A data processing method, apparatus, terminal equipment, and medium

Abstract

This application relates to the field of data processing technology, and provides a data processing method, apparatus, terminal device, and computer-readable storage medium. The method includes: acquiring data to be processed collected by a vehicle during a test; if the key information of the data to be processed fails to match any of the preset tags in a preset tag set, then determining a first tag corresponding to the data to be processed based on the key information; adding the first tag to the preset tag set, and storing the data to be processed in association with the first tag. Compared with the prior art which requires manual labeling, this method can directly add a first tag corresponding to the data to be processed based on the key information when it detects that the data to be processed fails to match any of the preset tags. This achieves accurate data matching without manual intervention, reducing labor costs and improving the accuracy of data matching. Adding the first tag to the preset tag set also facilitates subsequent data matching.

Description

Technical Field

[0001] This application belongs to the field of data processing technology, and in particular relates to a data processing method, apparatus, terminal equipment and computer-readable storage medium. Background Technology

[0002] The development of autonomous driving requires extensive real-vehicle testing. As a result, a large amount of test data is generated during the testing phase, such as test data records, CAN signals during vehicle operation, and log information from the underlying processor.

[0003] To screen data from different scenarios for experimentation and verification, existing technologies typically rely on manual methods to compare and label the test data, categorizing it into different scenarios. However, manual methods are prone to errors, resulting in high labor costs and low accuracy. Summary of the Invention

[0004] This application provides a data processing method, apparatus, terminal device, and computer-readable storage medium, which not only reduces labor costs but also improves the accuracy of data matching.

[0005] In a first aspect, embodiments of this application provide a data processing method, including:

[0006] Acquire the data to be processed collected by the vehicle during the testing process;

[0007] If the key information of the data to be processed fails to match any of the preset tags in the preset tag set, then the first tag corresponding to the data to be processed is determined based on the key information.

[0008] The first tag is added to the preset tag set, and the data to be processed is associated with and stored with the first tag.

[0009] Optionally, acquiring the data to be processed collected by the vehicle during the testing process includes:

[0010] Obtain vehicle test data during the testing process;

[0011] Determine the time corresponding to the abnormal data present in the vehicle test data;

[0012] The effective data time range is determined based on the time, and the data in the vehicle test data that falls within the effective data time range is identified as the data to be processed.

[0013] Optionally, after acquiring the data to be processed collected by the vehicle during the testing process, the following may also be included:

[0014] If the key information of the data to be processed successfully matches the second tag in the preset tag set, the data to be processed is associated with and stored with the second tag.

[0015] Optionally, determining the first tag corresponding to the data to be processed based on the key information includes:

[0016] Determine the appropriate scenarios and text formats for each preset tag;

[0017] Extract the first keyword corresponding to the adapted scenario from the key information;

[0018] The format of the first keyword is adjusted according to the text format to obtain the first tag.

[0019] Optionally, the data to be processed includes multiple data sets. After adding the first tag to the preset tag set and associating and storing the data to be processed with the first tag, the method further includes:

[0020] Multiple data sets to be processed are classified according to the preset label set to obtain multiple first datasets; wherein each first dataset contains at least one data set to be processed under the same label;

[0021] Output the label matching result information of the preset label set based on the multiple first datasets.

[0022] Optionally, after adding the first tag to the preset tag set and associating and storing the data to be processed with the first tag, the method further includes:

[0023] Receive a data query request; the data query request carries the attribute information of the data to be queried;

[0024] Perform keyword extraction on the attribute information to obtain the second keyword corresponding to the data to be queried;

[0025] Based on the second keyword, a target dataset is selected from the plurality of first datasets.

[0026] Optionally, the data to be processed includes vehicle information and test result information; after adding the first tag to the preset tag set and associating and storing the data to be processed with the first tag, the method further includes:

[0027] Based on the vehicle information and the test result information, multiple datasets to be processed are classified to obtain multiple second datasets;

[0028] Based on the multiple second datasets, the vehicle test pass rate is calculated.

[0029] The testing process for the vehicle is adjusted based on the test pass rate and / or the tag matching results.

[0030] Secondly, embodiments of this application provide a data processing apparatus, including:

[0031] The first acquisition unit is used to acquire the data to be processed collected by the vehicle during the testing process;

[0032] The first determining unit is configured to determine the first tag corresponding to the data to be processed based on the key information if the key information of the data to be processed fails to match each of the preset tags in the preset tag set.

