Commercial vehicle portable OBD automatic test method and related device
Through the portable OBD automated testing method for commercial vehicles, the test project prediction model and automated execution technology are used to solve the problems of incomplete testing and low efficiency in the existing technology, and more efficient and accurate testing is achieved.
Patent Information
- Application Number
- CN202411568649.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-05
- Publication Date
- 2025-02-18
AI Technical Summary
The existing technology cannot fully cover the test projects, resulting in low test accuracy and seamless switching between test projects, resulting in low testing efficiency.
Provide a portable OBD automated testing method for commercial vehicles. By receiving user test applications, using preset test project prediction models, predicting and sorting test projects, automatically executing test projects, and finally feedback test results.
Improves the accuracy and efficiency of the test project, reduces human errors, saves testing costs, and improves testing flexibility and coverage.
Smart Images
Figure CN119473894A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of computer technology, specifically to the technical fields of intelligent transportation and autonomous driving, and in particular to a portable OBD automated testing method and related devices for commercial vehicles. Background Art
[0002] During the vehicle development process, due to the needs of development business, the vehicle is often tested and the development business is adjusted based on the test results.
[0003] Generally, there is a fixed test vehicle for each vehicle model, so that various test services can be carried out on the test vehicle. The current test services include: single node test, system integration test, real vehicle test, etc. The existing test method requires the tester to cooperate in inputting the required test items each time, and then implement the test items through semi-automatic methods.
[0004] Although the current testing solutions can achieve semi-automated testing, they often fail to fully cover the test items related to the testing requirements of the development business due to inaccurate human judgment. Moreover, there is no seamless switching between test items, which leads to low test accuracy and low test efficiency. Summary of the invention
[0005] The present application provides a portable OBD automated testing method and related devices for commercial vehicles to solve the problems in the prior art of being unable to fully cover the test items resulting in low test accuracy, and the problems of time-consuming and labor-intensive execution of the test items and the inability to achieve seamless switching resulting in low test efficiency.
[0006] The technical solution is as follows:
[0007] In a first aspect, a commercial vehicle portable OBD automated testing method is provided, comprising:
[0008] Receiving a test application submitted by a user, wherein the test application carries at least one test requirement of the user for vehicle development;
[0009] Based on at least one test requirement in the test application, one or more test items corresponding to the test application are predicted using a preset test item prediction model; wherein the test item prediction model is obtained by repeated training based on historical test requirements and corresponding test items; the one or more test items are directly or indirectly associated with the current test requirement; and the test content of each test item is generated based on software code and hardware tool configuration;
[0010] If a test item is predicted, the test vehicle is tested according to the test content of the test item;
[0011] If multiple test items are predicted, the multiple test items are sorted according to the priorities corresponding to the multiple test items and the association with the test requirements, and the test vehicle is tested according to the test content of each test item in turn based on the sorting result;
[0012] The test result is fed back to the user.
[0013] In a possible implementation, the plurality of test items are sorted according to the priorities corresponding to the plurality of test items and the association with the test requirements, and the test vehicle is tested in turn according to the test content of each test item based on the sorting result, specifically including:
[0014] Preliminarily sorting the multiple test items according to the order of priorities corresponding to the multiple test items from high to low;
[0015] If there are at least two test items of the same priority level after the preliminary sorting, re-sorting the at least two test items of the same priority level according to the degree of association with the test requirements;
[0016] Based on the sorting result, each test item is executed in sequence: the test vehicle is tested according to the test content of the test item.
[0017] In a possible implementation, testing the test vehicle according to the test content of the test item specifically includes:
[0018] According to the test item, searching for corresponding test content from a test item library;
[0019] Based on the tool identification carried in the test content, prompt and trigger to start the software and / or hardware test tool corresponding to the tool identification;
[0020] The test vehicle is tested based on the turned-on test tool and the test content.
