Car washing method, recommendation method, vehicle, and wearable device

Abstract

This application discloses a car washing method, a recommendation method, a vehicle, and a wearable device, belonging to the field of vehicle control technology. The car washing method of this application includes: in response to receiving an instruction to start a car washing mode, obtaining the vehicle's location information as a text prompt and the vehicle's external environment information as an image prompt; concatenating the text prompt and the image prompt to obtain an input prompt, wherein the weight of the text prompt is proportional to the positioning accuracy and descriptive clarity of the location information; inputting the input prompt into a large language model to obtain the car wash location type output by the large language model; obtaining car wash settings corresponding to the car wash location type, and setting the vehicle status based on the car wash settings.

Description

Technical Field

[0001] This application relates to the field of vehicle control, and more particularly to a car washing method, a recommended method, a vehicle, and a wearable device. Background Technology

[0002] With the development of car wash equipment and the upgrading of car wash functions, car wash methods have evolved from manual car wash to semi-automatic car wash and then to unmanned car wash.

[0003] The vehicle control system has evolved along with car wash methods, and currently includes controls designed to support unmanned car wash scenarios. However, the system does not consider adaptation to manual or semi-automatic car washes, resulting in a poor user experience. Summary of the Invention

[0004] In a first aspect, embodiments of this application provide a car washing method applied to a vehicle, including:

[0005] In response to receiving a command to start the car wash mode, the vehicle's location information is obtained as a text prompt and the external environment information is obtained as an image prompt;

[0006] The input prompt is obtained by concatenating the text prompt and the image prompt, wherein the weight of the text prompt is proportional to the positioning accuracy and the clarity of the description of the location information;

[0007] The input prompt is fed into a large language model to obtain the type of car wash location where the vehicle is located, as output by the large language model.

[0008] Obtain the car wash settings corresponding to the car wash location type, and set the vehicle status based on the car wash settings.

[0009] In some embodiments, it also includes at least one of the following:

[0010] The location information of the vehicle is determined based on at least one of the vehicle's latitude and longitude information and the location information of the vehicle.

[0011] Information about the vehicle's external environment is obtained using the vehicle's external camera.

[0012] In some embodiments, obtaining the car wash settings corresponding to the car wash location type includes:

[0013] If the car wash location type is determined to be an automatic machine car wash or a self-service manual car wash, then the car wash settings corresponding to the controllable components supported by the car wash location type and the vehicle model are obtained.

[0014] In some embodiments, setting the vehicle status based on the car wash settings includes:

[0015] If the type of car wash is determined to be an automatic car wash, then at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers of the vehicle shall be turned off.

[0016] If the car wash location is determined to be a self-service manual car wash, then the car locking function is disabled, and at least one of the following functions of the vehicle is turned off: rearview mirror, sunroof, windows, trunk, and windshield wipers.

[0017] If the car wash location is determined to be a manual car wash at a car wash shop, then the vehicle's infotainment system settings will be disabled, and at least one of the following functions will be turned off: rearview mirror, sunroof, windows, trunk, and windshield wipers.

[0018] In some embodiments, before setting the vehicle status based on the car wash settings, the method further includes:

[0019] If the type of car wash location is determined to be an automatic machine car wash or a self-service manual car wash, then guidance information matching the car wash machine model of the car wash location where the vehicle is located is obtained;

[0020] The guidance information is played on the vehicle's onboard terminal;

[0021] In response to detecting a shift in the driver's attention during one phase of the guidance information, the device that detected the shift in the driver's attention is identified, and the process of the guidance information and subsequent processes are sent to the device that detected the shift.

[0022] In some embodiments, it also includes:

[0023] If the type of car wash is determined to be manual car wash at a car wash shop, then the historical evaluations of the car wash where the vehicle is located are summarized to obtain the evaluation focus information of the car wash.

[0024] Receive images of the car body before and after a car wash from wearable devices;

[0025] Car wash evaluation information is generated based on at least one of the evaluation focus information and the before-and-after images of the car body.

[0026] Secondly, embodiments of this application provide a method for recommending car wash modes, applied to a wearable device that establishes a communication connection with a vehicle, including:

[0027] In response to receiving a message from the vehicle indicating that the car wash location type is a self-service manual car wash, the user is guided to take a picture of the vehicle's body to obtain an image of the vehicle's body. The car wash location type is obtained by the vehicle based on input prompts into a large language model. The input prompts are obtained by concatenating text prompts and image prompts. The text prompts are the vehicle's location information, and the image prompts are the external environment information. The weight of the text prompts is proportional to the positioning accuracy and descriptive clarity of the location information.

[0028] Based on the vehicle image, a car wash mode is recommended to the wearer.

[0029] In some embodiments, it also includes:

[0030] Determine whether the car wash location is an automatic machine car wash or a self-service manual car wash, and receive guidance information sent by the vehicle;

[0031] Collect status images of the car wash machine and determine the real-time status of the car wash machine based on the status images;

[0032] Based on the guidance information and the real-time status, operation prompts are provided.

[0033] In some embodiments, it also includes:

[0034] Images of the car body area being washed are captured during the car wash process;

[0035] Dirt analysis is performed on the vehicle body area image to obtain dirt analysis results;

[0036] Based on the dirt analysis results, at least one of dirt alerts and cleaning guidance will be provided.

[0037] Thirdly, embodiments of this application provide a vehicle including 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 method described above.

[0038] Fourthly, embodiments of this application provide a wearable device, including 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 method described above.

[0039] Fifthly, embodiments of this application provide a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any of the above descriptions.

[0040] Sixthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the above descriptions. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in this invention or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a schematic flowchart of a car washing method provided in one embodiment of this application.

[0043] Figure 2 This is a schematic diagram of a car wash scenario provided in one embodiment of this application.

[0044] Figure 3 This is a schematic diagram of a car wash scenario provided in one embodiment of this application.

[0045] Figure 4 This is a flowchart illustrating a method for recommending car wash modes according to an embodiment of this application.

[0046] Figure 5 This is a schematic diagram of the structure of a vehicle provided in one embodiment of this application.

[0047] Figure 6 This is a schematic diagram of the structure of a wearable device provided in one embodiment of this application. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0049] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, not limited in number; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0050] With the development of car wash equipment and the upgrading of car wash functions, car wash methods have evolved from manual car wash to semi-automatic car wash and then to unmanned car wash.

[0051] The vehicle control system has also evolved with the development of car wash methods. Currently, there are car wash control items designed to support unmanned car wash scenarios. For example, the vehicle control system can send a command to enter car wash mode to the body control system and the air conditioning system. The body control system controls the windows, sunroof, rearview mirrors and wipers to close, and the air conditioning system controls the air conditioning to turn off, in order to adapt to unmanned car wash scenarios.

[0052] However, car wash control features tailored for unmanned car wash scenarios may not be compatible with manual or semi-automatic car washes, and may even cause problems for their execution. Current in-vehicle systems do not consider adapting to manual or semi-automatic car washes, resulting in a poor user experience.

