Vehicle positioning data processing method and device, electronic equipment and readable medium

Abstract

Embodiments of the present application provide a vehicle positioning data processing method and device, electronic equipment and readable medium. The method comprises: obtaining positioning data uploaded by a vehicle in a streaming data form; according to at least one preset storage scenario, using an analysis method corresponding to the storage scenario to analyze the position accuracy of the positioning data; wherein the storage scenario comprises at least one of a real-time storage scenario, a historical trajectory storage scenario, and an all-data storage scenario; and according to the position accuracy analysis result of the positioning data, storing or deleting the positioning data. Thus, for various data storage scenarios in the server, different analysis methods can be used to efficiently determine the positioning data with accurate position in the positioning data uploaded by the vehicle, and then the positioning data with high position accuracy is retained. While effectively saving storage space, the accuracy of subsequent data analysis can be improved, and no obvious adverse effects on the existing data analysis efficiency are produced.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a method for processing vehicle positioning data, a device for processing vehicle positioning data, an electronic device, and a computer-readable medium. Background Technology

[0002] In existing technologies, real-time monitoring of vehicle operating status is typically required for vehicle management. Therefore, a vehicle locator can be installed to acquire the vehicle's status in real time, including vehicle location data and its source. Generally, after obtaining the vehicle location data, the server needs to store it and analyze the vehicle's status based on this data. However, vehicle location data may contain anomalies. Analyzing the vehicle based on anomaly-laden location data can easily lead to incorrect judgments about its operating status. Summary of the Invention

[0003] The present invention provides a method, apparatus, electronic device, and computer-readable storage medium for processing vehicle positioning data to solve the problem of possible anomalies in vehicle positioning data.

[0004] This invention discloses a method for processing vehicle location data, which is applied to a server. The method includes:

[0005] Acquire location data uploaded by the vehicle in the form of streaming data;

[0006] The location accuracy of the positioning data is analyzed using an analysis method corresponding to the preset storage scenario, based on at least one preset storage scenario; wherein, the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario;

[0007] Based on the location accuracy analysis results of the location data, store or delete the location data.

[0008] Optionally, when the storage scenario is a real-time storage scenario, the step of analyzing the location accuracy of the positioning data using the analysis method corresponding to the storage scenario includes:

[0009] Determine if standard data exists.

[0010] In the presence of the standard data, a first average speed is calculated based on the time and location information of the positioning data and the time and location information of the standard data, and / or a first distance is calculated based on the location information of the positioning data and the location information of the standard data;

[0011] If the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, the positioning data is determined to be accurate, and the positioning data is used as new standard data.

[0012] Optionally, after the step of determining whether standard data exists, the method further includes:

[0013] If the standard data exists, calculate a first time difference between the time point of the positioning data and the standard data;

[0014] If the first time difference is within a preset first time range, the steps of calculating the first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, and / or calculating the first distance based on the location information of the positioning data and the location information of the standard data are executed.

[0015] If the first time difference is not within the preset first time range, the standard data is deleted.

[0016] Optionally, the method further includes:

[0017] If the standard data does not exist, obtain a preset number of location data.

[0018] Based on the distance difference between adjacent location data in time sequence, a first valid data is selected from the preset number of location data, and the first valid data is used as the standard data.

[0019] Optionally, when the storage scenario is a historical trajectory storage scenario, the step of analyzing the location accuracy of the positioning data using the analysis method corresponding to the storage scenario includes:

[0020] Determine if any hazardous standard data exists;

[0021] In the presence of hazardous standard data, a second average speed is calculated based on the time and location information of the positioning data and the time and location information of the hazardous standard data, and / or a second distance is calculated based on the location information of the positioning data and the location information of the hazardous standard data;

[0022] Based on the second average speed and / or the second distance, at least one location data set is determined; the location data set contains at least one location data set that is sequentially continuous in time.

[0023] Based on the location data set, at least one target location data with accurate location is selected.

[0024] Optionally, the step of calculating a second average speed based on the time and location information of the positioning data and the time and location information of the hazard standard data when hazard standard data exists, and / or calculating a second distance based on the location information of the positioning data and the location information of the hazard standard data, includes:

[0025] In the presence of dangerous standard data, the positioning data in a preset time sequence will be used as the positioning data to be confirmed;

[0026] A second average speed is calculated based on the time and location information of the location data to be confirmed and the time and location information of the hazard standard data, and / or a second distance is calculated based on the location information of the location data to be confirmed and the location information of the hazard standard data;

[0027] The step of determining at least one location data set based on the second average speed and / or the second distance includes:

[0028] Based on the second average speed and / or the second distance, determine whether to add the location data to be confirmed to the location data set;

[0029] If the second average speed is within a preset second speed range and / or the second distance is within a preset second distance range, the positioning data to be confirmed will be added to the positioning data set;

[0030] The next location data that is adjacent to the location data to be confirmed in time sequence is taken as the new location data to be confirmed. It is then determined whether to add the location data to be confirmed to the location data set, until the second average speed is not within the preset second speed range and / or the second distance is not within the preset second distance range, and the location data set is then combined into the target location data set.

[0031] Optionally, the step of determining at least one location data set based on the second average speed and / or the second distance further includes:

[0032] The location data to be confirmed that are not within the preset second speed range and / or the second distance is not within the preset second distance range are taken as new hazard standard data. The target location data set is determined again based on the new hazard standard data until no new hazard standard data is found.

[0033] Optionally, the step of filtering at least one target location data with accurate location based on the location data set includes:

[0034] Based on the aforementioned location data set, location data that appears more than a preset threshold number of times will be used as calibration location data;

[0035] Starting from the calibration positioning data, the positioning data on the left and right sides of the calibration positioning data in the positioning data set are traversed in time order, and the distance difference between adjacent positioning data in time order is compared to see if it is within the third distance range.

[0036] If the distance difference between adjacent time-series positioning data is within the third distance range, the positioning data that is far away from the calibration positioning data among the adjacent time-series positioning data will be deleted, and the positioning data that is close to the calibration positioning data among the adjacent time-series positioning data will be used as the target positioning data with accurate location.

[0037] If the distance difference between adjacent location data in time sequence is not within the third distance range, the location data is retained as the target location data with accurate location.

[0038] Optionally, the method further includes:

[0039] Determine if comparative data exists;

[0040] In the presence of comparative data, based on the time sequence, the distance difference between the target positioning data and the comparative data is compared sequentially to see if it falls within the fourth distance range;

[0041] If the distance difference between the target positioning data and the comparison data is not within the fourth distance range, the target positioning data is retained;

[0042] If at least three retained target positioning data are obtained, the vector angle between target positioning data that are adjacent in time sequence is calculated to obtain at least two vector angles.

[0043] Compare whether the difference between the angles of adjacent vectors in the time sequence is within a preset range of angle differences;

[0044] If the difference between the included angles of adjacent vectors in time sequence is not within the preset range of included angle difference, the target positioning data corresponding to the included vector angle is retained;

[0045] The target positioning data corresponding to the latest vector angle in the time sequence is used as the new comparison data. Based on the new comparison data, the target positioning data to be retained is determined until there is no new comparison data. The retained target positioning data is then used as trajectory data.

[0046] Optionally, the method further includes:

[0047] A pre-defined mathematical analysis model is used to filter out valid target data from the trajectory data;

[0048] Based on the target's valid data, the vehicle's historical trajectory is generated.

