Commercial vehicle fault processing method, system and device and storage medium

Abstract

The invention discloses a fault processing method, system and device for a commercial vehicle and a storage medium. The method comprises the steps that a plurality of target commercial vehicles collect data through internal and external sensors configured on the target commercial vehicles, send the data to a local data collector for data integration and storage, and upload the data to a cloud background. After the cloud background carries out fault scanning on the vehicle related information to detect a fault code, fault identification is carried out on the vehicle related information containing the fault code through a preset fault identification model, and validity verification is carried out on the fault code by using a fault identification result; according to the method and the system, the fault case is generated after the verification is valid, and the identifier of the fault case is pushed to the corresponding maintenance client, so that the maintenance client can access the cloud background based on the identifier of the fault case to search the matched fault case, and effective and accurate troubleshooting and positioning are carried out on the corresponding target commercial vehicle. According to the scheme, the interaction timeliness from the vehicle end to the vehicle engineer can be improved, and the troubleshooting, positioning and maintenance efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of new energy vehicles, specifically to the technical fields such as intelligent driving and vehicle networking, and particularly relates to a fault handling method, system, device and storage medium for commercial vehicles. Background Art

[0002] Currently, when a commercial vehicle breaks down, it mostly relies on a diagnostic instrument to locate the vehicle-wide faults.

[0003] However, this traditional method has many limitations: First, it can only detect after a fault occurs, unable to perform predictive diagnosis of potential faults, making it difficult to take measures in advance to avoid fault occurrence, increasing the risks and emergencies during vehicle operation. Second, it lacks the ability to systematically count and analyze faults, unable to extract valuable information from a large amount of fault data, which is not conducive to the optimization and improvement of vehicle performance. Third, it cannot efficiently identify and push fault information to the responsible engineers in relevant fields, resulting in untimely fault handling, affecting vehicle repair efficiency and normal use, and further causing increased operating costs and economic losses.

[0004] Therefore, there is an urgent need for a new fault monitoring and handling solution for commercial vehicles to solve the above problems. Summary of the Invention

[0005] The present application provides a fault handling method, system, device and storage medium for commercial vehicles to solve the problems that the existing fault handling solutions for commercial vehicles cannot perform predictive diagnosis, lack the ability to count and analyze faults, and cannot efficiently identify, diagnose and accurately push for repair.

[0006] The technical solutions are as follows:

[0007] In a first aspect, a fault handling method for commercial vehicles is provided, which is applied to a fault handling system for commercial vehicles. The system includes: a plurality of target commercial vehicles, a cloud background that has established a communication connection with each target commercial vehicle, and a plurality of maintenance clients connected to the cloud background; wherein, each target commercial vehicle is equipped with internal and external sensors and a data collector; the method includes:

[0008] Each target commercial vehicle collects information on the external driving environment and the internal state of the vehicle based on the configured internal and external sensors, sends it to the local data collector for integrated storage, and uploads the integrated vehicle-related information to the cloud background; wherein, the vehicle-related information carries the vehicle identifier or data collector identifier of its corresponding target commercial vehicle.

[0009] The cloud background receives multiple vehicle-related information in real time and scans for fault codes for each vehicle-related information; after detecting a fault code, the vehicle-related information containing the fault code is input into a preset fault recognition model, and the validity of the detected fault code is verified based on the fault recognition result. If the verification result is valid, a fault use case is generated based on the vehicle-related information containing the fault code, and the identifier of the fault use case is pushed to the maintenance client corresponding to the fault type of the fault code.

[0010] Based on the received identifier of the fault use case, the maintenance client accesses the cloud background to find a matching fault use case for fault troubleshooting and positioning of the target commercial vehicle corresponding to the fault use case.

[0011] In a possible implementation, after the cloud background receives multiple vehicle-related information in real time, the method further includes:

[0012] The cloud background classifies and stores the multiple vehicle-related information according to the vehicle identifier, and establishes multiple vehicle information databases for the maintenance client to view quickly.

[0013] In a possible implementation, after the cloud background receives multiple vehicle-related information in real time, the method further includes:

[0014] The cloud background extracts vehicle key information from the vehicle-related information, and the vehicle key information at least includes: driving road information, obstacle information, weather information, driver status information, and driving behavior information.

