Vehicle operation information analysis method, device, equipment and storage medium

Abstract

The present application discloses a vehicle operation information analysis method, device, equipment and storage medium, which relates to the field of data analysis technology, including: collecting log information on each server, and performing preprocessing operations on the log information to obtain processed log information; extracting key information from the log information, and performing preset aggregation operations based on the key information and the processed log information to obtain aggregated information; determining abnormal vehicle passing behaviors based on preset data analysis operations and the aggregated information, and counting all the abnormal vehicle passing behaviors to obtain vehicle operation information. The present application processes a large amount of log information to obtain key information and processed log information, performs preset aggregation operations based on the above information, and converts abstract system logs into intuitive vehicle operation information, thereby improving the speed, accuracy and readability of information analysis.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to a vehicle operation information analysis method, device, equipment and storage medium. Background Art

[0002] With the elimination of provincial boundary stations on my country's highways and the popularization of non-stop toll collection, problems in lane transaction processes have also increased sharply. One of the sources used by users to judge various transaction anomalies is the log of the lane software, but the content of the lane log is numerous and the number is large, and it is difficult to accurately locate the problem and read it. Users cannot directly obtain key information, accurately judge the type of anomaly, or view the proportion of various anomalies at a macro level. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a vehicle operation information analysis method, device, equipment and storage medium, which can improve the speed, accuracy and readability of information analysis. The specific scheme is as follows:

[0004] In a first aspect, the present application discloses a vehicle operation information analysis method, comprising:

[0005] Collecting log information on each server and performing preprocessing operations on the log information to obtain processed log information;

[0006] Extracting key information from the log information, and performing a preset aggregation operation based on the key information and the processed log information to obtain aggregated information;

[0007] Based on the preset data analysis operation, the aggregated information is used to determine abnormal vehicle passing behaviors, and all the abnormal vehicle passing behaviors are counted to obtain vehicle operation information.

[0008] Optionally, collecting log information on each server includes:

[0009] The log information on each server is collected through the log collection and processing tool deployed on the Lane software, and the log information is sent to Logstash.

[0010] Optionally, performing a preprocessing operation on the log information to obtain processed log information includes:

[0011] Acquire a toll booth number and a lane number in the log information, and combine the toll booth number with the lane number to obtain combined information;

[0012] The combined information is used as a primary key and the log information is processed based on the preprocessing operation to obtain processed log information; the processed log information is log information with the same primary key.

[0013] Optionally, extracting key information from the log information includes:

[0014] The key information is extracted from the log information by a rule matching method; wherein the key information includes coil signals and vehicle passing behaviors.

[0015] Optionally, performing a preset aggregation operation based on the key information and the processed log information to obtain aggregated information includes:

[0016] Obtaining the key information corresponding to the processed log information to obtain target key information;

[0017] combining the coil signals in the target key information to obtain a combined coil signal;

[0018] The combined coil signal is converted into aggregated information through a preset aggregation method.

[0019] Optionally, combining the coil signals in the target key information to obtain a combined coil signal includes:

[0020] Combining the corresponding coil signals according to the acquisition order of the log information;

[0021] When the target end coil signal indicating the end of aggregation is combined, the combination is stopped and the combined coil signal is acquired.

[0022] Optionally, the determining the abnormal vehicle passing behavior based on the preset data analysis operation and the aggregated information includes:

[0023] Determine the abnormal vehicle passing behavior corresponding to each of the aggregated information based on a preset abnormal vehicle passing behavior determination rule;

[0024] The total number of abnormal vehicle passing times corresponding to each abnormal vehicle passing behavior is counted.

[0025] In a second aspect, the present application discloses a vehicle operation information analysis device, comprising:

[0026] A log information preprocessing module, used to collect log information on each server and perform preprocessing operations on the log information to obtain processed log information;

[0027] A key information extraction module, used to extract key information from the log information;

[0028] An aggregation module, used for performing a preset aggregation operation based on the key information and the processed log information to obtain aggregated information;

[0029] A behavior determination module, used to determine abnormal vehicle passing behavior based on a preset data analysis operation and the aggregated information;

[0030] The operation information determination module is used to collect statistics of all abnormal vehicle passing behaviors to obtain vehicle operation information.

