Vehicle turning data processing method, device and equipment

Abstract

The present invention provides a method, apparatus and device for processing vehicle turning data. The method includes obtaining a vehicle driving data set, sorting the vehicle driving data set based on the data acquisition time, determining a first sorting field corresponding to each vehicle driving data, grouping the vehicle driving data set, sorting the grouped vehicle driving data, determining a second sorting field corresponding to each vehicle driving data, performing grouping processing on the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group, determining the driving direction angle difference corresponding to each continuous driving data group, obtaining a target driving direction angle difference whose driving direction angle difference is not less than a preset angle difference threshold, and then setting the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data. This embodiment improves the accuracy of determining the vehicle inflection point, and further improves the accuracy of determining the turning speed.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of big data, and in particular, to a method, device and equipment for processing vehicle turning data. Background Art

[0002] With the development of computer technology, more and more technologies are applied in the financial field. The traditional financial industry is gradually transforming into financial technology (Fintech), and big data technology is no exception. However, due to the security and real-time requirements of the financial industry, higher requirements are also put forward for big data technology. With the popularization of vehicles in people's lives, the number of vehicles running on the road is increasing rapidly. Accordingly, people's attention to driving safety is also getting higher and higher.

[0003] The turning speed of a vehicle is an important indicator to measure whether a driver has good driving habits. Therefore, the driving safety can be determined by the turning speed. In the prior art, when determining the turning speed of a vehicle, it is necessary to first determine whether it is an inflection point, and then determine the vehicle speed corresponding to the inflection point as the turning speed. When determining the inflection point, generally, an angle difference threshold is first set, and then the driving direction angle differences corresponding to adjacent two vehicle driving data are calculated in sequence, and the vehicle driving data with the driving direction angle difference greater than the angle difference threshold is obtained, and then the vehicle driving data can be determined as the vehicle inflection point.

[0004] However, when simply relying on the driving direction angle difference between adjacent two vehicle driving data and the angle difference threshold to determine the vehicle inflection point, if the angle difference threshold is set too large, the vehicle driving data with a smaller inflection point angle may be ignored. If the angle difference threshold is set too small, the determined inflection points may be relatively numerous, reducing the accuracy of inflection point determination, and thus affecting the accuracy of turning speed determination. Summary of the Invention

[0005] The embodiments of the present invention provide a method, device and equipment for processing vehicle turning data to improve the accuracy of inflection point determination, and thus improve the accuracy of turning speed determination.

[0006] In a first aspect, the embodiments of the present invention provide a method for processing vehicle turning data, including:

[0007] Obtain a vehicle driving data set, where the vehicle driving data set includes a plurality of vehicle driving data, and each vehicle driving data includes a data acquisition time;

[0008] Sort the vehicle driving data set based on the data acquisition time, and determine a first sorting field corresponding to each vehicle driving data;

[0009] Group the vehicle driving data set according to a preset grouping rule, sort the grouped vehicle driving data, and determine a second sorting field corresponding to each vehicle driving data;

[0010] Perform grouping processing on the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group;

[0011] Determine the driving direction angle difference corresponding to each continuous driving data group, obtain a target driving direction angle difference whose driving direction angle difference is not less than a preset angle difference threshold, and then set the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data.

[0012] Optionally, each vehicle driving data includes the driving speed corresponding to the vehicle. Then, grouping the vehicle driving data set according to a preset grouping rule, sorting the grouped vehicle driving data, and determining a second sorting field corresponding to each vehicle driving data includes:

[0013] Group the vehicle driving data set based on the driving speed corresponding to each vehicle to obtain a first vehicle driving data subset and a second vehicle driving data subset;

[0014] Sort the vehicle driving data in the first vehicle driving data subset and the second vehicle driving data subset respectively based on the data acquisition time, and determine a second sorting field corresponding to each vehicle driving data.

[0015] Optionally, each vehicle driving data includes the driving speed corresponding to the vehicle. Then, performing grouping processing on the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group includes:

[0016] Determine a first difference between the first sorting field and the second sorting field corresponding to each vehicle driving data;

[0017] Determine the vehicle driving data with a driving speed greater than a preset speed and the same first difference as a continuous driving data group.

