Vehicle data processing method and device, computer equipment, storage medium and computer program product

Abstract

The invention relates to a vehicle data processing method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: determining a target driving state corresponding to target vehicle data, obtaining a first vehicle data table corresponding to the target driving state, and obtaining a non-empty second vehicle data table corresponding to other preset driving states; under the condition that the second vehicle data table meets the independent statistical condition, performing statistics on the vehicle data in the second vehicle data table to obtain a data statistical result, emptying the second vehicle data table, and writing the target vehicle data into the first vehicle data table; or under the condition that the independent statistical condition is not met, all the vehicle data in the second vehicle data table are moved to the first vehicle data table, and the target vehicle data are written into the first vehicle data table. By adopting the method, real-time statistics can be carried out on the vehicle data generated by the vehicle in different driving states in the vehicle driving process.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a vehicle data processing method, apparatus, computer equipment, storage medium and computer program product. Background Art

[0002] With the development of new energy vehicles, due to the need to analyze the driving behavior of drivers of new energy vehicles and analyze the vehicle's operating status in different scenarios, new energy vehicle companies usually need to collect the vehicle's actual operating data during driving for real-time data statistics, and display the statistical results on the display devices of new energy vehicles or technicians, so that drivers or technicians can know the vehicle's operating status in a timely manner.

[0003] In the related technology, a TBOX (Telematics BOX, a vehicle-mounted communication terminal used for vehicles to communicate with external networks) can be installed on the vehicle to enable the vehicle to send vehicle data to the outside, and a vehicle data processing platform can also be set up to store, process, analyze and display the data at a fixed frequency.

[0004] However, in the related art, the different driving states of the vehicle during the driving process and the various statistical data corresponding to the different driving states can generally only be displayed to the driver after the vehicle has completed a driving, resulting in the generation and display of statistical data not being timely. Therefore, it is necessary to provide a solution that can classify the data reported by the vehicle into different driving states and generate the corresponding statistical results of the vehicle in different driving states in real time. Summary of the invention

[0005] Based on this, it is necessary to provide a vehicle data processing method, device, computer equipment, storage medium and computer program product to address the above technical problems.

[0006] In a first aspect, the present application provides a vehicle data processing method. The method comprises:

[0007] Obtain target vehicle data uploaded by the target vehicle, determine a target driving state corresponding to the target vehicle data from each preset driving state, obtain a first vehicle data table corresponding to the target driving state, and obtain a second vehicle data table that is not empty from vehicle data tables corresponding to preset driving states other than the target driving state;

[0008] If the second vehicle data table meets the independent statistical condition, statistical processing is performed on each vehicle data in the second vehicle data table to obtain the data statistical result of the preset driving state corresponding to the second vehicle data table, the second vehicle data table is cleared, and the target vehicle data is written into the first vehicle data table; or

[0009] When the second vehicle data table does not satisfy the independent statistical condition, all vehicle data in the second vehicle data table are moved to the first vehicle data table, and the target vehicle data is written into the first vehicle data table.

[0010] In one embodiment, the method further comprises:

[0011] Determine the data collection time range corresponding to the second vehicle data table according to the collection time of each vehicle data in the second vehicle data table, and determine that the second vehicle data table meets the independent statistical condition when the length of the data collection time range is greater than a preset time threshold; and / or,

[0012] Obtain a vehicle data range corresponding to the target driving state, respectively determine the difference between each vehicle data in the second vehicle data table and each boundary value of the vehicle data range, and determine that the second vehicle data table satisfies the independent statistical condition when all the difference values ​​corresponding to more than a preset number of vehicle data are greater than a preset difference threshold.

[0013] In one embodiment, each of the preset driving states has an importance level, and the method further includes:

[0014] When the importance level of the preset driving state corresponding to the second vehicle data table is higher than the importance level of the target driving state, the target vehicle data is written into the first vehicle data table, and the process jumps to the step of obtaining the target vehicle data uploaded by the target vehicle; or

[0015] When the importance level of the preset driving state corresponding to the second vehicle data table is lower than the importance level of the target driving state, determining whether the second vehicle data table satisfies an independent statistical condition;

[0016] Before writing the target vehicle data into the first vehicle data table, the method further includes:

[0017] If the first vehicle data table is not empty, statistical processing is performed on the vehicle data in the first vehicle data table to obtain data statistical results of the preset driving state corresponding to the first vehicle statistical table, and the first vehicle data table is cleared.

[0018] In one embodiment, obtaining the target vehicle data uploaded by the target vehicle includes:

[0019] In a statistical period, receiving an uplink message sent by the target vehicle, wherein the uplink message includes a vehicle data reporting message;

[0020] When the statistical period ends, obtaining the vehicle data carried by each of the vehicle data reporting messages received during the statistical period;

[0021] Traversing each of the vehicle data from early to late according to the collection time of each of the vehicle data, and taking the currently traversed vehicle data as the target vehicle data;

[0022] The method further comprises:

[0023] When all vehicle data within the statistical period have been traversed, the vehicle data in the vehicle data table corresponding to each of the preset driving states are statistically processed to obtain the data statistical results of each of the preset driving states, and the vehicle data table corresponding to each of the preset driving states is cleared.

[0024] In one embodiment, the uplink message further includes a vehicle logout message, and before determining the target driving state corresponding to the target vehicle data from each preset driving state, the method further includes:

[0025] Determine a preceding uplink message of a vehicle data reporting message to which the target vehicle data belongs;

[0026] In the case where the preceding uplink message is the vehicle logout message, the vehicle data in the vehicle data table corresponding to each of the preset driving states is statistically processed to obtain the data statistical results of each of the preset driving states, and the vehicle data table corresponding to each of the preset driving states is cleared.

[0027] In one embodiment, the method further comprises:

[0028] In a case where the preceding uplink message is not the vehicle logout message, determining a time difference between a collection time of the target vehicle data and a collection time of preceding vehicle data of the target vehicle data;

[0029] When the time difference is greater than a preset time difference threshold, the vehicle data in the vehicle data table corresponding to each preset driving state is statistically processed to obtain the data statistical results of each preset driving state, and the vehicle data table corresponding to each preset driving state is cleared.