[0033] The adding unit is used to add the first tag to the preset tag set and associate the data to be processed with the first tag for storage.

[0034] Thirdly, embodiments of this application provide a terminal device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the data processing method as described in any one of the first aspects above.

[0035] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the data processing method as described in any one of the first aspects above.

[0036] Fifthly, embodiments of this application provide a computer program product that, when run on a terminal device, enables the terminal device to execute the data processing method described in any one of the first aspects.

[0037] The beneficial effects of the embodiments in this application compared with the prior art are:

[0038] This application provides a data processing method that acquires data to be processed collected by a vehicle during testing. If the key information of the data to be processed fails to match any of the preset tags in a preset tag set, a first tag corresponding to the data to be processed is determined based on the key information. The first tag is added to the preset tag set, and the data to be processed is associated with and stored with the first tag. Compared with the prior art, which requires manual labeling, the method provided in this application can directly add a first tag corresponding to the data to be processed based on the key information when it is detected that the data to be processed fails to match any of the preset tags. This achieves accurate data matching without manual intervention, reducing labor costs and improving the accuracy of data matching. Adding the first tag to the preset tag set also facilitates subsequent data matching. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating the implementation of a data processing method provided in an embodiment of this application;

[0041] Figure 2 This is a flowchart illustrating the implementation of a data processing method provided in another embodiment of this application;

[0042] Figure 3 This is a flowchart illustrating the implementation of a data processing method provided in another embodiment of this application;

[0043] Figure 4 This is a flowchart illustrating the implementation of a data processing method provided in another embodiment of this application;

[0044] Figure 5 This is a flowchart illustrating the implementation of a data processing method provided in another embodiment of this application;

[0045] Figure 6 This is a schematic diagram of the structure of a data processing apparatus provided in an embodiment of this application;

[0046] Figure 7 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Detailed Implementation

[0047] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0048] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0049] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0050] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0051] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0052] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0053] Please see Figure 1 , Figure 1 This is a flowchart illustrating the implementation of a data processing method according to an embodiment of this application. In this embodiment, the data processing method is executed by a terminal device.

[0054] like Figure 1 As shown, a data processing method provided in one embodiment of this application may include S101 to S103, which are described in detail below:

[0055] In S101, the data to be processed collected by the vehicle during the testing process is acquired.

[0056] In practical applications, the development of autonomous driving requires extensive real-vehicle testing, which generates a large amount of test data, such as test data records, CAN signals during vehicle operation, and log information from the underlying processor. To achieve automatic management of this test data, and to compare and label it to categorize it into different scenarios, users can send data processing requests to the terminal device.

[0057] In this embodiment, the terminal device detects a data processing request sent by the user by detecting that the user triggers a first preset operation on the terminal device. The first preset operation can be set according to actual needs and is not limited here. For example, the first preset operation can be clicking a first preset control on the terminal device. Therefore, when the terminal device detects that the first preset control has been clicked, it indicates that the first preset operation has been detected, that is, a data processing request sent by the user has been detected.

[0058] After detecting the aforementioned data processing request, the terminal device can acquire the data to be processed collected by the vehicle during the testing process. This data to be processed may include multiple data sets.

[0059] In one embodiment of this application, the terminal device can obtain data to be processed in real time through a server with which it is wirelessly connected. The server can be a computer or a cloud server.

[0060] In another embodiment of this application, the terminal device can also acquire the data to be processed collected by the vehicle during the testing process through the following steps, detailed below:

[0061] Obtain vehicle test data during the testing process;

[0062] Determine the time corresponding to the abnormal data present in the vehicle test data;

[0063] The effective data time range is determined based on the time, and the data in the vehicle test data that falls within the effective data time range is identified as the data to be processed.

[0064] In one implementation of this embodiment, the terminal device can obtain vehicle test data during the testing process in real time through a server with which it is wirelessly connected. The server can be a computer or a cloud server.

[0065] In another implementation of this embodiment, the terminal device can pre-acquire vehicle test data during the testing process through other devices and store the vehicle test data in its own memory. When the terminal device needs to retrieve the vehicle test data, it can retrieve the vehicle test data from its own memory. The other devices can be various sensors that collect data during the vehicle testing process.

[0066] It should be noted that vehicle test data refers to all data generated during the vehicle's testing process. Each data point includes the time it was generated.