[0018] Optionally, for each continuous driving data group, determining the driving direction angle difference corresponding to the vehicle driving data in the continuous driving data group, obtaining a target driving direction angle difference that is not less than a preset angle difference threshold, and then setting the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data includes:

[0019] For each of the continuous driving data groups, determine the driving direction angle differences corresponding to the vehicle driving data in the continuous driving data group to obtain a first set of driving direction angle differences;

[0020] Obtain the maximum driving direction angle difference from the first set of driving direction angle differences to obtain a first maximum driving direction angle difference;

[0021] If the first maximum driving direction angle difference is not less than a preset angle difference threshold, set the vehicle driving data corresponding to the first maximum driving direction angle difference as vehicle turning data.

[0022] Optionally, for each of the continuous driving data groups, determine the driving direction angle differences corresponding to the vehicle driving data in the continuous driving data group, obtain the target driving direction angle differences that are not less than the preset angle difference threshold among the driving direction angle differences, and then set the vehicle driving data corresponding to the target driving direction angle differences as vehicle turning data, including:

[0023] For each of the continuous driving data groups, determine the interval duration between the vehicle driving data according to the data acquisition time included in each vehicle driving data in the continuous driving data group;

[0024] Obtain the target vehicle driving data with the interval duration within a preset duration threshold to obtain a target vehicle driving data set;

[0025] Determine the driving direction angle differences corresponding to the target vehicle driving data in the target vehicle driving data set to obtain a second set of driving direction angle differences;

[0026] Obtain the maximum driving direction angle difference from the second set of driving direction angle differences to obtain a second maximum driving direction angle difference;

[0027] If the second maximum driving direction angle difference is not less than the preset angle difference threshold, set the vehicle driving data corresponding to the second maximum driving direction angle difference as vehicle turning data.

[0028] Optionally, after setting the vehicle driving data corresponding to the target driving direction angle differences as vehicle turning data, further include:

[0029] Group and sort the vehicle driving data set based on whether the vehicle driving data is vehicle turning data, and determine the third sorting field corresponding to each vehicle driving data;

[0030] Determine the second difference between the first sorting field and the third sorting field corresponding to each vehicle driving data;

[0031] Determine the vehicle driving data with the same second difference and being vehicle turning data as continuous turning data.

[0032] Optionally, the grouping and sorting of the vehicle driving data set based on whether the vehicle driving data is vehicle turning data, and determining the third sorting field corresponding to each vehicle driving data includes:

[0033] Group the vehicle driving data set based on whether the vehicle driving data is vehicle turning data to obtain a third vehicle driving data subset and a fourth vehicle driving data subset;

[0034] Sort the vehicle driving data in the third vehicle driving data subset and the fourth vehicle driving data subset respectively based on the data acquisition time, and determine the third sorting field corresponding to each vehicle driving data.

[0035] In a second aspect, an embodiment of the present invention provides a vehicle turning data processing device, including:

[0036] An acquisition module, configured to acquire a vehicle driving data set, where the vehicle driving data set includes a plurality of vehicle driving data, and each vehicle driving data includes a data acquisition time;

[0037] A processing module, configured to sort the vehicle driving data set based on the data acquisition time, and determine the first sorting field corresponding to each vehicle driving data;

[0038] The processing module is further configured to group the vehicle driving data set based on a preset grouping rule, and sort the grouped vehicle driving data to determine the second sorting field corresponding to each vehicle driving data;

[0039] The processing module is further configured to perform a grouping process on the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group;

[0040] The processing module is further configured to, for each continuous driving data group, determine the driving direction angle difference corresponding to each vehicle driving data in the continuous driving data group, obtain the target driving direction angle difference that is not less than the preset angle difference threshold in the driving direction angle difference, and then set the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data.

[0041] In a third aspect, an embodiment of the present invention provides a vehicle turning data processing device, including: at least one processor and a memory;

[0042] The memory stores computer execution instructions;

[0043] The at least one processor executes the computer-executable instructions stored in the memory, such that the at least one processor executes the vehicle turning data processing method according to any one of the first aspect.

[0044] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the vehicle turning data processing method according to any one of the first aspect is implemented.

[0045] In a fifth aspect, an embodiment of the present invention provides a computer program product, including a computer program. When the computer program is executed by a processor, the vehicle turning data processing method according to the first aspect and various possible designs of the first aspect is implemented.