[0030] In a second aspect, the present application also provides a vehicle data processing device. The device comprises:

[0031] an acquisition module, configured to acquire target vehicle data uploaded by a target vehicle, determine a target driving state corresponding to the target vehicle data from each preset driving state, acquire a first vehicle data table corresponding to the target driving state, and acquire a second vehicle data table that is not empty from vehicle data tables corresponding to preset driving states other than the target driving state;

[0032] A processing module is used to perform statistical processing on each vehicle data in the second vehicle data table when the second vehicle data table meets the independent statistical conditions, obtain the data statistical results of the preset driving state corresponding to the second vehicle data table, clear the second vehicle data table, and write the target vehicle data into the first vehicle data table; or when the second vehicle data table does not meet the independent statistical conditions, move all vehicle data in the second vehicle data table to the first vehicle data table, and write the target vehicle data into the first vehicle data table.

[0033] In one embodiment, the device further comprises:

[0034] A first determination module is used to determine the data collection time range corresponding to the second vehicle data table according to the collection time of each vehicle data in the second vehicle data table, and determine that the second vehicle data table meets the independent statistical condition when the length of the data collection time range is greater than a preset time length threshold; and / or obtain the vehicle data range corresponding to the target driving state, respectively determine the difference between each vehicle data in the second vehicle data table and each boundary value of the vehicle data range, and determine that the second vehicle data table meets the independent statistical condition when all the differences corresponding to more than a preset number of vehicle data are greater than a preset difference threshold.

[0035] In one embodiment, each of the preset driving states has an importance level, and the device further includes:

[0036] A second determination module is used to write the target vehicle data into the first vehicle data table and jump to the step of obtaining the target vehicle data uploaded by the target vehicle when the importance level of the preset driving state corresponding to the second vehicle data table is higher than the importance level of the target driving state; or to determine whether the second vehicle data table meets the independent statistical condition when the importance level of the preset driving state corresponding to the second vehicle data table is lower than the importance level of the target driving state;

[0037] The first statistical module is used to perform statistical processing on the vehicle data in the first vehicle data table if the first vehicle data table is not empty, obtain the data statistical results of the preset driving state corresponding to the first vehicle statistical table, and clear the first vehicle data table.

[0038] In one embodiment, the acquisition module is further used for:

[0039] In a statistical period, receiving an uplink message sent by the target vehicle, wherein the uplink message includes a vehicle data reporting message;

[0040] When the statistical period ends, obtaining the vehicle data carried by each of the vehicle data reporting messages received during the statistical period;

[0041] Traversing each of the vehicle data from early to late according to the collection time of each of the vehicle data, and taking the currently traversed vehicle data as the target vehicle data;

[0042] The device also includes:

[0043] The second statistical module is used to perform statistical processing on the vehicle data in the vehicle data table corresponding to each preset driving state after all the vehicle data within the statistical period have been traversed, obtain the data statistical results of each preset driving state, and clear the vehicle data table corresponding to each preset driving state.

[0044] In one embodiment, the uplink message further includes a vehicle logout message, and the device further includes:

[0045] A third determination module, used to determine a preceding uplink message of the vehicle data reporting message to which the target vehicle data belongs;

[0046] The third statistical module is used to perform statistical processing on the vehicle data in the vehicle data table corresponding to each of the preset driving states when the previous uplink message is the vehicle logout message, obtain the data statistical results of each of the preset driving states, and clear the vehicle data table corresponding to each of the preset driving states.

[0047] In one embodiment, the device further comprises:

[0048] A fourth determination module, for determining, when the preceding uplink message is not the vehicle logout message, a time difference between a collection time of the target vehicle data and a collection time of a preceding vehicle data of the target vehicle data;

[0049] The fourth statistical module is used to perform statistical processing on the vehicle data in the vehicle data table corresponding to each of the preset driving states when the time difference is greater than the preset time difference threshold, obtain the data statistical results of each of the preset driving states, and clear the vehicle data table corresponding to each of the preset driving states.

[0050] In a third aspect, the present application further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, any one of the above methods is implemented.

[0051] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, any of the above methods is implemented.

[0052] In a fifth aspect, the present application further provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, any of the above methods is implemented.

[0053] The vehicle data processing method, device, computer equipment, storage medium and computer program product obtain the target vehicle data, and after determining the target driving state to which the target vehicle data belongs from each preset driving state, determine whether the second vehicle data table corresponding to other preset driving states is empty. If there is a non-empty second vehicle data table, it indicates that the target vehicle may have switched driving states at the time of collecting the target vehicle data, and it is necessary to perform data statistics on the previous driving state. At this time, by verifying whether the second vehicle data table meets the independent statistical condition, it can be determined whether the driving state classification of the vehicle data in the second vehicle data table is appropriate. In the case where the second vehicle data table meets the independent statistical condition, the second vehicle data table is counted and the target vehicle data is written into the first vehicle data table. In the case where the second vehicle data table does not meet the independent statistical condition, the vehicle data in the second vehicle data table is moved to the first vehicle data table, that is, the vehicle data is reclassified into the target driving state. Therefore, during the vehicle driving process, the vehicle data generated by the vehicle under different driving states can be counted in real time, thereby improving the real-time nature of the generated data statistical results. At the same time, the driving state classification of the vehicle data can also be corrected in real time, thereby improving the accuracy of the data statistical results corresponding to each driving state. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic flow chart of a vehicle data processing method in one embodiment;

[0055] Figure 2 is a flow chart of a vehicle data processing method in one embodiment taking importance levels into consideration;

[0056] Figure 3 is a flow chart of step 102 in one embodiment;

[0057] Figure 4 It is a schematic diagram of a flow chart for respectively counting vehicle data before and after the vehicle is turned off in one embodiment;

[0058] Figure 5 It is a schematic diagram of a flow chart of respectively collecting statistics on discontinuous vehicle data in one embodiment;

[0059] Figure 6 A schematic flow chart of a vehicle data processing method in one embodiment;

[0060] Figure 7 is a structural block diagram of a vehicle data processing device in one embodiment;

[0061] Figure 8 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] In one embodiment, Figure 1 As shown, a vehicle data processing method is provided. This embodiment takes the method applied to a server as an example for illustration. It is understandable that the method can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0064] Step 102, obtain the target vehicle data uploaded by the target vehicle, determine the target driving state corresponding to the target vehicle data from each preset driving state, obtain a first vehicle data table corresponding to the target driving state, and obtain a second vehicle data table that is not empty from the vehicle data tables corresponding to the preset driving states other than the target driving state.

