Quality analysis method and device for vehicle message data

Abstract

The invention discloses a quality analysis method and device for vehicle message data, relates to the technical field of vehicle data analysis, and mainly aims to identify message faults caused by non-message contents. According to the main technical scheme, the method comprises the steps of obtaining multiple groups of vehicle message information, wherein each group of vehicle message information comprises an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data; according to a preset deviation value calculation method, respectively processing the actual multi-dimensional message period and the standard message period corresponding to each group of vehicle message information to obtain a period deviation analysis result corresponding to each group of vehicle message information; and determining a quality analysis result corresponding to each group of vehicle message information according to the periodic deviation analysis result corresponding to each group of vehicle message information. The method is used for analyzing the quality of the vehicle message data.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle data analysis, and in particular to a method and device for quality analysis of vehicle message data. Background Art

[0002] In the vehicle system, each electronic control unit (ECU) exchanges information through message data, so the quality of message data is crucial to the normal operation of the vehicle. The appearance of abnormal messages may cause vehicle system instability or even cause failures. Therefore, the analysis of message data quality is an important measure to ensure the safe driving of the vehicle.

[0003] Currently, the analysis of message data quality mainly relies on preset screening criteria, which are used to determine whether the message content is correct, that is, only the messages with faulty content are screened. However, in actual application scenarios, even if the data content of multiple messages under the same message ID is correct, message failures may still occur. This shows that if the message failure is caused by something other than the message content itself, it is difficult for existing technical means to detect these abnormal situations. The consequence of this situation is that the vehicle control strategy may not be adjusted in time for the message failure, which will have an adverse effect on the overall performance of the vehicle. Summary of the invention

[0004] In view of the above problems, the present invention provides a method and device for quality analysis of vehicle message data, the main purpose of which is to identify message faults caused by non-message content itself.

[0005] In order to solve the above technical problems, the present invention proposes the following solutions:

[0006] In a first aspect, the present invention provides a method for quality analysis of vehicle message data, the method comprising:

[0007] Acquire multiple groups of vehicle message information, each group of vehicle message information includes an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data;

[0008] According to a preset deviation value calculation method, the actual multi-dimensional message period and the standard message period corresponding to each group of vehicle message information are processed respectively to obtain a period deviation analysis result corresponding to each group of vehicle message information;

[0009] The quality analysis result corresponding to each group of vehicle message information is determined according to the period deviation analysis result corresponding to each group of vehicle message information.

[0010] In a second aspect, the present invention provides a quality analysis device for vehicle message data, the device comprising:

[0011] An information acquisition unit, used to acquire multiple groups of vehicle message information, each group of vehicle message information including an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data;

[0012] A cycle processing unit, used to process the actual multi-dimensional message cycle and the standard message cycle corresponding to each group of vehicle message information acquired by the information acquisition unit according to a preset deviation value calculation method, and obtain a cycle deviation analysis result corresponding to each group of vehicle message information;

[0013] The result analysis unit is used to determine the quality analysis result corresponding to each group of vehicle message information according to the period deviation analysis result corresponding to each group of vehicle message information obtained by the period processing unit.

[0014] In order to achieve the above-mentioned purpose, according to the third aspect of the present invention, a storage medium is provided, which includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the vehicle message data quality analysis method of the first aspect mentioned above.

[0015] In order to achieve the above-mentioned object, according to a fourth aspect of the present invention, a processor is provided, wherein the processor is used to run a program, wherein the vehicle message data quality analysis method of the above-mentioned first aspect is executed when the program is run.

[0016] By means of the above technical scheme, the present invention provides a method and device for quality analysis of vehicle message data. First, multiple groups of vehicle message information can be collected, each group of information not only contains vehicle message data, but also involves the corresponding actual multi-dimensional message period and standard message period. Then, a preset deviation value calculation method is used to compare and analyze the actual multi-dimensional message period of these vehicle message information with the standard message period, and then the periodic deviation analysis results of each group of message information are calculated. Based on these periodic deviation analysis results, the data quality analysis results of each group of vehicle message information can be determined. Compared with the prior art, the present invention does not focus on the message failure caused by the message content itself, but effectively identifies the message failure that may be caused by non-message content itself (such as message period) by comparing the difference between the actual multi-dimensional message period and the standard message period in each group of message information. Therefore, the vehicle control strategy can be adjusted in time for the message failure caused by the message period problem to prevent the overall performance of the vehicle from being adversely affected.