[0031] In a third aspect, the present application discloses an electronic device, comprising:

[0032] Memory, used to store computer programs;

[0033] A processor is used to execute the computer program to implement the steps of the vehicle operation information analysis method disclosed above.

[0034] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the vehicle operation information analysis method disclosed above is implemented.

[0035] It can be seen that the present application provides a vehicle operation information analysis method, including: collecting log information on each server, and performing preprocessing operations on the log information to obtain processed log information; extracting key information from the log information, and performing preset aggregation operations based on the key information and the processed log information to obtain aggregated information; determining abnormal vehicle passing behaviors based on preset data analysis operations and the aggregated information, and counting all the abnormal vehicle passing behaviors to obtain vehicle operation information. It can be seen that the present application processes a large amount of log information to obtain key information and processed log information, and performs preset aggregation operations based on the above information to convert abstract system logs into intuitive vehicle operation information. Users can directly obtain vehicle operation information, which improves the speed, accuracy and readability of information analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0037] Figure 1 A flow chart of the vehicle operation information analysis method disclosed in this application;

[0038] Figure 2 A flowchart of a specific vehicle operation information analysis method disclosed in this application;

[0039] Figure 3A flowchart of a specific vehicle operation information analysis method disclosed in this application;

[0040] Figure 4 A schematic diagram of the structure of the vehicle operation information analysis device provided in this application;

[0041] Figure 5 A structural diagram of an electronic device provided for this application. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] At present, with the popularization of the cancellation of provincial boundary stations and the promotion of non-stop toll collection on my country's highways, the problems in the lane transaction process have also increased sharply. One of the sources used by users to judge various types of transaction anomalies is the log of the lane software, but the lane logs are numerous and large in number and cannot accurately locate the problem. The readability is poor, and users cannot directly obtain key information, accurately judge the type of anomaly, or view the proportion of various anomalies at a macro level. To this end, this application provides a vehicle operation information analysis method that can improve the speed, accuracy, and readability of information analysis.

[0044] The embodiment of the present invention discloses a vehicle operation information analysis method, see Figure 1 As shown, the method includes:

[0045] Step S11: collect log information on each server, and perform preprocessing operations on the log information to obtain processed log information.

[0046] In this embodiment, the log information on each server is collected, and the log information is preprocessed to obtain the processed log information. Specifically, the log information on each server is collected by the log collection and processing tool deployed on the Lane software, and the log information is sent to Logstash. Before collecting the log information on each server, the lightweight log collection and processing tool Filebeat is first deployed on the Lane software. Filebeat takes up few resources and is suitable for collecting logs on each server. The collected logs are then transferred to Logstash, and then Logstash is used to perform log analysis, filtering and other operations.

[0047] It is understandable that if Figure 2As shown in the figure, after the lane industrial computer generates logs, the lane logs are collected through Filebeat, and then the log information is sent to Logstash for parsing, enriching and converting the log information, and the results obtained after parsing and conversion are stored in the database, so as to obtain the corresponding data from the database and display it on the user page or other application systems.

[0048] Step S12: extract key information from the log information, and perform a preset aggregation operation based on the key information and the processed log information to obtain aggregated information.

[0049] In this embodiment, the log information on each server is collected, and a pre-processing operation is performed on the log information to obtain the processed log information, and then the key information in the log information is extracted, and a preset aggregation operation is performed based on the key information and the processed log information to obtain the aggregated information. Specifically, the key information is extracted from the log information by a rule matching method; wherein the key information includes coil signals and vehicle passing behaviors. The key information corresponding to the processed log information is obtained to obtain the target key information; the coil signals in the target key information are combined to obtain the combined coil signal; and the combined coil signal is converted into the aggregated information by a preset aggregation method. Wherein, the coil signals in the target key information are combined to obtain the combined coil signal, including: combining the corresponding coil signals in the order of obtaining the log information; when the target end coil signal representing the end of aggregation is combined, the combination is stopped and the combined coil signal is obtained.