[0065] In an embodiment of the present application, the server simultaneously receives vehicle data reporting messages periodically sent to the server by multiple vehicles, and the vehicle data reporting messages carry vehicle data collected by the vehicle through sensors. Vehicle data may include various types of data, such as: speed data, position coordinate data, power data (if the vehicle is a new energy vehicle), fuel consumption data (if the vehicle is a fuel vehicle), etc. The specific data included can be determined based on the communication protocol used between the vehicle and the server (such as the GB / T32970 protocol, etc.). The target vehicle is any one of the vehicles, and the target vehicle data refers to the vehicle data that the server currently needs to process for the target vehicle.

[0066] The embodiments of the present application do not specifically limit how the server obtains the target vehicle data. In one example, the server can identify which vehicle the vehicle data belongs to based on the unique vehicle identification code (such as the VIN code (Vehicle Identification Number)) carried in the vehicle data, and temporarily store the vehicle data in the message queue corresponding to the vehicle, and pull one vehicle data from the message queue each time as the target vehicle data. That is, the server can perform streaming processing on the acquired vehicle data. In another example, after identifying which vehicle the vehicle data belongs to, the server can store the vehicle data in the data table corresponding to the vehicle in the database, and traverse the data table regularly, and use the currently traversed vehicle data as the target vehicle data. That is, the server can perform batch processing on the acquired vehicle data. The specific data processing method to be adopted can be determined according to actual needs, and the embodiments of the present application do not specifically limit this.

[0067] After the server obtains the target vehicle data that needs to be processed, it determines which driving state the target vehicle data corresponds to, which is equivalent to determining the driving state of the target vehicle at the time of collecting the target vehicle data. Multiple preset driving states can be set in advance according to the actual needs of data statistics, such as: highway driving state, urban road driving state, congestion state, stationary state, etc. Then, according to the various types of data contained in the target vehicle data, the target driving state corresponding to the target vehicle data is determined.

[0068] The embodiments of the present application do not limit how to determine the target driving state corresponding to the target vehicle data. In one example, a corresponding vehicle data range can be set for each of the above-mentioned preset driving states, and the vehicle data range can be composed of a data range corresponding to each data type contained in the vehicle data. According to the data range to which each type of data in the target vehicle data belongs, the target driving state corresponding to the target vehicle data can be determined. This method is more efficient in determining the target driving state.

[0069] Taking the preset driving state including the highway driving state, the urban road driving state and other driving states, and the vehicle data including at least the speed data and the position coordinate data as an example, it is assumed that in the vehicle data range corresponding to the highway driving state, the data range corresponding to the speed data is A1 to B1, and the data range corresponding to the position coordinate data is A2 to B2; in the vehicle data range corresponding to the urban road driving state, the data range corresponding to the speed data is C1 to D1, and the data range corresponding to the position coordinate data is C2 to D2; other driving states correspond to the data range not covered by the first two driving states. Then, when the speed data in the target vehicle data belongs to C1 to D1, and the position coordinate data belongs to C2 to D2, it can be judged that the target driving state corresponding to the target vehicle data is the urban road driving state. When the speed data in the target vehicle data belongs to C1 to D1, and the position coordinate data belongs to A2 to B2, it can be judged that the target driving state corresponding to the target vehicle data is other driving states.

[0070] In another example, the server may cache a preset number of vehicle data processed for the target vehicle before processing the target vehicle data, or vehicle data processed within a preset length of time before processing the target vehicle data (hereinafter referred to as cached data). A classification model that can receive a data sequence as input and output the driving state to which the last data of the data sequence belongs can be trained, and the server can call the classification model. When determining the target driving state, the server can combine the cached data and the target vehicle data into a data sequence in the order of collection time, input the data sequence into the classification model, and obtain the target driving state corresponding to the target vehicle data. That is, it is equivalent to referring to the data uploaded by the target vehicle before the target vehicle data when judging the target driving state to which the target vehicle data belongs. In this way, the accuracy of judging the target driving state is higher.

[0071] Each preset driving state has a corresponding vehicle data table in the server. The vehicle data table stores the vehicle data that has not been counted in each preset driving state. After determining the target driving state corresponding to the target vehicle data, the server reads the vehicle data table corresponding to the target driving state (the first vehicle data table), and reads the vehicle data tables corresponding to each other preset driving state (the second vehicle data table) respectively. If each second vehicle data table is empty, it means that the driving state of the target vehicle at this time is the same as before. At this time, the target vehicle data can be written into the first vehicle data table, and the next target vehicle data can be obtained. Furthermore, the number of vehicle data currently stored in the first vehicle data table can also be determined, and the first vehicle data table can be counted once when the number of vehicle data is greater than a certain threshold, and then the first vehicle data table is cleared to ensure that the server can return at least one data statistical result to the target vehicle every certain time interval.

[0072] If any of the second vehicle data tables is not empty, it indicates that the current driving state of the target vehicle may be different from the previous one, and the previous driving state may have ended. Therefore, it is possible to determine whether the various vehicle data generated by the target vehicle in the previous driving state need to be counted.

[0073] Step 104, when the second vehicle data table meets the independent statistical conditions, statistical processing is performed on each vehicle data in the second vehicle data table to obtain the data statistical results of the preset driving state corresponding to the second vehicle data table, the second vehicle data table is cleared, and the target vehicle data is written into the first vehicle data table. Or,

[0074] Step 106, when the second vehicle data table does not meet the independent statistical condition, all vehicle data in the second vehicle data table are moved to the first vehicle data table, and the target vehicle data is written into the first vehicle data table.