[0017] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0019] Figure 1 A flow chart of a method for quality analysis of vehicle message data provided by an embodiment of the present invention is shown;

[0020] Figure 2 A flow chart of another method for quality analysis of vehicle message data provided by an embodiment of the present invention is shown;

[0021] Figure 3 A block diagram showing a quality analysis device for vehicle message data provided by an embodiment of the present invention is shown;

[0022] Figure 4 A block diagram showing the composition of another vehicle message data quality analysis device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0024] In view of the fact that the existing message data quality analysis method mainly focuses on screening messages with faulty content, this method often cannot detect message faults caused by factors other than the message content. In view of this defect, the present invention proposes a method for quality analysis of vehicle message data. Through in-depth research and a lot of innovative work, the inventors found that the message sending cycle - that is, the time interval between two consecutive messages under the same message ID - is an important factor that may cause message failure. If the message sending cycle does not meet the standard or has a large deviation from the standard cycle, the vehicle's control unit may not be able to output the necessary control instructions in time, thereby affecting the overall operating performance of the vehicle. Therefore, the present invention evaluates the data quality of each group of vehicle message information by analyzing the deviation between the actual message cycle and the standard message cycle. Unlike traditional analysis methods, this method does not involve direct verification of the message content, but determines the quality through periodic analysis, which makes the analysis process more intuitive and more efficient. In addition, the message cycle is directly related to the capture time of the message, so it can more accurately reflect the quality of the message, providing a solid and reliable basis for data analysis.

[0025] The embodiment of the present invention provides a vehicle message data quality analysis method, the execution subject of which is a vehicle network message quality analysis system. The system can be connected to the vehicle interface to automatically collect the vehicle's message files and perform vehicle message data quality analysis. The specific implementation method can be referred to Figure 1 , Figure 1 A vehicle message data quality analysis method provided by an embodiment of the present invention includes the following specific execution steps: Figure 1 As shown, including:

[0026] 101. Acquire multiple groups of vehicle message information, each group of vehicle message information including an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data.

[0027] In this step, the DBC file and BLF file of the vehicle may be obtained first.

[0028] Among them, the DBC file is used to define the message format, signal attributes and network configuration on the vehicle network (such as the CAN bus), including predefined message information, such as the message ID and its corresponding standard message period.

[0029] Generally, DBC files can be obtained through the following methods:

[0030] Contact the vehicle manufacturer or system integrator directly to request the DBC file in order to obtain detailed vehicle model and configuration information; use third-party tools or services, such as CANalyzer, CANape, etc., which sometimes come with some standard DBC files; use professional tools (such as Vector CANdb++, CANape, etc.) to create DBC files, that is, users can manually enter or import signal definitions, message IDs and other necessary information based on the vehicle's specification documents and network topology.

[0031] BLF files are a binary log file format used to record vehicle network communication data. BLF files can be obtained in the following ways:

[0032] Through on-board network diagnostic tools, such as CANalyzer, CANape, CANdela, etc., these tools usually support recording data on the CAN bus and saving it in BLF format; for vehicles that support the OBD-II protocol, you can use an OBD-II adapter to connect to the on-board diagnostic port and use software that supports the BLF recording function to record; you can also read data directly from the vehicle's electronic control unit (ECU) and then convert it to BLF format using the corresponding software.

[0033] It should be noted that in the process of obtaining DBC and BLF files, any acquisition method can be used, as long as the acquisition and use of sensitive information requires appropriate authorization or permission.

[0034] In addition, BLF files can be acquired periodically or in real time. The difference between these two methods is that if the BLF file is acquired periodically, the quality analysis of the message data is performed on the vehicle message data in the acquired BLF file whose acquisition timestamp is within the period; if the BLF file is acquired in real time, the acquired time is used as the deadline, and the vehicle message data in the BLF file whose acquisition timestamp is the deadline and before is analyzed. Through these two different acquisition methods, the quality analysis of the message data can be flexibly performed according to actual needs.

[0035] After obtaining the DBC file and the BLF file, the DBC file and the BLF file can be parsed respectively according to a preset parsing method to obtain the defined message information in the DBC file and the actual message information in the BLF file.

[0036] The defined message information includes multiple message IDs, the standard message period and DBC channel corresponding to each message ID. The actual message information includes multiple vehicle message data, the message ID and DBC channel corresponding to each vehicle message data, and the acquisition timestamp corresponding to each vehicle message data.