[0050] Step S13: determining abnormal vehicle passing behaviors based on preset data analysis operations and the aggregated information, and counting all the abnormal vehicle passing behaviors to obtain vehicle operation information.

[0051] In this embodiment, after performing a preset aggregation operation based on the key information and the processed log information to obtain the aggregated information, the abnormal vehicle passing behavior is determined based on the preset data analysis operation and the aggregated information, and all the abnormal vehicle passing behaviors are counted to obtain the vehicle operation information. Specifically, the abnormal vehicle passing behavior corresponding to each of the aggregated information is determined based on a preset abnormal vehicle passing behavior determination rule; the total number of abnormal vehicle passing times corresponding to each abnormal vehicle passing behavior is counted, and all the abnormal vehicle passing behaviors are counted to obtain the vehicle operation information.

[0052] Currently, there are a large number of logs that cannot be accurately located, users cannot accurately determine the type of anomalies, and cannot view the proportion of various anomalies at a macro level. Therefore, this application designs a log analysis platform, which can perform in-depth analysis of lane logs, meet different scenarios according to existing conditions, analyze detailed transactions of ETC lanes, and form the impact of various factors on the ETC lane pass rate. The present invention is responsible for the first-level processing of logs in the log analysis platform, and can analyze the operation of the vehicle based on the coil state when the vehicle passes, and convert lane log information with poor readability into intuitive vehicle passing conditions.

[0053] It can be seen that the present application provides a vehicle operation information analysis method, including: collecting log information on each server, and performing preprocessing operations on the log information to obtain processed log information; extracting key information from the log information, and performing preset aggregation operations based on the key information and the processed log information to obtain aggregated information; determining abnormal vehicle passing behaviors based on preset data analysis operations and the aggregated information, and counting all the abnormal vehicle passing behaviors to obtain vehicle operation information. It can be seen that the present application processes a large amount of log information to obtain key information and processed log information, and performs preset aggregation operations based on the above information to convert abstract system logs into intuitive vehicle operation information. Users can directly obtain vehicle operation information, which improves the speed, accuracy and readability of information analysis.

[0054] See also Figure 3 As shown, the embodiment of the present invention discloses a vehicle operation information analysis method. Compared with the previous embodiment, this embodiment further illustrates and optimizes the technical solution.

[0055] Step S21: Collect log information on each server.

[0056] Step S22: Obtain the toll booth number and lane number in the log information, and combine the toll booth number with the lane number to obtain combined information.

[0057] In this embodiment, after collecting the log information on each server, the toll booth number and lane number in the log information are obtained, and the toll booth number and lane number are combined to obtain combined information. It can be understood that the log information contains a lot of information. In order to uniformly process the information with the same number, the toll booth number in the log information is combined with the lane number to obtain combined information, so that the log information with the same toll booth number and lane number can be uniformly processed using the combined information.

[0058] Step S23: using the combined information as a primary key and processing the log information based on the preprocessing operation to obtain processed log information; the processed log information is log information with the same primary key.

[0059] In this embodiment, after the toll booth number and the lane number are combined to obtain combined information, the combined information is used as the primary key and the log information is processed based on the preprocessing operation to obtain processed log information; the processed log information is the log information with the same primary key. It can be understood that after obtaining the combined information, the logs with the same combined information are counted with the combined information as the primary key to obtain the processed log information.

[0060] Step S24: extract key information from the log information, and perform a preset aggregation operation based on the key information and the processed log information to obtain aggregated information.

