Vehicle abnormity prompting method, device and equipment

Abstract

The embodiment of the invention provides a vehicle abnormity prompting method, device and equipment. The method comprises the steps that interaction information of a user of a first vehicle is acquired; under the condition that the interaction information contains specific information, an image collected by a first vehicle according to the specific information is obtained, and the specific information contains the orientation and fault information of a second vehicle which breaks down; identifying the identity information of the second vehicle according to the collected image; first abnormity reminding information is sent to a server, the first abnormity reminding information comprises identity information and fault information of the second vehicle, the first abnormity reminding information is used for reminding the server to send second abnormity reminding information to the second vehicle, and the second abnormity reminding information comprises the fault information. According to the method, when the real-time interaction information of the user is utilized to determine that the fault vehicle exists, the abnormal reminding information is sent to the fault vehicle, so that proper prevention measures are taken, and the driving risk is reduced.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to a method, device, and equipment for vehicle anomaly prompting. Background Art

[0002] With the popularization and use of vehicles, it has become increasingly common for vehicles to malfunction during driving. These malfunctions may include, but are not limited to, the failure of a certain light in the headlight or taillight, a punctured tire, vehicle self-ignition, damage to body parts such as the bumper being hit, or even the risk of parts falling off.

[0003] During the driving process, the driver is very likely not to detect in a timely manner that the vehicle being driven has a malfunction. Therefore, there is a relatively high driving risk. Summary of the Invention

[0004] In view of this, embodiments of this application propose a method, device, and equipment for vehicle anomaly prompting, which can send an anomaly reminder message to a malfunctioning vehicle when it is determined that there is a malfunctioning vehicle by using the real-time feedback of the user, thereby reducing the driving risk that the driver cannot detect in a timely manner that the vehicle being driven has a malfunction during the driving process.

[0005] In a first aspect, an embodiment of this application provides a method for vehicle anomaly prompting. The method includes: obtaining the interaction information of the user of a first vehicle; in the case that the interaction information includes specific information, obtaining an image collected by the first vehicle according to the specific information, where the specific information includes the orientation and malfunction information of a second vehicle with a malfunction; identifying the identity information of the second vehicle according to the collected image; sending a first anomaly reminder message to a server, where the first anomaly reminder message includes the identity information and malfunction information of the second vehicle, and the first anomaly reminder message is used to prompt the server to send a second anomaly reminder message to the second vehicle, and the second anomaly reminder message includes the malfunction information.

[0006] In a second aspect, an embodiment of this application provides a device for vehicle anomaly prompting. The device includes: an interaction information obtaining module, configured to obtain the interaction information of the user of a first vehicle; an image obtaining module, configured to obtain an image collected by the first vehicle according to the specific information in the case that the interaction information includes specific information, where the specific information includes the orientation and malfunction information of a second vehicle with a malfunction; an identity information determining module, configured to identify the identity information of the second vehicle according to the collected image; and an anomaly information sending module, configured to send a first anomaly reminder message to a server, where the first anomaly reminder message includes the identity information and malfunction information of the second vehicle, and the first anomaly reminder message is used to prompt the server to send a second anomaly reminder message to the second vehicle, and the second anomaly reminder message includes the malfunction information.

[0007] In one possible implementation, the vehicle abnormality prompting device further includes: a fault identification module, configured to perform fault identification on the image to obtain a fault identification result; an abnormality information sending module, further configured to send a first abnormality reminder information to the server when the fault identification result matches the fault information.

[0008] In one possible implementation, the vehicle abnormality prompting device further includes: a prompt information display module, configured to display a confirmation prompt message for sending the fault when the fault identification result does not match the fault information; the abnormality information sending module, further configured to send a first abnormality reminder information to the server when receiving a confirmation sending feedback input by the user for the confirmation prompt message for sending the fault.

[0009] In one possible implementation, the first abnormality reminder information and the second abnormality reminder information further include the image.

[0010] In one possible implementation, the image acquisition module is further configured to control a specified camera of the first vehicle to collect an image in a target direction, where the specified camera of the first vehicle is a camera among multiple cameras of the first vehicle that can collect an image in the target direction of the first vehicle, and the target direction is determined according to the orientation of the second vehicle; and receive the image collected by the specified camera.