[0037] It should be noted that for multiple message data of the same message ID, they can represent different values ​​of the same data item at different time points, or the same value can be sent repeatedly at different time points. For example, multiple vehicle message data of the same message ID can be the reading A of a certain sensor at time t=0, while the second message can be the same reading A or another reading B of the same sensor at time t=100ms. Such message data reflects the change of the sensor over time or the status of repeated transmission.

[0038] Based on this, multiple vehicle message data in the actual message information can be grouped according to the message ID and DBC channel to obtain a group of vehicle message data corresponding to each message ID and DBC channel. Then, the acquisition timestamp difference between every two message data in each group of vehicle message data is calculated to obtain multiple acquisition timestamp differences corresponding to each group of vehicle message data. These timestamp differences actually represent the actual message period between every two messages under the same message ID. Then, the actual multi-dimensional message period corresponding to each group of vehicle message data is calculated based on the multiple acquisition timestamp differences corresponding to each group of vehicle message data. Finally, a group of vehicle message data corresponding to each message ID, the actual multi-dimensional message period corresponding to each group of vehicle message data, and the standard message period corresponding to each message ID are combined to determine a group of vehicle message information corresponding to each message ID.

[0039] The actual multi-dimensional message cycle may include a maximum cycle, a minimum cycle, and an average cycle. The maximum value of the multiple acquisition timestamp differences corresponding to each group of vehicle message data is determined as the maximum cycle corresponding to each group of vehicle message data; the minimum value of the multiple acquisition timestamp differences corresponding to each group of vehicle message data is determined as the minimum cycle corresponding to each group of vehicle message data; the quotient between the sum of the multiple acquisition timestamp differences corresponding to each group of vehicle message data and the number of messages is determined as the average cycle corresponding to each group of vehicle message data.

[0040] Exemplarily, there are five messages under the same message ID, the acquisition timestamp of the first message is 0ms; the acquisition timestamp of the second message is 100ms; the acquisition timestamp of the third message is 200ms; the acquisition timestamp of the fourth message is 300ms; and the acquisition timestamp of the fifth message is 500ms.

[0041] From the above data, we can see that the periods between messages are:

[0042] The period from the first message to the second message is 100ms (100ms-0ms).

[0043] The period from the second message to the third message is 100ms (200ms-100ms).

[0044] The period from the third message to the fourth message is 100ms (300ms-200ms).

[0045] The period from the fourth message to the fifth message is 200ms (500ms-300ms).

[0046] Among them, the maximum period is 200ms, the minimum period is 100ms, and the average period is (100ms+100ms+100ms+200ms / 4=125ms)

[0047] The DBC (Database Configuration) channel of a message refers to the information defined in the DBC file that describes the message transmission path in the vehicle network. In the vehicle network, especially the CAN (Controller Area Network) bus system, the DBC file is used to define various parameters in the network, including but not limited to message ID, signal definition, node configuration, etc.

[0048] The DBC channel specifically refers to the transmission path of the message in the network, which usually includes the following aspects:

[0049] 1. Bus identifier: specifies the physical bus where the message is located, such as CAN1, CAN2, etc.

[0050] 2. Sending node: specifies the ECU (Electronic Control Unit) that sends the message.

[0051] 3. Receiving node: specifies one or more ECUs that receive the message.

[0052] In the DBC file, each message is associated with one or more DBC channels. These channel information is used to clarify how messages are sent and received in the network. In this way, when analyzing or simulating network behavior, the source and destination of the message can be tracked based on the DBC channel information, which is very important for understanding and debugging the vehicle network.

[0053] It should also be noted that the actual DBC file and BLF file may include more information, but the embodiments of the present invention do not list them one by one, but it does not mean that they do not exist. For example, in the embodiments of the present invention, features such as the current cycle, the total number of detections, and the message duration in the vehicle message data in the BLF file can also be determined. Among them, the current cycle is helpful for engineers to quickly locate the message segment where the abnormality occurs later. The current cycle is the cycle of the last message that appears in a group of vehicle message data, and the total number of detections is the number of messages in this group. Message duration = average cycle × total number of detections.

[0054] 102. According to a preset deviation value calculation method, the actual multi-dimensional message period and the standard message period corresponding to each group of vehicle message information are processed respectively to obtain a period deviation analysis result corresponding to each group of vehicle message information.

[0055] In this step, according to the preset deviation value calculation method, the maximum period and standard message period, the minimum period and standard message period, and the average period and standard message period in the actual multi-dimensional message period corresponding to each group of vehicle message information can be processed separately to obtain the maximum period deviation analysis results, the minimum period deviation analysis results, and the average period deviation analysis results.