[0046] An embodiment of the present invention provides a vehicle turning data processing method, device, and equipment. After adopting the above solution, it is possible to first obtain a vehicle driving data set including a plurality of vehicle driving data, then sort the vehicle data set based on the data acquisition time included in each vehicle driving data, determine the first sorting field corresponding to each vehicle driving data, group the vehicle driving data set based on a preset grouping rule, and sort the grouped vehicle driving data to determine the second sorting field corresponding to each vehicle driving data. Then, group processing is performed on the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group. However, for each continuous driving data group, determine the driving direction angle difference corresponding to each continuous driving data in the continuous driving data group, and obtain the target driving direction angle difference in the driving direction angle difference that is not less than the preset angle difference threshold. Then, the vehicle driving data corresponding to the target driving direction angle difference can be set as vehicle turning data. By adding a vehicle continuous driving recognition process and grouping the vehicle driving data set with whether continuous driving as a reference basis to determine the continuous driving data group, then for each vehicle driving data in the continuous driving data group, respectively determine a plurality of driving direction angle differences, and then compare the plurality of driving direction angle differences with the angle threshold, no longer limited to only determining the driving direction angle difference corresponding to adjacent vehicle driving data, improving the accuracy of vehicle inflection point determination, and further improving the accuracy of turning speed determination. Description of the Drawings

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0048] Figure 1 Schematic diagram of the application of vehicle driving data in the prior art;

[0049] Figure 2 Schematic diagram of the architecture of the application system for the vehicle turning data processing method provided by an embodiment of the present invention;

[0050] Figure 3 Schematic flow chart of the vehicle turning data processing method provided by an embodiment of the present invention;

[0051] Figure 4 Schematic flow chart of the vehicle turning data processing method provided by another embodiment of the present invention;

[0052] Figure 5 Schematic diagram of the structure of the vehicle turning data processing device provided by an embodiment of the present invention;

[0053] Figure 6 Schematic diagram of the hardware structure of the vehicle turning data processing device provided by an embodiment of the present invention. Detailed implementation manners

[0054] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0055] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can also include other sequence examples in addition to the examples illustrated or described. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0056] In the prior art, the turning speed of a vehicle is an important indicator to measure whether a driver has good driving habits. Therefore, the driving safety can be determined by the turning speed. In the prior art, when determining the turning speed of a vehicle, it is necessary to first determine whether it is an inflection point, and then determine the vehicle speed corresponding to the inflection point as the turning speed. During the driving process of a vehicle, it can be positioned and navigated in real time globally through GPS (Global Positioning System), and the position point information of the vehicle can be determined, which can also be called vehicle driving data. Continuous vehicle driving data can form a vehicle driving data set. Among them, the vehicle driving data can include the data acquisition time, the longitude where the vehicle is located, the latitude where the vehicle is located, the vehicle driving direction (angle degree: 0-359, with the due north direction as 0 degree, and counted in the clockwise direction), and the driving speed, etc. Moreover, the amount of vehicle driving data obtained increases exponentially with the reduction of the acquisition time interval. Assuming that the acquisition time interval is 1 second, the number of reported data of a vehicle in a day will reach 86,400. The turning speed of a driver is an important indicator to measure whether a driver has good driving habits. Therefore, we need to accurately identify the turning points of the vehicle from a large amount of data, so as to analyze the turning speed of the vehicle.

[0057] When determining the inflection point, generally, an angle difference threshold is first set, and then the driving direction angle differences corresponding to two adjacent vehicle driving data are calculated in turn, and the vehicle driving data with the driving direction angle difference greater than the angle difference threshold is obtained, and then the vehicle driving data can be determined as the vehicle inflection point. However, when solely relying on the driving direction angle difference between two adjacent vehicle driving data and the angle difference threshold to determine the vehicle inflection point, if the angle difference threshold is set too large, the vehicle driving data with a smaller inflection point angle may be ignored. If the angle difference threshold is set too small, the determined inflection points may be relatively numerous. Figure 1 It is a schematic diagram of the application of vehicle driving data in the prior art, as Figure 1 shown. In this embodiment, the angle difference threshold is set to 70 degrees, that is, if the angle difference between two adjacent points exceeds 70 degrees, it is considered that a turning has occurred. For the turning scenario with continuously small-angle changes in this embodiment, since the angle difference between each two adjacent reported points does not reach the threshold, it cannot be effectively identified, reducing the accuracy of inflection point determination, and further affecting the accuracy of turning speed determination.