[0061] In this embodiment, the combined information is used as the primary key and the log information is processed based on the preprocessing operation to obtain the processed log information, then the key information in the log information is extracted, and a preset aggregation operation is performed based on the key information and the processed log information to obtain the aggregated information. It can be understood that in Logstash, key information such as coil signals and vehicle passing behaviors are extracted from the original log through rule matching so as to be used in subsequent aggregation.

[0062] Furthermore, the key information corresponding to the processed log information is obtained to obtain the target key information; the corresponding coil signals are combined in the order in which the log information is obtained; when the target end coil signal representing the end of aggregation is combined, the combination is stopped and the combined coil signal is obtained; the combined coil signal is converted into the aggregated information through a preset aggregation method. It is understandable that since there are multiple log information for the vehicle, the coil status information is first combined according to the order in which the log information is obtained to obtain a combined coil signal that can represent the complete status of the vehicle. It should be pointed out that in the process of combining coil signals, the "drop bar" behavior is used as the end mark of the coil status aggregation, that is, when the coil signal is a drop bar, the coil signal is stopped from being combined to obtain the current combined coil signal. The combined coil signal is converted into the aggregated information, and the specific conversion method is as shown in the following table:

[0063]

[0064] For example, when the coil signal is 00000000, convert 00000000 to C, and when the coil signal is drop bar, convert drop bar to A.

[0065] The obtained combined coil signal is converted according to the above table information to obtain the aggregated information. In the aggregation process, the coil states in each log are combined, and the "drop" behavior is used as the end mark of coil state aggregation. The obtained combined coil signal is converted into aggregated information, and the combination of coil states is analyzed after completion.

[0066] Step S25: Based on the preset data analysis operation and the aggregated information, abnormal vehicle passing behaviors are determined, and all the abnormal vehicle passing behaviors are counted to obtain vehicle operation information.

[0067] In this embodiment, after performing a preset aggregation operation based on the key information and the processed log information to obtain the aggregated information, the abnormal vehicle passing behavior is determined based on the preset data analysis operation and the aggregated information, and all the abnormal vehicle passing behaviors are counted to obtain the vehicle operation information. It can be understood that the abnormal vehicle passing behaviors corresponding to different aggregated information are preset, and then it is determined whether there is abnormal vehicle passing behavior in the currently obtained aggregated information. If so, the aggregated information representing the abnormal vehicle passing behavior is extracted, and the total number of abnormal vehicle passing times for each abnormal process behavior is counted. It should be pointed out that after detailed data analysis, the permutations and combinations of different coil states and the number of occurrences are defined as different abnormal vehicle passing behaviors. For example, when the coil state satisfies the regular expression / (.*)CDC(.*) / , the abnormal type is set to "coil distance is too large". After the total number of abnormal vehicle passing times corresponding to each abnormal vehicle passing behavior is obtained, the obtained information is analyzed and the final result obtained by the analysis is output.

[0068] This application can describe and reflect the operating status of the equipment when vehicles pass through the toll station lanes in a panoramic, immersive, materialized and truthful manner; it can accurately locate a large number of logs, and transform abstract system logs into intuitive and definable vehicle passing status, giving people deep insights and providing a basis for further analysis of the logs. It lays a solid foundation for toll stations to deal with abnormal traffic conditions and enhances the management and operation level of toll highways.

[0069] For the specific content of the above step S21, reference may be made to the corresponding content disclosed in the above embodiments, which will not be repeated here.

[0070] It can be seen that the embodiment of the present application collects log information on each server; obtains the toll station number and lane number in the log information, and combines the toll station number with the lane number to obtain combined information; uses the combined information as the primary key and processes the log information based on the preprocessing operation to obtain processed log information; the processed log information is the log information with the same primary key; extracts key information from the log information, and performs a preset aggregation operation based on the key information and the processed log information to obtain aggregated information; determines abnormal vehicle passing behaviors based on preset data analysis operations and the aggregated information, and counts all the abnormal vehicle passing behaviors to obtain vehicle operation information, thereby improving the speed, accuracy and readability of information analysis.