[0021] In a possible implementation, after feeding back the test result to the user, the method further includes:
[0022] Receive a configuration application submitted by a user, wherein the configuration application carries a new test project script determined by the user based on the user's own test requirements, and the configuration application is submitted when the user's evaluation of the test result is unreasonable;
[0023] Generate a new test item based on the new test item script in the configuration application;
[0024] The test content of the new test item is updated to the test item library.
[0025] In one possible implementation, the test item prediction model is a neural network model, including at least one of the following: a deep neural network, a recurrent neural network, and a convolutional neural network.
[0026] In a second aspect, a portable OBD automatic testing device for commercial vehicles is provided, comprising:
[0027] A receiving module, used to receive a test application submitted by a user, wherein the test application carries at least one test requirement of the user for vehicle development;
[0028] A prediction module, configured to predict one or more test items corresponding to the test application based on at least one test requirement in the test application using a preset test item prediction model; wherein the test item prediction model is obtained by repeated training based on historical test requirements and corresponding test items; the one or more test items are directly or indirectly associated with the current test requirement; and the test content of each test item is generated based on software code and hardware tool configuration;
[0029] a test module, configured to test the test vehicle according to the test content of the test item if a test item is predicted; and
[0030] for, if a plurality of test items are predicted, sorting the plurality of test items according to the priorities corresponding to the plurality of test items and the association with the test requirements, and testing the test vehicle according to the test content of each test item in turn based on the sorting result;
[0031] The sending module is used to feed back the test result to the user.
[0032] In a third aspect, a computer-readable storage medium is provided, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the method of the aspect as described above and any possible implementation method.
[0033] In a fourth aspect, an electronic device is provided, including:
[0034] at least one processor; and
[0035] a memory communicatively connected to the at least one processor; wherein,
[0036] The memory stores instructions that can be executed 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 perform the method of any possible implementation manner and the aspects described above.
[0037] According to a fifth aspect, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the above-mentioned aspects and any possible implementation method.
[0038] In a sixth aspect, a commercial vehicle testing system based on an OBD interface is provided, comprising the electronic device as described above.
[0039] The beneficial effects of the technical solution provided by this application include at least:
[0040] It can be seen from the above technical scheme that the embodiment of the present application can use the test item prediction model based on at least one test requirement in the test application submitted by the user to predict one or more test items that are directly or indirectly associated with the test requirement for the test application, and the test content of each test item is generated based on the software code and hardware tool configuration; if a test item is predicted, the test vehicle is tested according to the test content of the test item; if multiple test items are predicted, the multiple test items are first sorted according to the priorities corresponding to the multiple test items and the association with the test requirements, and then the test vehicle is tested according to the test content of each test item in turn based on the sorting results; finally, the test results are returned to the user. This test scheme does not require the participation of testers. After receiving the test application submitted by the tester, the model trained by machine learning is automatically predicted. Compared with the tester and the test items selected by experience, the accuracy of determining the test items is improved, thereby improving the test accuracy. Moreover, the switching between test items does not require the participation of testers, and is automatically executed in sequence according to the sorting results, which improves the test efficiency and saves the test cost. In addition, considering that the test content of each test item is generated based on software code and hardware tool configuration, the test solution can cover a more comprehensive range of test items and can flexibly expand and configure test items according to user needs, thereby improving test flexibility and breadth.
[0041] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0043] Figure 1 It is a schematic diagram of the steps of the commercial vehicle portable OBD automated testing method provided in an embodiment of the present application.
[0044] Figure 2 It is a schematic diagram of the test flow provided in the embodiment of the present application.
[0045] Figure 3 It is a structural block diagram of a portable OBD automatic testing device for commercial vehicles provided in an embodiment.
[0046] Figure 4 It is a block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0047] The following is a description of exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art 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 the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.
[0048] Obviously, the described embodiments are only part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.
[0049] It should be noted that the terminal devices involved in the embodiments of the present application may include but are not limited to mobile phones, personal digital assistants (PDAs), wireless handheld devices, tablet computers and other smart devices; display devices may include but are not limited to personal computers, televisions and other devices with display functions.