[0015] The features extracted based on the vehicle key information are input into a fault probability prediction model to predict the fault probability and fault type of the target commercial vehicle corresponding to the vehicle-related information in the future time; wherein, the fault probability prediction model is repeatedly trained based on the vehicle-related information of the target commercial vehicle in the historical time and the fault labels determined by the fault occurrence situation.

[0016] The prediction result and the result analyzed based on the driving behavior information are integrated into fault evaluation information for storage and sent to the maintenance client corresponding to the fault type for vehicle fault prediction, reminder, and tracking.

[0017] In a possible implementation, after the maintenance client receives the fault evaluation information, the method further includes:

[0018] Access the cloud background to find a fault use case corresponding to the fault type predicted in the current fault evaluation information.

[0019] Combined with the found fault use case, the prediction result in the fault evaluation information is corrected to update fault tracking and management.

[0020] In a possible implementation, the method further includes:

[0021] The maintenance client accesses the cloud background to view vehicle-related information and / or fault cases of different target commercial vehicles.

[0022] In a second aspect, a fault handling system for commercial vehicles is provided, including: a plurality of target commercial vehicles, a cloud background communicatively connected to each target commercial vehicle, and a plurality of maintenance clients connected to the cloud background; wherein, each target commercial vehicle is configured with internal and external sensors and a data collector;

[0023] Each target commercial vehicle is configured to collect vehicle external driving environment and vehicle internal state information based on the configured internal and external sensors, send the information to the local data collector for integrated storage, and upload the integrated vehicle-related information to the cloud background; wherein, the vehicle-related information carries the vehicle identifier or data collector identifier of its corresponding target commercial vehicle;

[0024] The cloud background is configured to receive a plurality of vehicle-related information in real time and perform a fault code scan on each vehicle-related information; after detecting a fault code, input the vehicle-related information containing the fault code into a preset fault recognition model, perform validity verification on the detected fault code based on the fault recognition result, if the verification result is valid, generate a fault case based on the vehicle-related information containing the fault code, and push the identifier of the fault case to the maintenance client corresponding to the fault type of the fault code;

[0025] The maintenance client is configured to access the cloud background based on the received identifier of the fault case, search for a matching fault case, and perform fault troubleshooting and positioning on the target commercial vehicle corresponding to the fault case.

[0026] In a third aspect, an electronic device is provided, including:

[0027] At least one processor; and

[0028] A memory communicatively connected to the at least one processor; wherein,

[0029] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the methods of the above aspects and any possible implementation manners.

[0030] Fourthly, a computer-readable storage medium is provided, in which at least one instruction is stored, and the at least one instruction is loaded and executed by a processor to implement the method of the above-mentioned aspects and any possible implementation manners.

[0031] Fifthly, a computer program product is provided, including a computer program which implements the method of the above-mentioned aspects and any possible implementation manners when being executed by a processor.

[0032] Sixthly, an autonomous vehicle is provided, including the electronic device as described above.

[0033] The beneficial effects of the technical solution provided by this application at least include:

[0034] As can be seen from the above technical solution, in the embodiments of this application, multiple target commercial vehicles collect data through internal and external sensors configured by themselves, and send the data to a local data collector for data integration and storage. Then, the data is uploaded to the cloud background. The cloud background receives the vehicle-related information uploaded by multiple target commercial vehicles. After detecting a fault code through fault scanning, the vehicle-related information containing the fault code is subjected to fault identification through a preset fault identification model. Then, the validity of the fault code is verified by using the fault identification result to ensure the accuracy of the fault; and after the verification is effective, a fault use case is generated, and the identifier of the fault use case is pushed to the corresponding maintenance client. In this way, the maintenance client can access the cloud background based on the identifier of the fault use case to find a matching fault use case, and perform effective and accurate fault troubleshooting and positioning on the corresponding target commercial vehicle. Therefore, this solution can improve the interaction timeliness from the vehicle end to the automotive engineer. The real-time and automatic upload of vehicle-related information, the fault analysis and processing function of the cloud background and the real-time and automatic push function enable the engineer to quickly understand the vehicle information, and improve the fault troubleshooting and positioning and maintenance efficiency.

[0035] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of this application, nor is it used to limit the scope of this application. Other features of this application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of this application, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of this application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0037] Figure 1 It is a schematic diagram of the steps of a fault handling method for a commercial vehicle provided by an embodiment of this application.