[0056] Of course, it is also possible to integrate the maximum cycle deviation analysis result, the minimum cycle deviation analysis result, and the average cycle deviation analysis result to obtain an overall cycle deviation analysis result, which is not specifically limited here.

[0057] The preset deviation value calculation method may be an absolute deviation calculation method or a relative deviation calculation method, without specific limitation.

[0058] 103. Determine a quality analysis result corresponding to each group of vehicle message information according to a period deviation analysis result corresponding to each group of vehicle message information.

[0059] In this step, one or more standard results corresponding to the periodic deviation analysis results can be set. If the maximum periodic deviation analysis result, the minimum periodic deviation analysis result, and the average periodic deviation analysis result are used respectively, these results can be compared with the set one or more standard analysis results to measure the quality analysis results corresponding to each group of vehicle message data.

[0060] Another method is to integrate the maximum cycle deviation analysis results, the minimum cycle deviation analysis results, and the average cycle deviation analysis results to obtain an overall cycle deviation analysis result. This overall result can be compared with a comprehensive standard analysis result to measure the quality analysis result corresponding to each group of vehicle message data.

[0061] The above two methods can be selected according to actual needs and are not specifically limited in this embodiment.

[0062] Based on the above Figure 1It can be seen from the implementation method that the quality analysis method of vehicle message data provided by the present invention can first collect multiple groups of vehicle message information, each group of information not only contains vehicle message data, but also involves the corresponding actual multi-dimensional message cycle and standard message cycle. Then, a pre-set deviation value calculation method is used to compare and analyze the actual multi-dimensional message cycle of these vehicle message information with the standard message cycle, and then the periodic deviation analysis results of each group of message information are calculated. Based on these periodic deviation analysis results, the data quality analysis results of each group of vehicle message information can be determined. Compared with the prior art, the present invention does not focus on the message failure caused by the message content itself, but by comparing the difference between the actual multi-dimensional message cycle and the standard message cycle in each group of message information, it effectively identifies the message failure that may be caused by non-message content itself (such as message cycle). Therefore, the vehicle control strategy can be adjusted in time for the message failure caused by the message cycle problem to prevent the overall performance of the vehicle from being adversely affected.

[0063] Furthermore, as a Figure 1 The embodiment shown in the figure is refined and expanded. The embodiment of the present invention also provides another method for analyzing the quality of vehicle message data, such as Figure 2 As shown, the specific steps are as follows:

[0064] 201. Acquire multiple groups of vehicle message information, each group of vehicle message information including an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data.

[0065] Among them, the specific implementation of this step is the same as step 101, and can achieve the same technical effect and solve the same technical problem, and will not be repeated here.

[0066] 202. According to a preset deviation value calculation method, the actual multi-dimensional message period and the standard message period corresponding to each group of vehicle message information are processed respectively to obtain a period deviation analysis result corresponding to each group of vehicle message information.

[0067] The reason why each set of vehicle message information has a corresponding standard message cycle is that in the vehicle network, different ECUs need to coordinate their work. The standard message cycle represents the standard cycle for each ECU to receive the required information, thereby ensuring the synchronous operation of the system.

[0068] In this way, the maximum cycle deviation analysis result corresponding to each group of vehicle message information can be obtained according to the deviation value calculation formula and the maximum cycle and standard message cycle in the actual multi-dimensional message cycle corresponding to each group of vehicle message information.

[0069] At the same time, according to the deviation value calculation formula, based on the minimum period and standard message period in the actual multi-dimensional message period corresponding to each group of vehicle message information, the minimum period deviation analysis result corresponding to each group of vehicle message information is obtained.

[0070] And according to the deviation value calculation formula, according to the average period and standard message period in the actual multi-dimensional message period corresponding to each group of vehicle message information, the average period deviation analysis result corresponding to each group of vehicle message information is obtained.

[0071] Among them, in this embodiment, the preferred deviation value calculation formula is relative deviation calculation, specifically:

[0072]

[0073] In the formula, δ max is the maximum cycle deviation analysis result, in %; T m is the standard message period, in seconds; T max is the maximum period, in seconds.

[0074]

[0075] In the formula, δ min is the minimum period deviation analysis result, in %; T min is the minimum period, in seconds.

[0076]

[0077] In the formula, δ avg is the average period deviation analysis result, in %; T avg is the average period in seconds.

[0078] 203. Obtain a first expected deviation analysis result and a second expected deviation analysis result.