[0053] To address this, this application provides a car washing method that uses a Large Language Model (LLM) to perceive the type of car wash location where the vehicle is located, and then sets the vehicle status based on the car wash settings corresponding to the type of car wash location. This method can adapt to various car wash scenarios in a targeted manner, thereby optimizing the user experience.

[0054] In some embodiments, the car washing method can be implemented by the vehicle itself, specifically by the vehicle's in-vehicle infotainment system. The in-vehicle infotainment system refers to an onboard terminal, a terminal located inside the vehicle for human-machine interaction, providing various optional functions, such as viewing and controlling vehicle status, scheduling and using vehicle-related services (such as car washing and refueling), and internet-based applications such as social networking and web browsing. Other examples include vehicle location and navigation functions, and multimedia playback functions.

[0055] In some embodiments, wearable devices that establish a communication connection with a vehicle can recommend car wash modes based on the type of car wash location sent by the vehicle and images of the vehicle body captured by the wearable device. Wearable devices can be a general term for devices that are intelligently designed and developed using wearable technology, such as gloves, watches, AR (Augmented Reality) head-mounted displays, VR (Virtual Reality) head-mounted displays, or MR (Mixed Reality) head-mounted displays equipped with far-field communication modules and / or near-field communication modules.

[0056] Figure 1 This is a schematic flowchart illustrating a car washing method provided in one embodiment of this application. Figure 1 As shown, a car washing method is provided, which can be applied to vehicles. The method includes the following steps: step 110, step 120, step 130, and step 140. These method steps are merely one possible implementation of this application.

[0057] Step 110: In response to receiving the instruction to start the car wash mode, obtain the vehicle's location information as a text prompt and the vehicle's external environment information as an image prompt.

[0058] Specifically, when a user is preparing to wash their vehicle, they can input a command to start the car wash mode through human-computer interaction. Here, the form of human-computer interaction can be voice interaction, button interaction, touchscreen interaction, gesture interaction, etc., and this application embodiment does not specifically limit this.

[0059] Accordingly, the vehicle can receive a command to activate the car wash mode. This command is essentially the trigger signal for the vehicle to initiate the car wash mode. After receiving this command, the vehicle can respond by acquiring its location information and external environmental information.

[0060] The vehicle's location information reflects its location. Specifically, the vehicle's location information can be represented as its latitude and longitude, or as the location information of the place where the vehicle is located, such as "XX Car Wash," or the street and address of the XX Car Wash. This application does not specifically limit this information.

[0061] Vehicle external environment information is used to reflect the environment outside the vehicle. Specifically, this external environment information can be represented as an image or video of the external environment, etc., but this application embodiment does not specifically limit this.

[0062] Understandably, vehicle location information reflects the location of the vehicle, from which the type of car wash currently being conducted can be inferred. For example, some locations may offer automated car washes, some may offer self-service manual car washes, and others may offer in-person car washes at a car wash shop. Vehicle location information can be represented in text form, and therefore can be used as input into a large language model to predict the type of car wash the vehicle is in. This text prompt is the text input into the large language model to guide it in determining the type of car wash the vehicle is in.

[0063] Information about the vehicle's external environment reflects its surroundings. Specifically, in the context of preparing to wash the vehicle, this information reflects the environment of the car wash location, allowing for the inference of the type of car wash being washed. This external environment information can be represented as an image, thus serving as an input to a large language model to predict the type of car wash the vehicle is in. This image cue is input into the large language model as an image to guide its judgment of the car wash type.

[0064] For example, Figure 2 This is a schematic diagram of a car wash scenario provided in one embodiment of this application, such as... Figure 2 As shown, cameras can be installed on the exterior of the vehicle. Figure 2 The dotted line in the image represents the camera's field of view. The camera can capture the external environment of the vehicle. For example, if the vehicle is in a car wash, the camera can capture images of the car wash, including signs such as "XX Self-Service Car Wash," as information about the vehicle's external environment.

[0065] Step 120: Concatenate the text prompt and the image prompt to obtain the input prompt, wherein the weight of the text prompt is proportional to the positioning accuracy and descriptive clarity of the location information.

[0066] Specifically, after obtaining the text prompt and the image prompt respectively, these two can be concatenated, and the result can be used as the input prompt. This input prompt is fed into a large language model to guide it in determining the type of car wash the vehicle is in. It can be understood that the resulting input prompt integrates the vehicle's location information (text prompt) and the external environment information (image prompt), comprehensively reflecting relevant information about the car wash from both text and image modalities. This provides rich reference information for predicting the type of car wash the vehicle is in based on a large language model.

[0067] Furthermore, when concatenating text and image prompts, the weights of these two elements can be used. Specifically, the weight of the text prompt is proportional to the positioning accuracy of the location information itself and the clarity of the location description.

[0068] Understandably, the positioning accuracy of location information reflects the fineness of its representation of the vehicle's location. Higher positioning accuracy results in a more detailed representation of the vehicle's location, and thus a stronger reliability of the car wash type determined by location analysis. Therefore, the weight of text prompts can be directly proportional to the positioning accuracy; that is, the higher the positioning accuracy, the higher the weight of text prompts, the larger the proportion of text prompts in the input prompts, and the stronger the reliance on text prompts when inferring the car wash type based on a large language model.

[0069] The clarity of location information description refers to the level of detail, accuracy, and ease of understanding provided when describing the vehicle's location. Higher clarity indicates a more accurate representation of the vehicle's location, leading to greater reliability in determining the type of car wash the vehicle is located based on location information analysis. Therefore, the weight of text prompts is directly proportional to the clarity of location information description; that is, higher clarity results in a higher weight for text prompts, a larger proportion of text prompts in the input prompts, and a stronger reliance on text prompts when inferring the type of car wash the vehicle is located using a large language model.

[0070] Furthermore, the weight of an image prompt can be determined based on the weight of a text prompt. For example, the weight of an image prompt can be expressed as the difference between 1 and the weight of a text prompt.

[0071] By weighting the text and image prompts during concatenation, the resulting input prompts can not only carry both text and image prompts, but also the degree to which each prompt influences the type of car wash location the vehicle is located in the final output of the large language model. This controls the reasoning process of the large language model and optimizes its reasoning performance.

[0072] Step 130: Input the input prompt into a large language model to obtain the type of car wash location where the vehicle is located, as output by the large language model.

[0073] Specifically, after receiving the input prompt, the input prompt can be input into the large language model as a prompt. The large language model infers the type of car wash where the vehicle is located based on the input prompt, thereby obtaining the type of car wash where the vehicle is located output by the large language model.

[0074] Here, the large-scale language model is trained on massive amounts of text data and is capable of understanding and generating human language, including answering questions, translating text, summarizing articles, and creating content. Large-scale language models typically contain billions or even trillions of parameters, using complex neural network structures to capture the statistical regularities and patterns of language. Applying this large-scale language model to the embodiments of this application, guided by input prompts, to infer the type of car wash where the vehicle is located, can significantly improve the efficiency and accuracy of car wash type determination.