[0038] Figure 2 It is a schematic diagram of a fault handling architecture for a commercial vehicle provided by another embodiment of the present application.

[0039] Figure 3 It is a block diagram of a fault handling system for a commercial vehicle provided by an embodiment of the present application.

[0040] Figure 4 It is a block diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0041] The following describes exemplary embodiments of the present application with reference to the accompanying drawings. Various details of the embodiments of the present application are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0042] Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts fall within the scope of protection of the present application.

[0043] It should be noted that the terminal devices involved in the embodiments of the present application may include, but are not limited to, intelligent devices such as mobile phones, personal digital assistants (PDAs), wireless handheld devices, and tablet computers (Tablet Computers); display devices may include, but are not limited to, devices with display functions such as personal computers and televisions.

[0044] In addition, the term "and / or" herein is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after.

[0045] In view of the lack of the ability to statistically analyze faults in the existing fault handling solutions for commercial vehicles, which cannot efficiently identify and diagnose faults and accurately push maintenance, this application proposes a fault handling solution for commercial vehicles. Its main inventive concept lies in that multiple target commercial vehicles collect data through internal and external sensors configured on their own, and send it to the local data collector for data integration and storage. Then, it is uploaded to the cloud background. The cloud background receives the vehicle-related information uploaded by multiple target commercial vehicles. After detecting a fault code through fault scanning, it performs fault identification on the vehicle-related information containing the fault code through a preset fault identification model. Then, it uses the fault identification result to perform validity verification on the fault code to ensure the accuracy of the fault; and generates a fault case after the verification is valid, and pushes the identifier of the fault case to the corresponding maintenance client. In this way, the maintenance client can access the cloud background based on the identifier of the fault case to find a matching fault case, and perform effective and accurate fault troubleshooting and positioning on the corresponding target commercial vehicle. Thus, this solution can improve the interaction timeliness from the vehicle end to the automotive engineer. The real-time and automatic upload of vehicle-related information, the fault analysis and processing of the cloud background, and the real-time and automatic push function enable the engineer to quickly understand the vehicle information, and improve the fault troubleshooting and positioning and maintenance efficiency.

[0046] Referring to Figure 1 shown, it is a schematic diagram of the steps of a fault handling method for commercial vehicles provided by an embodiment of this application. At the same time, combined with Figure 2 the schematic diagram of the fault handling architecture of the commercial vehicle shown.

[0047] As Figure 2 shown, the fault handling system 200 of the commercial vehicle includes: multiple target commercial vehicles 201, a cloud background 202 that has established a communication connection with each target commercial vehicle 201, and multiple maintenance clients 203 connected to the cloud background 202; among them, each target commercial vehicle 201 is configured with internal and external sensors 2011 and a data collector 2012. The internal and external sensors 2011 can be sensor components such as a monocular camera and / or a multi-camera and / or a radar, and are specifically installed or integrated inside or outside the target commercial vehicle 201 for collecting the internal driving state of the target commercial vehicle 201, or for collecting information such as the external driving environment or driving state of the target commercial vehicle 201.

[0048] The multiple target commercial vehicles 201 can be respectively linked to the cloud background 202 through a communication link established by a wireless communication module, and the specific communication mode and protocol are not limited.

[0049] The cloud backend 202 can be a cloud service device provided by the manufacturer of the target commercial vehicle 201 or an autonomous driving module service provider. It can be orchestrated, deployed, and updated through container technology to provide more reliable and diversified cloud-native services. For example, fault code detection and validity verification of fault codes in this application can all be achieved through functions or modules deployed through container technology.

[0050] The maintenance clients 203 can be maintained by different automotive engineers and can be specifically deployed based on fault type. For example, if a target commercial vehicle can be roughly classified into 10 fault types, then 10 different maintenance clients 203 can be deployed, each maintaining a different fault type. Furthermore, if a target commercial vehicle can be classified into 5 fault types, then 5 different types of maintenance clients 203 can be deployed, each type being maintained by multiple automotive engineers.

[0051] like Figure 1 As shown, the commercial vehicle fault handling method may include the following steps:

[0052] Step 102: Each target commercial vehicle collects information about the vehicle's external driving environment and internal status based on its configured internal and external sensors, and sends the information to a local data collector for integration and storage. The integrated vehicle-related information is then uploaded to the cloud backend; wherein the vehicle-related information carries the vehicle identification or data collector identification of the corresponding target commercial vehicle.