[0050] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.
[0051] Although the current test solution can achieve semi-automatic testing, considering that the corresponding test items are selected manually, key test items are often missed due to inaccurate human judgment, resulting in failure to fully cover the test items related to the test requirements of the development business. Moreover, the switching between test items also requires human participation and management, and seamless switching cannot be achieved, resulting in low test accuracy and low test efficiency.
[0052] To this end, the present application proposes a commercial vehicle portable OBD automated testing solution, the inventive concept of which is: based on at least one test requirement in the test application submitted by the user, a test item prediction model is used to predict one or more test items that are directly or indirectly associated with the test requirement for the test application, and the test content of each test item is generated based on the software code and hardware tool configuration; if one test item is predicted, the test vehicle is tested according to the test content of the test item; if multiple test items are predicted, the multiple test items are first sorted according to the priorities corresponding to the multiple test items and the association with the test requirements, and then the test vehicle is tested according to the test content of each test item in turn based on the sorting results; finally, the test results are returned to the user. The test solution does not require the participation of the tester. After receiving the test application submitted by the tester, the model trained by machine learning is automatically predicted. Compared with the tester and the test items selected by experience, the accuracy of determining the test items is improved, thereby improving the test accuracy. Moreover, the switching between test items does not require the participation of the tester, and is automatically executed in sequence according to the sorting results, which improves the test efficiency and saves the test cost. In addition, considering that the test content of each test item is generated based on software code and hardware tool configuration, the test solution can cover a more comprehensive range of test items and can flexibly expand and configure test items according to user needs, thereby improving test flexibility and breadth.
[0053] The commercial vehicle testing scheme involved in this application is described in detail below through specific embodiments.
[0054] Reference Figure 1 As shown, it is a schematic diagram of the steps of the portable OBD automated testing method for commercial vehicles provided in an embodiment of the present application. It should be noted that the executor of the commercial vehicle testing solution can be a test device connected to the commercial vehicle based on the OBD interface. In the present application, the test device can be a software module with computing and data processing capabilities, or it can be an electronic device integrated with similar software modules. Optionally, the executor of the test device in the present application can be a test platform for commercial vehicles, which can provide testing services for new energy vehicles, self-driving vehicles, etc., such as electric trucks, unmanned delivery vehicles, unmanned taxis and other types of test vehicles.
[0055] like Figure 1 As shown, the commercial vehicle portable OBD automated testing method may specifically include the following steps:
[0056] Step 102: Receive a test application submitted by a user, where the test application carries at least one test requirement of the user for vehicle development.
[0057] In the present application, the user may be a developer or a tester. In other words, a developer may directly connect to the test device and input the developer's test application through the user interface of the client of the test device; or a tester may connect to the test device, but before that, the tester needs to collect the test requirements of one or more developers, generate corresponding test applications according to the test requirements, and input them into the user interface of the client of the test device.
[0058] The test application carries one or more test requirements required for vehicle development, where each test requirement can be a description of a specific test service, such as testing a vehicle system; or, it can be a description of a test of a component, such as testing a gearbox. Or, it can be other types, for example, the test requirement is a test code, and the test code represents a specific test service or a test of a component. Regardless of the type of test requirement, as long as the test device can read and identify it, this application does not limit it.
[0059] Step 104: Based on at least one test requirement in the test application, use a preset test item prediction model to predict one or more test items corresponding to the test application; wherein the test item prediction model is obtained by repeated training based on historical test requirements and corresponding test items; the one or more test items are directly or indirectly associated with this test requirement; and the test content of each test item is generated based on software code and hardware tool configuration.