[0075] In an embodiment of the present application, the independent statistical condition is used to determine whether, on the basis of acquiring the target vehicle data, each vehicle data in the second vehicle data table is more appropriately counted as the vehicle data under the target driving state. For example, when the number of each vehicle data in the second vehicle data table is small, the acquisition time range covered by each vehicle data is short, and the vehicle data range corresponding to each vehicle data and the target vehicle data is relatively close, it can be determined that the vehicle data in the second vehicle data table is more suitable as the data under the target driving state. At this time, it can be determined that the second vehicle data table does not meet the independent statistical condition. When the second vehicle data table does not meet the above conditions, or the second vehicle data table meets the above conditions, but the preset driving state corresponding to the second vehicle data table is a preset driving state with higher importance, it can be determined that the second vehicle data table meets the independent statistical condition.

[0076] If the second vehicle data table meets the independent statistical condition, a statistical process may be performed on each vehicle data in the second vehicle data table. The statistical process may include but is not limited to calculating the moving distance, average speed, power consumption or fuel consumption of the target vehicle based on each vehicle data. After obtaining the data statistical results, the server may send the data statistical results to the target vehicle, so that the target vehicle displays the data statistical results on a display device, so that the driver can timely understand the operating status of the target vehicle.

[0077] After completing the statistics of the second vehicle data table, the server clears the second vehicle data table. The server also needs to write the target vehicle data into the first vehicle data table. When the second vehicle data table meets the independent statistics condition, there is no order relationship between the step of writing the target vehicle data into the first vehicle data table and the step of counting the second vehicle data table. This step can be executed before or after counting the second vehicle data table, or it can be executed in parallel with counting the second vehicle data table.

[0078] If the second vehicle data table does not meet the independent statistical conditions, it is necessary to move each vehicle data in the second vehicle data table to the first vehicle data table, which is equivalent to taking each vehicle data recorded in the second vehicle data table as data generated under the target driving state for statistical purposes. Since it is necessary to ensure that the vehicle data in each vehicle data table are arranged in the order of collection time, it is necessary to write the target vehicle data into the first vehicle data table after moving each vehicle data in the second vehicle data table to the first vehicle data table.

[0079] After writing the target vehicle data into the first vehicle data table, the server continues to obtain the target vehicle data. When the server fails to obtain new target vehicle data within a certain preset time, or when the server receives a message from the target vehicle indicating that the target vehicle has been shut down and offline, the server can perform a statistics on the vehicle data tables of all preset driving states, and send the data statistics results to the target vehicle for display. The server can also obtain all data statistics results generated during the entire journey of the target vehicle from ignition to shutdown, and further perform comprehensive statistics on each data statistical result (for example, calculating the total time of the entire journey, the average speed, the proportion of the duration of each preset driving state in the total journey time, etc.), and then send the comprehensive statistical results to the target vehicle for display, so that the driver can obtain more information about the operating status of the target vehicle.

[0080] The above process is explained below with an actual example. Assume that there are two preset driving states: static state and moving state. The criterion for static state is that the speed data carried in the vehicle data is 0, and the criterion for moving state is that the speed data carried in the vehicle data is greater than 0. Except for the time point A when the speed of the target vehicle temporarily drops to 0, the speed of the target vehicle at other time points is greater than 0.

[0081] All vehicle data collected before time point A are classified as moving state and stored in the vehicle data table corresponding to the moving state. When processing vehicle data a collected at time point A, since the speed data carried in vehicle data a is 0, vehicle data a is classified as stationary. The server obtains the vehicle data table of the stationary state and the vehicle data table of the moving state. Since the vehicle data table of the moving state is not empty, the server makes a judgment on whether the vehicle data table of the moving state meets the independent statistical conditions. Assuming that the vehicle data table of the moving state meets the independent statistical conditions, the server performs statistics on the vehicle data table to obtain the data statistical results, clears the vehicle data table, and writes the vehicle data a into the vehicle data table of the moving state.

[0082] The server continues to obtain the target vehicle data. The speed data carried by the vehicle data b collected at time point B one moment after time point A is greater than 0, so the vehicle data b is classified as a moving state. The server obtains the vehicle data table in the stationary state and the vehicle data table in the moving state. Since the vehicle data table in the stationary state is not empty, the server makes a judgment on whether the vehicle data table in the stationary state meets the independent statistical conditions. At this time, since there is only one vehicle data in the vehicle data table in the stationary state, it can be considered that the state of the target vehicle at time point B is closer to the temporary drop in speed to 0 at a certain moment in the moving process, rather than the conversion from a moving process to a stationary process. Therefore, the vehicle data table in the stationary state does not meet the independent statistical conditions. The server moves the vehicle data a to the vehicle data table in the moving state, and then writes the vehicle data b after the vehicle data a.

[0083] The server continues to obtain the target vehicle data. If the speed data carried by a certain vehicle data c is subsequently collected as 0, the vehicle data c is classified as a stationary state. At this time, the vehicle data table in motion meets the independent statistical conditions, so the server performs a statistical analysis on the vehicle data table in motion. In the above process, although there is a vehicle data a with a speed data of 0 in the middle, the target vehicle is still regarded as being in motion throughout the entire journey during the statistical process. It can be seen that through the above method, the classification judgment of previous data can be corrected in real time in the real-time data processing scenario, thereby improving the statistical accuracy of the data generated by the vehicle under different driving conditions.

[0084] The vehicle data processing method provided by the embodiment of the present application obtains the target vehicle data, and after determining the target driving state to which the target vehicle data belongs from each preset driving state, determines whether the second vehicle data table corresponding to other preset driving states is empty. If there is a non-empty second vehicle data table, it indicates that the target vehicle may have switched driving states at the time of collecting the target vehicle data, and it is necessary to perform a data statistics on the previous driving state. At this time, by verifying whether the second vehicle data table meets the independent statistical condition, it can be determined whether the driving state classification of the vehicle data in the second vehicle data table is appropriate. In the case where the second vehicle data table meets the independent statistical condition, the second vehicle data table is counted and the target vehicle data is written into the first vehicle data table. In the case where the second vehicle data table does not meet the independent statistical condition, the vehicle data in the second vehicle data table is moved to the first vehicle data table, that is, the vehicle data is reclassified into the target driving state. Therefore, in the process of vehicle driving, the vehicle data generated by the vehicle under different driving states can be counted in real time to improve the real-time nature of the generated data statistical results. At the same time, the driving state classification of the vehicle data can also be corrected in real time to improve the accuracy of the data statistical results corresponding to each driving state.