[0067] In this embodiment, abnormal data is used to describe data generated by the vehicle during the test that does not conform to the preset results. The preset results can be set according to actual needs and are not limited here.

[0068] After determining the time corresponding to the abnormal data in the vehicle test data, in order to improve the processing efficiency of the terminal device and facilitate subsequent adjustments and optimizations of the test process by relevant personnel based on the vehicle test data, the terminal device can determine the effective data time range corresponding to the time of the abnormal data, and identify all data in the vehicle test data that falls within this effective data time range as data to be processed. The effective data time range can be set according to actual needs and is not limited here.

[0069] In one implementation of this embodiment, to improve the processing efficiency of the terminal device, abnormal data is stored so that the vehicle testing process can be adjusted and optimized subsequently based on the stored abnormal data. The terminal device can determine the effective data time range with the time corresponding to the abnormal data as the center and a set duration as the range. The set duration can be set according to actual needs and is not limited here. For example, the set duration can be ±1 second.

[0070] Based on this, assuming the time corresponding to the abnormal data is 12:20:01 (i.e., 12:20:01), and the duration is set to 1 second, the terminal device can identify all data within the period from 12:20:00 (i.e., 12:20:00) to 12:20:02 (i.e., 12:20:02) as data to be processed.

[0071] In this embodiment, after acquiring the data to be processed, the terminal device performs keyword extraction on the data to obtain key information corresponding to the data. This key information includes, but is not limited to, vehicle information and the test scenario. Vehicle information includes, but is not limited to, vehicle model and speed.

[0072] In one embodiment of this application, when the data to be processed includes image data, the terminal device can perform image recognition on the image data in the data to be processed to determine the text information corresponding to the image data, and then perform keyword extraction operation based on the text information to obtain the key information corresponding to the data to be processed.

[0073] It should be noted that if any of the above-mentioned key information is not present in the data to be processed, the terminal device can set the field of the non-existent key information to null to indicate that the key information is not present in the data to be processed.

[0074] In this embodiment, after obtaining key information of the data to be processed, the terminal device can match the key information with each preset tag in the preset tag set. The preset tags can be set according to actual needs and are not limited here.

[0075] In some possible implementations, preset labels are used to describe different test scenarios.

[0076] It should be noted that test scenarios include, but are not limited to, internal and external scenarios. Internal scenarios refer to test scenarios based on vehicle information, including but not limited to vehicle model and speed. For example, a test scenario based on different vehicle models at the same speed, or a test scenario based on the same vehicle at different speeds.

[0077] External scenarios refer to test scenarios constructed based on environmental information. Environmental information includes, but is not limited to, weather information and road information.

[0078] Based on this, in this embodiment, the preset labels can be set as uphill scene, downhill scene, desert scene, scene of different vehicle types at the same speed, or scene of the same vehicle at different speeds, etc.

[0079] In one embodiment of this application, when the terminal device detects that the key information of the data to be processed fails to match each preset tag in the preset tag set, it may execute step S102.

[0080] In another embodiment of this application, when the terminal device detects that the key information of the data to be processed is successfully matched with the second tag in the preset tag set, it indicates that there is a preset tag in the preset tag set that matches the key information of the data to be processed. Therefore, the terminal device associates and stores the data to be processed with the aforementioned second tag.

[0081] In one implementation of this embodiment, the terminal device can associate and store the data to be processed and the second tag in an Excel spreadsheet for easy access by relevant personnel.

[0082] In another implementation of this embodiment, the terminal device can associate and store the above-mentioned data to be processed and the second tag in a database to avoid loss.

[0083] In S102, if the key information of the data to be processed fails to match any of the preset tags in the preset tag set, then the first tag corresponding to the data to be processed is determined based on the key information.

[0084] In this embodiment of the application, when the terminal device detects that the key information of the data to be processed fails to match any of the preset tags in the preset tag set, it indicates that there is no preset tag in the preset tag set that matches the key information of the data to be processed. Therefore, the terminal device determines the first tag corresponding to the data to be processed based on the key information of the data to be processed.

[0085] In one embodiment of this application, the terminal device can specifically be configured as follows: Figure 2 S201 to S203, as shown, define the first label mentioned above, as detailed below:

[0086] In S201, the appropriate scenarios and text formats corresponding to each preset label are determined.

[0087] In S202, a first keyword corresponding to the adapted scenario is extracted from the key information.

[0088] In S203, the format of the first keyword is adjusted according to the text format to obtain the first tag.