[0075] Understandably, the type of car wash location obtained from this, i.e., the type of car wash the vehicle is currently in, can be any of the following: automatic machine car wash, self-service manual car wash, or manual car wash at a car wash shop. Automatic machine car washes cater to unmanned car wash scenarios, while self-service and manual car washes at car wash shops cater to manually operated car wash scenarios. The difference between self-service and manual car washes is that self-service car washes require the car owner to perform the car wash operation themselves, while manual car washes at car wash shops are performed by car wash shop employees.

[0076] Step 140: Obtain the car wash settings corresponding to the car wash location type, and set the vehicle status based on the car wash settings.

[0077] Specifically, since the car washing methods differ across different types of car wash locations, corresponding car wash settings can be pre-configured for each type of car wash location, so that each type of car wash location has corresponding car wash settings that can be specifically adapted to the car wash methods under that type of car wash location.

[0078] Therefore, after obtaining the type of car wash location where the vehicle is located, the corresponding car wash settings can be obtained. Based on the obtained car wash settings corresponding to the car wash type, the vehicle's status can be set accordingly, so that the vehicle after the status settings are set can be more adapted to the car wash operation under the car wash type.

[0079] For example, car wash settings may include status settings for the vehicle's rearview mirrors, sunroof, trunk, windshield wipers, etc. By setting the vehicle status based on the car wash settings, the rearview mirrors, sunroof, trunk, windshield wipers, etc., can be controlled to close.

[0080] In this embodiment, the vehicle's location information and external environment information are used as text prompts and image prompts, respectively. These are then concatenated to obtain an input prompt, which is fed into a large language model to infer the vehicle's car wash location type. This achieves accurate and reliable car wash location type determination and improves the efficiency of such determination. Consequently, car wash settings corresponding to different car wash location types can be set for the vehicle, allowing the vehicle to automatically adapt to the car wash operation under the specified location type after the settings are configured. This enhances the vehicle's intelligence in car wash scenarios and optimizes the user experience.

[0081] It should be noted that each implementation method of this application can be freely combined, rearranged, or executed individually, and does not need to rely on or depend on a fixed execution order.

[0082] In some embodiments, the above car washing method further includes:

[0083] The location information of the vehicle is determined based on at least one of the vehicle's latitude and longitude information and the location information of the vehicle.

[0084] Specifically, the vehicle's location information can be determined based on at least one of the vehicle's latitude and longitude information and the location information of the vehicle.

[0085] The vehicle's latitude and longitude information is obtained through the Global Positioning System (GPS) or other similar satellite positioning technologies. This information directly provides the vehicle's precise location on the Earth's surface. Latitude and longitude are typically expressed in degrees (°), minutes ('), and seconds (").

[0086] Location information refers to the specific location or area where the vehicle is currently located, such as "XX Car Wash in City A" or "CC Self-Service Car Wash Center in City B". Location information is usually obtained through at least one of the following technologies: map matching, Wi-Fi positioning, Bluetooth beacon, mobile network base station positioning, or it can be obtained through user input (such as manually selecting a location).

[0087] After obtaining the vehicle's latitude and longitude information or the vehicle's location information, the vehicle's latitude and longitude information or the vehicle's location information can be directly used as the vehicle's location information; or, if both the vehicle's latitude and longitude information and the vehicle's location information are obtained, these two can be combined to obtain accurate vehicle location information obtained through multi-source positioning.

[0088] In some embodiments, the above car washing method further includes:

[0089] Information about the vehicle's external environment is obtained using the vehicle's external camera.

[0090] Specifically, the vehicle's external cameras are mainly used to capture visual information about the vehicle's surroundings. The visual information collected is crucial for the vehicle's environmental perception, path planning, obstacle detection, and safe driving.

[0091] An external camera can capture optical images of the area around a vehicle. Specifically, when preparing to wash a vehicle, the optical images captured by the external camera can contain environmental information about the car wash location, such as the model of the car wash machine. The acquired optical images can then be used as external environmental information to assist a large language model in determining the type of car wash location where the vehicle is located.

[0092] In some embodiments, step 140, obtaining the car wash settings corresponding to the car wash location type, includes:

[0093] If the car wash location type is determined to be an automatic machine car wash or a self-service manual car wash, then the car wash settings corresponding to the controllable components supported by the car wash location type and the vehicle model are obtained.

[0094] Specifically, when determining whether the car wash location is an automatic machine car wash or a self-service manual car wash, the vehicle model also needs to be considered when obtaining the car wash settings corresponding to the car wash location type.

[0095] It is understandable that different vehicle models may support different controllable components. For example, some vehicle models support automatic opening and closing of the rearview mirrors, while others do not.

[0096] Therefore, when retrieving car wash settings corresponding to a car wash location type, it is necessary to consider not only which components the car wash location type itself needs to control, but also which components the vehicle model actually supports controlling. This results in car wash settings that are both compatible with the car wash location type and that the vehicle itself can control. For example, car wash settings suitable for the vehicle model can be retrieved from a cloud or vehicle-side database.

[0097] In this embodiment, the car wash settings are determined by combining the car wash location type and the vehicle model, which ensures the feasibility of setting the vehicle status based on the car wash settings and enables the vehicle to automatically adapt to the car wash operation under the car wash location type after the vehicle status is set, thereby improving the intelligence of the vehicle in the car wash scenario and optimizing the user experience.

[0098] In some embodiments, step 140, setting the vehicle status based on the car wash settings, includes:

[0099] If the type of car wash is determined to be an automatic car wash, then at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers of the vehicle shall be turned off.

[0100] If the car wash location is determined to be a self-service manual car wash, then the car locking function is disabled, and at least one of the following functions of the vehicle is turned off: rearview mirror, sunroof, windows, trunk, and windshield wipers.

[0101] If the car wash location is determined to be a manual car wash at a car wash shop, then the vehicle's infotainment system settings will be disabled, and at least one of the following functions will be turned off: rearview mirror, sunroof, windows, trunk, and windshield wipers.

[0102] Specifically, when the car wash location is determined to be an automatic car wash, the car wash settings include at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers. After confirming the car wash settings, at least one of the following can be directly controlled to close: rearview mirrors, sunroof, windows, trunk, and windshield wipers. Alternatively, after prompting the user for confirmation, at least one of the following can be controlled to close: rearview mirrors, sunroof, windows, trunk, and windshield wipers. This completes the vehicle status setting for the automatic car wash, ensuring that the vehicle environment after the status setting is suitable for the fully automatic car wash machine used in self-service car washes, preventing scratches on vehicle parts, and avoiding water ingress during the automatic car wash process.

[0103] When the car wash location is determined to be a self-service manual car wash, the car wash settings can include a car locking function, and can also include at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers. After determining the car wash settings, the car locking function can be directly disabled, and at least one of the following functions can be controlled to close: rearview mirrors, sunroof, windows, trunk, and windshield wipers. Alternatively, after prompting the user for confirmation, the car locking function can be disabled, and at least one of the following functions can be controlled to close: rearview mirrors, sunroof, windows, trunk, and windshield wipers. This completes the vehicle status settings for self-service manual car washes, ensuring that the vehicle environment is adapted to the needs of self-service manual car washes, and allowing users to open and close doors, windows, and the trunk at any time during the self-service manual car wash process to retrieve items from the vehicle.