[0053] In this application, environmental perception cameras, radars, and in-vehicle status sensors deployed throughout the vehicle can be used to collect information about the vehicle's external driving environment and internal state, enabling comprehensive monitoring and recording of the vehicle's internal and external driving conditions and environment. External driving environment information includes obstacle monitoring, driving road information, and automatically acquired driving weather information. Internal vehicle status information includes driver status monitoring information and in-vehicle natural language input information.

[0054] All data and information obtained by internal and external sensors of the target commercial vehicle can be sent to the local data collector for integration and summary, local storage, and upload the information to the cloud background to ensure reliable data transmission and local backup.

[0055] Step 104: The cloud background receives multiple vehicle-related information in real time and scans the fault codes for each vehicle-related information; after detecting a fault code, the vehicle-related information containing the fault code is input into a preset fault recognition model, and the validity of the detected fault code is verified based on the fault recognition result. If the verification result is valid, a fault use case is generated based on the vehicle-related information containing the fault code, and the identifier of the fault use case is pushed to the maintenance client corresponding to the fault type of the fault code.

[0056] Among them, the preset fault recognition model can be obtained by repeatedly training the fault labels determined based on the vehicle-related information and fault types of the target commercial vehicle in historical time.

[0057] The cloud background scans and detects the fault codes in the vehicle-related information, uses the trained preset fault recognition model to judge the validity of the fault codes. For valid fault codes, fault use cases are automatically generated, and the identifiers of the fault use cases are pushed to the relevant responsible persons. The specific push method can be by text message or phone call reminder. At the same time, the identifier of the fault use case will be sent to the maintenance APP maintained by the relevant responsible person through online push. Thus, the valid fault information can be quickly and accurately pushed to the relevant responsible engineers, enabling the engineers to obtain the detailed information of the faulty vehicle, including the vehicle information, specific faults, and driving status information, at the first time, greatly shortening the fault response time and improving the fault handling efficiency.

[0058] For example, the cloud background, as the server, after receiving the vehicle-related information, first scans and detects it. If a fault code is detected, the vehicle-related information is input into the preset fault recognition model, and the fault recognition result is output. For example, the fault code is P13XX, which represents unstable tire pressure; after inputting the vehicle-related information containing this fault code into the preset fault recognition model, the output result is also unstable tire pressure. Then, if it is consistent with the fault code, it is determined that the fault code is valid. After that, a fault use case can be generated based on the vehicle-related information, and the identifier of the fault use case is marked as T1, and the fault use case and its identifier are saved.

[0059] In the solution of this application, in addition to verifying the validity of the fault codes to improve the accuracy of fault diagnosis and location, the cloud background can also classify and store the multiple vehicle-related information according to the vehicle identifier, and establish multiple vehicle information databases for the maintenance client to view quickly. For example Figure 2As shown in the figure, multiple vehicle information databases are established in the cloud background. That is, the number of vehicle information databases established is equal to the number of target commercial vehicles. In this way, the vehicle-related information of each target commercial vehicle at different times can be stored in the corresponding vehicle information database in the cloud background, without information crossover and confusion, improving the vehicle information management level. In short, the classified storage and efficient retrieval of the vehicle data are realized, which is convenient for engineers to view the information of different vehicles and at different times. Through the generation of fault use cases and the problem tracking and management function, the faults are systematically recorded and analyzed, which helps to summarize the fault rules, optimize the vehicle performance and maintenance strategies, and reduce the operation cost.

[0060] Furthermore, the cloud background of the present application can also extract the vehicle key information from the vehicle-related information. The vehicle key information at least includes: driving road information, obstacle information, weather information, driver status information, and driving behavior information. The features extracted based on the vehicle key information are input into the fault probability prediction model, and the fault probability and fault type that the target commercial vehicle corresponding to the vehicle-related information will occur in the future are predicted. Among them, the fault probability prediction model is obtained by repeatedly training based on the vehicle-related information of the target commercial vehicle at historical times and the fault labels determined by the fault occurrence situations. The prediction result and the result analyzed based on the driving behavior information are integrated into the fault evaluation information for storage, and sent to the maintenance client corresponding to the fault type, so as to perform fault prediction, reminder, and tracking on the target commercial vehicle. Through the real-time analysis of the vehicle driving data and the predictive maintenance calculation, the potential fault risks can be discovered in advance, the predictive diagnosis of the faults can be realized, the opportunity for early intervention in vehicle maintenance can be provided, and the fault occurrence probability can be reduced.