[0049] This invention also provides a vehicle location data processing device applied to a server, the method comprising:

[0050] The location acquisition module is used to acquire the location data uploaded by the vehicle in the form of streaming data;

[0051] An accuracy analysis module is used to analyze the location accuracy of the positioning data according to at least one preset storage scenario and using the analysis method corresponding to the storage scenario; wherein, the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario;

[0052] The data processing module is used to store or delete the positioning data based on the location accuracy analysis results of the positioning data.

[0053] Optionally, the accuracy analysis module includes:

[0054] The standard data determination submodule is used to determine whether standard data exists.

[0055] The first calculation submodule is used to calculate a first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, when the standard data exists, and / or to calculate a first distance based on the location information of the positioning data and the location information of the standard data;

[0056] The first accuracy determination submodule is used to determine that the positioning data is accurate if the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, and to use the positioning data as new standard data.

[0057] Optionally, the device further includes:

[0058] The first time difference calculation module is used to calculate the first time difference between the time point of the positioning data and the standard data when the standard data exists.

[0059] The first calculation module is used to perform the steps of calculating the first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, and / or calculating the first distance based on the location information of the positioning data and the location information of the standard data if the first time difference is within a preset first time range;

[0060] The standard data deletion module is used to delete the standard data if the first time difference is not within a preset first time range.

[0061] Optionally, the device further includes:

[0062] The positioning data acquisition module is used to acquire a preset number of positioning data if the standard data does not exist.

[0063] The effective data filtering module is used to select the first effective data from the preset number of positioning data based on the distance difference between adjacent positioning data in time sequence, and to use the first effective data as the standard data.

[0064] Optionally, the accuracy analysis module includes

[0065] The hazard standard data acquisition submodule is used to determine whether hazard standard data exists.

[0066] The second calculation submodule is used to calculate a second average speed based on the time point and location information of the positioning data and the time point and location information of the dangerous standard data when dangerous standard data is available, and / or to calculate a second distance based on the location information of the positioning data and the location information of the dangerous standard data.

[0067] A set determination submodule is used to determine at least one location data set based on the second average speed and / or the second distance; the location data set contains at least one location data set that is sequentially continuous in time.

[0068] The second accuracy determination submodule is used to filter at least one target positioning data with accurate location based on the positioning data set.

[0069] Optionally, the second calculation submodule includes:

[0070] The pending data confirmation unit is used to use positioning data in a preset time sequence as positioning data to be confirmed when dangerous standard data exists.

[0071] The first calculation unit is used to calculate a second average speed based on the time point and location information of the location data to be confirmed and the time point and location information of the hazard standard data, and / or to calculate a second distance based on the location information of the location data to be confirmed and the location information of the hazard standard data;

[0072] Optionally, the set determination submodule includes:

[0073] A data addition confirmation unit is used to determine, based on the second average speed and / or the second distance, whether to add the positioning data to be confirmed to the positioning data set;

[0074] A data adding unit is used to add the positioning data to be confirmed to the positioning data set if the second average speed is within a preset second speed range and / or the second distance is within a preset second distance range;

[0075] The set determination unit is used to take the next location data that is adjacent to the location data to be confirmed in time sequence as the new location data to be confirmed, and to determine again whether to add the location data to be confirmed to the location data set, until the second average speed is not within the preset second speed range and / or the second distance is not within the preset second distance range, and to combine the location data set into the target location data set.

[0076] Optionally, the set determination submodule further includes:

[0077] The target set determination unit is used to take the unconfirmed positioning data where the second average speed is not within a preset second speed range and / or the second distance is not within a preset second distance range as new hazard standard data, and to determine the target positioning data set again based on the new hazard standard data until no new hazard standard data exists.

[0078] Optionally, the second accuracy determination submodule includes:

[0079] The calibration positioning data determination unit is used to select positioning data that appears more than a preset threshold as calibration positioning data based on the positioning data set.

[0080] The calibration distance determination unit is used to take the calibration positioning data as the starting point, traverse the positioning data on the left and right sides of the calibration positioning data in the positioning data set according to the time sequence, and compare whether the distance difference between adjacent positioning data in the time sequence is within the third distance range.

[0081] The first accuracy confirmation unit is used to delete the positioning data that is far away from the calibration positioning data in the time-sequential adjacent positioning data when the distance difference between the time-sequential adjacent positioning data is within a third distance range, and to take the positioning data that is close to the calibration positioning data in the time-sequential adjacent positioning data as the target positioning data with accurate position.

[0082] The second accuracy confirmation unit is used to retain the positioning data as the target positioning data with accurate location if the distance difference between adjacent positioning data in time sequence is not within the third distance range.

[0083] Optionally, the device further includes:

[0084] The comparison data determination module is used to determine whether comparison data exists.

[0085] The comparison unit is used to compare, in the presence of comparison data, whether the distance difference between the target positioning data and the comparison data is within a fourth distance range based on time order.

[0086] The first positioning data retention module is used to retain the target positioning data when the distance difference between the target positioning data and the comparison data is not within the fourth distance range;

[0087] The vector angle calculation module is used to calculate the vector angle between target positioning data that are adjacent in time sequence, given that at least three retained target positioning data have been obtained, to obtain at least two vector angles.

[0088] The angle difference calculation module is used to compare whether the difference between the angles of adjacent vectors in time sequence is within a preset angle difference range;

[0089] The second positioning data retention module is used to retain the target positioning data corresponding to the vector angle when the difference between the angles of adjacent vectors in time sequence is not within a preset range of angle difference.

[0090] The target positioning data corresponding to the latest vector angle in the time sequence is used as the new comparison data. Based on the new comparison data, the target positioning data to be retained is determined until there is no new comparison data. The retained target positioning data is then used as trajectory data.

[0091] Optionally, the device further includes:

[0092] The model analysis module is used to filter valid target data from trajectory data using a preset mathematical analysis model.

[0093] The historical trajectory generation module is used to generate the historical trajectory of the vehicle based on the target valid data.

[0094] This invention also discloses an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0095] The memory is used to store computer programs;

[0096] When the processor executes a program stored in the memory, it implements the method described in the embodiments of the present invention.

[0097] This invention also discloses one or more computer-readable media storing instructions that, when executed by one or more processors, cause the processors to perform the methods described in this invention.

[0098] The embodiments of the present invention have the following advantages:

[0099] The vehicle positioning data processing method provided by this invention, applied to a server, includes: acquiring positioning data uploaded by a vehicle in streaming form; analyzing the location accuracy of the positioning data using an analysis method corresponding to at least one preset storage scenario; wherein the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario; and storing or deleting the positioning data based on the location accuracy analysis result. Therefore, for various data storage scenarios on the server, different analysis methods can be used to efficiently determine the accurate positioning data from the vehicle-uploaded positioning data, and then retain the positioning data with high accuracy. This effectively saves storage space while improving the accuracy of subsequent data analysis without significantly negatively impacting the efficiency of existing data analysis. Attached Figure Description

[0100] Figure 1 This is a flowchart of the steps of a vehicle positioning data processing method provided in an embodiment of the present invention;

[0101] Figure 2 This is a flowchart of another method for processing vehicle positioning data provided in an embodiment of the present invention;

[0102] Figure 3 This is a flowchart of another method for processing vehicle positioning data provided in an embodiment of the present invention;

[0103] Figure 4 This is a structural block diagram of a vehicle positioning data processing device provided in an embodiment of the present invention;

[0104] Figure 5 This is a block diagram of an electronic device provided in an embodiment of the present invention;

[0105] Figure 6 This is a schematic diagram of a computer-readable medium provided in an embodiment of the present invention. Detailed Implementation

[0106] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0107] In this embodiment of the invention, a server can be used to acquire and analyze location data uploaded by vehicles. The server can contain various storage scenarios, and the location data stored in different scenarios can be used for different forms of analysis. Ensuring the relative accuracy of data stored in different scenarios has a significant impact on subsequent analyses. Therefore, this embodiment of the invention employs different analysis methods to analyze the location accuracy of vehicle-uploaded location data for different storage scenarios, ensuring that the location data in different storage scenarios is relatively accurate.