[0060] Considering that the accuracy of the test items selected manually is not enough and has great limitations. Therefore, in the present application scheme, the selected neural network model can be repeatedly trained based on the historical test requirements as training samples and the test items corresponding to the historical test requirements as labels, so as to obtain a converged test item prediction model for predicting the test items. Furthermore, after receiving the test application, at least one test requirement in the test application is input into the test item prediction model to predict one or more test items corresponding to the test application. Moreover, the predicted test items have a direct or indirect correlation with the current test requirements. For example, the test requirement is to test the gearbox, and the predicted test items are: "test gearbox" and "test engine", among which "test gearbox" has a direct correlation with the test requirement, and because the engine will also affect the gearbox, "test engine" has an indirect correlation with the test requirement.
[0061] In the present application, the test content of each test item is generated based on the software code and hardware tool configuration. In other words, each test item is configurable, and the software code and hardware tools need to support the configuration at the same time. For example, for the test item of testing current, it is necessary to write the corresponding software test code to trigger the execution of the corresponding test content. At the same time, there must be a hardware tool that can execute the test content, such as a multimeter. It should be understood that the hardware tool can be a component or device that comes with the test vehicle, or it can be an external test gadget, and this application does not limit this.
[0062] In addition, in the present application, each test item can be regarded as a minimum test item unit, that is, the test item prediction model predicts the test items with the smallest granularity, and its accuracy is relatively high.
[0063] Optionally, the test item prediction model is a neural network model, including at least one of the following: deep neural network, recurrent neural network, convolutional neural network and other machine learning models. In addition, other achievable non-neural network models can be flexibly selected according to needs, such as decision tree models, etc. This application does not describe this in detail. The model principle can refer to the existing solution, and the test item related content can refer to the above examples.
[0064] Step 106: If a test item is predicted, the test vehicle is tested according to the test content of the test item.
[0065] If a test item is predicted, the corresponding test content is searched from the test item library according to the test item; based on the tool identifier carried in the test content, a prompt and trigger are provided to open the software and / or hardware test tool corresponding to the tool identifier; and the test vehicle is tested based on the opened test tool and the test content.
[0066] It should be noted that in the test project library, multiple test projects are stored in advance, and each test project is configured with corresponding test content generated based on software code and hardware tools. After a test project is predicted, the test content is matched from the test project library according to the test project, and then the corresponding software test tool and / or hardware test tool is triggered to be started based on the tool identifier, and then the test tool is used to execute the test content to complete the test of the test vehicle.
[0067] The test items in the test item library include: current test items, voltage test items, resistance test items, capacitance test items, bus message waveform test items, bus message data test items, diagnostic protocol test items (which contain many test contents formulated through diagnostic protocols), diagnostic DTC consistency test items, real vehicle diagnostic flash test items, offline electrical inspection test items, etc.
[0068] Among them, current, voltage and resistance test: This test tool has a built-in small multimeter to test the bus segment resistance, voltage and current. According to the set resistance, current and voltage, the physical layer is tested for troubleshooting. Bus waveform analysis test: The built-in oscilloscope displays the waveform, tests the physical layer level signal voltage, bus communication voltage, signal rising and falling edge jump time, BusOff self-recovery test, and vehicle segment waveform test to prevent the problem of poor waveform signal. Diagnostic protocol test: The host computer (client) tests the commonly used diagnostic protocols of the whole vehicle by configuring the UDS test items to meet the basic requests and responses of the diagnostic service and the accuracy of the negative response NRC. Diagnostic flash test: Configure the software flash package and perform forward test and interrupt transmission test. Offline electrical inspection test: The diagnostic module configures the key message signal, and the service or key message signal analysis determines the electronic and electrical function test of the whole vehicle. Diagnostic DTC consistency test: The host computer tests the power-on and power-off moments, the use of high-power electrical appliances, and whether there is a fault report when the whole vehicle is driving normally, and analyzes whether the DM1 message is consistent with the fault read by the service. In addition, it may also include: diagnostic service test or key message signal analysis test and other test items. The above is only used as an example, and does not show the test contents of the test items covered by this application one by one.
[0069] Step 108: If multiple test items are predicted, the multiple test items are sorted according to their respective priorities and their association with the test requirements, and the test vehicle is tested in turn according to the test content of each test item based on the sorting result.