[0061] Step 106: The maintenance client accesses the cloud background based on the received identifier of the fault use case, searches for the matching fault use case, so as to perform fault troubleshooting and positioning on the target commercial vehicle corresponding to the fault use case.

[0062] The identifier of the fault use case can be related information such as license plate number, VIN number, data collector number, fault name, fault time, and the fault number automatically generated in the background.

[0063] Optionally, after the maintenance client receives the fault evaluation information, it can also access the cloud background to search for the fault use case corresponding to the fault type predicted in the current fault evaluation information. Combining the found fault use case, the prediction result in the fault evaluation information is corrected, and the fault tracking and management are updated.

[0064] Optionally, the maintenance client can also access the cloud background to view the vehicle-related information and / or fault use cases of different target commercial vehicles.

[0065] After receiving the fault push information, automotive engineers log in to the maintenance client interface and access the search function of the cloud background to find the corresponding fault cases. On the fault case page, view all relevant information when the fault occurred, including vehicle driving data, environmental information collected by sensors, etc., and conduct fault analysis by combining their own professional knowledge. During the process of analyzing problems, engineers can update the analysis progress, record treatment measures and results under the fault cases to achieve the tracking management of fault problems. At the same time, engineers can also view the information of other relevant vehicles by accessing the vehicle data interface of the cloud background, compare and analyze the causes of faults, summarize experience and lessons, and provide references for subsequent vehicle maintenance and fault handling.

[0066] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0067] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0068] Figure 3 The block diagram of the fault handling system of a commercial vehicle provided by an embodiment of the present application is shown, as Figure 3As shown in the figure. The fault handling system 300 of the commercial vehicle in this embodiment may include a plurality of target commercial vehicles 301, a cloud background 302 communicatively connected to each target commercial vehicle 301, and a plurality of maintenance clients 303 connected to the cloud background 302. Among them, each target commercial vehicle 301 is configured with internal and external sensors and a data collector; each target commercial vehicle 301 is used to collect vehicle external driving environment and vehicle internal state information based on the configured internal and external sensors, and send them to the local data collector for integrated storage, and upload the vehicle-related information obtained by integration to the cloud background; among them, the vehicle-related information carries the vehicle identification or data collector identification of its corresponding target commercial vehicle. The cloud background 302 is used to receive a plurality of vehicle-related information in real time, and perform a fault code scan on each vehicle-related information; after detecting a fault code, input the vehicle-related information containing the fault code into a preset fault identification model, and perform validity verification on the detected fault code based on the fault identification result. If the verification result is valid, generate a fault use case based on the vehicle-related information containing the fault code, and push the identification of the fault use case to the maintenance client corresponding to the fault type of the fault code. The maintenance client 303 accesses the cloud background based on the received identification of the fault use case, searches for a matching fault use case, and performs fault troubleshooting and positioning on the target commercial vehicle corresponding to the fault use case.

[0069] It should be noted that part of the fault handling system of the commercial vehicle in this embodiment may be an application located on the local terminal, or may also be a functional unit such as a plug-in or software development kit (SDK) set in the application located on the local terminal, or may also be a processing engine located in the network-side server, or may also be a distributed system located on the network side. For example, the processing engine or distributed system in the network-side autonomous driving platform, etc. This embodiment does not make special limitations on this.

[0070] It can be understood that the application may be a native app installed on the local terminal, or may also be a web app of a browser on the local terminal. This embodiment does not limit this.

[0071] Optionally, in a possible implementation manner of this embodiment, after the cloud background 302 receives a plurality of vehicle-related information in real time, it is further used to classify and store the plurality of vehicle-related information according to the vehicle identification, and establish a plurality of vehicle information databases for the maintenance client 303 to view quickly.