[0011] In one possible implementation, the interaction information acquisition module is further configured to acquire interaction information of a user collected by a voice module of the first vehicle in a wake-up state.

[0012] In one possible implementation, the vehicle abnormality prompting device further includes a voice recognition module and a semantic analysis module. The voice recognition module is configured to perform voice recognition on the interaction information collected by the voice module of the first vehicle to obtain a voice recognition result; the semantic recognition module is configured to perform semantic analysis on the voice recognition result to obtain a semantic analysis result, and the semantic analysis result is used to indicate whether there is a second vehicle with a fault and the orientation of the second vehicle.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory; one or more programs are stored in the memory and are configured to be executed by the processor to implement the above method.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which program code is stored, and when the program code is run by a processor, the above method is executed.

[0015] Fifth aspect, an embodiment of the present application provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device obtains the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the above-mentioned method.

[0016] A vehicle anomaly prompting method, device and equipment provided by an embodiment of the present application. The method includes: obtaining interaction information of a user of a first vehicle; when the interaction information includes specific information, obtaining an image collected by the first vehicle according to the specific information, where the specific information includes the orientation and fault information of a second vehicle with a fault; identifying the identity information of the second vehicle according to the collected image; sending a first anomaly reminder message to a server, where the first anomaly reminder message includes the identity information and fault information of the second vehicle, and the first anomaly reminder message is used to prompt the server to send a second anomaly reminder message to the second vehicle, and the second anomaly reminder message includes the fault information. By adopting the above method, when it is determined according to the user's interaction information that there is a second vehicle with a fault around, when the vehicle identity information of the second vehicle is obtained by acquiring an image and performing image recognition, a fault prompt is sent to the client associated with the second vehicle in a timely manner, so that the driver or user of the second vehicle can more quickly realize the potential risk, thereby taking appropriate preventive measures and reducing the possibility of accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0018] Figure 1 A flowchart showing a vehicle anomaly prompting method provided by an embodiment of the present application;

[0019] Figure 2 Another flowchart showing a vehicle anomaly prompting method provided by an embodiment of the present application;

[0020] Figure 3 A connection block diagram of a first vehicle provided by an embodiment of the present application;

[0021] Figure 4 An application scenario diagram showing a vehicle anomaly prompting method provided by an embodiment of the present application;

[0022] Figure 5The connection block diagram of a vehicle anomaly prompt device proposed by an embodiment of the present application is shown;

[0023] Figure 6 The structural block diagram of an electronic device for executing the method of the embodiment of the present application is shown. Detailed implementation manners

[0024] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art.

[0025] In addition, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of the present application. However, those skilled in the art will realize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be used. In other cases, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present application.

[0026] The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0027] The flowcharts shown in the drawings are only illustrative and do not necessarily include all the content and operations / steps, nor are they necessarily executed in the described order. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0028] It should be noted that: "a plurality" mentioned herein refers to two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0029] In addition, it should be noted that in the embodiments of the present application, the collection, use, processing, and storage of application information are all subject to the user's permission and need to comply with the regulations of the region where it is located.

[0030] A vehicle anomaly prompt method provided by the present application can be applied to an electronic device, which can be a server, a terminal device, a vehicle, or a combination of one or more of the above.

[0031] In some embodiments, the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN), and big data and artificial intelligence platforms.

[0032] The terminal device can be a smartphone, a tablet computer, a laptop computer, a desktop computer, a smart voice interaction device, a smart home appliance, a vehicle-mounted terminal, etc., but is not limited thereto.

[0033] Figure 1 Specifically, the vehicle anomaly prompt method of the present application is shown, which can be applied to an electronic device. The method includes:

[0034] Step S110: Obtain the interaction information of the user of the first vehicle.

[0035] Among them, the user of the first vehicle can include the user riding in the first vehicle or the user to whom the first vehicle belongs.

[0036] The above interaction information can be voice information or text information, etc. Such as "The turn signal of the vehicle ahead is not on", "The brake light of the vehicle ahead is not on", "The bumper of the vehicle behind is about to fall off", "The tire of the vehicle in the front left has no air", etc.

[0037] Among them, if the interaction information is text information, then the above step S110 can be to obtain the information provided by the user through touch screen input, in-vehicle device keyboard input or other text input methods.