[0070] Optionally, the present application may preliminarily sort the multiple test items according to the order of their respective priorities from high to low; if there are at least two test items of the same priority level after the preliminary sorting, then the at least two test items of the same priority level are re-sorted according to the degree of association with the test requirements; based on the sorting result, execute for each test item in turn: test the test vehicle according to the test content of the test item.
[0071] In fact, the priorities of multiple test items and the degree of relevance to the test requirements can also be considered at the same time, and the priorities and degrees of relevance can be scored and weighted respectively. In this way, the score value of each test item can be calculated, sorted according to the score value, and each test item can be executed in turn based on the sorting result: the test vehicle is tested according to the test content of the test item.
[0072] In the present application, the degree of association with the test requirement is determined by direct association or indirect association with the test requirement. For example, a direct association is scored higher, an indirect association is scored lower, and the larger the interval of the indirect association, the lower the score.
[0073] When testing the test vehicle according to the test content of the test item, the corresponding test content can be found from the test item library according to the test item; based on the tool identifier carried in the test content, a prompt and trigger to start the software and / or hardware test tool corresponding to the tool identifier is triggered; based on the started test tool and the test content, the test vehicle is tested. For details, please refer to the example description of predicting a test item, which will not be repeated here.
[0074] Step 110: Feedback the test result to the user.
[0075] The test result can be fed back to the client interface of the test device in the form of a test report, which is more intuitive and convenient.
[0076] In the present application, the transmission of test requirements and test results can rely on the link established by the OBD interface, that is, a communication connection is established between the OBD interface of the test vehicle and the test device to transmit data.
[0077] Optionally, after the test results are fed back to the user, if the user's evaluation of the test results is unreasonable, that is, the test results do not meet the user's needs, a configuration application submitted by the user can also be received, the configuration application carries a new test project script determined by the user based on his own test needs; based on the new test project script in the configuration application, a new test project is generated; and the test content of the new test project is updated to the test project library.
[0078] In other words, if the user is not satisfied with the current test results or test items, he or she can also apply for configuration updates to the test item library to flexibly expand the test items and improve the flexibility and breadth of the test.
[0079] Figure 2 A schematic diagram of the test process provided for an embodiment of the present application.
[0080] After the test vehicle is connected to the test device through the test OBD interface, it can receive test applications or configuration applications. For test applications, the corresponding test items are predicted based on the internal model. Some examples of test items are given on the right. Due to the different hardware tools used, the first row uses test tools such as multimeters and oscilloscopes, and the second row uses the client interface. Therefore, the test items in the two rows on the right can be executed at the same time. For configuration applications, configurable test scripts are generated and the test project library is updated. Through this portable test tool, all test items of the whole vehicle are analyzed. Users only need to configure the relevant test items, which can be executed through the configured test scripts, and finally generate a visual test report, which is convenient and efficient.
[0081] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.
[0082] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0083] Figure 3 FIG. 1 shows a block diagram of a portable OBD automated testing device for commercial vehicles provided by an embodiment of the present application. Figure 3As shown. The commercial vehicle test 300 based on the OBD interface of this embodiment may include a receiving module 301, a prediction module 302, a testing module 303 and a sending module 304. The receiving module 301 is used to receive a test application submitted by a user, and the test application carries at least one test requirement for the user to develop a whole vehicle; the prediction module 302 is used to predict one or more test items corresponding to the test application based on the at least one test requirement in the test application using a preset test item prediction model; wherein the test item prediction model is obtained by repeated training based on historical test requirements and corresponding test items; the one or more test items have a direct or indirect association with the current test requirement; the testing module 303 is used to test the test vehicle according to the test content of the test item if a test item is predicted; and, if multiple test items are predicted, the multiple test items are sorted according to the priorities corresponding to the multiple test items and the association with the test requirements, and the test vehicle is tested according to the test content of each test item in turn based on the sorting result; the sending module 304 is used to feed back the test results to the user.