[0089] In this embodiment, each preset tag in the preset tag set is used to describe different test scenarios for vehicle testing. Therefore, the terminal device can extract the content information corresponding to each preset tag in the preset tag set and determine the appropriate scenario and text format corresponding to each preset tag based on the content information.

[0090] After obtaining the adaptation scenarios corresponding to each preset tag, the terminal device can determine the scenario description based on these adaptation scenarios, and search for the first keyword corresponding to the scenario description from the key information of the data to be processed based on the scenario description, and extract the first keyword from the key information of the data to be processed.

[0091] To standardize the labels and facilitate retrieval, the terminal device can adjust the format of the first keyword according to the text format corresponding to the preset label, thereby obtaining a first label with the same preset label format.

[0092] In S103, the first tag is added to the preset tag set, and the data to be processed is associated with and stored with the first tag.

[0093] In this embodiment, after determining the first tag corresponding to the data to be processed, the terminal device can add a new first tag to the data to be processed and add the first tag to a preset tag set in order to improve the tag matching success rate of the next data to be processed. Simultaneously, the terminal device associates and stores the data to be processed with the first tag to improve the search efficiency of subsequent terminal devices.

[0094] It should be noted that after the terminal device adds the first tag to the preset tag set, the first tag becomes a preset tag in the preset tag set.

[0095] In one implementation of this application, the terminal device can associate and store the above-mentioned data to be processed and the first tag in an Excel spreadsheet for easy access by relevant personnel.

[0096] In another implementation of this application, the terminal device can associate and store the above-mentioned data to be processed and the first tag in a database to avoid loss.

[0097] In one embodiment of this application, when the terminal device associates and stores the data to be processed with the first tag, it can output the data to be processed and the first tag to the display interface of the terminal device for display, so as to prompt the user that the data to be processed has been stored and to facilitate other relevant personnel to view it.

[0098] In another embodiment of this application, after the terminal device associates and stores the data to be processed with the first tag, it can obtain the current time when the terminal device processes the data to be processed in real time.

[0099] In this embodiment, when the terminal device detects that the current time has reached the set report output time, it can output the latest scene coverage report based on the correspondence between all the data to be processed stored in the database and / or Excel spreadsheet and each preset tag in the preset tag set.

[0100] The scenario coverage report describes the scenario coverage of the vehicle during testing and the problems that occurred during testing. Specifically, it describes the test scenarios that the vehicle has used during testing, the problems that occurred in the test scenarios that have been used, and the percentage and coverage of the test scenarios that have been used among all the test scenarios that need to be tested.

[0101] It should be noted that the report output time can be set according to actual needs, and there is no restriction here.

[0102] In some possible embodiments, in order to improve the real-time performance of the output scene coverage report, the set report output time can be the time when any piece of data to be processed is associated with and stored with the first tag, or the time when any piece of data to be processed is associated with and stored with a preset tag. That is, after detecting that any piece of data to be processed is associated with and stored with the first tag, or that the piece of data to be processed is associated with and stored with the preset tag, the terminal device can output the latest scene coverage report based on the correspondence between all the stored pieces of data to be processed and each preset tag in the preset tag set (including the correspondence between any piece of data to be processed and the first tag, or the correspondence between the piece of data to be processed and the preset tag).

[0103] In some other possible embodiments, to avoid the terminal device being constantly in the output scene coverage report stage, which would lead to a waste of terminal device resources, the terminal device can set the report output time according to a set duration. The set duration could be 24 hours.

[0104] The method in this application will be illustrated with a specific example. The background of this example is: the vehicle test data is the data obtained after testing a certain X model vehicle at a speed Y under weather B.

[0105] First, the terminal device uses real-time data from multiple sensors (such as speed sensors) installed in different testing scenarios, or from vehicle test data under different testing scenarios. Then, when the terminal device detects an abnormal data point within the vehicle test data for a scenario described as "a certain model of vehicle being tested at a certain speed under certain weather conditions," indicating a testing problem, the terminal device can identify this abnormal data as data to be processed.

[0106] Afterwards, the terminal device can determine the key information of the data to be processed and match this key information with a preset tag set consisting of different test scenarios stored in the terminal device's internal storage or in a database wirelessly connected to the terminal device. Each preset tag in the preset tag set describes the test scenario corresponding to different weather conditions, including weather A, weather B, weather C, and weather D.