[0038] If the interaction information is voice information, then the above step S110 can be to obtain the voice information collected by the voice module. Among them, the voice module can be the voice module of the vehicle or the voice module of the terminal device (such as a mobile phone, a tablet, etc.). In this case, the above terminal device can be a device associated with the first vehicle, and the first vehicle can be the vehicle currently ridden by the user.

[0039] It is worth mentioning that the voice module is usually in a low-power listening state, waiting for a specific wake-up word (such as "Hello, XXX" or "Hi, XX car") to activate. Once the voice module is successfully awakened, it starts recording the user's voice and can also convert the recorded voice information into text information.

[0040] That is, in an implementable manner, the above step S110 includes:

[0041] Obtain the interaction information of the user collected by the voice module of the first vehicle in the wake-up state.

[0042] Step S120: When the interaction information includes specific information, obtain an image collected by the first vehicle according to the specific information, where the specific information includes the orientation and fault information of the second vehicle with a fault.

[0043] Specifically, if the interaction information is voice information, perform voice recognition on the interaction information collected by the voice module of the first vehicle to obtain a voice recognition result; perform semantic analysis on the voice recognition result to obtain a semantic analysis result, where the semantic analysis result is used to indicate the second vehicle with a fault, as well as the orientation and fault information of the second vehicle, where the orientation refers to the orientation of the second vehicle relative to the first vehicle.

[0044] If the interaction information is text information, perform semantic analysis on the text information to obtain a semantic analysis result, where the semantic analysis result is used to indicate the second vehicle with a fault, as well as the orientation and fault information of the second vehicle, where the orientation refers to the orientation of the second vehicle relative to the first vehicle.

[0045] Among them, performing semantic analysis on the text information (voice recognition result) can specifically be to extract features from the text information (voice recognition result) to obtain semantic features. Perform semantic understanding on the semantic features to obtain the semantic understanding result of the text information (voice recognition result).

[0046] Specifically, semantic parsing can be performed on the semantic features to obtain a semantic parsing result. Exemplarily, taking the text information (voice recognition result) as "the brake light of the vehicle in the front left is not on" as an example, parsing the semantic features corresponding to the above problem, the obtained result is: "direction = front left", "vehicle component = brake light", "status = not on". That is, through the semantic analysis result, there is a second vehicle in the target orientation (front left) of the first vehicle, and the second vehicle has a corresponding fault (brake light not on).

[0047] Among them, the target direction can refer to the direction relative to the front orientation of the target vehicle, and the target direction can be any one of the front, rear, left, right, front left, front right, rear left, and rear right.

[0048] The above step S120 can specifically be: Obtain at least one image that can show the orientation and has the closest image acquisition time to the interaction information acquisition time from multiple images collected by the obtained camera.

[0049] The above step S120 can also be:

[0050] Control the specified camera of the first vehicle to collect an image in the target direction; receive the image collected by the specified camera.

[0051] Wherein, the specified camera of the first vehicle is a camera among the multiple cameras of the first vehicle that can collect an image in the target direction of the first vehicle, and the target direction is determined according to the orientation of the second vehicle.

[0052] Specifically, a camera with a field of view range that can cover the target orientation can be selected according to the field of view ranges and current states of the multiple cameras on the first vehicle. Exemplarily, if the target orientation is "front", the front camera is selected; if it is "right", the right-side camera is selected. Subsequently, the angle and focal length of the camera can also be dynamically adjusted during the image collection process of the specified camera to ensure capturing the clearest vehicle image of the second vehicle.

[0053] By adopting the above settings, an image of the second vehicle can be accurately obtained.

[0054] Step S130: Identify the identity information of the second vehicle according to the collected image.

[0055] Wherein, the vehicle identity information can specifically be license plate information or vehicle identification number, etc., which can uniquely identify the second vehicle.

[0056] In an implementable manner of the present application, the vehicle identity information includes the license plate number.