[0104] When the car wash location is determined to be a manual car wash at a car wash shop, the car wash settings can include vehicle infotainment system settings, and at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers. After determining the car wash settings, the vehicle infotainment system settings can be disabled directly, and at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers can be closed. Alternatively, after prompting the user for confirmation, the vehicle infotainment system settings can be disabled, and at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers can be closed. This completes the vehicle status settings for a manual car wash at a car wash shop, ensuring that the vehicle environment is adapted to the needs of a manual car wash and that the vehicle infotainment system settings are not changed during the manual car wash process, thereby protecting the owner's privacy and security.

[0105] In some embodiments, before setting the vehicle status based on the car wash settings in step 140, the method further includes:

[0106] If the type of car wash location is determined to be an automatic machine car wash or a self-service manual car wash, then guidance information matching the car wash machine model of the car wash location where the vehicle is located is obtained;

[0107] The guidance information is played on the vehicle's onboard terminal;

[0108] In response to detecting a shift in the driver's attention during one phase of the guidance information, the device that detected the shift in the driver's attention is identified, and the process of the guidance information and subsequent processes are sent to the device that detected the shift.

[0109] Specifically, when the car wash is an automatic machine, users need to operate the machine to ensure its proper functioning and will settle their payment after use. Similarly, when the car wash is a self-service manual machine, users also need to operate it to ensure its proper functioning and will settle their payment after use.

[0110] In other words, regardless of whether the car wash is an automatic machine or a self-service manual car wash, the user needs to perform a series of operations on the car wash machine. To ensure that the user can use the car wash machine normally, guidance information matching the model of the car wash machine at the car wash location can be obtained. This guidance information is used to guide the user to operate the car wash machine correctly to ensure its normal use. For example, it may include steps for using the car wash machine, and it may also include corresponding troubleshooting steps for different states of the car wash machine. This application embodiment does not specifically limit this.

[0111] After receiving the guidance information, it can be played on the in-vehicle terminal. The in-vehicle terminal referred to here is the vehicle's infotainment system. Playing the guidance information on the in-vehicle terminal can take the form of broadcasting the guidance information via voice, or via video or text, or a combination of video and audio. This application does not specifically limit the specific form of this method.

[0112] It can be explained that the guidance information itself can be understood as a combination of multiple processes. That is, the guidance information itself contains the complete process of operating the car wash machine, which can be divided into multiple processes, corresponding to multiple operation steps. For example, the first process may be to determine the vehicle model (such as sedan, SUV, or more specific brand and model) on the display area of ​​the car wash machine; the second process is to select the car wash mode, such as normal wash or fine wash; the third process is to make further selections on the car wash mode, such as selecting the brand of cleaning agent, foam amount, water pressure, and car wash time; the fourth process may be to start the car wash and scan the QR code to pay.

[0113] During the guidance process, the driver's attention can be detected in real time, and it can be determined whether the driver's attention has shifted. Here, driver attention refers to the attention state of the vehicle user. Driver attention detection can be achieved through in-vehicle cameras. For example, the in-vehicle camera can capture the driver's face in real time, especially the driver's eye movements. By analyzing the driver's eye tracking data, it can be determined whether the driver's gaze has deviated from the in-vehicle terminal, thereby inferring whether the driver's attention has shifted.

[0114] When a shift in the driver's attention is detected, the device that caused this shift can be identified. Here, "device" refers to the electronic device from which the driver's attention is diverted from the in-vehicle terminal. For example, it could be an electronic device that the driver's gaze is directed towards after their eyes have left the in-vehicle terminal. For instance, if the driver is not viewing the in-vehicle guidance information but is instead operating their mobile phone, the mobile phone can be considered the device that caused the shift.

[0115] After the transfer device is determined, a process of the guidance information being played on the vehicle terminal, as well as the subsequent process, can be sent to the transfer device so that the transfer device can continue playing the guidance information from the vehicle terminal. This ensures that users can understand the usage guidance of the car wash machine through the transfer device, so that users can use the car wash machine correctly.

[0116] In some embodiments, the car washing method further includes:

[0117] If the type of car wash is determined to be manual car wash at a car wash shop, then the historical evaluations of the car wash where the vehicle is located are summarized to obtain the evaluation focus information of the car wash.

[0118] Receive images of the car body before and after a car wash from wearable devices;

[0119] Car wash evaluation information is generated based on at least one of the evaluation focus information and the before-and-after images of the car body.

[0120] Specifically, when a car wash is performed manually at a car wash shop, the washing process needs to be inspected and the car wash shop evaluated afterward. This application provides a method for intelligently generating car wash evaluation information, thereby achieving intelligent assessment of the car wash experience.

[0121] When evaluating a car wash, historical reviews of the car wash location can be referenced. Specifically, a large number of historical user reviews of the car wash location can be collected from the internet, for example, by using web scraping to retrieve historical reviews. After obtaining these historical reviews, they can be summarized to extract key evaluation points. Summarizing historical reviews can involve identifying high-frequency words, phrases, or themes, or counting the number of reviews for each category of evaluation indicators, thereby summarizing the positive and negative review rates for each indicator. This embodiment does not specifically limit this approach. The resulting evaluation point information, based on historical reviews, provides information that users should pay attention to. Specifically, it can be information extracted from historical reviews that accurately reflects the general evaluations of the car wash location by historical users. It is understood that this evaluation point information can prompt users to focus on potential problems at the car wash when accepting the car wash experience.

[0122] In addition, when evaluating a car wash, images of the vehicle before and after the wash can be used as a reference. These images can be taken by the user using a wearable device before and after the wash. Understandably, comparing these images provides a clearer picture of the wash's effectiveness.

[0123] Therefore, car wash evaluation information can be generated based on evaluation focus information or before-and-after images of the car body, or a combination of evaluation focus information and before-and-after images. For example, at least one of the evaluation focus information and before-and-after images can be input into a large language model, which will then output the car wash evaluation information. Furthermore, after the large language model outputs the car wash evaluation information, the user can adjust the content of the evaluation information.

[0124] In this embodiment of the invention, car wash evaluation information can be generated based on at least one of the evaluation focus information and before-and-after images of the car body, thereby realizing the intelligent generation of car wash experience evaluation, greatly improving the intelligence level of car wash experience evaluation, and optimizing user experience.

[0125] Figure 3 This is a schematic diagram of a car wash scenario provided in one embodiment of this application. Figure 3 This document provides a car wash scenario that illustrates the car wash process when the car wash location is a self-service manual car wash. Figure 3 This includes the vehicle, the person, and the car wash tools held by the person. The person is the vehicle owner, who wears smart glasses that communicate with the vehicle. In this self-service car wash scenario, the smart glasses worn by the owner can interact with the vehicle, providing guidance for the owner's self-service car wash.