[0079] 204. Determine the quality analysis result corresponding to each group of vehicle message information according to the relationship between the maximum cycle deviation analysis result, the minimum cycle deviation analysis result and the average cycle deviation analysis result and the first expected deviation analysis result and the second expected deviation analysis result corresponding to each group of vehicle message information.

[0080] The deviation degree of the second expected deviation analysis result is greater than that of the first expected deviation analysis result. The first expected deviation analysis result may be 20%, and the second expected deviation analysis result may be 1000%.

[0081] Specifically, in steps 203-204, if there is a target analysis result greater than the first expected deviation analysis result in the maximum cycle deviation analysis result, the minimum cycle deviation analysis result, and the average cycle deviation analysis result corresponding to each group of vehicle message information, the quality analysis result corresponding to each group of vehicle message information is determined to be abnormal. That is, as long as one of the maximum cycle deviation analysis result, the minimum cycle deviation analysis result, and the average cycle deviation analysis result is greater than the first expected deviation analysis result, the quality analysis result of the vehicle message data in the group of vehicle message information is abnormal. This is because as long as one of these three key indicators exceeds the relatively small first expected deviation analysis result, it means that the vehicle message information has a large difference from the standard in terms of period, which may imply that the message data is unstable during transmission, the delay fluctuation is large, or there are some interference factors. In this case, the quality of the message data is affected and cannot be considered to be completely normal, so it is determined to be abnormal.

[0082] If the maximum cycle deviation analysis result corresponding to each group of vehicle message information is greater than the second expected deviation analysis result, the quality analysis result corresponding to each group of vehicle message information is determined to be lost. This is because when the maximum cycle deviation reaches such a high ratio, it means that the cycle of the message is seriously deviated from the standard. It is likely that the message has been interrupted or lost for a long time during the transmission process, resulting in a huge cycle deviation. In this case, it can be judged that the message data is not transmitted normally to a large extent, so it is determined to be in a lost state; if the maximum cycle deviation analysis result, the minimum cycle deviation analysis result and the average cycle deviation analysis result corresponding to each group of vehicle message information are all less than the first expected deviation analysis result, the quality analysis result corresponding to each group of vehicle message information is determined to be normal, which means that the deviation of the message data from the standard in each key cycle indicator is within a small acceptable range, indicating that the transmission of the message data is relatively stable and regular, and there is no obvious abnormality, so the quality analysis result is determined to be normal.

[0083] In addition, it should be noted that after obtaining the quality analysis results of each vehicle message information, the results can be visualized for easy viewing by staff. There may be null values ​​in the results, where null values ​​mean that these messages do not exist in the BLF file, and the period and deviation degree are not calculated, but these messages exist in the DBC file.

[0084] It should be noted that although the present invention can obtain BLF files in real time or periodically, no matter which method is used, it is necessary to perform quality analysis on each vehicle message data in the BLF file. This is because if the quality analysis of a message is missed, it may cause vehicle failure. Therefore, it is very important to ensure a comprehensive quality assessment of each message data.

[0085] Based on this, the embodiment of the present invention can also specifically set up a maintenance list of a BLF file for synchronizing the message ID and content of each vehicle message data recorded in the BLF file. In this way, after outputting the quality analysis result of the vehicle message, the message ID corresponding to the quality analysis result can be compared with the message ID in the maintenance list to confirm whether the message data corresponding to some message IDs are missed.

[0086] In addition, the maintenance list can be updated regularly or in real time to accurately reflect the latest changes in message data. At the same time, it is also necessary to pay attention to whether the quality analysis results do not match the maintenance list. If this happens, it may mean that abnormal behavior occurred during the message quality analysis process, or that the maintenance list has synchronization anomalies. To this end, the system should be able to automatically generate an abnormality report and notify relevant personnel in time for timely processing.

[0087] In addition, the vehicle network message quality analysis system of the embodiment of the present invention can be installed on the vehicle in the form of a physical device to capture and generate message files. The files are automatically transferred to the local server via the FTP protocol. A timing program is configured on the server to call the message anomaly detection algorithm (that is, the analysis method within the vehicle network message quality analysis system) to ensure timely analysis of message data. The analysis results will be recorded and registered in the database.

