicle seats.

5. The method according to claim 4, wherein: The type of the operation control instruction includes at least one of a text control instruction, a voice control instruction, an image control instruction and / or an audio control instruction, and the text meaning parsing of the operation control instruction includes: Extracting semantic information from the text control instruction, and matching the control flow of one or more corresponding vehicle components according to the semantic information, wherein the text control instruction is obtained by converting the text control instruction or directly obtained through an intelligent terminal; Extracting vector features from the image control instruction, matching images pre-stored in the generative pre-trained model according to the vector features, and matching corresponding control processes of one or more vehicle components based on the pre-stored images; The rhythm information in the audio control instruction is extracted, and the control flow of one or more corresponding vehicle machine components is matched according to the rhythm information.

6. The method according to claim 1, wherein: The type of the operation control instruction includes a video control instruction, and the obtaining of a vehicle control process for the operation control instruction includes: When the operation control instruction includes a video control instruction, a vehicle control process including video displayed on multiple screens is obtained, and the multiple screens include one or more of an instrument screen, a central control screen, and / or a secondary screen in the vehicle.

7. The method according to claim 5, wherein: The extracting the rhythm information in the audio control instruction comprises: Extracting frequency spectrum information in the audio control instruction; The rhythm information is extracted from the frequency spectrum information using discrete Fourier transform or fast Fourier transform.

8. The method according to claim 1, wherein: The vehicle control process includes one or more of a control sequence, a control method and / or a control time of one or more vehicle components, and the vehicle control process for obtaining the operation control instruction includes: According to the type of the operation control instruction, a vehicle control process of a vehicle machine component matching the type of the operation control instruction is obtained.

9. A control device for a vehicle light show, applied to a smart terminal, comprising: An operation control instruction acquisition module is used to acquire operation control instructions for the vehicle computer system; A vehicle control process acquisition module, used to acquire a vehicle control process for the operation control instruction, wherein the vehicle control process is generated by a generative pre-trained model according to the operation control instruction; A script file generation module, used to generate a script file executable by the vehicle system according to the vehicle control process; The vehicle control process execution module is used to provide the script file to the vehicle system, so that the vehicle system controls one or more vehicle components to execute the vehicle control process according to the script file.

10. An electronic device comprising a memory, a processor and a computer program stored in the memory, wherein the processor implements the method according to any one of claims 1 to 8 when executing the computer program.

11. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

Images