[0108] Reference Figure 1 The diagram illustrates a flowchart of a vehicle positioning data processing method provided in an embodiment of the present invention. This method is applied to a server and specifically includes the following steps:

[0109] Step 101: Obtain the location data uploaded by the vehicle in the form of streaming data;

[0110] In this embodiment of the invention, during vehicle operation, the vehicle's location can be determined in real time using positioning systems such as GPS (Global Positioning System) and BDS (BeiDou Navigation Satellite System). This allows the vehicle to continuously generate new positioning data, which is then continuously uploaded to the server in the form of streaming data. The server can then obtain the positioning data uploaded by the vehicle.

[0111] In the specific implementation, after obtaining the location data uploaded by the vehicle, the location data can be formatted for subsequent storage. Specifically, the uploaded data can be a JSON string, such as "{time:"time", location:geohash}", which can be converted into a Java object on the server using Java, containing two attributes: time and location, such as {time:"time", location:geohash}.

[0112] Step 102: Analyze the location accuracy of the positioning data using the analysis method corresponding to the preset storage scenario, based on at least one of the storage scenarios; wherein, the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario;

[0113] The server can analyze the vehicle-uploaded location data using various methods. Therefore, at least one storage scenario can be preset for different data analysis methods. Storage scenarios can include at least one of real-time storage, historical trajectory storage, and all data storage scenarios. After obtaining the vehicle-uploaded location data, the server can analyze the location data using the analysis methods corresponding to different storage scenarios to determine the location accuracy.

[0114] Specifically, in real-time storage scenarios, the server needs to store newly uploaded vehicle location data in real time after receiving it. Therefore, in real-time storage scenarios, the server needs to determine the reliability of the newly uploaded location data immediately after receiving it to avoid adverse effects on real-time data storage and analysis.

[0115] In historical trajectory storage scenarios, the server needs to analyze the vehicle's historical driving trajectory based on historically acquired location data. Therefore, the server can centrally acquire a certain amount of location data and then batch process it to update the vehicle's historical trajectory. For historical trajectory storage scenarios, the server does not need to analyze the accuracy of the data in real time. However, due to the large volume of location data uploaded by vehicles, analyzing the vehicle's historical trajectory based on all uploaded location data can easily lead to excessive server computation and potentially excessive redundant data storage. Therefore, for historical trajectory storage scenarios, while analyzing whether the acquired location data needs to be retained, it can further determine the valid data to be retained based on the degree of change between location data, thereby simultaneously achieving data accuracy analysis and data sparsity processing.

[0116] For all storage scenarios, it can be mainly used to back up and store data uploaded by vehicles, so that it can store all the location data uploaded by vehicles without processing the location data.

[0117] In a practical implementation, a traffic splitter can be set up in the server to distribute the vehicle's uploaded location data to different storage scenarios. As a specific example of this invention, after obtaining the vehicle's uploaded location data, the traffic splitter in the server can copy the location data and distribute it to different storage scenarios for data processing. The server can then analyze the location data using an analysis method corresponding to the storage scenario, based on the data obtained from each scenario, to determine the location accuracy of the location data.

[0118] Step 103: Based on the location accuracy analysis results of the location data, store or delete the location data.

[0119] After the server analyzes and determines the location accuracy of the positioning data, it can select and retain positioning data with high accuracy and delete positioning data with low accuracy, based on actual needs. This allows for the retention of only accurate positioning data for different storage scenarios. This effectively saves storage space while also improving the accuracy of subsequent data analysis.

[0120] The vehicle positioning data processing method provided by this invention, applied to a server, includes: acquiring positioning data uploaded by a vehicle in streaming form; analyzing the location accuracy of the positioning data using an analysis method corresponding to at least one preset storage scenario; wherein the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario; and storing or deleting the positioning data based on the location accuracy analysis result. Therefore, for various data storage scenarios on the server, different analysis methods can be used to efficiently determine the accurate positioning data from the vehicle-uploaded positioning data, and then retain the positioning data with high accuracy. This effectively saves storage space while improving the accuracy of subsequent data analysis without significantly negatively impacting the efficiency of existing data analysis.

[0121] Reference Figure 2 The diagram illustrates a flowchart of a vehicle positioning data processing method provided in an embodiment of the present invention. This method is applied to a server and specifically includes the following steps:

[0122] Step 201: Obtain the location data uploaded by the vehicle in the form of streaming data;

[0123] Step 202: If the storage scenario is a real-time storage scenario, determine whether standard data exists.

[0124] In this embodiment of the invention, when the storage scenario is real-time storage, a standard data can be preset in the server, and the location accuracy of the real-time acquired positioning data can be determined based on this standard data. Therefore, when analyzing the real-time acquired positioning data, it is necessary to first determine whether standard data exists. This standard data can be determined based on previously acquired positioning data.

[0125] Generally, when standard data is unavailable and the server has just begun processing location data in a real-time storage scenario, the first piece of location data obtained by the server can be used as the standard data, provided that a certain amount of location data has been accumulated. Alternatively, depending on actual needs, after accumulating a certain amount of location data, the appropriate standard data can be determined through analysis.

[0126] In one embodiment of the present invention, the method further includes:

[0127] S11, If ​​the standard data does not exist, obtain a preset number of positioning data;

[0128] In the absence of standard data, a preset number of location data can be acquired, and standard data can be determined based on the accumulated preset number of location data. The preset number can be 5, 10, 20, 50, etc., and this invention does not impose any limitation on it.

[0129] S12, based on the distance difference between adjacent positioning data in time sequence, select the first valid data from the preset number of positioning data, and use the first valid data as the standard data.

[0130] In this embodiment of the invention, since the location data is uploaded in a streaming manner, the location data can have a chronological order of upload. Simultaneously, the location data can record the time point in time and the specific location where the data was generated. Based on the time points of the location data, it can be sorted to obtain location data arranged in chronological order.

[0131] Generally, location data is collected based on a preset period, and vehicle speed changes typically do not fluctuate drastically. Therefore, the distance difference between adjacent location data points in time sequence usually does not change drastically. This allows for the pre-defined range of distance differences between adjacent location data points in time sequence. If the distance difference falls within this range, the location data is considered valid. If the distance difference is outside this range, the location data deviates significantly from the normal range and is considered invalid. Therefore, a first set of valid location data can be selected, and then a standard set of data can be chosen from this first set. Typically, since the standard set is used for comparison with newly acquired location data, the newly acquired data is necessarily later in time than the previously acquired data. Therefore, the latest location data in time sequence from the first set of valid data, i.e., the location data most closely related to the newly acquired location data, can be prioritized as the standard set to better identify whether the newly acquired location data is accurate.

[0132] In one embodiment of the present invention, after the step of determining whether standard data exists, the method further includes:

[0133] S21, if the standard data exists, calculate the first time difference between the time point of the positioning data and the standard data;

[0134] Specifically, even when standard data exists, it's still necessary to determine whether it can be used for comparison with newly acquired location data. Generally, the first time difference between the newly acquired location data and the standard data can be calculated. If the first time difference is normal, the accuracy of the newly acquired location data can be analyzed relatively accurately. However, if the first time difference is too large, it can be assumed that the location of the standard data may deviate significantly from the location of the newly acquired location data. In this case, the accuracy of the newly acquired location data cannot be accurately analyzed based solely on the standard data.