[0107] Since the aforementioned preset tag set does not include a preset tag for describing XX weather, the terminal device needs to determine a first tag with the same preset tag format based on weather-related keywords in the key information of the data to be processed. That is, the first tag is set to "S weather". Here, "S weather" describes the XX weather in the data to be processed.

[0108] Based on this, the terminal device can store the first tag of the aforementioned S weather into a preset tag set, so that the updated preset tag set includes S weather, which facilitates the matching of subsequent data to be processed.

[0109] Simultaneously, the first tag of S Weather is associated with the data to be processed and stored in an Excel spreadsheet and / or database, and the correspondence between the first tag of S Weather and the data to be processed is displayed on the display screen of the terminal device.

[0110] As can be seen from the above, the data processing method provided in this application acquires data to be processed collected by a vehicle during the testing process; if the key information of the data to be processed fails to match any of the preset tags in the preset tag set, a first tag corresponding to the data to be processed is determined based on the key information; the first tag is added to the preset tag set, and the data to be processed is associated with and stored with the first tag. Compared with the prior art which requires manual labeling, the method provided in this application can directly add a first tag corresponding to the data to be processed based on the key information when it is detected that the data to be processed fails to match any of the preset tags, thereby achieving accurate matching of data without manual intervention, which not only reduces labor costs but also improves the accuracy of data matching. At the same time, adding the first tag to the preset tag set also facilitates subsequent data matching.

[0111] Please see Figure 3 , Figure 3 This is another data processing method provided in this application. Relative to... Figure 1 In a corresponding embodiment, this embodiment may further include S301 to S302 after S103, as detailed below:

[0112] In S301, multiple data to be processed are classified according to the preset label set to obtain multiple first datasets; wherein each first dataset contains at least one data to be processed under the same label.

[0113] In S302, the label matching result information of the preset label set is output according to the plurality of first datasets.

[0114] In this embodiment, after the terminal device associates and stores the data to be processed with the first tag, that is, after determining the correspondence between the data to be processed and the preset tag, it can classify multiple data to be processed according to each preset tag in the preset tag set to obtain multiple first datasets. Each first dataset contains at least one data to be processed under the same preset tag.

[0115] The preset label set is used to describe different test scenarios for the vehicle.

[0116] It should be noted that since the newly added first label exists in the preset label set at this time, when classifying multiple data to be processed according to the preset label set, there are some remaining preset labels in the preset label set that do not match any data to be processed, that is, the data to be processed corresponding to the remaining preset labels is zero.

[0117] Based on this, the terminal device can output label matching results for a preset label set according to multiple first datasets. The label matching results describe the scene coverage during vehicle testing, i.e., the ratio of the test scenes used during vehicle testing to all test scenes.

[0118] Specifically, the terminal device can determine the preset labels corresponding to each of the data to be processed based on multiple first datasets, that is, determine the preset labels that have been matched in the preset label set, thereby determining the test scenarios that have been tested. Based on this, the terminal device can calculate the scenario coverage of the vehicle test based on the first number of preset labels that have been matched and the second number of all preset labels in the preset label set, that is, determine the label matching result information of the preset label set.

[0119] The method of this embodiment will be specifically described with reference to the example of S103.

[0120] Since the terminal device has associated and stored multiple data to be processed with preset tags, such as the first data to be processed corresponding to weather S, the second data to be processed corresponding to weather A, the third data to be processed corresponding to weather B, the fourth data to be processed corresponding to weather A, and the fifth data to be processed corresponding to weather S, the terminal device can classify the data according to the preset tags corresponding to each data to be processed to obtain multiple first datasets: the first dataset under weather A, the first dataset under weather B, and the first dataset under weather S. That is, the number of preset tags that have been matched is 3.

[0121] Since the preset tag set also includes preset tags for weather C and weather D, and no data is associated with the preset tags for weather C and weather D, the terminal device can calculate that the standard matching result information is 60%, that is, the scene coverage rate is 60%.

[0122] As can be seen from the above, the data processing method provided in this embodiment classifies multiple data to be processed according to a preset label set to obtain multiple first datasets; wherein each first dataset contains at least one data to be processed under the same label; and outputs the label matching result information of the preset label set according to the multiple first datasets, so that relevant personnel can adjust and optimize the vehicle testing process according to the label matching result information.