[0126] Figure 4 This is a flowchart illustrating a recommended car wash mode method according to one embodiment of this application. Figure 4 As shown, a recommended method for car wash modes is provided. This method can be applied to wearable devices that have established a communication connection with the vehicle, such as... Figure 3 The smart glasses worn by the car owner are shown. The method includes the following steps: step 410, step 420. The method steps are merely one possible implementation of this application.

[0127] Step 410: In response to receiving information from the vehicle that the car wash location type is self-service manual car wash, guide the wearer to take a picture of the vehicle body to obtain an image of the vehicle body; the car wash location type is the output obtained by the vehicle based on inputting input prompts into a large language model, the input prompts are obtained by splicing text prompts and image prompts, the text prompts are the vehicle's location information, the image prompts are the external environment information, and the weight of the text prompts is proportional to the positioning accuracy and descriptive clarity of the location information.

[0128] Specifically, when preparing to wash a vehicle, the vehicle can obtain its location information and information about the external environment.

[0129] The vehicle's location information reflects its location. Specifically, the vehicle's location information can be represented as its latitude and longitude, or as the location information of the place where the vehicle is located, such as "XX Car Wash," or the street and address of the XX Car Wash. This application does not specifically limit this information.

[0130] Vehicle external environment information is used to reflect the environment outside the vehicle. Specifically, this external environment information can be represented as an image or video of the external environment, etc., but this application embodiment does not specifically limit this.

[0131] Understandably, vehicle location information reflects the location of the vehicle, from which the type of car wash currently being conducted can be inferred. For example, some locations may offer automated car washes, some may offer self-service manual car washes, and others may offer in-person car washes at a car wash shop. Vehicle location information can be represented in text form, and therefore can be used as input into a large language model to predict the type of car wash the vehicle is in. This text prompt is the text input into the large language model to guide it in determining the type of car wash the vehicle is in.

[0132] Information about the vehicle's external environment reflects its surroundings. Specifically, in the context of preparing to wash the vehicle, this information reflects the environment of the car wash location, allowing for the inference of the type of car wash being washed. This external environment information can be represented as an image, thus serving as an input to a large language model to predict the type of car wash the vehicle is in. This image cue is input into the large language model as an image to guide its judgment of the car wash type.

[0133] After receiving both text and image prompts, the vehicle can combine them and use the result as the input prompt. This input prompt is fed into a large language model to guide its determination of the type of car wash the vehicle is in. In essence, the resulting input prompt integrates the vehicle's location information (textual prompt) and the external environment information (image prompt), comprehensively reflecting relevant information about the car wash from both textual and image modalities. This provides rich reference information for predicting the type of car wash the vehicle is in based on a large language model.

[0134] Furthermore, when stitching together text and image prompts, the vehicle can achieve this based on the weights of these two elements. The weight of the text prompt is directly proportional to the positioning accuracy of the location information itself and the clarity of the location description.

[0135] Understandably, the positioning accuracy of location information reflects the fineness of its representation of the vehicle's location. Higher positioning accuracy results in a more detailed representation of the vehicle's location, and thus a stronger reliability of the car wash type determined by location analysis. Therefore, the weight of text prompts can be directly proportional to the positioning accuracy; that is, the higher the positioning accuracy, the higher the weight of text prompts, the larger the proportion of text prompts in the input prompts, and the stronger the reliance on text prompts when inferring the car wash type based on a large language model.

[0136] The clarity of location information description refers to the level of detail, accuracy, and ease of understanding provided when describing the vehicle's location. Higher clarity indicates a more accurate representation of the vehicle's location, leading to greater reliability in determining the type of car wash the vehicle is located based on location information analysis. Therefore, the weight of text prompts is directly proportional to the clarity of location information description; that is, higher clarity results in a higher weight for text prompts, a larger proportion of text prompts in the input prompts, and a stronger reliance on text prompts when inferring the type of car wash the vehicle is located using a large language model.

[0137] Furthermore, the weight of an image prompt can be determined based on the weight of a text prompt. For example, the weight of an image prompt can be expressed as the difference between 1 and the weight of a text prompt.

[0138] By weighting the text and image prompts when concatenating them, the resulting input prompts can not only carry the text and image prompts, but also the degree of influence of each prompt on the type of car wash location the vehicle is in, as output by the final large-scale language model. This controls the reasoning process of the large-scale language model and optimizes its reasoning performance.

[0139] Subsequently, the vehicle can input the input prompt as a prompt into the large language model, which then infers the type of car wash the vehicle is in based on the input prompt, thus obtaining the type of car wash the vehicle is in as output by the large language model.

[0140] Here, the large-scale language model is trained on massive amounts of text data and is capable of understanding and generating human language, including answering questions, translating text, summarizing articles, and creating content. Large-scale language models typically contain billions or even trillions of parameters, using complex neural network structures to capture the statistical regularities and patterns of language. Applying this large-scale language model to the embodiments of this application, guided by input prompts, to infer the type of car wash where the vehicle is located, can significantly improve the efficiency and accuracy of car wash type determination.

[0141] Understandably, the type of car wash location obtained from this, i.e., the type of car wash the vehicle is currently in, can be any of the following: automatic machine car wash, self-service manual car wash, or manual car wash at a car wash shop. Automatic machine car washes cater to unmanned car wash scenarios, while self-service and manual car washes at car wash shops cater to manually operated car wash scenarios. The difference between self-service and manual car washes is that self-service car washes require the car owner to perform the car wash operation themselves, while manual car washes at car wash shops are performed by car wash shop employees.

[0142] If the car wash location is determined to be a self-service car wash, the vehicle can send information indicating that the car wash location is an automatic car wash to the wearable device. Correspondingly, the wearable device can receive this information from the vehicle.

[0143] Upon receiving information that the car wash location is an automatic car wash, the wearable device can respond to the received information by issuing a prompt message and guiding the wearer to take a picture of the vehicle body with the wearable device. In this way, the wearable device obtains an image of the vehicle body before it is washed.

[0144] The wearer here is typically the car owner, i.e., the user washing their vehicle at an automatic car wash. The prompts can be in the form of voice or images to guide the wearer in taking pictures of the car body.

[0145] Step 420: Based on the vehicle image, recommend a car wash mode to the wearer.

[0146] Specifically, the captured images of the vehicle body provide a clear picture of its dirt level. Therefore, a car wash mode can be determined based on these images, and then recommended to the wearer. This car wash mode can be a standard, high-pressure, or foam wash, among others. During the mode determination process, image analysis models can be applied to analyze the vehicle body images, thereby identifying and classifying dirty areas. After determining the type of dirty area in each image, a corresponding car wash mode can be configured for each type of dirty area, thus achieving intelligent car wash mode recommendation.

[0147] In this embodiment, the vehicle's location information and external environment information are used as text prompts and image prompts, respectively. These text and image prompts are then concatenated to obtain an input prompt, which is fed into a large language model to infer the type of car wash location. This achieves accurate and reliable car wash location type determination and improves the efficiency of such determination. When the car wash location is determined to be a self-service manual car wash, intelligent car wash mode recommendations are implemented by collecting vehicle images, further optimizing the user experience.