[0135] S22, if the first time difference is within a preset first time range, execute the steps of calculating the first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, and / or calculating the first distance based on the location information of the positioning data and the location information of the standard data;

[0136] In this embodiment of the invention, a first time range can be preset. This first time range can be determined based on actual needs, such as 10s, 20s, 1min, 10min, 30min, 1h, etc., and the invention does not impose any limitations on this. If the first time difference is within the preset first time range, then the first time difference can be considered normal, and the newly acquired positioning data can be analyzed relatively accurately to determine whether it is normal. Subsequent analysis based on average speed and distance to determine the reliability of the newly acquired positioning data can then continue.

[0137] S23, if the first time difference is not within the preset first time range, delete the standard data.

[0138] If the difference in the first time is not within the preset first time range, it is impossible to accurately analyze whether the newly acquired positioning data is accurate. In this case, the existing standard data can be deleted and new standard data can be acquired to ensure the accuracy of data analysis.

[0139] Step 203: If the standard data exists, calculate a first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, and / or calculate a first distance based on the location information of the positioning data and the location information of the standard data;

[0140] Specifically, when standard data exists, the location of newly acquired positioning data typically does not deviate significantly from the location of the standard data. Therefore, it can be determined whether the location of the newly acquired positioning data deviates significantly from the location of the standard data based on the average speed and / or distance. Thus, a first average speed can be calculated based on the time and location information of the positioning data and the time and location information of the standard data, and / or a first distance can be calculated based on the location information of the positioning data and the location information of the standard data.

[0141] In practical implementation, the time difference between the location data's time point and the standard data's time point can be calculated, along with the distance difference between the location data's position and the standard data's position. The ratio of the time difference to the distance difference is the first average velocity, and the distance difference is the first distance.

[0142] Step 204: If the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, determine that the positioning data is accurate, and use the positioning data as new standard data.

[0143] In this embodiment of the invention, a first speed range and a first distance range can be preset. If the first average speed is within the preset first speed range, it can be considered that the first average speed is within the normal range, and the newly acquired positioning data is accurate. The first speed range can be 180km / h, 240km / h, etc., and the invention does not limit this. If the first distance is within the preset first distance range, it can be considered that the first distance is within the normal range, and the newly acquired positioning data is accurate. The first distance range is determined based on the positioning data acquisition cycle, the vehicle's maximum speed, etc., such as 40m, 60m, etc., and the invention does not limit this.

[0144] If the location data is confirmed to be accurate, it can be used as new standard data for comparison with subsequently acquired location data. This allows for continuous, real-time analysis to determine the reliability of newly acquired location data.

[0145] Step 205: Based on the location accuracy analysis results of the location data, store or delete the location data.

[0146] After the server analyzes and determines the location accuracy of the positioning data, it can select and retain positioning data with high accuracy and delete positioning data with low accuracy, based on actual needs. This allows for the real-time retention of accurate positioning data in real-time storage scenarios. This effectively saves storage space while also improving the accuracy of subsequent data analysis.

[0147] The vehicle positioning data processing method provided by this invention, applied to a server, includes: acquiring positioning data uploaded by a vehicle in streaming form; determining whether standard data exists in a real-time storage scenario; if the standard data exists, calculating a first average speed based on the time and location information of the positioning data and the time and location information of the standard data, and / or calculating a first distance based on the location information of the positioning data and the location information of the standard data; if the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, determining that the positioning data is accurate, and using the positioning data as new standard data; and storing or deleting the positioning data based on the location accuracy analysis result. Therefore, for various data storage scenarios on the server, different analysis methods can be used to efficiently determine accurate positioning data from the vehicle-uploaded positioning data, and then retain the positioning data with high accuracy. This effectively saves storage space while improving the accuracy of subsequent data analysis without significantly negatively impacting the efficiency of existing data analysis.

[0148] Reference Figure 3 The diagram illustrates a flowchart of a vehicle positioning data processing method provided in an embodiment of the present invention. This method is applied to a server and specifically includes the following steps:

[0149] Step 301: Obtain the location data uploaded by the vehicle in the form of streaming data;

[0150] Step 302: In the case that the storage scenario is a historical trajectory storage scenario, determine whether there is dangerous standard data;

[0151] In the case of storing historical trajectories, the embodiments of the present invention can focus on obtaining positioning data that can be used to generate historical trajectories. Therefore, in determining whether the positioning data uploaded by the vehicle is accurate, analysis can also be performed based on whether the positioning data can form reasonable trajectory data.

[0152] First, a hazard standard data point can be set for the historical trajectory storage scenario. Based on this hazard standard data point, it can be determined whether the location of at least one time-sequentially consecutive location data point is relatively accurate. If no hazard standard data point is available, the earliest time-sequential location data point currently acquired by the server can be used as the hazard standard data point.

[0153] Step 303: In the presence of hazardous standard data, calculate a second average speed based on the time and location information of the positioning data and the time and location information of the hazardous standard data, and / or calculate a second distance based on the location information of the positioning data and the location information of the hazardous standard data;

[0154] Specifically, when hazard standard data exists, generally speaking, the position of at least one location data point with a similar time sequence to the hazard standard data will not deviate significantly from the position of the hazard standard data. Therefore, based on average speed and / or distance, it can be determined whether the position of at least one location data point with a similar time sequence to the hazard standard data deviates significantly from the position of the hazard standard data. Thus, a second average speed can be calculated based on the time and location information of the location data and the time and location information of the hazard standard data, and / or a second distance can be calculated based on the location information of the location data and the location information of the hazard standard data.

[0155] In practical implementation, the time difference between the location data's time point and the hazard standard data's time point can be calculated, along with the distance difference between the location of the location data and the location of the hazard standard data. The ratio of the time difference to the distance difference is the second average velocity, and the distance difference is the second distance.

[0156] Step 304: Based on the second average speed and / or the second distance, determine at least one location data set; the location data set contains at least one location data set that is sequentially continuous in time.

[0157] In this embodiment of the invention, it can be determined whether the second average speed and / or the second distance between at least one time-sequentially consecutive positioning data and the hazard standard data are both within the normal range. If they are both within the normal range, the at least one time-sequentially consecutive positioning data can be combined into a positioning data set. This method can be used to confirm one or more positioning data sets so that subsequent further filtering of positioning data suitable for determining historical trajectories can be based on the positioning data sets.

[0158] In one embodiment of the present invention, the step of calculating a second average speed based on the time point and location information of the positioning data and the time point and location information of the hazard standard data when hazard standard data is present, and / or calculating a second distance based on the location information of the positioning data and the location information of the hazard standard data, includes:

[0159] S31, In the presence of dangerous standard data, the positioning data in the preset time sequence shall be used as the positioning data to be confirmed;

[0160] Specifically, in historical trajectory storage scenarios, after acquiring a certain amount of location data, the location data that can be used for historical trajectories can be determined from this data. Thus, the server can possess several sets of location data arranged in chronological order.

[0161] In the presence of dangerous standard data, a preset time sequence can be used as the starting point for the location data to be confirmed, and the location data can be analyzed sequentially to determine whether it can be used to form a continuous historical trajectory.

[0162] Specifically, the preset time sequence can be determined according to actual needs, such as the second time sequence, the third time sequence, the fourth time sequence, etc., and the present invention does not limit this.