[0085] In one embodiment, the method further includes:

[0086] Determine the data collection time range corresponding to the second vehicle data table according to the collection time of each vehicle data in the second vehicle data table, and determine that the second vehicle data table meets the independent statistical condition when the length of the data collection time range is greater than a preset time threshold; and / or,

[0087] Obtain a vehicle data range corresponding to the target driving state, determine the difference between each vehicle data in the second vehicle data table and each boundary value of the vehicle data range, and determine that the second vehicle data table meets the independent statistical condition when all the difference values ​​corresponding to each vehicle data are greater than a preset difference threshold.

[0088] In an embodiment of the present application, the independent statistical condition may be that the vehicle data in the second vehicle data table covers a sufficiently long time range, that is, the target vehicle is in the preset driving state corresponding to the second vehicle data table for a long enough time; or the difference between the vehicle data in the second vehicle data table and the vehicle data range corresponding to the target driving state is large enough, that is, the vehicle data in the second vehicle data table is not suitable for being classified into the target driving state for statistics.

[0089] The time range covered by the vehicle data in the second vehicle data table can be determined according to the collection time of each vehicle data. When the target vehicle reports the vehicle data, it will carry the timestamp corresponding to the time point of collecting the vehicle data in the vehicle data. The moment represented by the timestamp is also the collection time of the vehicle data. Since the vehicle data is arranged in the vehicle data table in the order of collection time, the collection time of the vehicle data arranged at the last position in the second vehicle data table can be subtracted from the collection time of the vehicle data arranged at the first position to obtain the data collection time range. If the length of the data collection time range is greater than the preset time length threshold, it indicates that each vehicle data in the second vehicle data table is suitable for being counted as a separate driving state and meets the independent statistical conditions. If the length of the data collection time range is less than or equal to the preset time length threshold, it indicates that each vehicle data in the second vehicle data table is more suitable for being counted together with the data under other driving states, and the second vehicle data table does not meet the independent statistical conditions.

[0090] The vehicle data range corresponding to the target driving state is preset. In the embodiment of the present application, the target driving state corresponding to the target vehicle data is determined according to the vehicle data range corresponding to which preset driving state the target vehicle data belongs to. The specific definition of the vehicle data range can be referred to the description of the aforementioned embodiment, and the embodiment of the present application will not be repeated. Taking the case that the vehicle data only includes data of one data type, and the vehicle data range also only includes the data range of the data type, assuming that the data range of the data type is A to B, C to D and E to F, then for each vehicle data, the difference between the vehicle data and A, B, C, D, E, and F can be calculated respectively. If at least one of the six differences corresponding to most of the vehicle data is less than or equal to the preset difference threshold, it can be determined that each vehicle data in the second vehicle data table is suitable for being counted as data under the target driving state, and the second vehicle data table does not meet the independent statistical condition. If at least a preset number (which can be set to a fixed value, or set to a certain proportion of the total number of vehicle data in the second vehicle data table) of the six differences of the vehicle data are greater than the preset difference threshold, the second vehicle data table meets the independent statistical condition. In the case where the vehicle data includes multiple types of data, the above process can be referred to to make a difference between each type of data and each boundary value of the data range corresponding to the data type in the vehicle data range, and the embodiments of the present application will not be repeated here.

[0091] In one embodiment, each preset driving state has an importance level, such as Figure 2 As shown, the above method also includes:

[0092] Step 202, when the importance level of the preset driving state corresponding to the second vehicle data table is higher than the importance level of the target driving state, write the target vehicle data into the first vehicle data table and jump to step 102; or,

[0093] Step 204, when the importance level of the preset driving state corresponding to the second vehicle data table is lower than the importance level of the target driving state, determining whether the second vehicle data table satisfies the independent statistical condition;

[0094] In step 104, before writing the target vehicle data into the first vehicle data table, the method further includes:

[0095] Step 206: If the first vehicle data table is not empty, statistical processing is performed on the vehicle data in the first vehicle data table to obtain the data statistical results of the preset driving state corresponding to the first vehicle statistical table, and the first vehicle data table is cleared.

[0096] In the embodiment of the present application, each preset driving state has an importance level, and the vehicle data of the preset driving state with lower importance can be merged into the preset driving state with higher importance for statistics, but the vehicle data of the preset driving state with higher importance cannot be merged into the preset driving state with lower importance. The importance level can be set by those skilled in the art according to actual needs. For example, when it is necessary to focus on the performance of the vehicle on the highway, the importance level of the highway driving state can be set higher, and the importance level of other driving states can be set lower.

[0097] If, after acquiring each second vehicle data table in step 102 of the aforementioned embodiment, the importance level of the preset driving state corresponding to the second vehicle data table that is not empty is higher than the importance level of the target driving state, then regardless of whether the second vehicle data table meets the independent statistical condition, the vehicle data in the second vehicle data table cannot be merged into the first vehicle data table. At this time, only the step of writing the target vehicle data into the first vehicle data table can be executed, and the process jumps to the step of acquiring the target vehicle data, and waits for the next acquisition of the target vehicle data to continue to determine whether the second vehicle data table meets the independent statistical condition.

[0098] If the importance level of the preset driving state corresponding to the second vehicle data table is lower than the importance level of the target driving state, it is possible to continue to determine whether the second vehicle data table meets the independent statistical condition and execute steps 104 and 106 in the above embodiment.

[0099] It should be noted that in the embodiment of the present application, when the target vehicle data is written into the first vehicle data table, the data in the second vehicle data table is neither moved nor counted. Therefore, when the vehicle data needs to be written into the second vehicle data table next time, the data to be written next time and the current data in the second vehicle data table are not continuous data. If these data are counted together, the accuracy of the statistics may be affected. Therefore, before writing a certain vehicle data into a certain vehicle data table each time, it can be determined whether the vehicle data table is empty. If it is not empty, the vehicle data table is counted once and the vehicle data table is cleared, and then the vehicle data is written into the vehicle data table to ensure that the data used for each statistics is continuous data.