[0123] Please see Figure 4 , Figure 4 This is another embodiment of the data processing method provided in this application. Compared to... Figure 3 In a corresponding embodiment, this embodiment may further include S401 to S403 after S103, as detailed below:

[0124] In S401, a data query request is received; the data query request carries the attribute information of the data to be queried.

[0125] In S402, a keyword extraction operation is performed on the attribute information to obtain the second keyword corresponding to the data to be queried.

[0126] In S403, a target dataset is selected from the plurality of first datasets based on the second keyword.

[0127] In practical applications, after the terminal device associates and stores the data to be processed with the second tag, it can output a prompt message to indicate that the data has been stored.

[0128] Based on this, in conjunction with S301 to S302, when a user needs to access the first dataset that has been stored, they can send a data query request to the terminal device.

[0129] In this embodiment, the terminal device detects a data query request sent by a user by: detecting that the user has opened a preset APP or detecting that the user has performed a second preset operation within the preset APP. The second preset operation can be set according to actual needs and is not limited here. For example, the second preset operation can be: clicking a second preset control in the preset APP. Based on this, when the terminal device detects that the aforementioned second preset control has been clicked, it indicates that the second preset operation has been detected, that is, a data query request sent by the user has been detected.

[0130] After detecting the above data query request, the terminal device can extract the attribute information of the data to be queried from the data query request.

[0131] The attribute information includes, but is not limited to: vehicle model, vehicle speed, and vehicle test scenario.

[0132] In this embodiment, since each first dataset has its own corresponding preset label, and the preset label is used to describe the test scenario of the vehicle, the terminal device can perform keyword extraction operation on the attribute information of the data to be queried to obtain the second keyword corresponding to the data to be queried, that is, obtain the second keyword related to the test scenario from the attribute information of the data to be queried.

[0133] Afterwards, the terminal device can obtain the target dataset from multiple first datasets based on the second keyword mentioned above, that is, the first dataset that is the same as the test scenario of the data to be queried.

[0134] As can be seen from the above, the data processing method provided in this embodiment involves receiving a data query request; the data query request carrying attribute information of the data to be queried; performing keyword extraction on the attribute information to obtain a second keyword corresponding to the data to be queried; and selecting a target dataset from multiple first datasets based on the second keyword. Using this method, the terminal device can quickly find the target dataset that matches the attribute information of the data to be queried, improving the efficiency of data retrieval and facilitating users to promptly access relevant data.

[0135] Please see Figure 5 , Figure 5 This is another embodiment of the data processing method provided in this application. Compared to... Figure 3 or Figure 4 In a corresponding embodiment, this embodiment may further include S501 to S503 after S103, as detailed below:

[0136] In S501, multiple datasets to be processed are classified according to the vehicle information and the test result information to obtain multiple second datasets.

[0137] In this embodiment, since each piece of data to be processed includes vehicle information and test result information, the terminal device can classify multiple pieces of data to be processed based on the vehicle information and test result information of each piece of data to be processed, thus obtaining multiple second datasets. In each second dataset, the vehicle information and test result information of each piece of data to be processed are identical.

[0138] It should be noted that vehicle information includes, but is not limited to, vehicle speed.

[0139] Test result information describes the test results of the vehicle under different vehicle information. This test result information includes, but is not limited to, test failures and test successes.

[0140] Test failure is used to describe a vehicle that did not meet preset expectations during the test. These preset expectations can be set according to actual needs and are not restricted here.

[0141] It should be noted that when a test fails, the test result information also includes the reason for the test failure.

[0142] In S502, the vehicle test pass rate is calculated based on the multiple second datasets.

[0143] In this embodiment, after obtaining multiple second datasets, the terminal device can count the number of each second dataset and calculate the test pass rate of different vehicles under different vehicle information based on the number of each second dataset and the test results corresponding to each dataset.

[0144] In S503, the testing process for the vehicle is adjusted based on the test pass rate and / or the tag matching result information.

[0145] In this embodiment, after obtaining the test pass rates of different vehicles under different vehicle information, the terminal device can compare the test pass rates with a set threshold. The set threshold can be set according to actual needs and is not limited here.

[0146] When the terminal device detects that the pass rate of a vehicle under a certain vehicle information is less than a set threshold, it means that the vehicle has failed the test under that vehicle information. Therefore, the terminal device can increase the number of tests for that vehicle under that vehicle information, thus completing the adjustment of the test process for that vehicle.