[0088] Furthermore, as a response to the above Figure 1 In order to realize the method shown in the figure, the embodiment of the present invention also provides a vehicle message data quality analysis device for analyzing the above Figure 1 The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 3 As shown, the device comprises:

[0089] The information acquisition unit 301 is used to acquire multiple groups of vehicle message information, each group of vehicle message information includes an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data;

[0090] The cycle processing unit 302 is used to process the actual multi-dimensional message cycle and the standard message cycle corresponding to each group of vehicle message information obtained by the information obtaining unit 301 according to a preset deviation value calculation method, and obtain a cycle deviation analysis result corresponding to each group of vehicle message information;

[0091] The result analysis unit 303 is used to determine the quality analysis result corresponding to each group of vehicle message information according to the period deviation analysis result corresponding to each group of vehicle message information obtained by the period processing unit 302.

[0092] Furthermore, as a response to the above Figure 2 In order to realize the method shown in the figure, the embodiment of the present invention also provides another vehicle message data quality analysis device for analyzing the above Figure 2 The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 4 As shown, the device comprises:

[0093] The information acquisition unit 301 is used to acquire multiple groups of vehicle message information, each group of vehicle message information includes an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data;

[0094] The cycle processing unit 302 is used to process the actual multi-dimensional message cycle and the standard message cycle corresponding to each group of vehicle message information obtained by the information obtaining unit 301 according to a preset deviation value calculation method, and obtain a cycle deviation analysis result corresponding to each group of vehicle message information;

[0095] The result analysis unit 303 is used to determine the quality analysis result corresponding to each group of vehicle message information according to the period deviation analysis result corresponding to each group of vehicle message information obtained by the period processing unit 302.

[0096] In an optional implementation manner, the periodic processing unit 302 includes:

[0097] The first cycle processing module 3021 is used to obtain the maximum cycle deviation analysis result corresponding to each group of vehicle message information according to the deviation value calculation formula, according to the maximum cycle in the actual multi-dimensional message cycle corresponding to each group of vehicle message information and the standard message cycle;

[0098] The second cycle processing module 3022 is used to obtain the minimum cycle deviation analysis result corresponding to each group of vehicle message information according to the deviation value calculation formula, the minimum cycle in the actual multi-dimensional message cycle corresponding to each group of vehicle message information and the standard message cycle;

[0099] The third cycle processing module 3023 is used to obtain the average cycle deviation analysis result corresponding to each group of vehicle message information according to the deviation value calculation formula, the average cycle in the actual multi-dimensional message cycle corresponding to each group of vehicle message information and the standard message cycle.

[0100] In an optional implementation manner, the result analysis unit 303 includes:

[0101] A result acquisition module 3031 is used to acquire a first expected deviation analysis result and a second expected deviation analysis result, wherein the deviation degree of the second expected deviation analysis result is greater than that of the first expected deviation analysis result;

[0102] The result analysis module 3032 is used to determine the quality analysis result corresponding to each group of vehicle message information based on the relationship between the maximum period deviation analysis result, the minimum period deviation analysis result and the average period deviation analysis result corresponding to each group of vehicle message information and the first expected deviation analysis result and the second expected deviation analysis result obtained by the result acquisition module 3031.

[0103] In an optional implementation manner, the result analysis module 3032 is specifically used for:

[0104] If there is a target analysis result greater than the first expected deviation analysis result among the maximum cycle deviation analysis result, the minimum cycle deviation analysis result and the average cycle deviation analysis result corresponding to each group of vehicle message information, the quality analysis result corresponding to each group of vehicle message information is determined to be abnormal;

[0105] If the maximum period deviation analysis result corresponding to each group of vehicle message information is greater than the second expected deviation analysis result, the quality analysis result corresponding to each group of vehicle message information is determined to be lost;

[0106] If the maximum period deviation analysis result, the minimum period deviation analysis result and the average period deviation analysis result corresponding to each group of vehicle message information are all smaller than the first expected deviation analysis result, the quality analysis result corresponding to each group of vehicle message information is determined to be normal.

[0107] In an optional implementation manner, before the information acquisition unit 301 acquires multiple groups of vehicle message information, the device further includes an information collating unit 304, and the information collating unit 304 includes:

[0108] The file collection module 3041 is used to collect DBC files and BLF files in the vehicle system according to a preset interface;

[0109] The first file parsing module 3042 is used to parse the DBC file collected by the file collection module 3041 according to a preset parsing method to obtain definition message information, wherein the definition message information includes multiple message IDs, a standard message period corresponding to each message ID, and a DBC channel;

[0110] The second file parsing module 3043 is used to parse the BLF file collected by the file collection module 3041 according to the preset parsing method to obtain actual message information, wherein the actual message information includes multiple vehicle message data, a message ID and a DBC channel corresponding to each vehicle message data, and an acquisition timestamp corresponding to each vehicle message data;

[0111] The information acquisition module 3044 is used to obtain multiple groups of vehicle message information based on the definition message information obtained by the first file parsing module 3042 and the actual message information obtained by the second file parsing module 3043.