[0100] In one embodiment, Figure 3 As shown, in step 102, obtaining the target vehicle data uploaded by the target vehicle includes:

[0101] Step 302, receiving an uplink message sent by a target vehicle within a statistical period, the uplink message including a vehicle data reporting message;

[0102] Step 304, when the statistical period ends, obtaining the vehicle data carried in each vehicle data reporting message received during the statistical period;

[0103] Step 306, traverse each vehicle data from early to late according to the collection time of each vehicle data, and use the currently traversed vehicle data as the target vehicle data;

[0104] The above method further includes:

[0105] Step 308, when all vehicle data within the statistical period have been traversed, statistical processing is performed on the vehicle data in the vehicle data table corresponding to each preset driving state to obtain the data statistical results of each preset driving state, and the vehicle data table corresponding to each preset driving state is cleared.

[0106] In the embodiment of the present application, the vehicle data reported by each target vehicle is processed in the form of batch processing. The target vehicle will send an uplink message when it needs to report vehicle data or report other transactions to the server. The uplink message includes a vehicle data reporting message carrying vehicle data. The server receives and parses the vehicle data reporting message in a statistical cycle (the length can be set by a person skilled in the art according to actual needs, such as 5 minutes, 10 minutes, etc.), and temporarily stores the parsed vehicle data in a database. After a statistical cycle ends, read the data of each vehicle acquired in the statistical cycle, and traverse the data of each vehicle in the order from early to late according to the collection time, and use the currently traversed vehicle data as the target vehicle data.

[0107] After all vehicle data in this statistical period are traversed, the vehicle data in the vehicle data table corresponding to all preset driving states can also be statistically processed so that the server can return the data statistical results to the target vehicle at least once every statistical period.

[0108] In one embodiment, the uplink message also includes a vehicle logout message, such as Figure 4 As shown, in step 102, before determining the target driving state corresponding to the target vehicle data from each preset driving state, the method further includes:

[0109] Step 402, determining the preceding uplink message of the vehicle data reporting message to which the target vehicle data belongs;

[0110] Step 404, when the preceding uplink message is a vehicle logout message, statistical processing is performed on the vehicle data in the vehicle data table corresponding to each preset driving state to obtain the data statistical results of each preset driving state, and the vehicle data table corresponding to each preset driving state is cleared.

[0111] In the embodiment of the present application, when the target vehicle and the server communicate using the gb / t32970 protocol, the target vehicle will send a vehicle logout message to the server when the engine is turned off. Since the target vehicle may still be in the startup state after the engine is turned off, and will still send uplink messages to the server normally, it is necessary to consider whether the target vehicle is turned off during the statistical period when performing data statistics, and to perform statistics on the data before and after the engine is turned off.

[0112] The server can cache each uplink message received in each statistical period. When traversing each vehicle data, each time a vehicle data is traversed, the vehicle data reporting message corresponding to the vehicle data can be obtained, and it can be confirmed whether the preceding reporting message of the vehicle data reporting message (that is, the previous reporting message of the vehicle data reporting message) is a vehicle logout message. If so, the server performs a statistical processing on the vehicle data in the vehicle data table corresponding to each preset driving state, clears the vehicle data in the vehicle data table corresponding to each preset driving state, and then executes the step of determining the target driving state corresponding to the target vehicle data, and writes the target vehicle data into the first vehicle data table to avoid confusion of data before and after shutdown. If not, the server normally executes the step of determining the target driving state corresponding to the target vehicle data.

[0113] In one embodiment, Figure 5 As shown, in step 102, before determining the target driving state corresponding to the target vehicle data from each preset driving state, the method further includes:

[0114] Step 502, when the preceding uplink message is not a vehicle logout message, determining the time difference between the collection time of the target vehicle data and the collection time of the preceding vehicle data of the target vehicle data;

[0115] Step 504, when the time difference is greater than the preset time difference threshold, statistical processing is performed on the vehicle data in the vehicle data table corresponding to each preset driving state to obtain the data statistical results of each preset driving state, and the vehicle data table corresponding to each preset driving state is cleared.

[0116] In the embodiment of the present application, due to poor communication quality, TBOX failure, or failure of a certain vehicle data to be successfully collected or successfully parsed, there may be discontinuities between the various vehicle data obtained by the server within a statistical cycle. If discontinuous data are put together for statistics, the accuracy of the statistics may be affected. Therefore, after the server obtains the target vehicle data each time, it can determine the time difference between the acquisition time of the target vehicle data and its predecessor vehicle data (that is, the previous vehicle data collected before the target vehicle data). If the time difference is greater than the preset time difference threshold, it can be considered that the target vehicle data and its predecessor vehicle data are discontinuous, and the server performs a statistical processing on the vehicle data in the vehicle data table corresponding to each preset driving state, clears the vehicle data in the vehicle data table corresponding to each preset driving state, and then executes the step of determining the target driving state corresponding to the target vehicle data, and writing the target vehicle data into the first vehicle data table. If the time difference is less than or equal to the preset time difference threshold, the step of determining the target driving state corresponding to the target vehicle data and writing the target vehicle data into the first vehicle data table is normally executed.

[0117] In one embodiment, a vehicle data processing method is provided. The present application embodiment is described by taking the preset driving state including the moving state and the stationary state as an example, and the above method includes:

[0118] S1, after receiving vehicle data through the gb / t32960 protocol within a statistical period, writes the data into the database.

[0119] S2, sort the vehicle data in ascending order according to the collection time, and traverse the sorted vehicle data.

[0120] S3, for the currently traversed target vehicle data, determine the preceding uplink message of the vehicle data reporting message to which the target vehicle data belongs, and if the preceding uplink message is a vehicle logout message, execute S8, and then execute S4; if the preceding uplink message is not a vehicle logout message, determine the time difference between the collection time of the target vehicle data and the collection time of the preceding vehicle data of the target vehicle data, and if the time difference is greater than a preset time difference threshold, execute S8, and then execute S4. If the preceding uplink message is not a vehicle logout message, and the time difference is less than or equal to the preset time difference threshold, execute S4.