[0057] In this case, the above step S130 can be: use the license plate information recognition model to recognize the image to obtain a license plate information recognition result. Among them, the above license plate information recognition model can be pre-trained, and the specific training process can be: obtain a first image sample data set for training the license plate information recognition model. The first image data set can include multiple first sample images and the license plate information label corresponding to each first sample image. The license plate information recognition model adopted can include a feature extraction layer and a classification layer. The feature extraction layer is used to extract the semantic features of the sample image, and the classification layer is used to perform classification recognition based on the extracted semantic features to obtain the license plate recognition result in the first sample image. Then, based on the license plate recognition result of the first sample image and the license plate information label, a first recognition loss is determined to adjust the parameters of the license plate information recognition model based on the first recognition loss until the first training end condition is reached, and the license plate information recognition model is obtained. The first training end condition is that the number of iterations reaches a first preset number or the first recognition loss is less than a first preset loss.

[0058] Step S140: Send a first exception reminder message to the server. The first exception reminder message includes the identity information and fault information of the second vehicle. The first exception reminder message is used to prompt the server to send a second exception reminder message to the second vehicle. The second exception reminder message includes the fault information.

[0059] Among them, the above-mentioned server may include one or more of a vehicle back-end server, a vehicle management office server, etc. As long as the above-mentioned server can send a second exception reminder message including the fault corresponding to the second vehicle to the client associated with the second vehicle according to the vehicle identity information of the second vehicle.

[0060] In an implementable manner, the server includes a vehicle back-end server and a vehicle management office server. Among them, after receiving the first exception reminder message, the vehicle back-end server sends the first exception reminder message to the vehicle management office server, so that the vehicle management office server sends a second exception reminder message to the second vehicle according to the vehicle identity information.

[0061] In this implementation manner, the vehicle management office server can also query the client associated with the vehicle identity information according to the vehicle identity information in the first exception reminder message, that is, the client associated with the second vehicle, and send a second exception reminder message including the fault corresponding to the second vehicle to the client associated with the second vehicle.

[0062] Among them, the vehicle back-end server generally refers to a server system maintained by an automobile manufacturer, a fleet operation company or a third-party service provider. It is mainly used to manage and monitor the vehicle status and services of a specific brand or fleet. The vehicle management office server refers to an official server system maintained by the government traffic management department (such as a vehicle management office, a traffic management bureau), which stores the vehicle information (including vehicle identity information) of multiple vehicles and the corresponding driver information (such as the client information bound by the driver).

[0063] Exemplarily, if the interaction information is "the taillight of the vehicle in front is not on", and the identified vehicle identity information is "Shanghai A123XXXX", the generated first exception reminder message is "License plate number: Shanghai 123XXXX; Fault: Taillight is not on". The electronic device can use the HTTPS protocol to send the first exception reminder message to the vehicle back-end server. The vehicle back-end server can forward the first exception reminder message to the vehicle management office server. The vehicle management office server generates a second exception reminder message based on the first exception reminder message: "Your vehicle (license plate number: Shanghai A123XXXX) has a problem with the taillight not being on. Please check and repair it as soon as possible.", and sends the second exception reminder message to the client associated with the second vehicle by means of SMS, email or application notification. Among them, the client can be an in-vehicle terminal, a mobile terminal, etc.

[0064] Please refer to Figure 2 , in one implementable manner, before performing step S140, the method further includes:

[0065] Step S150: Perform fault identification on the image to obtain a fault identification result.

[0066] The fault identification result is used to indicate whether there is a fault corresponding to the second vehicle in the image, and includes the specific fault type when there is a fault.

[0067] The above-mentioned fault identification of the collected image can specifically be to perform fault identification using a fault identification model. The fault identification model can be pre-trained. The specific training process can be: obtaining a second image sample dataset used for training the fault identification model. The second image dataset includes multiple second sample images and the fault label corresponding to each second sample image. The adopted fault identification model can include a feature extraction layer and a classification layer. The feature extraction layer is used to extract the semantic features of the second sample image, and the classification layer is used to perform classification and identification based on the extracted semantic features to obtain the fault identification result in the sample image. Then, based on the fault identification result and the fault label of the sample image, a second identification loss is determined, and the parameters of the fault identification model are adjusted based on the second identification loss until the second training end condition is reached, and the fault identification model is obtained. Among them, the second training end condition is that the number of iterations reaches a second preset number or the first identification loss is less than a second preset loss.

[0068] Step S160: Determine whether the fault identification result matches the fault information.