[0072] Optionally, in a possible implementation of this embodiment, after the cloud background 302 receives multiple pieces of vehicle-related information in real time, it is further configured to extract vehicle key information from the vehicle-related information. The vehicle key information at least includes: driving road information, obstacle information, weather information, driver status information, and driving behavior information; input the features extracted based on the vehicle key information into a failure probability prediction model to predict the failure probability and failure type of the target commercial vehicle corresponding to the vehicle-related information in the future time; wherein, the failure probability prediction model is repeatedly trained based on the vehicle-related information of the target commercial vehicle at historical times and the failure labels determined according to the failure occurrence situations; integrate the prediction result with the result analyzed based on the driving behavior information into failure evaluation information for storage, and send it to the maintenance client 303 corresponding to the failure type, so as to facilitate failure reminder and tracking of the target commercial vehicle.

[0073] Optionally, in a possible implementation of this embodiment, after the maintenance client 303 receives the failure evaluation information, it is further configured to access the cloud background 302 to find a failure use case corresponding to the failure type predicted in the current failure evaluation information; combine the found failure use case to correct the prediction result in the failure evaluation information and update the failure tracking and management.

[0074] Optionally, in a possible implementation of this embodiment, the maintenance client 303 is further configured to access the cloud background 302 to view the vehicle-related information and / or failure use cases of different target commercial vehicles.

[0075] In this embodiment, multiple target commercial vehicles collect data through internally and externally configured sensors, and send it to the local data collector for data integration and storage. Then, it is uploaded to the cloud background. The cloud background receives the vehicle-related information uploaded by multiple target commercial vehicles. After detecting a fault code through a fault scan, it performs fault identification on the vehicle-related information containing the fault code through a preset fault identification model. Then, it uses the fault identification result to verify the validity of the fault code to ensure the accuracy of the fault; and generates a fault use case after the verification is effective, and pushes the identifier of the fault use case to the corresponding maintenance client. In this way, the maintenance client can access the cloud background based on the identifier of the fault use case to find a matching fault use case and perform effective and accurate fault troubleshooting and positioning on the corresponding target commercial vehicle. Thus, this solution can improve the interaction timeliness from the vehicle end to the automotive engineer. The real-time and automatic upload of vehicle-related information, the fault analysis and processing of the cloud background, and the real-time and automatic push function enable the engineer to quickly understand the vehicle information and improve the fault troubleshooting and positioning and maintenance efficiency.

[0076] An embodiment of the present application provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is loaded and executed by a processor to implement the method for fault handling of a commercial vehicle as described above.

[0077] An embodiment of the present application provides an electronic device, which includes a processor and a memory. At least one instruction is stored in the memory, and the instruction is loaded and executed by the processor to implement the method for fault handling of a commercial vehicle as described above.

[0078] An embodiment of the present application provides an autonomous vehicle, including the electronic device as described above. Specifically, the autonomous vehicle can be a vehicle at L2 level or above.

[0079] In the technical solution of the present application, the processing of the collection, storage, use, processing, transmission, provision, and disclosure of the user's personal information involved all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0080] Figure 4 FIG. shows a schematic block diagram of an exemplary electronic device 400 that can be used to implement the embodiments of the present application. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described herein and / or claimed.

[0081] As Figure 4 shown, the electronic device 400 includes a computing unit 401, which can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 402 or the computer program loaded from the storage unit 408 into the random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.

[0082] Multiple components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disc, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0083] The computing unit 401 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 executes the various methods and processes described above, such as the method for fault handling of a commercial vehicle. For example, in some embodiments, the method for fault handling of a commercial vehicle can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method for fault handling of a commercial vehicle described above can be executed. Alternatively, in other embodiments, the computing unit 401 can be configured to execute the method for fault handling of a commercial vehicle by any other suitable means (e.g., by means of firmware).

[0084] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), system-on-chip systems (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs, which can be executed and / or interpreted on a programmable system including at least one programmable processor, the programmable processor can be a special or general-purpose programmable processor, can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, at least one input device, and at least one output device.

[0085] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program codes cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0086] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0087] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0088] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0089] A computer system can include a client and a server. The client and the server are generally far from each other and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, a server of a distributed system, or a server incorporating blockchain.

[0090] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the disclosure of this application can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution disclosed in this application can be achieved, and this is not limited herein.

[0091] The above specific embodiments do not constitute a limitation on the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the protection scope of this application.