[0071] See also Figure 4 As shown, the embodiment of the present application also discloses a vehicle operation information analysis device, including:

[0072] The log information preprocessing module 11 is used to collect the log information on each server and perform preprocessing operations on the log information to obtain processed log information;

[0073] A key information extraction module 12, used to extract key information from the log information;

[0074] An aggregation module 13, configured to perform a preset aggregation operation based on the key information and the processed log information to obtain aggregated information;

[0075] A behavior determination module 14, configured to determine abnormal vehicle passing behavior based on a preset data analysis operation and the aggregated information;

[0076] The operation information determination module 15 is used to collect statistics of all the abnormal vehicle passing behaviors to obtain vehicle operation information.

[0077] It can be seen that the present application includes: collecting log information on each server, and performing preprocessing operations on the log information to obtain processed log information; extracting key information from the log information, and performing preset aggregation operations based on the key information and the processed log information to obtain aggregated information; determining abnormal vehicle passing behaviors based on preset data analysis operations and the aggregated information, and counting all the abnormal vehicle passing behaviors to obtain vehicle operation information. It can be seen that the present application processes a large amount of log information to obtain key information and processed log information, and performs preset aggregation operations based on the above information to convert abstract system logs into intuitive vehicle operation information. Users can directly obtain vehicle operation information, which improves the speed, accuracy and readability of information analysis.

[0078] In some specific embodiments, the log information preprocessing module 11 specifically includes:

[0079] A log information collection unit, used to collect log information on each server through a log collection and processing tool deployed on the Lane software;

[0080] A log information sending unit, used to send the log information to Logstash;

[0081] A number acquisition unit, used to acquire the toll station number and lane number in the log information;

[0082] A number combination unit, used for combining the toll booth number with the lane number to obtain combination information;

[0083] The log preprocessing unit is used to use the combined information as a primary key and process the log information based on the preprocessing operation to obtain processed log information; the processed log information is the log information with the same primary key.

[0084] In some specific embodiments, the key information extraction module 12 specifically includes:

[0085] The key information extraction unit is used to extract key information from the log information by a rule matching method; wherein the key information includes coil signals and vehicle passing behaviors.

[0086] In some specific embodiments, the aggregation module 13 specifically includes:

[0087] a target key information determining unit, configured to obtain the key information corresponding to the processed log information to obtain the target key information;

[0088] A coil signal combining unit, used for combining the corresponding coil signals according to the acquisition order of the log information;

[0089] A combined coil signal determination unit, configured to stop combining and obtain the combined coil signal when a target end coil signal representing the end of aggregation is combined;

[0090] The aggregation unit is used to convert the combined coil signal into aggregated information through a preset aggregation method.

[0091] In some specific embodiments, the behavior determination module 14 specifically includes:

[0092] An abnormal vehicle passing behavior determination unit, used to determine the abnormal vehicle passing behavior corresponding to each of the aggregated information based on a preset abnormal vehicle passing behavior determination rule;

[0093] The total abnormal vehicle passing times counting unit is used to count the total abnormal vehicle passing times corresponding to each abnormal vehicle passing behavior.

[0094] In some specific embodiments, the operation information determination module 15 specifically includes:

[0095] The operation information determination unit is used to collect statistics of all abnormal vehicle passing behaviors to obtain vehicle operation information.

[0096] Furthermore, an embodiment of the present application also provides an electronic device. Figure 5 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0097] Figure 5 The present invention provides a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the vehicle operation information analysis method disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0098] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0099] In addition, the memory 22, as a carrier for storing resources, can be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0100] The operating system 221 is used to manage and control the hardware devices and computer programs 222 on the electronic device 20, and may be Windows Server, Netware, Unix, Linux, etc. In addition to computer programs that can be used to complete the vehicle operation information analysis method performed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 may further include computer programs that can be used to complete other specific tasks.