[0069] Among them, the method for determining whether the fault identification result matches the fault information can be to determine whether the fault information is included in the fault identification result. If not, it does not match; if so, it matches. It can also be to perform a semantic similarity judgment on the fault identification result and the fault information. If the semantic similarity is greater than a preset threshold, it matches; if it is not greater than the preset threshold, it does not match.

[0070] If the fault identification result matches the fault information, then perform the above-mentioned step S140.

[0071] By adopting the above steps S150 - S160, the fault identification result is matched with the fault information reported by the user to ensure the consistency between the two. If the matching is successful, it indicates that the user's reported fault has been verified, reducing the invalid prompts caused by misidentification or false reporting by the user, and improving the reliability of fault reporting and the user experience.

[0072] In one implementable manner, if the fault identification result does not match the fault information, the method can further include:

[0073] Step S180: Display the fault sending confirmation prompt message.

[0074] Among them, the fault sending confirmation prompt message is used to prompt the user whether to send the first exception reminder message to the server.

[0075] The device for displaying the fault sending confirmation prompt message can be the terminal device associated with the first vehicle or the in-vehicle terminal of the first vehicle, and no specific limitation is made here.

[0076] By displaying the fault sending confirmation prompt message, so that the user can determine whether to send the feedback information of the first exception reminder message to the background server based on the fault sending confirmation information. Among them, if the user determines to send the first exception reminder message to the server, the user can input the confirmation sending feedback through the interaction device. If the user does not need to send the first exception reminder message to the server, the user can input the cancellation sending feedback through the interaction device.

[0077] Step S190: Confirm whether the confirmation sending feedback input by the user in response to the fault sending confirmation prompt message is obtained.

[0078] If so, execute step S140.

[0079] In this case, if the confirmation sending feedback input by the user in response to the fault sending confirmation prompt message is not obtained, the above step S140 will no longer be executed.

[0080] By adopting the above steps S180 - S190, it can be realized that in the case where the fault identification result is inconsistent with the fault information reported by the user, unnecessary alarms can be avoided through the user confirmation link, saving resources and reducing interference. In addition, it also allows the user to participate in the decision-making process and increases the transparency of the fault reporting process.

[0081] It is worth mentioning that the above fault identification process can be without setting. That is, before executing the step of sending the first exception reminder message including the vehicle identity information of the second vehicle and the fault corresponding to the second vehicle to the background server, the method can further include: generating a fault sending confirmation prompt message; controlling the interaction device associated with the first vehicle to display the fault sending confirmation prompt message; when the confirmation sending feedback input by the user in response to the fault sending confirmation prompt message is obtained, executing the step of sending the first exception reminder message including the vehicle identity information of the second vehicle and the fault corresponding to the second vehicle to the background server.

[0082] Please refer to Figure 3As shown, taking the specific application of the vehicle anomaly prompt method in the first vehicle as an example, a vehicle assistant (such as a voice module), a vehicle host, an intelligent driving domain controller, and multiple cameras (only the case of including two cameras is shown in the figure) are provided on the first vehicle. The multiple cameras are respectively arranged at different positions on the body of the first vehicle and are used to collect images in different directions relative to the front of the first vehicle, such as the front, the left front, the right front, the rear, the left rear, and the right rear, etc.

[0083] Please refer to Figure 4 , during the driving process of the first vehicle, if the driver or passenger discovers that the brake light of the second vehicle in front of the self-lane is damaged; wake up the vehicle assistant of the first vehicle through voice; then, the driver or passenger can say "The brake lights of the vehicle in the front and rear are broken" to the vehicle assistant. The vehicle assistant recognizes the direction as "Target direction = front" and the specific fault as "Fault = brake light broken" through voice recognition; then, the vehicle assistant sends the recognized direction and fault to the vehicle host, and the vehicle host then sends a service instruction to recognize the vehicle license plate to the intelligent driving domain controller; according to the received service instruction, the intelligent driving domain controller controls the camera on the first vehicle that is used to collect images in the target direction to collect images in the target direction and performs license plate recognition on the images to obtain the license plate information of the second vehicle; the intelligent driving domain controller feeds back the license plate information to the vehicle host; the vehicle host generates a first anomaly reminder message based on the license plate information and the corresponding fault, and sends the first anomaly reminder message to the vehicle end background server through the network. When the vehicle end background server receives the first anomaly reminder message, it forwards the first anomaly reminder message to the vehicle management office server. The vehicle management office server queries the client associated with the vehicle identity information according to the vehicle identity information in the first anomaly reminder message, that is, the client associated with the second vehicle, and sends a second anomaly reminder message including the fault corresponding to the second vehicle to the client associated with the second vehicle. Among them, the client associated with the second vehicle can be the in-vehicle terminal of the second vehicle or the mobile terminal managed by the second vehicle.