[0084] It should be noted that part or all of the commercial vehicle portable OBD automatic testing device of this embodiment may be an application located in 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 in the local terminal, or may also be a processing engine located in a network-side server, or may also be a distributed system located on the network side, for example, a processing engine or distributed system in an autonomous driving platform on the network side, etc. This embodiment does not specifically limit this.
[0085] It is understandable that the application may be a local program (nativeApp) installed on the local terminal, or may be a webpage program (webApp) of a browser on the local terminal, which is not limited in this embodiment.
[0086] Optionally, in a possible implementation of this embodiment, the test module 303 is specifically used to preliminarily sort the multiple test items according to the order of their respective priorities from high to low; if there are at least two test items with the same priority level after the preliminary sorting, then according to the degree of association with the test requirements, the at least two test items with the same priority level are re-sorted; based on the sorting result, for each test item in turn, execute: testing the test vehicle according to the test content of the test item.
[0087] Optionally, in a possible implementation of this embodiment, when the test module 303 tests the test vehicle according to the test content of the test item, it is specifically used to search for corresponding test content from a test item library according to the test item; based on the tool identifier carried in the test content, prompt and trigger the opening of the software and / or hardware test tool corresponding to the tool identifier; and test the test vehicle based on the opened test tool and the test content.
[0088] Optionally, in a possible implementation of this embodiment, the commercial vehicle testing device based on the OBD interface further includes: a generating module and an updating module; after the sending module feeds back the test result to the user:
[0089] The receiving module is further used to receive a configuration application submitted by a user, wherein the configuration application carries a new test project script determined by the user based on his / her own test requirements, and the configuration application is submitted when the user's evaluation of the test result is unreasonable;
[0090] The generating module is used to generate a new test item based on the new test item script in the configuration application;
[0091] The updating module is used to update the test content of the new test item to the test item library.
[0092] Optionally, in a possible implementation of this embodiment, the test item prediction model is a neural network model, including at least one of the following: a deep neural network, a recurrent neural network, and a convolutional neural network.
[0093] In this embodiment, based on at least one test requirement in the test application submitted by the user, the test item prediction model can be used to predict one or more test items that are directly or indirectly associated with the test requirement for the test application, and the test content of each test item is generated based on the software code and hardware tool configuration; if one test item is predicted, the test vehicle is tested according to the test content of the test item; if multiple test items are predicted, the multiple test items are first sorted according to the priorities corresponding to the multiple test items and the association with the test requirements, and then the test vehicle is tested according to the test content of each test item in turn based on the sorting results; finally, the test results are returned to the user. This test scheme does not require the participation of testers. After receiving the test application submitted by the tester, the model trained by machine learning is automatically predicted. Compared with the tester and the test items selected by experience, the accuracy of determining the test items is improved, thereby improving the test accuracy. Moreover, the switching between test items does not require the participation of the tester, and is automatically executed in sequence according to the sorting results, thereby improving the test efficiency and saving the test cost. In addition, considering that the test content of each test item is generated based on software code and hardware tool configuration, the test solution can cover a more comprehensive range of test items and can flexibly expand and configure test items according to user needs, thereby improving test flexibility and breadth.
[0094] An embodiment of the present application provides a computer-readable storage medium, wherein the storage medium stores at least one instruction, and the at least one instruction is loaded and executed by a processor to implement the commercial vehicle testing method based on the OBD interface as described above.
[0095] An embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the commercial vehicle testing method based on the OBD interface as described above.
[0096] An embodiment of the present application provides a portable OBD automated testing system for commercial vehicles, including the electronic device described above. Specifically, the testing system can be applied to autonomous driving vehicles, for example, can be applied to L2 level and above vehicle testing.
[0097] In the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the relevant laws and regulations and do not violate public order and good morals.
[0098] Figure 4A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, 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 and / or required herein.
[0099] like Figure 4 As shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a 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 via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.
[0100] 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 disk, 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 through a computer network such as the Internet and / or various telecommunication networks.