[0058] Based on the above problems, the present application determines a continuous driving data group by adding a vehicle continuous driving recognition process and grouping the vehicle driving data set based on whether it is continuous driving, and determines the corresponding driving direction angle difference between each piece of data in the continuous driving data group, no longer limited to only determining the driving direction angle difference corresponding to adjacent vehicle driving data, achieving the technical effects of both improving the accuracy of vehicle inflection point determination and improving the accuracy of turning speed determination.

[0059] Figure 2 The architecture schematic diagram of the application system for the vehicle turning data processing method provided by the embodiment of the present invention is shown in Figure 2 As shown, the application system may include: a vehicle 201, an in-vehicle terminal 202 deployed on the vehicle. The in-vehicle terminal 202 is deployed with a GPS positioning system, which can determine the vehicle driving data set during the vehicle driving process. In addition, the application system may further include a server 203. The vehicle driving data set determined by the in-vehicle terminal 202 can be sent to the server 203 through a communication network, and the server 203 can further process the obtained vehicle driving data set to finally determine the vehicle turning data.

[0060] In addition, there may be one vehicle 201 or multiple vehicles. In this embodiment, there are multiple vehicles 201. Each vehicle includes a vehicle identifier. When the server processes the obtained vehicle driving data set, it can process the vehicle driving data set corresponding to each vehicle based on the vehicle identifier.

[0061] The technical solution of the present invention will be described in detail below with specific embodiments. These specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0062] Figure 3 The flowchart of the vehicle turning data processing method provided by the embodiment of the present invention. The method of this embodiment can be executed by the server. As Figure 3 shown, the method of this embodiment may include:

[0063] S301: Obtain a vehicle driving data set, where the vehicle driving data set includes multiple vehicle driving data, and each vehicle driving data includes a data acquisition time.

[0064] In this embodiment, when analyzing vehicle driving data to determine vehicle inflection points, multiple vehicle driving data can be obtained first to obtain a vehicle driving data set.

[0065] In addition, the obtained vehicle driving data may also be the driving data of multiple vehicles. The vehicle driving data can also be classified according to the vehicle identifier first, and the vehicle driving data belonging to the same vehicle is classified into one category to obtain the vehicle driving data set corresponding to each vehicle.

[0066] Furthermore, the vehicle driving data can include the data acquisition time of each vehicle driving data, that is, the time when the on-vehicle terminal obtains the vehicle driving data. When obtaining the vehicle driving data, the server can obtain the vehicle driving data from the on-vehicle terminal once every preset time period. Among them, there may be multiple pieces of obtained vehicle driving data, obtaining a vehicle driving data set, and the data acquisition times of each vehicle driving data in the obtained vehicle driving data set are different. Exemplarily, the vehicle driving data can be obtained once every 1 second.

[0067] In addition, the server can also obtain the vehicle driving data from the vehicle terminal in real time. The obtained vehicle driving data is one, and the obtained vehicle driving data contains a data acquisition time.

[0068] In addition, the vehicle driving data can also include the longitude where the vehicle is located, the latitude where the vehicle is located, the driving direction, the driving speed, etc.

[0069] S302: Sort the vehicle driving data set based on the data acquisition time, and determine the first sorting field corresponding to each vehicle driving data.

[0070] In this embodiment, after obtaining the vehicle driving data set, the vehicle driving data in the vehicle driving data set may be stored in a disordered manner. To facilitate the processing of the vehicle driving data set, the vehicle driving data set can be sorted according to the pre-stored sorting rules. Exemplarily, the corresponding vehicle driving data in the vehicle driving data set can be sorted based on the data acquisition time carried by each vehicle driving data in the vehicle driving data set, and the first sorting field corresponding to each vehicle driving data is determined.

[0071] As shown in Table 1, it is the vehicle driving data table after sorting. In this table, it includes 9 pieces of vehicle driving data 1-9 obtained every second.

[0072] Table 1 Vehicle Driving Data Table

[0073]

[0074] As shown in Table 2, it is the vehicle driving data table carrying the first sorting field. In this table, it contains the first sorting field determined according to the data acquisition time of each vehicle driving data.