[0148] In some embodiments, the car washing method further includes:

[0149] Determine whether the car wash location is an automatic machine car wash or a self-service manual car wash, and receive guidance information sent by the vehicle;

[0150] Collect status images of the car wash machine and determine the real-time status of the car wash machine based on the status images;

[0151] Based on the guidance information and the real-time status, operation prompts are provided.

[0152] Specifically, when the car wash is an automatic machine, the user needs to operate the machine to ensure its proper functioning and to settle the payment after use. Similarly, when the car wash is a self-service manual car wash, the user also needs to operate the machine to ensure its proper functioning and to settle the payment after use.

[0153] That is, regardless of whether the car wash is an automatic machine or a self-service manual car wash, the user needs to perform a series of operations on the car wash machine. To ensure that the user can use the car wash machine normally, the vehicle can obtain guidance information matching the model of the car wash machine at the car wash location. This guidance information is used to guide the user to operate the car wash machine correctly to ensure its normal use. For example, it may include steps for using the car wash machine, and it may also include corresponding troubleshooting steps for different states of the car wash machine. This application embodiment does not specifically limit this.

[0154] Therefore, after obtaining the guidance information, the vehicle can send it to the wearable device. Correspondingly, the wearable device can receive the guidance information sent by the vehicle.

[0155] The wearable device itself can capture images of the car wash machine within the car wash area where the vehicle is located, thereby obtaining a status image of the car wash machine. It is understood that this status image reflects the current state of the car wash machine, for example, it could be an image containing the content displayed on the car wash machine's screen. After capturing the status image of the car wash machine, the wearable device can analyze the real-time state of the car wash machine based on the status image. Here, the analysis of the real-time state of the car wash machine can be obtained by image classification of the status image or by OCR (Optical Character Recognition) recognition of the text content in the status image; this application embodiment does not specifically limit this. For example, the real-time state of the car wash machine obtained in this way could be one of the following states: vehicle model selection, car wash mode selection, car wash detail selection, payment, etc.

[0156] After obtaining the real-time status of the car wash machine, this status can be combined with the guidance information received from the vehicle to provide operation prompts, thereby guiding the wearer to operate the car wash machine according to the prompts. Furthermore, the guidance information can be divided into different operation prompts according to different car wash machine statuses. Therefore, after determining the real-time status of the car wash machine, the operation prompts corresponding to the real-time status can be matched from the guidance information and displayed. For example, when the real-time status is vehicle model selection, the operation prompts in the guidance information can guide the wearer to select the model of the vehicle to be washed from the various vehicle models displayed on the car wash machine; as another example, when the real-time status is car wash mode selection, the operation prompts in the guidance information can guide the wearer to select the car wash mode suitable for the degree of dirt on the car body from the various car wash modes displayed on the car wash machine. This application embodiment does not specifically limit this.

[0157] In this embodiment of the application, by combining guidance information with the real-time status of the car wash machine, the wearable device can provide the wearer with timely and reliable operation prompts, thereby guiding the wearer to use the car wash machine correctly.

[0158] In some embodiments, the car washing method further includes:

[0159] Images of the car body area being washed are captured during the car wash process;

[0160] Dirt analysis is performed on the vehicle body area image to obtain dirt analysis results;

[0161] Based on the dirt analysis results, at least one of dirt alerts and cleaning guidance will be provided.

[0162] Specifically, regarding self-service robotic car washes, the wearable device can capture images of the area of ​​the car body being washed while the user is washing the vehicle. It's understood that these images refer to the areas of the car body being cleaned.

[0163] After obtaining the vehicle body area image, dirt analysis can be performed on it to obtain the dirt analysis results. This dirt analysis can be performed by applying an image analysis model to the vehicle body area image, thereby identifying and classifying dirty areas within the image. This image analysis model can be GooLeNet, Vision Transformer, Swin Transformer, etc. From the resulting dirt analysis results, dirty areas in the vehicle body area image can be selected. For example, a bounding box can be generated using the coordinates of the upper left and lower right corners of the dirty area obtained from the image analysis model, and the dirty area can then be selected using this bounding box. Furthermore, in the dirt analysis results, the dirty areas in the vehicle body area image can be classified according to the severity of dirt. For example, the severity of dirt can be classified by an image analysis model. After obtaining the severity of dirt, the severity of dirt can be directly identified, or different colored recognition boxes can be used to reflect different degrees of dirt severity. For example, the severity of dirt can be divided into 1-3 categories, with category 1 being the most severe and category 3 being the least severe. A red recognition box is used for category 1, a yellow recognition box is used for category 2, and a green recognition box is used for category 3. This application embodiment does not specifically limit this.

[0164] After obtaining the dirt analysis results, the wearer can be alerted to dirt based on the results. The dirt alert can be given by displaying an image of the vehicle body area on the wearable device and marking the dirty areas and the degree of dirt in the dirty areas. Alternatively, the wearer can be alerted to focus on cleaning the dirty areas by vibration, sound or other means.

[0165] Furthermore, cleaning guidance can be provided to the wearer based on dirt analysis results. This guidance can be achieved through vibration, sound, and images. Specific guidance content can include cleaning methods for dirty areas, suggested spraying techniques for water or foam guns, appropriate washing angles and pressures, recommended cleaning steps, and spray directions. During cleaning guidance, the wearable device can provide voice instructions on how to handle the current type of stain, displaying the required level of cleaning on the screen and in the glasses. It can also dynamically and intelligently recommend appropriate washing angles and pressures, washing steps, and spray directions based on the water or foam gun spraying patterns of the car wash machine, using voice or images. Through real-time detection, it can provide feedback on the cleaning progress via voice, images, or vibration; for example, it can vibrate to prompt the wearer to clean the next area after cleaning is complete.

[0166] In addition, after cleaning is complete, the wearable device can also prompt the wearer on how to check the cleanliness and how to deal with water stains.

[0167] In this embodiment, by analyzing the dirt on the vehicle body area image, at least one of dirt prompts and cleaning guidance is provided to the wearer, which effectively improves the intelligence level of vehicle washing in the self-service robot car wash scenario and optimizes the user experience.

[0168] In some embodiments, acquiring images of the vehicle body area being washed during the car wash process includes:

[0169] During the car wash process, the wearer's eyes are tracked, and images of the car body area being washed are collected based on the eye tracking results.

[0170] Specifically, during the process of washing a vehicle, the wearable device can track the wearer's eyes. Here, eye tracking, also known as gaze tracking, is a technology that uses sensors (such as infrared devices, image acquisition devices, etc.) on the wearable device to capture and extract eye feature information, measure eye movement, and estimate the direction of gaze or the position of the eye's gaze point.

[0171] During the process of washing a vehicle, the wearer's gaze will focus on the dirty areas of the car body, i.e., the areas on the car body that need to be cleaned. The wearable device can then track the wearer's eyes to pinpoint the area of ​​the car body being cleaned. Based on this eye-tracking result, the wearable device can capture an image of the area of ​​the car body being cleaned.

[0172] In this embodiment, eye-tracking technology is used to acquire images of the vehicle body area, thereby providing a basis for timely dirt alerts and cleaning guidance.