[0112] In an optional implementation manner, the information acquisition module 3044 is specifically used to:

[0113] According to the message ID and the DBC channel, the multiple vehicle message data in the actual message information are grouped to obtain a group of vehicle message data corresponding to each message ID and the DBC channel;

[0114] Calculate the acquisition timestamp difference between every two vehicle message data in each group of vehicle message data to obtain multiple acquisition timestamp differences corresponding to each group of vehicle message data;

[0115] Calculate the actual multi-dimensional message period corresponding to each group of vehicle message data according to the difference of multiple acquisition timestamps corresponding to each group of vehicle message data;

[0116] A group of vehicle message data corresponding to each message ID, an actual multi-dimensional message period corresponding to each group of vehicle message data, and a standard message period corresponding to each message ID are determined as a group of vehicle message information corresponding to each message ID.

[0117] In an optional implementation manner, when calculating the actual multi-dimensional message period corresponding to each group of vehicle message data according to the multiple acquisition timestamp differences corresponding to each group of vehicle message data, the information acquisition module 3044 is specifically used to:

[0118] Determine the maximum value among a plurality of acquisition timestamp differences corresponding to each set of vehicle message data as the maximum period corresponding to each set of vehicle message data;

[0119] Determine the minimum value among a plurality of acquisition timestamp differences corresponding to each set of vehicle message data as the minimum period corresponding to each set of vehicle message data;

[0120] Determine the quotient between the sum of the multiple acquisition time stamp differences corresponding to each group of vehicle message data and the number of messages as the average period corresponding to each group of vehicle message data;

[0121] The maximum period, the minimum period and the average period are determined as the actual multi-dimensional message period corresponding to each group of vehicle message data.

[0122] Furthermore, an embodiment of the present invention further provides a storage medium, wherein the storage medium is used to store a computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the above Figure 1-2 The quality analysis method of vehicle message data described in.

[0123] Furthermore, an embodiment of the present invention further provides a processor, the processor is used to run a program, wherein the program executes the above Figure 1-2 The quality analysis method of vehicle message data described in.

[0124] 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.

[0125] It is understandable that the related features in the above methods and devices can be referenced to each other. In addition, the "first", "second" and the like in the above embodiments are used to distinguish the embodiments, and do not represent the advantages and disadvantages of the embodiments.

[0126] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0127] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description of the above specific languages ​​is for disclosing the best mode of the present invention.

[0128] In addition, the memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0129] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0130] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0131] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0132] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0133] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0134] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0135] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0136] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0137] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0138] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for quality analysis of vehicle message data, characterized in that: The method comprises: Acquire multiple groups of vehicle message information, each group of vehicle message information includes an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data; According to a preset deviation value calculation method, the actual multi-dimensional message period and the standard message period corresponding to each group of vehicle message information are processed respectively to obtain a period deviation analysis result corresponding to each group of vehicle message information; The quality analysis result corresponding to each group of vehicle message information is determined according to the period deviation analysis result corresponding to each group of vehicle message information.

2. The method according to claim 1, characterized in that According to the preset deviation value calculation method, the actual multi-dimensional message period and the standard message period corresponding to each group of vehicle message information are processed respectively to obtain the period deviation analysis result corresponding to each group of vehicle message information, including: According to the deviation value calculation formula, according to the maximum period in the actual multi-dimensional message period corresponding to each group of vehicle message information and the standard message period, the maximum period deviation analysis result corresponding to each group of vehicle message information is obtained; According to the deviation value calculation formula, according to the minimum period in the actual multi-dimensional message period corresponding to each group of vehicle message information and the standard message period, the minimum period deviation analysis result corresponding to each group of vehicle message information is obtained; According to the deviation value calculation formula, based on the average period in the actual multi-dimensional message period corresponding to each group of vehicle message information and the standard message period, the average period deviation analysis result corresponding to each group of vehicle message information is obtained.