[0075] Table 2 Vehicle Driving Data Table Carrying the First Sorting Field

[0076]

[0077]

[0078] S303: Group the vehicle driving data set based on a preset grouping rule, sort the grouped vehicle driving data, and determine a second sorting field corresponding to each vehicle driving data.

[0079] In this embodiment, it is also possible to first group the vehicle driving data set based on a preset grouping rule, and then sort the grouped vehicle driving data to determine a second sorting field corresponding to each vehicle driving data.

[0080] Furthermore, the preset grouping rule can be to group based on the driving speed of the vehicle, that is, group the vehicle driving data set by determining whether the vehicle is in a running state. Correspondingly, grouping the vehicle driving data set based on the preset grouping rule, sorting the grouped vehicle driving data, and determining a second sorting field corresponding to each vehicle driving data can specifically include:

[0081] Group the vehicle driving data set based on the driving speed corresponding to each vehicle to obtain a first vehicle driving data subset and a second vehicle driving data subset.

[0082] Sort the vehicle driving data in the first vehicle driving data subset and the second vehicle driving data subset respectively based on the data acquisition time to determine a second sorting field corresponding to each vehicle driving data.

[0083] Specifically, the vehicle driving data set can be grouped according to whether the driving speed of the vehicle is zero to obtain a first vehicle driving data subset with a non-zero driving speed and a second vehicle driving data subset with a zero driving speed. Then, sort according to the data acquisition time of the vehicle driving data in each vehicle driving data subset to determine a second sorting field corresponding to each vehicle driving data. As shown in Table 3, it is a vehicle driving data table carrying the first sorting field and the second sorting field. In this table, it includes the first sorting field determined according to the data acquisition time of each vehicle driving data, and the second sorting field obtained by re-grouping and then sorting the vehicle driving data. Among them, after re-grouping, the vehicle driving data corresponding to labels 1, 2, 4, 5, 6, 8, and 9 is the first vehicle driving data subset, and the vehicle driving data corresponding to labels 3 and 7 is the second vehicle driving data subset.

[0084] Table 3 Vehicle Driving Data Table Carrying the First Sorting Field and the Second Sorting Field

[0085]

[0086]

[0087] In addition, when grouping the vehicle driving data set according to whether the vehicle is in the running state, in addition to judging by the driving speed, it can also be judged by rules such as whether the longitude and latitude of the vehicle are continuously at the same longitude and latitude. Each vehicle driving data includes the longitude position and latitude position corresponding to the vehicle, that is, if the longitude and latitude of the vehicle do not change in multiple consecutive vehicle driving data obtained, it means that the vehicle position has not changed, and it can also be used to determine that the vehicle is in a stationary state. Then, group the vehicle driving data set based on the preset grouping rules, sort the grouped vehicle driving data, and determine the second sorting field corresponding to each vehicle driving data, which may specifically include:

[0088] Determine several vehicle driving data that are continuously at the same position according to the longitude position and latitude position of each vehicle to obtain the fifth vehicle driving data subset, and obtain the sixth vehicle driving data subset according to the vehicle driving data whose longitude position and latitude position are not continuously at the same position. Sort the vehicle driving data in the fifth vehicle driving data subset and the sixth vehicle driving data subset respectively based on the data acquisition time, and determine the second sorting field corresponding to each vehicle driving data.

[0089] S304: Group the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group.

[0090] In this embodiment, each continuous driving data group corresponds to a continuous driving process of a vehicle. After obtaining the first sorting field and the second sorting field, the vehicle driving data set can be grouped according to the first sorting field and the second sorting field to obtain continuous driving data groups. Among them, there may be one or more continuous driving data groups, and the number of vehicle driving data in each continuous driving data group is also different, which may be one or more.

[0091] Furthermore, each vehicle driving data includes the driving speed corresponding to the vehicle. Then, grouping the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group may specifically include:

[0092] Determine the first difference between the first sorting field and the second sorting field corresponding to each vehicle driving data. Determine the vehicle driving data with a driving speed greater than the preset speed and the same first difference as a continuous driving data group.

[0093] Specifically, when determining the continuous driving data group, the difference between the two sorting fields corresponding to each vehicle driving data determined in advance, that is, the first sorting field and the second sorting field, can be processed to determine the first difference between the first sorting field and the second sorting field corresponding to each vehicle driving data. Then, the vehicle driving data with a driving speed greater than the preset speed and the same first difference is determined as a continuous driving data group. Among them, the preset speed can be zero.