[0084] By adopting the above solution, when driving the first vehicle, if you want to remind that there is a fault in the surrounding vehicles of the vehicle you are driving, you only need to say a voice of "The XX part of the vehicle in the XX direction is broken", and you can send the content you want to remind to the client associated with the vehicle you want to remind, so that the owner or driver of the vehicle can discover the fault information of the vehicle earlier, and then can further repair the vehicle to reduce potential safety hazards.

[0085] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0086] Please refer to Figure 5 , another embodiment of the present application provides a vehicle abnormality prompting device 200, and the vehicle abnormality prompting device 200 includes: an interaction information acquisition module 210, configured to acquire interaction information of a user of a first vehicle; an image acquisition module 220, configured to acquire an image collected by the first vehicle according to the specific information when the interaction information includes specific information, where the specific information includes the position and fault information of a second vehicle that has a fault; an identity information determination module 230, configured to identify the identity information of the second vehicle according to the acquired image; and an abnormality information sending module 240, configured to send a first abnormality reminder information to a server, where the first abnormality reminder information includes the identity information and fault information of the second vehicle, and the first abnormality reminder information is used to prompt the server to send a second abnormality reminder information to the second vehicle, and the second abnormality reminder information includes the fault information.

[0087] In an implementable manner, the vehicle abnormality prompting device 200 further includes: a fault identification module, configured to perform fault identification on the image to obtain a fault identification result; and the abnormality information sending module is further configured to send the first abnormality reminder information to the server when the fault identification result matches the fault information.

[0088] In an implementable manner, the vehicle abnormality prompting device 200 further includes: a prompt information display module, configured to display a fault sending confirmation prompt information when the fault identification result does not match the fault information; and the abnormality information sending module is further configured to send the first abnormality reminder information to the server when receiving a confirmation sending feedback input by the user for the fault sending confirmation prompt information.

[0089] In an implementable manner, the first abnormality reminder information and the second abnormality reminder information further include the image.

[0090] In an implementable manner, the image acquisition module 220 is further configured to control a specified camera of the first vehicle to collect an image in a target direction, where the specified camera of the first vehicle is a camera among multiple cameras of the first vehicle that can collect an image in the target direction of the first vehicle, and the target direction is determined according to the orientation of the second vehicle; and receive the image collected by the specified camera.

[0091] In an implementable manner, the interaction information acquisition module 210 is further configured to acquire interaction information of a user collected by the voice module of the first vehicle in a wake-up state.

[0092] In an implementable manner, the vehicle anomaly prompt device 200 further includes a voice recognition module and a semantic analysis module. The voice recognition module is configured to perform voice recognition on the interaction information collected by the voice module of the first vehicle to obtain a voice recognition result; the semantic recognition module is configured to perform semantic analysis on the voice recognition result to obtain a semantic analysis result, and the semantic analysis result is used to indicate whether there is a second vehicle with a fault and the orientation of the second vehicle.

[0093] Each module in the above device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above respective modules. It should be noted that the device embodiments in this application correspond to the foregoing method embodiments. The specific principles in the device embodiments can refer to the content in the foregoing method embodiments and will not be elaborated here.

[0094] Next, Figure 6 an electronic device provided by this application will be described.

[0095] Please refer to Figure 6 , based on the vehicle anomaly prompt method provided in the foregoing embodiments, another electronic device 100 provided in the embodiments of this application includes a processor 102 that can execute the foregoing method. The electronic device 100 can be a server, a terminal device, or a vehicle, and the terminal device can be a device such as a smart phone, a tablet computer, a computer, or a portable computer.

[0096] The electronic device 100 further includes a memory 104. Among them, a program that can execute the content in the foregoing embodiments is stored in the memory 104, and the processor 102 can execute the program stored in the memory 104.