[0163] S32, calculate a second average speed based on the time point and location information of the location data to be confirmed and the time point and location information of the hazard standard data, and / or calculate a second distance based on the location information of the location data to be confirmed and the location information of the hazard standard data;

[0164] In one embodiment of the present invention, the step of determining at least one location data set based on the second average speed and / or the second distance includes:

[0165] S41, based on the second average speed and / or the second distance, determine whether to add the location data to be confirmed to the location data set;

[0166] Specifically, it can be determined whether the second average speed and / or the second distance between the location data to be confirmed and the hazard standard data are both within the normal range, so as to determine whether the location data to be confirmed needs to be added to the location data set so as to form location data that can be used to analyze historical trajectories.

[0167] S42, if the second average speed is within a preset second speed range and / or the second distance is within a preset second distance range, add the positioning data to be confirmed to the positioning data set;

[0168] If the second average speed is within a preset second speed range and / or the second distance is within a preset second distance range, then the second average speed and / or the second distance can be considered to be within the normal range. In this case, the location data to be confirmed can be used for the analysis of historical trajectories, and the location data to be confirmed is added to the location data set.

[0169] S43, the next location data that is adjacent to the location data to be confirmed in time sequence is taken as the new location data to be confirmed, and it is determined again whether to add the location data to be confirmed to the location data set, until the second average speed is not within the preset second speed range and / or the second distance is not within the preset second distance range, and the location data set is combined into the target location data set.

[0170] Subsequently, the next location data adjacent in time sequence to the location data to be confirmed can be used as the new location data to be confirmed. It is then determined again whether to add the location data to the location data set, thereby determining whether the next location data can be used for historical trajectory analysis. This results in a location data set containing location data with continuous time sequence. This continues until the second average speed between the location data to be confirmed and the danger standard data is outside the preset second speed range and / or the second distance is outside the preset second distance range. At this point, the location data to be confirmed is considered to be outside the normal range and unsuitable for forming continuous trajectory data with the preceding location data. Therefore, it is not necessary to continue adding location data to the location data set, and the current location data set is considered the confirmed target location data set.

[0171] In one embodiment of the present invention, the step of determining at least one location data set based on the second average speed and / or the second distance further includes:

[0172] S51, the positioning data to be confirmed where the second average speed is not within the preset second speed range and / or the second distance is not within the preset second distance range is taken as new danger standard data, and the target positioning data set is determined again based on the new danger standard data until no new danger standard data exists.

[0173] Specifically, if the second average speed between the location data to be confirmed and the hazard standard data is not within the preset second speed range and / or the second distance is not within the preset second distance range, that is, if the current location data to be confirmed is not suitable for forming continuous trajectory data with the prior location data, the current location data to be confirmed can be used as new hazard standard data, and the target location data set can be determined again based on the new hazard standard data, so as to continue to obtain a target location data set suitable for forming historical trajectories, until no new hazard standard data can be determined, that is, the current existing location data has been traversed.

[0174] As a specific example of the present invention, assuming the location data are numbered 1, 2, 3...8 in chronological order, location data number 1 can be used as the hazard standard data. Location data numbers 1 and 2 are then added to the location data set by default. Starting with location data number 3, the analysis is performed to determine whether the second average speed and / or the second distance between location data number 3 and the hazard standard data are within a preset second speed range. If it is determined that the second average speed and / or the second distance of location data number 3 are within the preset second speed range, then location data number 3 is added to the location data set. Subsequently, the same method is used to determine whether location data numbers 4, 5, and 6 can be added to the location data set. If it is determined that location data numbers 4 and 5 can be added, but location data number 6 cannot, then the location data set containing location data numbers 1-5 can be determined as the target location data set, and location data number 6 is used as the new hazard standard data. Subsequently, starting with location data number 4, which follows number 3, the location data is compared sequentially with the new hazard standard data to obtain the target location data set containing location data numbers 4-6. Then, location data number 7 is used as the hazard standard data, and starting with location data number 5, the location data is compared sequentially with the new hazard standard data to obtain the target location data set containing location data numbers 5-8. Thus, the target location data sets [1-6], [4-6], and [5-8] can be obtained.

[0175] Step 305: Based on the location data set, filter at least one target location data with accurate location.

[0176] In this embodiment of the invention, after obtaining the location data set, there may be repeated location data in the location data set. The repeated location data can be considered relatively accurate. Based on the repeated location data, the location can be accurately determined. This is suitable for generating target location data for historical trajectories.

[0177] In one embodiment of the present invention, the step of filtering at least one target positioning data with accurate location based on the positioning data set includes:

[0178] S61, based on the location data set, location data that appears more than a preset threshold number of times is used as calibration location data;

[0179] Specifically, location data that appears repeatedly in a location dataset can be considered relatively accurate. Therefore, location data that appears more than a preset threshold can be used as calibration location data. As a specific example of the present invention, the location data with the highest frequency can be used as calibration location data.

[0180] S62, taking the calibration positioning data as the starting point, traversing the positioning data on the left and right sides of the calibration positioning data in the positioning data set according to the time order, and comparing whether the distance difference between adjacent positioning data in the time order is within the third distance range.

[0181] Subsequently, starting from the calibrated positioning data, other positioning data that can be connected to the calibrated positioning data to form a historical trajectory can be searched. Thus, positioning data to the left and right of the calibrated positioning data in the positioning data set can be traversed in chronological order, and the distance difference between adjacent positioning data in chronological order can be compared to see if it falls within a third distance range. This determines whether the distance difference between adjacent positioning data in chronological order is too small. If the distance difference is too small, although the positioning data is suitable for generating a historical trajectory, it can be appropriately deleted to avoid the server using too much redundant data.

[0182] S63, when the distance difference between adjacent time-series positioning data is within the third distance range, delete the positioning data that is far away from the calibration positioning data among the adjacent time-series positioning data, and take the positioning data that is close to the calibration positioning data among the adjacent time-series positioning data as the target positioning data with accurate location.

[0183] If the distance difference between adjacent time-series positioning data is within the third distance range, it can be considered that there are positioning data that are too close. In this case, you can choose to delete the positioning data that is far away from the calibration positioning data among the adjacent time-series positioning data, and retain the positioning data that is close to the calibration positioning data among the adjacent time-series positioning data as the target positioning data with accurate location.

[0184] S64, if the distance difference between adjacent positioning data in time sequence is not within the third distance range, retain the positioning data as the target positioning data with accurate location.

[0185] If the distance difference between adjacent location data in time sequence is not within the third distance range, then there is no location data that is too close, and the location data can be retained as the target location data with accurate location.

[0186] Step 306: Based on the location accuracy analysis results of the location data, store or delete the location data.

[0187] After the server analyzes and determines the location accuracy of the positioning data, it can select and retain positioning data with high accuracy and delete positioning data with low accuracy, based on actual needs. This allows for the retention of only accurate positioning data for different storage scenarios. This effectively saves storage space while also improving the accuracy of subsequent data analysis.

[0188] In one embodiment of the present invention, the method further includes:

[0189] S71, Determine if comparative data exists;

[0190] Specifically, after determining the location data that can be used to generate historical trajectories, the location data can be further processed to reduce its sparsity. This allows us to first determine if comparative data exists, and then eliminate redundant location data based on this comparative data.

[0191] In the absence of comparable data, the earliest location data in chronological order among the currently retained location data can be used as the comparable data.

[0192] S72, if comparison data exists, based on the time sequence, compare whether the distance difference between the target positioning data and the comparison data is within the fourth distance range;

[0193] When comparative data is available, the distance difference between the target positioning data and the comparative data can be compared sequentially based on time order to determine whether it falls within the fourth distance range and whether the distance between the target positioning data and the comparative data is too small.