[0101] Furthermore, an embodiment of the present application also discloses a storage medium, in which a computer program is stored. When the computer program is loaded and executed by a processor, the steps of the vehicle operation information analysis method disclosed in any of the aforementioned embodiments are implemented.

[0102] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0103] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article 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, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0104] The vehicle operation information analysis method, device, equipment and storage medium provided by the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A vehicle operation information analysis method, characterized in that: include: Collecting log information on each server and performing preprocessing operations on the log information to obtain processed log information; Extracting key information from the log information, and performing a preset aggregation operation based on the key information and the processed log information to obtain aggregated information; Based on the preset data analysis operation and the aggregated information, abnormal vehicle passing behaviors are determined, and all abnormal vehicle passing behaviors are counted to obtain vehicle operation information; The step of extracting key information from the log information includes: Extract key information from the log information by rule matching method; wherein the key information includes coil signal and vehicle passing behavior; the coil signal is 0 or 1; The performing of a preset aggregation operation based on the key information and the processed log information to obtain aggregated information includes: Obtaining the key information corresponding to the processed log information to obtain target key information; combining the coil signals in the target key information to obtain a combined coil signal; The combined coil signal is converted into aggregated information by a preset aggregation method; the aggregated information is information that simply represents the combined coil signal.

2. The vehicle operation information analysis method according to claim 1, characterized in that: The log information collected on each server includes: The log information on each server is collected through the log collection and processing tool deployed on the Lane software, and the log information is sent to Logstash.

3. The vehicle operation information analysis method according to claim 1, characterized in that: The performing a preprocessing operation on the log information to obtain processed log information includes: Obtaining a toll booth number and a lane number in the log information, and combining the toll booth number with the lane number to obtain combined information; The combined information is used as a primary key and the log information is processed based on the preprocessing operation to obtain processed log information; the processed log information is log information with the same primary key.

4. The vehicle operation information analysis method according to claim 1, characterized in that: The step of combining the coil signals in the target key information to obtain a combined coil signal includes: Combining the corresponding coil signals according to the acquisition order of the log information; When the target end coil signal indicating the end of aggregation is combined, the combination is stopped and the combined coil signal is acquired.

5. The vehicle operation information analysis method according to any one of claims 1 to 4, characterized in that: The determining of abnormal vehicle passing behavior based on the preset data analysis operation and the aggregated information includes: Determine the abnormal vehicle passing behavior corresponding to each of the aggregated information based on a preset abnormal vehicle passing behavior determination rule; The total number of abnormal vehicle passing times corresponding to each abnormal vehicle passing behavior is counted.

6. A vehicle operation information analysis device, characterized in that: include: A log information preprocessing module, used to collect log information on each server and perform preprocessing operations on the log information to obtain processed log information; A key information extraction module, used to extract key information from the log information; An aggregation module, used for performing a preset aggregation operation based on the key information and the processed log information to obtain aggregated information; A behavior determination module, used to determine abnormal vehicle passing behavior based on a preset data analysis operation and the aggregated information; An operation information determination module is used to collect statistics of all abnormal vehicle passing behaviors to obtain vehicle operation information; Wherein, the key information extraction module specifically includes: A key information extraction unit, used to extract key information from the log information by a rule matching method; wherein the key information includes a coil signal and a vehicle passing behavior; the coil signal is 0 or 1; The aggregation module specifically includes: a target key information determining unit, configured to obtain the key information corresponding to the processed log information to obtain the target key information; A combined coil signal acquisition unit, used for combining the coil signals in the target key information to obtain a combined coil signal; The aggregation unit is used to convert the combined coil signal into aggregated information by a preset aggregation method; the aggregated information is information that simply represents the combined coil signal.

7. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the vehicle operation information analysis method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: Used to store computer programs; wherein, when the computer program is executed by a processor, the vehicle operation information analysis method as described in any one of claims 1 to 5 is implemented.

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