[0097] Among them, the processor 102 may include one or more cores for processing data and a message matrix unit. The processor 102 connects various parts within the entire electronic device 100 through various interfaces and circuits. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 104, and by calling data stored in the memory 104, it performs various functions of the electronic device 100 and processes data. Optionally, the processor 102 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 102 may integrate one or a combination of several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing display content; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 102 and may be implemented separately through a communication chip.

[0098] The memory 104 may include random access memory (RAM) and may also include read-only memory. The memory 104 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 104 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for implementing at least one function, instructions for implementing the following various method embodiments, etc. The data storage area may also store data obtained during the use of the electronic device 100 (such as interaction information, vehicle images), etc.

[0099] The electronic device 100 may further include a network module and a screen. The network module is used to receive and send electromagnetic waves, implement the mutual conversion between electromagnetic waves and electrical signals, so as to communicate with a communication network or other devices, such as communicating with an audio playback device. The network module may include various existing circuit elements for performing these functions, such as antennas, radio frequency transceivers, digital signal processors, encryption / decryption chips, subscriber identity module (SIM) cards, memories, and so on. The network module can communicate with various networks such as the Internet, enterprise intranets, wireless networks or communicate with other devices through a wireless network. The aforementioned wireless network may include a cellular phone network, a wireless local area network or a metropolitan area network. The screen can display interface content and perform data interaction, such as displaying the aforementioned interface and triggering operations through the screen, etc.

[0100] In some embodiments, the electronic device 100 may further include: a peripheral interface 106 and at least one peripheral device. The processor 102, the memory 104 and the peripheral interface 106 may be connected by a bus or signal lines. Each peripheral device can be connected to the peripheral interface through a bus, signal lines or a circuit board. Specifically, the peripheral devices include at least one of a radio frequency component 108, a positioning component 112, a camera 114, an audio component 116, a display screen 118, and a power supply 122, etc.

[0101] The peripheral interface 106 can be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 102 and the memory 104. In some embodiments, the processor 102, the memory 104 and the peripheral interface 106 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 102, the memory 104 and the peripheral interface 106 can be implemented on a separate chip or circuit board, and the embodiments of the present application do not limit this.

[0102] The radio frequency component 108 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency component 108 communicates with a communication network and other communication devices through electromagnetic signals. The radio frequency component 108 converts an electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency component 108 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and so on. The radio frequency component 108 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G, and 5G), a wireless local area network, and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency component 108 may further include a circuit related to NFC (Near Field Communication), which is not limited in this application.

[0103] The positioning component 112 is used to locate the current geographical location of the electronic device to implement navigation or LBS (Location-Based Service). The positioning component 112 can be a positioning component based on the US GPS (Global Positioning System), the Beidou system, or the Galileo system.

[0104] The camera 114 is used to capture images or videos. Optionally, the camera 114 includes a front camera and a rear camera. Usually, the front camera is set on the front panel of the electronic device 100, and the rear camera is set on the back of the electronic device 100. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth camera, a wide-angle camera, and a telephoto camera, to implement the function of background blurring by fusing the main camera and the depth camera, panoramic shooting by fusing the main camera and the wide-angle camera, and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera 114 may further include a flash. The flash can be a single-color temperature flash or a two-color temperature flash. The two-color temperature flash refers to the combination of a warm light flash and a cold light flash, which can be used for light compensation under different color temperatures.

[0105] The audio component 116 may include a microphone and a speaker. The microphone is used to collect sound waves of the user and the environment, and convert the sound waves into electrical signals for input to the processor 102 for processing, or input to the radio frequency component 108 to achieve voice communication. For the purpose of stereo collection or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the electronic device 100. The microphone may also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert the electrical signal from the processor 102 or the radio frequency component 108 into sound waves. The speaker may be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for uses such as ranging. In some embodiments, the audio component 114 may also include a headphone jack.