[0147] Alternatively, the terminal device can determine the untested test scenarios based on the tag matching results, and add the vehicle to be tested in that test scenario in the test process for any vehicle, thereby adjusting the vehicle's test process.

[0148] Alternatively, after detecting that the pass rate of a vehicle under a certain vehicle information is less than a set threshold and obtaining the tag matching result information, the terminal device can determine the test scenario corresponding to the lower pass rate of a vehicle under a certain vehicle information. In that test scenario, the number of tests for the vehicle under the aforementioned vehicle information is increased. At the same time, the terminal device increases the number of tests for the vehicle in unused test scenarios based on the tag matching result information, thereby completing the adjustment of the vehicle's testing process.

[0149] As can be seen from the above, the data processing method provided in this embodiment classifies multiple data to be processed according to vehicle information and test result information to obtain multiple second datasets; based on the multiple second datasets, the vehicle test pass rate is calculated; and based on the test pass rate and label matching result information, the vehicle test process is adjusted, thereby improving the test quality of the vehicle.

[0150] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0151] Corresponding to the data processing method described in the above embodiments, Figure 6 A schematic diagram of a data processing apparatus according to an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown. (Refer to...) Figure 6 The data processing device 600 includes: a first acquisition unit 61, a first determination unit 62, and an addition unit 63. Wherein:

[0152] The first acquisition unit 61 is used to acquire the data to be processed collected by the vehicle during the testing process.

[0153] The first determining unit 62 is used to determine the first tag corresponding to the data to be processed based on the key information if the key information of the data to be processed fails to match each preset tag in the preset tag set.

[0154] The adding unit 63 is used to add the first tag to the preset tag set and associate the data to be processed with the first tag for storage.

[0155] In one embodiment of this application, the first acquisition unit 61 specifically includes: a second acquisition unit, a second determination unit, and a third determination unit. Wherein:

[0156] The second acquisition unit is used to acquire vehicle test data of the vehicle during the testing process.

[0157] The second determining unit is used to determine the time corresponding to the abnormal data present in the vehicle test data.

[0158] The third determining unit is used to determine the effective data time range based on the time, and to determine the data in the vehicle test data that falls within the effective data time range as the data to be processed.

[0159] In one embodiment of this application, the data processing apparatus 600 further includes a storage unit.

[0160] The storage unit is used to associate and store the data to be processed with the second tag if the key information of the data to be processed is successfully matched with the second tag in the preset tag set.

[0161] In one embodiment of this application, the first determining unit 62 specifically includes: a fourth determining unit, a first extraction unit, and a first adjustment unit. Wherein:

[0162] The fourth determining unit is used to determine the appropriate scenarios and text formats corresponding to each preset label.

[0163] The first extraction unit is used to extract the first keyword corresponding to the adapted scenario from the key information.

[0164] The first adjustment unit is used to adjust the format of the first keyword according to the text format to obtain the first tag.

[0165] In one embodiment of this application, the data to be processed includes multiple data sets, and the data processing device 600 further includes: a first classification unit and an output unit. Wherein:

[0166] The first classification unit is used to classify multiple data to be processed according to the preset label set to obtain multiple first datasets; wherein each first dataset contains at least one data to be processed under the same label.

[0167] The output unit is used to output the label matching result information of the preset label set based on the multiple first datasets.

[0168] In one embodiment of this application, the data processing apparatus 600 further includes: a receiving unit, a second extraction unit, and a selection unit. Wherein:

[0169] The receiving unit is used to receive data query requests; the data query request carries attribute information of the data to be queried.

[0170] The second extraction unit is used to perform keyword extraction on the attribute information to obtain the second keyword corresponding to the data to be queried.

[0171] The selection unit is used to select a target dataset from the plurality of first datasets based on the second keyword.

[0172] In one embodiment of this application, the data to be processed includes vehicle information and test result information; the data processing device 600 further includes: a second classification unit, a statistics unit, and a second adjustment unit. Wherein:

[0173] The second classification unit is used to classify multiple datasets to be processed based on the vehicle information and the test result information, thereby obtaining multiple second datasets.

[0174] The statistics unit is used to calculate the vehicle test pass rate based on the multiple second datasets.

[0175] The second adjustment unit is used to adjust the testing process of the vehicle based on the test pass rate and / or the tag matching result information.