[0173] In some embodiments, a car washing method may include the following steps:

[0174] First, determine the type of car wash the vehicle is at by examining the vehicle itself:

[0175] The vehicle can collect its own location information as text prompts and collect external environmental information as image prompts. The text and image prompts are then input into a large language model, which uses text parsing and recognition technology and image recognition and parsing technology to reason about the text and image prompts, thereby determining the type of car wash location where the vehicle is located. For example, it can be any one of automatic machine car wash, self-service manual car wash, or manual car wash at a car wash shop.

[0176] Based on this, for car washes that are automated, the car wash method can also include the following steps:

[0177] The vehicle can retrieve car wash settings suitable for its model and compatible with the fully automatic car wash machine from a cloud / vehicle database. After prompting the user for confirmation, the car wash settings are executed, which may include linking the closing of the vehicle's rearview mirrors, sunroof, windows, trunk, and automatic wipers. By executing the car wash settings, the vehicle's environment is adapted to the fully automatic car wash machine, ensuring that the vehicle's rearview mirrors, spoiler, and other parts are not scratched.

[0178] In addition, the vehicle can match the car wash machine model from the cloud / vehicle database, obtain the corresponding guidance information suitable for beginners, and display the guidance information through the vehicle system to inform the car owner how to operate the current car wash machine, so as to achieve normal use of the car wash machine. After use, the vehicle system will prompt the car owner to complete the settlement operation.

[0179] Furthermore, the vehicle can detect whether the driver's attention has shifted. If the driver's attention has shifted and the driver does not see the guidance information displayed by the vehicle system, the vehicle can display the remaining guidance information through the driver's smartphone to inform the driver how to operate the car wash machine and enable normal use of the car wash machine. After use, the vehicle system will prompt the driver to complete the payment process.

[0180] Alternatively, the vehicle can match the car wash machine model from a cloud / vehicle database, obtain corresponding beginner-friendly guidance information, and transmit this information to the AR smart glasses worn by the driver. The AR smart glasses then display the guidance information, providing operational prompts for the driver to use the car wash machine. During this process, the AR smart glasses can capture the real-time status of the car wash machine through its camera and overlay corresponding operational guidance and audio prompts from the guidance information. Through real-time operational guidance, the driver is gradually guided to operate the car wash machine and complete the payment upon completion, allowing the driver wearing the AR smart glasses to directly perform the corresponding operations.

[0181] For car washes that are self-service or automated, the washing method may also include the following steps:

[0182] The vehicle can retrieve the appropriate car wash settings from the cloud / vehicle database, matching its model and compatibility with both manual and automatic car washes. After user confirmation, the system will enable actions such as leaving the car unlocked, closing windows, closing the trunk, and turning off the air conditioning. By executing these car wash settings, the vehicle can maintain the ability to open and close doors and windows and vacuum the trunk at any time during self-service car washes.

[0183] Additionally, vehicles can be matched with the car wash machine model through a database to obtain corresponding user guidance information for beginners. This guidance information can then be displayed via the vehicle's infotainment system, mobile phone, or AR smart glasses to instruct the driver on how to operate the car wash machine. The specific method of displaying the guidance information is the same as for automatic car washes, and will not be elaborated upon here.

[0184] Furthermore, car owners can use their smartphones to scan the car body from different angles and locations to assess dirt levels. The phone then intelligently recommends suitable car wash modes (normal, high-pressure, foam). During the wash, the phone is paired with the vehicle's UWB (Ultra Wide Band) sensor, allowing the vehicle to determine if the user is passing through a heavily soiled area. Upon detecting this, the vehicle can control the phone to alert the owner via a sound or vibration, indicating that the area requires cleaning.

[0185] In addition, for car owners wearing AR smart glasses, the glasses can also collect information on the dirt levels of different parts and angles of the car body, intelligently recommending the appropriate car wash mode (normal, high-pressure, foam). During the car wash process, when the AR smart glasses pass over a particularly dirty area, they can also alert the car owner by playing a prompt tone or vibrating to indicate that the current area needs cleaning.

[0186] In the process of judging and analyzing dirt based on the real-time framing function of AR smart glasses, AR smart glasses can capture the current image (such as any one of the left side of the car, right side of the car, rear of the car, front hood of the car, and top of the car) through the camera when the wearer is washing the vehicle. The image analysis model can be used to classify the current image, thereby realizing the identification and classification of dirty areas in the current image, and displaying the dirty areas and the degree of dirt in the current image.

[0187] In addition, the AR smart glasses also have eye-tracking capabilities. When the wearer's gaze falls on a dirty area, they will typically clean it. The AR smart glasses can provide cleaning prompts through vibration, sound, or images, and after cleaning, they can analyze the data to guide the owner on how to check the cleanliness and how to handle water stains.

[0188] For car washes that are done manually at car wash shops, the car wash method may also include the following steps:

[0189] The vehicle can retrieve the appropriate car wash settings from the cloud / vehicle database, matching the vehicle model and compatible with manual car wash settings at car washes. After user confirmation, a privacy mode is activated, disallowing adjustments to vehicle system settings; only opening and closing doors, windows, rearview mirrors, and the trunk are permitted. By implementing car wash settings, the owner's privacy and security are protected, and the settings cannot be altered or modified.

[0190] Furthermore, after the car wash is finished, the vehicle can search for historical reviews online, thus summarizing and commenting on the current car wash's past reviews and prompting car owners to pay attention to any issues with the car wash.

[0191] Furthermore, this method supports collecting images of the car's cleanliness before and after washing using devices such as smartphones or AR smart glasses. It then uses artificial intelligence to compare the cleanliness levels before and after washing, intelligently generating a car wash experience evaluation. This evaluation allows car owners to adjust settings, thus achieving intelligent scoring and assessment of the car wash experience.

[0192] Figure 5 An example is a schematic diagram of the physical structure of a vehicle, such as... Figure 5As shown, the vehicle may include a processor 510, a communications interface 520, a memory 530, and a communication bus 540, wherein the processor 510, communications interface 520, and memory 530 communicate with each other via the communication bus 540. The processor 510 can call logical instructions in the memory 530 to execute a car wash method, which includes: in response to receiving an instruction to start a car wash mode, obtaining the vehicle's location information as a text prompt and external environment information as an image prompt; concatenating the text prompt and the image prompt to obtain an input prompt, wherein the weight of the text prompt is proportional to the positioning accuracy and descriptive clarity of the location information; inputting the input prompt into a large language model to obtain the car wash location type output by the large language model; obtaining car wash settings corresponding to the car wash location type, and setting the vehicle status based on the car wash settings.