3. The method according to claim 2, characterized in that Determining the quality analysis result corresponding to each group of vehicle message information according to the period deviation analysis result corresponding to each group of vehicle message information includes: Obtaining a first expected deviation analysis result and a second expected deviation analysis result, wherein the deviation degree of the second expected deviation analysis result is greater than that of the first expected deviation analysis result; The quality analysis result corresponding to each group of vehicle message information is determined based on the relationship between the maximum cycle deviation analysis result, the minimum cycle deviation analysis result and the average cycle deviation analysis result and the first expected deviation analysis result and the second expected deviation analysis result corresponding to each group of vehicle message information.

4. The method according to claim 3, characterized in that According to the relationship between the maximum cycle deviation analysis result, the minimum cycle deviation analysis result, and the average cycle deviation analysis result corresponding to each group of vehicle message information and the first expected deviation analysis result and the second expected deviation analysis result, the quality analysis result corresponding to each group of vehicle message information is determined, including: If there is a target analysis result greater than the first expected deviation analysis result among the maximum cycle deviation analysis result, the minimum cycle deviation analysis result and the average cycle deviation analysis result corresponding to each group of vehicle message information, the quality analysis result corresponding to each group of vehicle message information is determined to be abnormal; If the maximum period deviation analysis result corresponding to each group of vehicle message information is greater than the second expected deviation analysis result, the quality analysis result corresponding to each group of vehicle message information is determined to be lost; If the maximum period deviation analysis result, the minimum period deviation analysis result and the average period deviation analysis result corresponding to each group of vehicle message information are all smaller than the first expected deviation analysis result, the quality analysis result corresponding to each group of vehicle message information is determined to be normal.

5. The method according to claim 1, characterized in that Before acquiring multiple groups of vehicle message information, the method further includes: Collect DBC files and BLF files in the vehicle system according to the preset interface; Parsing the DBC file according to a preset parsing method to obtain defined message information, wherein the defined message information includes multiple message IDs, a standard message period corresponding to each message ID, and a DBC channel; Parsing the BLF file according to the preset parsing method to obtain actual message information, wherein the actual message information includes a plurality of vehicle message data, a message ID and a DBC channel corresponding to each vehicle message data, and an acquisition timestamp corresponding to each vehicle message data; A plurality of groups of vehicle message information are obtained according to the defined message information and the actual message information.

6. The method according to claim 5, characterized in that According to the defined message information and the actual message information, multiple groups of vehicle message information are obtained, including: According to the message ID and the DBC channel, the multiple vehicle message data in the actual message information are grouped to obtain a group of vehicle message data corresponding to each message ID and the DBC channel; Calculate the acquisition timestamp difference between every two vehicle message data in each group of vehicle message data to obtain multiple acquisition timestamp differences corresponding to each group of vehicle message data; Calculate the actual multi-dimensional message period corresponding to each group of vehicle message data according to the difference of multiple acquisition timestamps corresponding to each group of vehicle message data; A group of vehicle message data corresponding to each message ID, an actual multi-dimensional message period corresponding to each group of vehicle message data, and a standard message period corresponding to each message ID are determined as a group of vehicle message information corresponding to each message ID.

7. The method according to claim 6, characterized in that The actual multi-dimensional message period corresponding to each group of vehicle message data is calculated according to the difference of multiple acquisition timestamps corresponding to each group of vehicle message data, including: Determine the maximum value among a plurality of acquisition timestamp differences corresponding to each set of vehicle message data as the maximum period corresponding to each set of vehicle message data; Determine the minimum value among a plurality of acquisition timestamp differences corresponding to each set of vehicle message data as the minimum period corresponding to each set of vehicle message data; Determine the quotient between the sum of the multiple acquisition time stamp differences corresponding to each group of vehicle message data and the number of messages as the average period corresponding to each group of vehicle message data; The maximum period, the minimum period and the average period are determined as the actual multi-dimensional message period corresponding to each group of vehicle message data.

8. A quality analysis device for vehicle message data, characterized in that: The device comprises: An information acquisition unit, used to acquire multiple groups of vehicle message information, each group of vehicle message information including an actual multi-dimensional message period and a standard message period corresponding to each group of vehicle message data; A cycle processing unit, used to process the actual multi-dimensional message cycle and the standard message cycle corresponding to each group of vehicle message information acquired by the information acquisition unit according to a preset deviation value calculation method, and obtain a cycle deviation analysis result corresponding to each group of vehicle message information; The result analysis unit is used to determine the quality analysis result corresponding to each group of vehicle message information according to the period deviation analysis result corresponding to each group of vehicle message information obtained by the period processing unit.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the vehicle message data quality analysis method according to any one of claims 1 to 7.

10. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the vehicle message data quality analysis method according to any one of claims 1 to claim 7.

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