[0106] The display screen 118 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos, and any combination thereof. When the display screen 118 is a touch display screen, the display screen 118 also has the ability to collect touch signals on or above the surface of the display screen 118. The touch signal may be input to the processor 102 as a control signal for processing. At this time, the display screen 118 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there may be one display screen 118, which is arranged on the front panel of the electronic device 100; in other embodiments, there may be at least two display screens 118, which are respectively arranged on different surfaces of the electronic device 100 or in a folded design; in still other embodiments, the display screen 118 may be a flexible display screen, which is arranged on the curved surface or the folding surface of the electronic device 100. Even, the display screen 118 can also be set as an irregular non-rectangular shape, that is, a special-shaped screen. The display screen 118 may be prepared using materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0107] The power supply 122 is used to supply power to each component in the electronic device 100. The power supply 122 may be alternating current, direct current, a disposable battery, or a rechargeable battery. When the power supply 122 includes a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery charged through a wired line, and a wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0108] The embodiment of the present application also provides a structural block diagram of a computer-readable storage medium. Program code is stored in the computer-readable medium, and the program code can be called by a processor to execute the method described in the above method embodiment.

[0109] The computer-readable storage medium can be an electronic memory such as flash memory, EEPROM (electrically erasable programmable read-only memory), EPROM, a hard disk, or ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium has a storage space for program code for executing any method step in the above method. These program codes can be read out from or written into one or more computer program products. The program code can be compressed in a suitable form, for example.

[0110] The embodiment of the present application also provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method described in the above various optional implementation manners.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements 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 the present application.

Claims

1. A method for vehicle anomaly prompting, characterized in that, The method includes: Obtaining interaction information of a user of a first vehicle; When the interaction information includes specific information, obtaining an image collected by the first vehicle according to the specific information, where the specific information includes the orientation and fault information of a second vehicle with a fault; Identifying the identity information of the second vehicle according to the collected image; Sending a first exception reminder message to a server, where the first exception reminder message includes the identity information and fault information of the second vehicle, and the first exception reminder message is used to prompt the server to send a second exception reminder message to the second vehicle, and the second exception reminder message includes the fault information.

2. The method according to claim 1, characterized in that Before sending the first exception reminder message to the server, the method further includes: Performing fault identification on the image to obtain a fault identification result; If the fault identification result matches the fault information, performing the step of sending the first exception reminder message to the server.

3. The method according to claim 2, wherein The method further includes: If the fault identification result does not match the fault information, displaying a confirmation prompt message for sending the fault; when a confirmation sending feedback input by the user for the confirmation prompt message for sending the fault is obtained, performing the step of sending the first exception reminder message to the server.

4. The method according to claim 2, wherein The first exception reminder message and the second exception reminder message further include the image.

5. The method according to claim 1, wherein The obtaining an image collected by the first vehicle according to the specific information includes: Controlling a specified camera of the first vehicle to collect an image in a target direction, where the specified camera of the first vehicle is a camera among multiple cameras of the first vehicle that can collect an image in the target direction of the first vehicle, and the target direction is determined according to the orientation of the second vehicle; Receiving the image collected by the specified camera.

6. The method according to claim 1, characterized in that, The obtaining interaction information of a user of a first vehicle includes: Obtaining interaction information of a user collected by a voice module of the first vehicle in a wake-up state.

7. The method according to claim 6, wherein After obtaining the interaction information of a user of the first vehicle, the method further includes: Performing voice recognition on the interaction information collected by the voice module of the first vehicle to obtain a voice recognition result; Performing semantic analysis on the voice recognition result to obtain a semantic analysis result, where the semantic analysis result is used to indicate whether there is a second vehicle with a fault and the orientation of the second vehicle.

8. A vehicle abnormal prompt device, characterized in that, The device includes: An interaction information obtaining module, configured to obtain interaction information of a user of a first vehicle; An image obtaining module, configured to obtain an image collected by the first vehicle according to the specific information when the interaction information includes the specific information, where the specific information includes the orientation and fault information of a second vehicle with a fault; An identity information determining module, configured to identify the identity information of the second vehicle according to the collected image; An exception information sending module, configured to send a first exception reminder message to a server, where the first exception reminder message includes the identity information and fault information of the second vehicle, and the first exception reminder message is used to prompt the server to send a second exception reminder message to the second vehicle, and the second exception reminder message includes the fault information.

9. An electronic device, characterized in that, Including: One or more processors; A memory; One or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs are configured to perform the method according to any one of claims 1-7.

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