[0194] S73, if the distance difference between the target positioning data and the comparison data is not within the fourth distance range, retain the target positioning data;

[0195] If the distance difference between the target positioning data and the comparison data is not within the fourth distance range, then the distance difference between the target positioning data and the comparison data is within an acceptable range, and the target positioning data can be retained. As a specific example of the present invention, the position in the positioning data can be represented by a geohash value. If the first 7 digits of the geohash value are the same, it can be considered that the distance difference between the target positioning data and the comparison data is no greater than 150m, and the distance difference between the target positioning data and the comparison data is within an acceptable range.

[0196] S74, if at least three retained target positioning data are obtained, calculate the vector angle between target positioning data that are adjacent in time sequence to obtain at least two vector angles;

[0197] If at least three retained target positioning data are obtained, the vector angle between adjacent target positioning data in time sequence can be calculated to determine whether there is a significant change in vehicle direction.

[0198] Specifically, each location data point can also record the vehicle's current driving direction. Based on this direction, a vector can be determined. An angle can be formed between two sequentially adjacent vectors, resulting in the vector angle. Based on this angle, it can be determined whether the vehicle's driving direction has changed. If the difference between the vector angles is greater than a preset angle difference, the vehicle's driving direction is considered to have changed significantly. In this case, to maintain the accuracy of the vehicle's trajectory, the target location data can be retained. However, if the difference between the vector angles is not greater than the preset angle difference, the vehicle's driving direction is considered not to have changed significantly. To appropriately reduce storage space usage, one of the two target location data points can be deleted.

[0199] S75, compare whether the difference between the angles of adjacent vectors in time sequence is within the preset range of angle difference;

[0200] S76, if the difference between the included angles of adjacent vectors in time sequence is not within the preset range of included angle difference, retain the target positioning data corresponding to the included angle of the vectors;

[0201] If the difference between the angles of adjacent vectors in the time sequence is within the preset angle difference range, it can be considered that the directional change of the adjacent positioning data is small, and the positioning data can be deleted. However, if the difference between the angles of adjacent vectors in the time sequence is not within the preset angle difference range, the directional change of the adjacent positioning data is large, and the positioning data needs to be retained.

[0202] S77, take the target positioning data corresponding to the vector angle with the latest time sequence as the new comparison data, and continue to determine the target positioning data to be retained based on the new comparison data, until there is no new comparison data, and use the retained target positioning data as trajectory data.

[0203] After determining the target positioning data that needs to be retained, the target positioning data corresponding to the latest vector angle in the time sequence can be used as new comparison data to continue determining the target positioning data that needs to be retained until there is no new comparison data. The retained target positioning data can be processed as sparsity data and can be used to generate trajectory data for historical trajectories.

[0204] In one embodiment of the present invention, the method further includes:

[0205] S81 uses a preset mathematical analysis model to filter out valid target data from trajectory data;

[0206] Furthermore, after sparsity processing, mathematical analysis models such as support vector machines and genetic algorithms can be used to further exclude trajectory data with similar locations, thereby further filtering to obtain the target effective data. Specifically, the mathematical analysis model can be trained in advance using training samples to obtain a mathematical analysis model that can be used to identify similar locations. Subsequently, this mathematical analysis model can be used to filter the target effective data from the trajectory data.

[0207] S82, Based on the target valid data, generate the historical trajectory of the vehicle.

[0208] Subsequently, the vehicle's historical trajectory can be generated using the target's valid data, and the vehicle's status can be analyzed based on the historical trajectory.

[0209] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0210] Reference Figure 4 The diagram shows a structural block diagram of a vehicle positioning data processing device provided in an embodiment of the present invention, which may specifically include the following modules:

[0211] The location acquisition module 401 is used to acquire the location data uploaded by the vehicle in the form of streaming data;

[0212] The accuracy analysis module 402 is used to analyze the location accuracy of the positioning data according to at least one preset storage scenario and the analysis method corresponding to the storage scenario; wherein, the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario;

[0213] The data processing module 403 is used to store or delete the positioning data based on the location accuracy analysis results of the positioning data.

[0214] Optionally, the accuracy analysis module includes:

[0215] The standard data determination submodule is used to determine whether standard data exists.

[0216] The first calculation submodule is used to calculate a first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, when the standard data exists, and / or to calculate a first distance based on the location information of the positioning data and the location information of the standard data;

[0217] The first accuracy determination submodule is used to determine that the positioning data is accurate if the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, and to use the positioning data as new standard data.

[0218] Optionally, the device further includes:

[0219] The first time difference calculation module is used to calculate the first time difference between the time point of the positioning data and the standard data when the standard data exists.

[0220] The first calculation module is used to perform the steps of calculating the first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, and / or calculating the first distance based on the location information of the positioning data and the location information of the standard data if the first time difference is within a preset first time range;

[0221] The standard data deletion module is used to delete the standard data if the first time difference is not within a preset first time range.

[0222] Optionally, the device further includes:

[0223] The positioning data acquisition module is used to acquire a preset number of positioning data if the standard data does not exist.

[0224] The effective data filtering module is used to select the first effective data from the preset number of positioning data based on the distance difference between adjacent positioning data in time sequence, and to use the first effective data as the standard data.

[0225] Optionally, the accuracy analysis module includes

[0226] The hazard standard data acquisition submodule is used to determine whether hazard standard data exists.

[0227] The second calculation submodule is used to calculate a second average speed based on the time point and location information of the positioning data and the time point and location information of the dangerous standard data when dangerous standard data is available, and / or to calculate a second distance based on the location information of the positioning data and the location information of the dangerous standard data.

[0228] A set determination submodule is used to determine at least one location data set based on the second average speed and / or the second distance; the location data set contains at least one location data set that is sequentially continuous in time.

[0229] The second accuracy determination submodule is used to filter at least one target positioning data with accurate location based on the positioning data set.

[0230] Optionally, the second calculation submodule includes:

[0231] The pending data confirmation unit is used to use positioning data in a preset time sequence as positioning data to be confirmed when dangerous standard data exists.

[0232] The first calculation unit is used to calculate a second average speed based on the time point and location information of the location data to be confirmed and the time point and location information of the hazard standard data, and / or to calculate a second distance based on the location information of the location data to be confirmed and the location information of the hazard standard data;

[0233] Optionally, the set determination submodule includes:

[0234] A data addition confirmation unit is used to determine, based on the second average speed and / or the second distance, whether to add the positioning data to be confirmed to the positioning data set;

[0235] A data adding unit is used to add the positioning data to be confirmed to the positioning data set if the second average speed is within a preset second speed range and / or the second distance is within a preset second distance range;

[0236] The set determination unit is used to take the next location data that is adjacent to the location data to be confirmed in time sequence as the new location data to be confirmed, and to determine again whether to add the location data to be confirmed to the location data set, until the second average speed is not within the preset second speed range and / or the second distance is not within the preset second distance range, and to combine the location data set into the target location data set.

[0237] Optionally, the set determination submodule further includes:

[0238] The target set determination unit is used to take the unconfirmed positioning data where the second average speed is not within a preset second speed range and / or the second distance is not within a preset second distance range as new hazard standard data, and to determine the target positioning data set again based on the new hazard standard data until no new hazard standard data exists.

[0239] Optionally, the second accuracy determination submodule includes:

[0240] The calibration positioning data determination unit is used to select positioning data that appears more than a preset threshold as calibration positioning data based on the positioning data set.

[0241] The calibration distance determination unit is used to take the calibration positioning data as the starting point, traverse the positioning data on the left and right sides of the calibration positioning data in the positioning data set according to the time sequence, and compare whether the distance difference between adjacent positioning data in the time sequence is within the third distance range.