[0094] As shown in Table 4, it is a vehicle driving data table carrying the first difference. In this table, it includes the first difference between the first sorting field and the second sorting field determined by processing the difference between the first sorting field and the second sorting field of each vehicle driving data. And in this table, the first differences of the vehicle driving data numbered 1-2 are the same, and the driving speed of the vehicle is not zero, so the vehicle driving data numbered 1-2 is a continuous driving data group. Similarly, the vehicle driving data numbered 4-6 is a continuous driving data group, and the vehicle driving data numbered 8-9 is a continuous driving data group.

[0095] Table 4 Vehicle driving data table carrying the first difference

[0096]

[0097]

[0098] S305: For each continuous driving data group, determine the driving direction angle difference corresponding to each vehicle driving data in the continuous driving data group, obtain the target driving direction angle difference that is not less than the preset angle difference threshold in the driving direction angle difference, and then set the vehicle driving data corresponding to the target driving direction angle difference as the vehicle turning data.

[0099] In this embodiment, the vehicle turning data is the data corresponding to the vehicle inflection point. After determining the continuous driving data group, the difference processing can be performed based on the driving directions corresponding to each continuous driving data in the continuous driving data group to obtain the driving direction angle difference corresponding to each vehicle driving data. Exemplarily, continuing with the data in Table 4 as an example, for the continuous driving data group 4-6, it includes vehicle driving data 4, vehicle driving data 5, and vehicle driving data 6. The driving direction of vehicle driving data 4 is 60 degrees, the driving direction of vehicle driving data 5 is 80 degrees, and the driving direction of vehicle driving data 6 is 90 degrees. Then, the driving direction angle differences between vehicle driving data 4 and vehicle driving data 5 and vehicle driving data 6 can be calculated respectively, and then the driving direction angle difference between vehicle driving data 5 and vehicle driving data 6 can be calculated.

[0100] Further, after determining the driving direction angle differences between the vehicle driving data, target driving direction angle differences not less than a preset angle difference threshold can be obtained from the driving direction angle differences, and then the vehicle driving data corresponding to the target driving direction angle differences can be set as vehicle turning data. Exemplarily, the angle difference threshold can be set to 70 degrees.

[0101] In addition, there can be one or more determined vehicle turning data, and each vehicle turning data can be determined as a vehicle inflection point, that is, a vehicle turning record can be determined once.

[0102] Furthermore, taking continuous driving record groups as units, in a continuous driving data group, as long as there is one vehicle turning data, the vehicle driving data corresponding to this continuous driving data group can be determined as a turning record.

[0103] Further, after determining the turning record, the driving speed of each vehicle turning data can be obtained, and this speed can be determined as the turning speed, and then the driving habits of the driver can be analyzed based on this turning speed. Generally, when the turning speed is within the range of 25 - 60 km / h, it can be concluded that the driver has good driving habits.

[0104] After adopting the above solution, a vehicle driving data set including multiple vehicle driving data can be obtained first, and then the vehicle data set can be sorted based on the data collection time included in each vehicle driving data to determine the first sorting field corresponding to each vehicle driving data. Then, the vehicle driving data set can be grouped based on a preset grouping rule, and the grouped vehicle driving data can be sorted to determine the second sorting field corresponding to each vehicle driving data. Then, the vehicle driving data set can be grouped and processed according to the first sorting field and the second sorting field to obtain at least one continuous driving data group. However, for each continuous driving data group, the driving direction angle differences corresponding to the continuous driving data in this continuous driving data group are determined, and target driving direction angle differences not less than a preset angle difference threshold are obtained. Then, the vehicle driving data corresponding to the target driving direction angle differences can be set as vehicle turning data. By adding a vehicle continuous driving recognition process and grouping the vehicle driving data set with whether it is continuous driving as a reference basis to determine continuous driving data groups, and then respectively determining multiple driving direction angle differences for the vehicle driving data in each continuous driving data group, and comparing the multiple driving direction angle differences with the angle threshold, it is no longer limited to only determining the driving direction angle differences corresponding to adjacent vehicle driving data, improving the accuracy of vehicle inflection point determination, and further improving the accuracy of turning speed determination.

[0105] Based on Figure 3 the method, some specific implementation schemes of this method are also provided in the embodiments of this specification, which will be described below.