[0101] The computing unit 401 may be a variety of general and / or special 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, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as a commercial vehicle testing method based on an OBD interface. For example, in some embodiments, a commercial vehicle testing method based on an OBD interface may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on 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 commercial vehicle testing method based on the OBD interface described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the commercial vehicle testing method based on the OBD interface in any other appropriate manner (for example, by means of firmware).
[0102] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0103] The program code for implementing the method 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, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0104] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0105] 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 pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types 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, voice input, or tactile input).
[0106] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.
[0107] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.
[0108] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps disclosed in this application can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in this application can be achieved, and this document does not limit this.
[0109] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art 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 should be included in the protection scope of this application.
Claims
1. A commercial vehicle portable OBD automated testing method, characterized in that: include: Receiving a test application submitted by a user, wherein the test application carries at least one test requirement of the user for vehicle development; Based on at least one test requirement in the test application, one or more test items corresponding to the test application are predicted using a preset test item prediction model; wherein the test item prediction model is obtained by repeated training based on historical test requirements and corresponding test items; the one or more test items are directly or indirectly associated with the current test requirement; and the test content of each test item is generated based on software code and hardware tool configuration; If a test item is predicted, the test vehicle is tested according to the test content of the test item; If multiple test items are predicted, the multiple test items are sorted according to the priorities corresponding to the multiple test items and the association with the test requirements, and the test vehicle is tested according to the test content of each test item in turn based on the sorting result; The test result is fed back to the user.
2. The method according to claim 1, characterized in that The plurality of test items are sorted according to the priorities corresponding to the plurality of test items and the correlation with the test requirements, and the test vehicle is tested in turn according to the test content of each test item based on the sorting result, specifically including: Preliminarily sorting the multiple test items according to the order of priorities corresponding to the multiple test items from high to low; If there are at least two test items of the same priority level after the preliminary sorting, re-sorting the at least two test items of the same priority level according to the degree of association with the test requirements; Based on the sorting result, each test item is executed in sequence: the test vehicle is tested according to the test content of the test item.
3. The method according to claim 2, characterized in that The test vehicle is tested according to the test contents of the test items, specifically including: According to the test item, searching for corresponding test content from a test item library; Based on the tool identification carried in the test content, prompt and trigger to start the software and / or hardware test tool corresponding to the tool identification; The test vehicle is tested based on the turned-on test tool and the test content.
4. The method according to claim 3, characterized in that After feeding back the test result to the user, the method further includes: Receive a configuration application submitted by a user, wherein the configuration application carries a new test project script determined by the user based on the user's own test requirements, and the configuration application is submitted when the user's evaluation of the test result is unreasonable; Generate a new test item based on the new test item script in the configuration application; The test content of the new test item is updated to the test item library.
5. The method according to any one of claims 1 to 4, characterized in that: The test item prediction model is a neural network model, including at least one of the following: a deep neural network, a recurrent neural network, and a convolutional neural network.
6. A portable OBD automatic test device for commercial vehicles, characterized in that: include: A receiving module, used to receive a test application submitted by a user, wherein the test application carries at least one test requirement of the user for vehicle development; A prediction module, configured to predict one or more test items corresponding to the test application based on at least one test requirement in the test application using a preset test item prediction model; wherein the test item prediction model is obtained by repeated training based on historical test requirements and corresponding test items; the one or more test items are directly or indirectly associated with the current test requirement; and the test content of each test item is generated based on software code and hardware tool configuration; a test module, configured to test the test vehicle according to the test content of the test item if a test item is predicted; and for, if a plurality of test items are predicted, sorting the plurality of test items according to the priorities corresponding to the plurality of test items and the association with the test requirements, and testing the test vehicle according to the test content of each test item in turn based on the sorting result; The sending module is used to feed back the test result to the user.
7. An electronic device comprising: at least one processor; as well as 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 to enable the at least one processor to perform the method according to any one of claims 1 to 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, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 5.
10. A portable OBD automatic testing system for commercial vehicles, comprising the electronic device according to claim 7.