[0242] The first accuracy confirmation unit is used to delete the positioning data that is far away from the calibration positioning data in the time-sequential adjacent positioning data when the distance difference between the time-sequential adjacent positioning data is within the third distance range, and to take the positioning data that is close to the calibration positioning data in the time-sequential adjacent positioning data as the target positioning data with accurate position.

[0243] The second accuracy confirmation unit is used to retain the positioning data as the target positioning data with accurate location if the distance difference between adjacent positioning data in time sequence is not within the third distance range.

[0244] Optionally, the device further includes:

[0245] The comparison data determination module is used to determine whether comparison data exists.

[0246] The comparison unit is used to compare, in the presence of comparison data, whether the distance difference between the target positioning data and the comparison data is within a fourth distance range based on time order.

[0247] The first positioning data retention module is used to retain the target positioning data when the distance difference between the target positioning data and the comparison data is not within the fourth distance range;

[0248] The vector angle calculation module is used to calculate the vector angle between target positioning data that are adjacent in time sequence, given that at least three retained target positioning data have been obtained, to obtain at least two vector angles.

[0249] The angle difference calculation module is used to compare whether the difference between the angles of adjacent vectors in time sequence is within a preset angle difference range;

[0250] The second positioning data retention module is used to retain the target positioning data corresponding to the vector angle when the difference between the angles of adjacent vectors in time sequence is not within a preset range of angle difference.

[0251] The target positioning data corresponding to the latest vector angle in the time sequence is used as the new comparison data. Based on the new comparison data, the target positioning data to be retained is determined until there is no new comparison data. The retained target positioning data is then used as trajectory data.

[0252] Optionally, the device further includes:

[0253] The model analysis module is used to filter valid target data from trajectory data using a preset mathematical analysis model.

[0254] The historical trajectory generation module is used to generate the historical trajectory of the vehicle based on the target valid data.

[0255] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0256] In addition, embodiments of the present invention also provide an electronic device, such as... Figure 5 As shown, it includes a processor 501, a communication interface 502, a memory 503, and a communication bus 504, wherein the processor 501, the communication interface 502, and the memory 503 communicate with each other through the communication bus 504.

[0257] Memory 503 is used to store computer programs;

[0258] When processor 501 executes the program stored in memory 503, it performs the following steps:

[0259] Acquire location data uploaded by the vehicle in the form of streaming data;

[0260] The location accuracy of the positioning data is analyzed using an analysis method corresponding to the preset storage scenario, based on at least one preset storage scenario; wherein, the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario;

[0261] Based on the location accuracy analysis results of the location data, store or delete the location data.

[0262] Optionally, when the storage scenario is a real-time storage scenario, the step of analyzing the location accuracy of the positioning data using the analysis method corresponding to the storage scenario includes:

[0263] Determine if standard data exists.

[0264] In the presence of the standard data, a first average speed is calculated based on the time and location information of the positioning data and the time and location information of the standard data, and / or a first distance is calculated based on the location information of the positioning data and the location information of the standard data;

[0265] If the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, the positioning data is determined to be accurate, and the positioning data is used as new standard data.

[0266] Optionally, after the step of determining whether standard data exists, the method further includes:

[0267] If the standard data exists, calculate a first time difference between the time point of the positioning data and the standard data;

[0268] If the first time difference is within a preset first time range, the steps of calculating the first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, and / or calculating the first distance based on the location information of the positioning data and the location information of the standard data are executed.

[0269] If the first time difference is not within the preset first time range, the standard data is deleted.

[0270] Optionally, the method further includes:

[0271] If the standard data does not exist, obtain a preset number of location data.

[0272] Based on the distance difference between adjacent location data in time sequence, a first valid data is selected from the preset number of location data, and the first valid data is used as the standard data.

[0273] Optionally, when the storage scenario is a historical trajectory storage scenario, the step of analyzing the location accuracy of the positioning data using the analysis method corresponding to the storage scenario includes:

[0274] Determine if any hazardous standard data exists;

[0275] In the presence of hazardous standard data, a second average speed is calculated based on the time and location information of the positioning data and the time and location information of the hazardous standard data, and / or a second distance is calculated based on the location information of the positioning data and the location information of the hazardous standard data;

[0276] Based on the second average speed and / or the second distance, at least one location data set is determined; the location data set contains at least one location data set that is sequentially continuous in time.

[0277] Based on the location data set, at least one target location data with accurate location is selected.

[0278] Optionally, the step of calculating a second average speed based on the time and location information of the positioning data and the time and location information of the hazard standard data when hazard standard data exists, and / or calculating a second distance based on the location information of the positioning data and the location information of the hazard standard data, includes:

[0279] In the presence of dangerous standard data, the positioning data in a preset time sequence will be used as the positioning data to be confirmed;

[0280] A second average speed is calculated based on the time and location information of the location data to be confirmed and the time and location information of the hazard standard data, and / or a second distance is calculated based on the location information of the location data to be confirmed and the location information of the hazard standard data;

[0281] The step of determining at least one location data set based on the second average speed and / or the second distance includes:

[0282] Based on the second average speed and / or the second distance, determine whether to add the location data to be confirmed to the location data set;

[0283] If the second average speed is within a preset second speed range and / or the second distance is within a preset second distance range, the positioning data to be confirmed will be added to the positioning data set;

[0284] The next location data that is adjacent to the location data to be confirmed in time sequence is taken as the new location data to be confirmed. It is then determined whether to add the location data to be confirmed to the location data set, until the second average speed is not within the preset second speed range and / or the second distance is not within the preset second distance range, and the location data set is then combined into the target location data set.

[0285] Optionally, the step of determining at least one location data set based on the second average speed and / or the second distance further includes:

[0286] The location data to be confirmed that are not within the preset second speed range and / or the second distance is not within the preset second distance range are taken as new hazard standard data. The target location data set is determined again based on the new hazard standard data until no new hazard standard data is found.

[0287] Optionally, the step of filtering at least one target location data with accurate location based on the location data set includes:

[0288] Based on the aforementioned location data set, location data that appears more than a preset threshold number of times will be used as calibration location data;

[0289] Starting from the calibration positioning data, the positioning data on the left and right sides of the calibration positioning data in the positioning data set are traversed in time order, and the distance difference between adjacent positioning data in time order is compared to see if it is within the third distance range.

[0290] If the distance difference between adjacent time-series positioning data is within the third distance range, the positioning data that is far away from the calibration positioning data among the adjacent time-series positioning data will be deleted, and the positioning data that is close to the calibration positioning data among the adjacent time-series positioning data will be used as the target positioning data with accurate location.

[0291] If the distance difference between adjacent location data in time sequence is not within the third distance range, the location data is retained as the target location data with accurate location.

[0292] Optionally, the method further includes:

[0293] Determine if comparative data exists;

[0294] In the presence of comparative data, based on the time sequence, the distance difference between the target positioning data and the comparative data is compared sequentially to see if it falls within the fourth distance range;

[0295] If the distance difference between the target positioning data and the comparison data is not within the fourth distance range, the target positioning data is retained;

[0296] If at least three retained target positioning data are obtained, the vector angle between target positioning data that are adjacent in time sequence is calculated to obtain at least two vector angles.

[0297] Compare whether the difference between the angles of adjacent vectors in the time sequence is within a preset range of angle differences;

[0298] If the difference between the included angles of adjacent vectors in time sequence is not within the preset range of included angle difference, the target positioning data corresponding to the included vector angle is retained;

[0299] The target positioning data corresponding to the latest vector angle in the time sequence is used as the new comparison data. Based on the new comparison data, the target positioning data to be retained is determined until there is no new comparison data. The retained target positioning data is then used as trajectory data.