[0176] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0177] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0178] Figure 7 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Figure 7 As shown, the terminal device 7 of this embodiment includes: at least one processor 70 ( Figure 7 (Only one is shown) a processor, a memory 71, and a computer program 72 stored in the memory 71 and executable on the at least one processor 70, wherein the processor 70 executes the computer program 72 to implement the steps in any of the above-described data processing method embodiments.

[0179] The terminal device may include, but is not limited to, a processor 70 and a memory 71. Those skilled in the art will understand that... Figure 7 This is merely an example of terminal device 7 and does not constitute a limitation on terminal device 7. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0180] The processor 70 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0181] In some embodiments, the memory 71 may be an internal storage unit of the terminal device 7, such as the RAM of the terminal device 7. In other embodiments, the memory 71 may be an external storage device of the terminal device 7, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal device 7. Furthermore, the memory 71 may include both internal and external storage units of the terminal device 7. The memory 71 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 71 can also be used to temporarily store data that has been output or will be output.

[0182] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0183] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the various method embodiments above.

[0184] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0185] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0186] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A data processing method, characterized in that, include: Acquire the data to be processed collected by the vehicle during the testing process; The data to be processed includes all data within a valid data time range, centered on the event corresponding to the abnormal data generated by the vehicle during the test that does not match the preset result, and with a set duration as the range. If the key information of the data to be processed fails to match any of the preset tags in the preset tag set, then the first tag corresponding to the data to be processed is determined based on the key information. Add the first tag to the preset tag set, and associate the data to be processed with the first tag for storage; Determining the first tag corresponding to the data to be processed based on the key information includes: Determine the appropriate scenarios and text formats for each preset tag; Extract the first keyword corresponding to the adapted scenario from the key information; The format of the first keyword is adjusted according to the text format to obtain the first tag.

2. The data processing method as described in claim 1, characterized in that, The process of acquiring the data to be processed collected by the vehicle during the testing process includes: Obtain vehicle test data during the testing process; Determine the time corresponding to the abnormal data present in the vehicle test data; The effective data time range is determined based on the time, and the data in the vehicle test data that falls within the effective data time range is identified as the data to be processed.

3. The data processing method as described in claim 1, characterized in that, After acquiring the data to be processed collected by the vehicle during the testing process, the process also includes: If the key information of the data to be processed successfully matches the second tag in the preset tag set, the data to be processed is associated with and stored with the second tag.

4. The data processing method according to any one of claims 1 to 3, characterized in that, The data to be processed includes multiple data sets. After adding the first tag to the preset tag set and associating the data to be processed with the first tag for storage, the data further includes: Multiple data sets to be processed are classified according to the preset label set to obtain multiple first datasets; wherein each first dataset contains at least one data set to be processed under the same label; Output the label matching result information of the preset label set based on the multiple first datasets.

5. The data processing method as described in claim 4, characterized in that, After adding the first tag to the preset tag set and associating the data to be processed with the first tag for storage, the method further includes: Receive a data query request; the data query request carries the attribute information of the data to be queried; Perform keyword extraction on the attribute information to obtain the second keyword corresponding to the data to be queried; Based on the second keyword, a target dataset is selected from the plurality of first datasets.

6. The data processing method as described in claim 4, characterized in that, The data to be processed includes vehicle information and test result information; After adding the first tag to the preset tag set and associating the data to be processed with the first tag for storage, the method further includes: Based on the vehicle information and the test result information, multiple datasets to be processed are classified to obtain multiple second datasets; Based on the multiple second datasets, the vehicle test pass rate is calculated. The testing process for the vehicle is adjusted based on the test pass rate and / or the tag matching results.

7. A data processing apparatus, characterized in that, include: The first acquisition unit is used to acquire the data to be processed collected by the vehicle during the testing process; The data to be processed includes all data within a valid data time range, centered on the event corresponding to the abnormal data generated by the vehicle during the test that does not match the preset result, and with a set duration as the range. The first determining unit is configured to determine the first tag corresponding to the data to be processed based on the key information if the key information of the data to be processed fails to match each of the preset tags in the preset tag set. An adding unit is used to add the first tag to the preset tag set and to associate and store the data to be processed with the first tag; The first determining unit specifically includes: The fourth determining unit is used to determine the appropriate scenario and text format corresponding to each preset label; The first extraction unit is used to extract a first keyword corresponding to the adaptation scenario from the key information; The first adjustment unit is used to adjust the format of the first keyword according to the text format to obtain the first tag.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the data processing method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the data processing method as described in any one of claims 1 to 6.

Images