[0121] S4, obtaining speed data in the target vehicle data, and when the speed data is equal to 0, determining that the target vehicle data corresponds to a stationary state, and when the speed data is greater than 0, determining that the target vehicle data corresponds to a moving state.

[0122] S5, if the target vehicle data corresponds to a stationary state, the target vehicle data is written into a stationary vehicle data table corresponding to the stationary state. If the target vehicle data corresponds to a moving state, when the stationary vehicle data table is not empty, the length of the data collection time range corresponding to the stationary vehicle data table is determined according to the collection time of the first and last vehicle data in the stationary vehicle data table, and S6 is executed if the length is greater than a preset time length threshold, and S7 is executed if the length is less than or equal to the preset time length threshold.

[0123] It should be noted that, if the scheme of setting importance levels for different preset driving states in the aforementioned embodiment is adopted, then this is equivalent to setting the importance level of the moving state to be higher than the importance level of the stationary state.

[0124] S6, performing statistics on the stationary vehicle data table and the moving vehicle data table respectively, clearing the stationary vehicle data table and the moving vehicle data table, and writing the target vehicle data into the moving vehicle data table corresponding to the moving state.

[0125] S7, writing all vehicle data in the stationary vehicle data table into the moving vehicle data table, and writing the target vehicle data into the moving vehicle data table corresponding to the moving state.

[0126] The above steps S3-S7 are repeatedly executed until all vehicle data are traversed, and then S8 is executed.

[0127] S8, statistically processing the vehicle data in the vehicle data table corresponding to each preset driving state to obtain the data statistical results of each preset driving state, and clearing the vehicle data table corresponding to each preset driving state.

[0128] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0129] Based on the same inventive concept, the embodiment of the present application also provides a vehicle data processing device for implementing the vehicle data processing method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more vehicle data processing device embodiments provided below can refer to the limitations of the vehicle data processing method above, and will not be repeated here.

[0130] In one embodiment, Figure 7 As shown, a vehicle data processing device 700 is provided, including: an acquisition module 702, a processing module 704, wherein:

[0131] The acquisition module 702 is used to acquire the target vehicle data uploaded by the target vehicle, determine the target driving state corresponding to the target vehicle data from each preset driving state, acquire a first vehicle data table corresponding to the target driving state, and acquire a second vehicle data table that is not empty from the vehicle data tables corresponding to the preset driving states other than the target driving state;

[0132] The processing module 704 is used to perform statistical processing on each vehicle data in the second vehicle data table when the second vehicle data table meets the independent statistical conditions, obtain the data statistical results of the preset driving state corresponding to the second vehicle data table, clear the second vehicle data table, and write the target vehicle data into the first vehicle data table; or when the second vehicle data table does not meet the independent statistical conditions, move all vehicle data in the second vehicle data table to the first vehicle data table, and write the target vehicle data into the first vehicle data table.

[0133] The vehicle data processing device provided in the embodiment of the present application obtains the target vehicle data, and after determining the target driving state to which the target vehicle data belongs from each preset driving state, determines whether the second vehicle data table corresponding to other preset driving states is empty. If there is a non-empty second vehicle data table, it indicates that the target vehicle may have switched driving states at the time of collecting the target vehicle data, and it is necessary to perform data statistics on the previous driving state. At this time, by verifying whether the second vehicle data table meets the independent statistical condition, it can be determined whether the driving state classification of the vehicle data in the second vehicle data table is appropriate. In the case where the second vehicle data table meets the independent statistical condition, the second vehicle data table is counted and the target vehicle data is written into the first vehicle data table. In the case where the second vehicle data table does not meet the independent statistical condition, the vehicle data in the second vehicle data table is moved to the first vehicle data table, that is, the vehicle data is reclassified into the target driving state. Therefore, in the process of vehicle driving, the vehicle data generated by the vehicle under different driving states can be counted in real time, thereby improving the real-time nature of the generated data statistical results. At the same time, the driving state classification of the vehicle data can also be corrected in real time, thereby improving the accuracy of the data statistical results corresponding to each driving state.

[0134] In one embodiment, the device further comprises:

[0135] A first determination module is used to determine the data collection time range corresponding to the second vehicle data table according to the collection time of each vehicle data in the second vehicle data table, and determine that the second vehicle data table meets the independent statistical condition when the length of the data collection time range is greater than a preset time length threshold; and / or obtain the vehicle data range corresponding to the target driving state, respectively determine the difference between each vehicle data in the second vehicle data table and each boundary value of the vehicle data range, and determine that the second vehicle data table meets the independent statistical condition when all the differences corresponding to more than a preset number of vehicle data are greater than a preset difference threshold.

[0136] In one embodiment, each of the preset driving states has an importance level, and the device further includes:

[0137] A second determination module is used to write the target vehicle data into the first vehicle data table and jump to the step of obtaining the target vehicle data uploaded by the target vehicle when the importance level of the preset driving state corresponding to the second vehicle data table is higher than the importance level of the target driving state; or to determine whether the second vehicle data table meets the independent statistical condition when the importance level of the preset driving state corresponding to the second vehicle data table is lower than the importance level of the target driving state;

[0138] The first statistical module is used to perform statistical processing on the vehicle data in the first vehicle data table if the first vehicle data table is not empty, obtain the data statistical results of the preset driving state corresponding to the first vehicle statistical table, and clear the first vehicle data table.

[0139] In one embodiment, the acquisition module 702 is further used to:

[0140] In a statistical period, receiving an uplink message sent by the target vehicle, wherein the uplink message includes a vehicle data reporting message;

[0141] When the statistical period ends, obtaining the vehicle data carried by each of the vehicle data reporting messages received during the statistical period;

[0142] Traversing each of the vehicle data from early to late according to the collection time of each of the vehicle data, and taking the currently traversed vehicle data as the target vehicle data;

[0143] The device also includes:

[0144] The second statistical module is used to perform statistical processing on the vehicle data in the vehicle data table corresponding to each preset driving state after all the vehicle data within the statistical period have been traversed, obtain the data statistical results of each preset driving state, and clear the vehicle data table corresponding to each preset driving state.