[0300] Optionally, the method further includes:

[0301] A pre-defined mathematical analysis model is used to filter out valid target data from the trajectory data;

[0302] Based on the target's valid data, the vehicle's historical trajectory is generated.

[0303] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0304] The communication interface is used for communication between the aforementioned terminal and other devices.

[0305] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0306] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0307] like Figure 6As shown, in another embodiment of the present invention, a computer-readable storage medium 601 is also provided, which stores instructions that, when executed on a computer, cause the computer to perform the vehicle positioning data processing method described in the above embodiment.

[0308] In another embodiment of the present invention, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the vehicle positioning data processing method described in the above embodiments.

[0309] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0310] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0311] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0312] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.

Claims

1. A method for processing vehicle positioning data, characterized in that, It is applied to a server, and the method includes: Acquire location data uploaded by the vehicle in the form of streaming data; The location accuracy of the positioning data is analyzed using an analysis method corresponding to the preset storage scenario, based on at least one preset storage scenario; wherein, the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario; Based on the location accuracy analysis results of the location data, store or delete the location data; Wherein, in the case of a real-time storage scenario, the step of analyzing the location accuracy of the positioning data using the analysis method corresponding to the storage scenario includes: Determine if standard data exists. In the presence of the standard data, a first average speed is calculated based on the time and location information of the positioning data and the time and location information of the standard data, and / or a first distance is calculated based on the location information of the positioning data and the location information of the standard data; If the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, the positioning data is determined to be accurate, and the positioning data is used as new standard data.

2. The method according to claim 1, characterized in that, After the step of determining whether standard data exists, the method further includes: If the standard data exists, calculate a first time difference between the time point of the positioning data and the standard data; If the first time difference is within a preset first time range, the steps of calculating the first average speed based on the time point and location information of the positioning data and the time point and location information of the standard data, and / or calculating the first distance based on the location information of the positioning data and the location information of the standard data are executed. If the first time difference is not within the preset first time range, the standard data is deleted.

3. The method according to claim 1 or 2, characterized in that, The method further includes: If the standard data does not exist, obtain a preset number of location data. Based on the distance difference between adjacent location data in time sequence, a first valid data is selected from the preset number of location data, and the first valid data is used as the standard data.

4. The method according to claim 1, characterized in that, When the storage scenario is a historical trajectory storage scenario, the step of analyzing the location accuracy of the positioning data using the analysis method corresponding to the storage scenario includes: Determine if any hazardous standard data exists; In the presence of hazardous standard data, a second average speed is calculated based on the time and location information of the positioning data and the time and location information of the hazardous standard data, and / or a second distance is calculated based on the location information of the positioning data and the location information of the hazardous standard data; Based on the second average speed and / or the second distance, at least one location data set is determined; the location data set contains at least one location data set that is sequentially continuous in time. Based on the location data set, at least one target location data with accurate location is selected.

5. The method according to claim 4, characterized in that, The steps of calculating a second average speed based on the time and location information of the positioning data and the time and location information of the hazard standard data when hazard standard data is present, and / or calculating a second distance based on the location information of the positioning data and the location information of the hazard standard data, include: In the presence of dangerous standard data, the positioning data in a preset time sequence will be used as the positioning data to be confirmed; A second average speed is calculated based on the time and location information of the location data to be confirmed and the time and location information of the hazard standard data, and / or a second distance is calculated based on the location information of the location data to be confirmed and the location information of the hazard standard data; The step of determining at least one location data set based on the second average speed and / or the second distance includes: Based on the second average speed and / or the second distance, determine whether to add the location data to be confirmed to the location data set; If the second average speed is within a preset second speed range and / or the second distance is within a preset second distance range, the positioning data to be confirmed will be added to the positioning data set; The next location data that is adjacent to the location data to be confirmed in time sequence is taken as the new location data to be confirmed. It is then determined whether to add the location data to be confirmed to the location data set, until the second average speed is not within the preset second speed range and / or the second distance is not within the preset second distance range, and the location data set is then combined into the target location data set.

6. The method according to claim 5, characterized in that, The step of determining at least one location data set based on the second average velocity and / or the second distance further includes: The location data to be confirmed that are not within the preset second speed range and / or the second distance is not within the preset second distance range are taken as new hazard standard data. The target location data set is determined again based on the new hazard standard data until no new hazard standard data is found.

7. The method according to claim 4, characterized in that, The step of filtering at least one target location data with accurate location based on the location data set includes: Based on the aforementioned location data set, location data that appears more than a preset threshold number of times will be used as calibration location data; Starting from the calibration positioning data, the positioning data on the left and right sides of the calibration positioning data in the positioning data set are traversed in time order, and the distance difference between adjacent positioning data in time order is compared to see if it is within the third distance range. If the distance difference between adjacent time-series positioning data is within the third distance range, the positioning data that is far away from the calibration positioning data among the adjacent time-series positioning data will be deleted, and the positioning data that is close to the calibration positioning data among the adjacent time-series positioning data will be used as the target positioning data with accurate location. If the distance difference between adjacent location data in time sequence is not within the third distance range, the location data is retained as the target location data with accurate location.

8. The method according to any one of claims 4-7, characterized in that, The method further includes: Determine if comparative data exists; In the presence of comparative data, based on the time sequence, the distance difference between the target positioning data and the comparative data is compared sequentially to see if it falls within the fourth distance range; If the distance difference between the target positioning data and the comparison data is not within the fourth distance range, the target positioning data is retained; If at least three retained target positioning data are obtained, the vector angle between target positioning data that are adjacent in time sequence is calculated to obtain at least two vector angles. Compare whether the difference between the angles of adjacent vectors in the time sequence is within a preset range of angle differences; If the difference between the included angles of adjacent vectors in time sequence is not within the preset range of included angle difference, the target positioning data corresponding to the included vector angle is retained; The target positioning data corresponding to the latest vector angle in the time sequence is used as the new comparison data. Based on the new comparison data, the target positioning data to be retained is determined until there is no new comparison data. The retained target positioning data is then used as trajectory data.

9. The method according to claim 8, characterized in that, The method further includes: A pre-defined mathematical analysis model is used to filter out valid target data from the trajectory data; Based on the target's valid data, the vehicle's historical trajectory is generated.

10. A device for processing vehicle positioning data, characterized in that, It is used in servers, and the device includes: The location acquisition module is used to acquire the location data uploaded by the vehicle in the form of streaming data; An accuracy analysis module is used to analyze the location accuracy of the positioning data according to at least one preset storage scenario and using the analysis method corresponding to the storage scenario; wherein, the storage scenario includes at least one of real-time storage scenario, historical trajectory storage scenario, and all data storage scenario; The data processing module is used to store or delete the positioning data based on the location accuracy analysis results of the positioning data; Wherein, in the case of a real-time storage scenario, the accuracy analysis module is specifically used for: Determine if standard data exists. In the presence of the standard data, a first average speed is calculated based on the time and location information of the positioning data and the time and location information of the standard data, and / or a first distance is calculated based on the location information of the positioning data and the location information of the standard data; If the first average speed is within a preset first speed range and / or the first distance is within a preset first distance range, the positioning data is determined to be accurate, and the positioning data is used as new standard data.

11. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory is used to store computer programs; When the processor executes a program stored in the memory, it implements the method as described in any one of claims 1-9.

12. One or more computer-readable media having instructions stored thereon that, when executed by one or more processors, cause the processors to perform the method as described in any one of claims 1-9.

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