[0193] Furthermore, the logical instructions in the aforementioned memory 530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0194] Figure 6 An example is a schematic diagram of the physical structure of a wearable device, such as... Figure 6As shown, the wearable device may include a processor 610, a communications interface 620, a memory 630, and a communication bus 640. The processor 610, communications interface 620, and memory 630 communicate with each other via the communication bus 640. The processor 610 can call logical instructions in the memory 630 to execute a car wash method. This method includes: in response to receiving information from a vehicle indicating that the car wash location type is self-service manual car wash, guiding the wearer to photograph the vehicle body to obtain an image of the vehicle body; the car wash location type is the output obtained by the vehicle based on input prompts to a large language model, the input prompts being obtained by concatenating text prompts and image prompts, the text prompts being the vehicle's location information, and the image prompts being the external environment information; the weight of the text prompts being proportional to the positioning accuracy and descriptive clarity of the location information; and determining a car wash mode based on the vehicle body image.

[0195] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0196] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the methods provided in the above-described method embodiments. The method includes: in response to receiving an instruction to start a car wash mode, obtaining the vehicle's location information as a text prompt and the vehicle's external environment information as an image prompt; concatenating the text prompt and the image prompt to obtain an input prompt, wherein the weight of the text prompt is proportional to the positioning accuracy and descriptive clarity of the location information; inputting the input prompt into a large language model to obtain the car wash location type of the vehicle output by the large language model; obtaining car wash settings corresponding to the car wash location type, and setting the vehicle status based on the car wash settings.

[0197] Alternatively, the method includes: in response to receiving information from the vehicle that the car wash location type is self-service manual car wash, guiding the wearer to photograph the vehicle body to obtain an image of the vehicle body; the car wash location type is the output of the vehicle based on input prompts to a large language model, the input prompts being obtained by concatenating text prompts and image prompts, the text prompts being the vehicle's location information, the image prompts being the vehicle's external environment information, and the weight of the text prompts being proportional to the positioning accuracy and descriptive clarity of the location information; and determining the car wash mode based on the vehicle body image.

[0198] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform the methods provided in the above-described method embodiments. The method includes: in response to receiving an instruction to start a car wash mode, obtaining the vehicle's location information as a text prompt and external environment information as an image prompt; concatenating the text prompt and the image prompt to obtain an input prompt, wherein the weight of the text prompt is proportional to the positioning accuracy and descriptive clarity of the location information; inputting the input prompt into a large language model to obtain the car wash location type output by the large language model; obtaining car wash settings corresponding to the car wash location type, and setting the vehicle status based on the car wash settings.

[0199] Alternatively, the method includes: in response to receiving information from the vehicle that the car wash location type is self-service manual car wash, guiding the wearer to photograph the vehicle body to obtain an image of the vehicle body; the car wash location type is the output of the vehicle based on input prompts to a large language model, the input prompts being obtained by concatenating text prompts and image prompts, the text prompts being the vehicle's location information, the image prompts being the vehicle's external environment information, and the weight of the text prompts being proportional to the positioning accuracy and descriptive clarity of the location information; and determining the car wash mode based on the vehicle body image.

[0200] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0201] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0202] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A car washing method applied to a vehicle, comprising: In response to receiving a command to start the car wash mode, the vehicle's location information is obtained as a text prompt and the external environment information is obtained as an image prompt; The input prompt is obtained by concatenating the text prompt and the image prompt, wherein the weight of the text prompt is proportional to the positioning accuracy and the clarity of the description of the location information; The input prompt is fed into a large language model to obtain the type of car wash where the vehicle is located, as output by the large language model. The input prompt carries the degree of influence of the text prompt and the image prompt on the type of car wash output by the large language model. Obtain the car wash settings corresponding to the car wash location type, and set the vehicle status based on the car wash settings.

2. The car washing method according to claim 1, further comprising at least one of the following: The location information of the vehicle is determined based on at least one of the vehicle's latitude and longitude information and the location information of the vehicle. Information about the vehicle's external environment is obtained using the vehicle's external camera.

3. The car washing method according to claim 1, wherein obtaining the car washing settings corresponding to the car wash location type includes: If the car wash location type is determined to be an automatic machine car wash or a self-service manual car wash, then the car wash settings corresponding to the controllable components supported by the car wash location type and the vehicle model are obtained.

4. The car washing method according to claim 1, wherein, The process of setting the vehicle status based on the car wash settings includes: If the type of car wash is determined to be an automatic car wash, then at least one of the following: rearview mirrors, sunroof, windows, trunk, and windshield wipers of the vehicle shall be turned off. If the car wash location is determined to be a self-service manual car wash, then the car locking function is disabled, and at least one of the following functions of the vehicle is turned off: rearview mirror, sunroof, windows, trunk, and windshield wipers. If the car wash location is determined to be a manual car wash at a car wash shop, then the vehicle's infotainment system settings will be disabled, and at least one of the following functions will be turned off: rearview mirror, sunroof, windows, trunk, and windshield wipers.

5. The car washing method according to claim 1, wherein, Before setting the vehicle status based on the car wash settings, the following is also included: If the type of car wash location is determined to be an automatic machine car wash or a self-service manual car wash, then guidance information matching the car wash machine model of the car wash location where the vehicle is located is obtained; The guidance information is played on the vehicle's onboard terminal; In response to detecting a shift in the driver's attention during one phase of the guidance information, the device that detected the shift in the driver's attention is identified, and the process of the guidance information and subsequent processes are sent to the device that detected the shift.

6. The car washing method according to claim 1, further comprising: If the type of car wash is determined to be manual car wash at a car wash shop, then the historical evaluations of the car wash where the vehicle is located are summarized to obtain the evaluation focus information of the car wash. Receive images of the car body before and after a car wash from wearable devices; Car wash evaluation information is generated based on at least one of the evaluation focus information and the before-and-after images of the car body.

7. A recommended method for a car wash mode, applied to a wearable device that establishes a communication connection with a vehicle, comprising: In response to receiving a message from the vehicle indicating that the car wash location is a self-service manual car wash, the wearer is guided to take a picture of the vehicle's body to obtain an image of the vehicle's body. The car wash location type is obtained by inputting input prompts into a large language model based on the vehicle. The input prompts are obtained by concatenating text prompts and image prompts. The text prompts are the vehicle's location information, and the image prompts are the external environment information. The weight of the text prompts is proportional to the positioning accuracy and descriptive clarity of the location information. The input prompts, carrying the text prompts and image prompts, influence the car wash location type output by the large language model. Based on the vehicle image, a car wash mode is recommended to the wearer.

8. The method for recommending car wash modes according to claim 7, further comprising: Determine whether the car wash location is an automatic machine car wash or a self-service manual car wash, and receive guidance information sent by the vehicle; Collect status images of the car wash machine and determine the real-time status of the car wash machine based on the status images; Based on the guidance information and the real-time status, operation prompts are provided.

9. The method for recommending car wash modes according to claim 7, further comprising: Images of the car body area being washed are captured during the car wash process; Dirt analysis is performed on the vehicle body area image to obtain dirt analysis results; Based on the dirt analysis results, at least one of dirt alerts and cleaning guidance will be provided.

10. A vehicle comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the car washing method as described in any one of claims 1 to 6.

11. A wearable device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the recommended method for the car wash mode as described in any one of claims 7 to 9.

12. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the car washing method as described in any one of claims 1 to 6, or the recommended method for implementing the car washing mode as described in any one of claims 7 to 9.

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