[0145] In one embodiment, the uplink message further includes a vehicle logout message, and the device further includes:

[0146] A third determination module, used to determine a preceding uplink message of the vehicle data reporting message to which the target vehicle data belongs;

[0147] The third statistical module is used to perform statistical processing on the vehicle data in the vehicle data table corresponding to each of the preset driving states when the previous uplink message is the vehicle logout message, obtain the data statistical results of each of the preset driving states, and clear the vehicle data table corresponding to each of the preset driving states.

[0148] In one embodiment, the device further comprises:

[0149] A fourth determination module, for determining, when the preceding uplink message is not the vehicle logout message, a time difference between a collection time of the target vehicle data and a collection time of a preceding vehicle data of the target vehicle data;

[0150] The fourth statistical module is used to perform statistical processing on the vehicle data in the vehicle data table corresponding to each of the preset driving states when the time difference is greater than the preset time difference threshold, obtain the data statistical results of each of the preset driving states, and clear the vehicle data table corresponding to each of the preset driving states.

[0151] Each module in the above device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module above.

[0152] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle data processing method is implemented.

[0153] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0154] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0155] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0156] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0157] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0158] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0159] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0160] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle data processing method, characterized in that: The method comprises: Obtain target vehicle data uploaded by the target vehicle, determine a target driving state corresponding to the target vehicle data from each preset driving state, obtain a first vehicle data table corresponding to the target driving state, and obtain a second vehicle data table that is not empty from vehicle data tables corresponding to preset driving states other than the target driving state; If the second vehicle data table meets the independent statistical condition, statistical processing is performed on each vehicle data in the second vehicle data table to obtain the data statistical result of the preset driving state corresponding to the second vehicle data table, the second vehicle data table is cleared, and the target vehicle data is written into the first vehicle data table; or When the second vehicle data table does not satisfy the independent statistical condition, all vehicle data in the second vehicle data table are moved to the first vehicle data table, and the target vehicle data is written into the first vehicle data table.

2. The method according to claim 1, characterized in that The method further comprises: Determine the data collection time range corresponding to the second vehicle data table according to the collection time of each vehicle data in the second vehicle data table, and determine that the second vehicle data table meets the independent statistical condition when the length of the data collection time range is greater than a preset time threshold; and / or, Obtain a vehicle data range corresponding to the target driving state, respectively determine the difference between each vehicle data in the second vehicle data table and each boundary value of the vehicle data range, and determine that the second vehicle data table satisfies the independent statistical condition when all the difference values ​​corresponding to more than a preset number of vehicle data are greater than a preset difference threshold.

3. The method according to claim 1, characterized in that Each of the preset driving states has an importance level, and the method further includes: When the importance level of the preset driving state corresponding to the second vehicle data table is higher than the importance level of the target driving state, the target vehicle data is written into the first vehicle data table, and the process jumps to the step of obtaining the target vehicle data uploaded by the target vehicle; or When the importance level of the preset driving state corresponding to the second vehicle data table is lower than the importance level of the target driving state, determining whether the second vehicle data table satisfies an independent statistical condition; Before writing the target vehicle data into the first vehicle data table, the method further includes: If the first vehicle data table is not empty, statistical processing is performed on the vehicle data in the first vehicle data table to obtain data statistical results of the preset driving state corresponding to the first vehicle statistical table, and the first vehicle data table is cleared.

4. The method according to claim 1, characterized in that The step of obtaining the target vehicle data uploaded by the target vehicle includes: In a statistical period, receiving an uplink message sent by the target vehicle, wherein the uplink message includes a vehicle data reporting message; When the statistical period ends, obtaining the vehicle data carried by each of the vehicle data reporting messages received during the statistical period; Traversing each of the vehicle data from early to late according to the collection time of each of the vehicle data, and taking the currently traversed vehicle data as the target vehicle data; The method further comprises: When all vehicle data within the statistical period have been traversed, the vehicle data in the vehicle data table corresponding to each of the preset driving states are statistically processed to obtain the data statistical results of each of the preset driving states, and the vehicle data table corresponding to each of the preset driving states is cleared.

5. The method according to claim 4, characterized in that The uplink message also includes a vehicle logout message. Before determining the target driving state corresponding to the target vehicle data from each preset driving state, the method further includes: Determine a preceding uplink message of a vehicle data reporting message to which the target vehicle data belongs; In the case where the preceding uplink message is the vehicle logout message, the vehicle data in the vehicle data table corresponding to each of the preset driving states is statistically processed to obtain the data statistical results of each of the preset driving states, and the vehicle data table corresponding to each of the preset driving states is cleared.

6. The method according to claim 5, characterized in that The method further comprises: In a case where the preceding uplink message is not the vehicle logout message, determining a time difference between a collection time of the target vehicle data and a collection time of preceding vehicle data of the target vehicle data; When the time difference is greater than a preset time difference threshold, the vehicle data in the vehicle data table corresponding to each preset driving state is statistically processed to obtain the data statistical results of each preset driving state, and the vehicle data table corresponding to each preset driving state is cleared.

7. A vehicle data processing device, characterized in that: The device comprises: an acquisition module, configured to acquire target vehicle data uploaded by a target vehicle, determine a target driving state corresponding to the target vehicle data from each preset driving state, acquire a first vehicle data table corresponding to the target driving state, and acquire a second vehicle data table that is not empty from vehicle data tables corresponding to preset driving states other than the target driving state; A processing module is used to perform statistical processing on each vehicle data in the second vehicle data table when the second vehicle data table meets the independent statistical conditions, obtain the data statistical results of the preset driving state corresponding to the second vehicle data table, clear the second vehicle data table, and write the target vehicle data into the first vehicle data table; or when the second vehicle data table does not meet the independent statistical conditions, move all vehicle data in the second vehicle data table to the first vehicle data table, and write the target vehicle data into the first vehicle data table.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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