Claims

1. A fault handling method for a commercial vehicle, characterized in that, A fault handling system applied to commercial vehicles, the system includes: a plurality of target commercial vehicles, a cloud background that has established a communication connection with each target commercial vehicle, and a plurality of maintenance clients connected to the cloud background; wherein, each target commercial vehicle is configured with internal and external sensors and a data collector; the method includes: Each target commercial vehicle collects vehicle external driving environment and vehicle internal state information based on the configured internal and external sensors, and sends them to the local data collector for integration and storage, and uploads the integrated vehicle-related information to the cloud background; wherein, the vehicle-related information carries the vehicle identifier or data collector identifier of its corresponding target commercial vehicle; The cloud background receives a plurality of vehicle-related information in real time and scans the fault codes for each vehicle-related information; after detecting a fault code, it inputs the vehicle-related information containing the fault code into a preset fault recognition model, and validates the detected fault code based on the fault recognition result. If the verification result is valid, it generates a fault use case based on the vehicle-related information containing the fault code, and pushes the identifier of the fault use case to the maintenance client corresponding to the fault type of the fault code; The maintenance client accesses the cloud background based on the received identifier of the fault use case, searches for a matching fault use case, and locates the fault of the target commercial vehicle corresponding to the fault use case.

2. The method according to claim 1, wherein After the cloud background receives a plurality of vehicle-related information in real time, the method further includes: The cloud background classifies and stores the plurality of vehicle-related information according to the vehicle identifier, and establishes a plurality of vehicle information libraries for the maintenance client to view quickly.

3. The method according to claim 1 or 2, characterized in that After the cloud background receives a plurality of vehicle-related information in real time, the method further includes: The cloud background extracts vehicle key information from the vehicle-related information, and the vehicle key information at least includes: driving road information, obstacle information, weather information, driver state information, and driving behavior information; Input the features extracted based on the vehicle key information into a fault probability prediction model, and predict the fault probability and fault type that the target commercial vehicle corresponding to the vehicle-related information will occur in the future; wherein, the fault probability prediction model is repeatedly trained based on the vehicle-related information of the target commercial vehicle in the historical time and the fault label determined by the fault occurrence situation; Integrate the prediction result with the result analyzed based on the driving behavior information into fault evaluation information for storage, and send it to the maintenance client corresponding to the fault type, so as to perform fault prediction, reminder and tracking on the vehicle.

4. The method according to claim 3, wherein After the maintenance client receives the fault evaluation information, the method further includes: Access the cloud background and search for a fault use case corresponding to the fault type predicted in the current fault evaluation information; Combine the found fault use case to correct the prediction result in the fault evaluation information and update the fault tracking and management.

5. The method according to claim 3, wherein The method further includes: The maintenance client accesses the cloud background to view the vehicle-related information and / or fault use cases of different target commercial vehicles.

6. A fault handling system for a commercial vehicle, characterized in that, Including: a plurality of target commercial vehicles, a cloud background that has established a communication connection with each target commercial vehicle, and a plurality of maintenance clients connected to the cloud background; wherein, each target commercial vehicle is configured with internal and external sensors and a data collector; Each target commercial vehicle is used to collect vehicle external driving environment and vehicle internal state information based on the configured internal and external sensors, and send them to the local data collector for integrated storage, and upload the vehicle-related information obtained by the integration to the cloud background; wherein, the vehicle-related information carries the vehicle identifier or data collector identifier of its corresponding target commercial vehicle; The cloud background is used to receive a plurality of vehicle-related information in real time and perform a fault code scan on each vehicle-related information; after detecting a fault code, input the vehicle-related information containing the fault code into a preset fault identification model, perform validity verification on the detected fault code based on the fault identification result, if the verification result is valid, generate a fault use case based on the vehicle-related information containing the fault code, and push the identifier of the fault use case to the maintenance client corresponding to the fault type of the fault code; The maintenance client is used to access the cloud background based on the received identifier of the fault use case, search for a matching fault use case, so as to perform fault troubleshooting and positioning on the target commercial vehicle corresponding to the fault use case.

7. An electronic device, including: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-5.

8. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.

9. A computer program product, including a computer program, where the computer program, when executed by a processor, implements the method according to any one of claims 1-5.

10. An autonomous vehicle, including the electronic device according to claim 7.

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