[0106] Figure 4 A schematic flowchart of a vehicle turning data processing method provided by another embodiment of the present invention is as follows Figure 4 As shown, S305 may specifically include:

[0107] S401: For each continuous driving data group, determine the driving direction angle difference corresponding to each vehicle driving data in the continuous driving data group to obtain a first set of driving direction angle differences.

[0108] S402: Obtain the maximum driving direction angle difference from the first set of driving direction angle differences to obtain a first maximum driving direction angle difference.

[0109] S403: If the first maximum driving direction angle difference is not less than a preset angle difference threshold, set the vehicle driving data corresponding to the first maximum driving direction angle difference as vehicle turning data.

[0110] In this embodiment, after determining the driving direction angle difference corresponding to each vehicle driving data in the continuous driving data group to obtain a first set of driving direction angle differences, the maximum driving direction angle difference can be obtained from the first set of driving direction angle differences to obtain a first maximum driving direction angle difference, and then the first maximum driving direction angle difference is compared with a preset angle difference threshold. If the first maximum driving direction angle difference is greater than or equal to the angle difference threshold, the vehicle driving data corresponding to the first maximum driving direction angle difference can be set as vehicle turning data, that is, this continuous driving record can be determined as a vehicle turning record.

[0111] If the first maximum driving direction angle difference is less than the angle difference threshold, this continuous driving record can be determined as a non-vehicle turning record.

[0112] Through this embodiment, it is possible to determine whether a continuous driving record is a vehicle turning record with only one judgment, reducing the amount of data processing, thereby improving the data processing efficiency and the accuracy of determining vehicle turning records.

[0113] In another embodiment, S305 may further include:

[0114] For each of the continuous driving data groups, determine the interval duration between each vehicle driving data according to the data acquisition time included in each vehicle driving data in the continuous driving data group.

[0115] Obtain the target vehicle driving data with the interval duration within a preset duration threshold to obtain a target vehicle driving data set.

[0116] Determine the driving direction angle difference corresponding to each target vehicle driving data in the target vehicle driving data set to obtain a second set of driving direction angle differences.

[0117] Obtain the maximum driving direction angle difference from the second driving direction angle difference set to obtain the second maximum driving direction angle difference.

[0118] If the second maximum driving direction angle difference is not less than the preset angle difference threshold, set the vehicle driving data corresponding to the second maximum driving direction angle difference as vehicle turning data.

[0119] In this embodiment, during the process of obtaining vehicle driving data, due to reasons such as network environment, device power, and device status, the time interval for obtaining vehicle driving data may be unstable. For example, after obtaining the second vehicle driving data, it may take a long time to obtain the third vehicle driving data, and the obtained vehicle driving data may not correspond to the actual vehicle driving data. To reduce the impact of the above situation on the accuracy of the finally determined vehicle turning data, a time duration threshold can be set to filter the obtained vehicle driving data, and then process the filtered vehicle driving data to finally determine the vehicle turning data. Exemplarily, the preset time duration can be set to any value between 2 - 5 seconds.

[0120] In addition, in another embodiment, after setting the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data, it may further include:

[0121] Group and sort the vehicle driving data set based on whether the vehicle driving data is vehicle turning data, and determine the third sorting field corresponding to each vehicle driving data.

[0122] Determine the second difference between the first sorting field and the third sorting field corresponding to each vehicle driving data.

[0123] Determine the vehicle driving data with the same second difference and being vehicle turning data as continuous turning data.

[0124] In this embodiment, after determining the vehicle turning data, each continuous driving record may include multiple vehicle turning data. To further improve the accuracy of determining vehicle turning data, the vehicle turning data can be further processed to be determined as continuous turning data.

[0125] Furthermore, grouping and sorting the vehicle driving data set based on whether the vehicle driving data is vehicle turning data, and determining the third sorting field corresponding to each vehicle driving data may specifically include:

[0126] Group the vehicle driving data set based on whether the vehicle driving data is vehicle turning data to obtain a third vehicle driving data subset and a fourth vehicle driving data subset.

[0127] Sort the vehicle driving data in the third vehicle driving data subset and the fourth vehicle driving data subset respectively based on the data acquisition time, and determine the third sorting field corresponding to each piece of the vehicle driving data.

[0128] Specifically, the vehicle driving data set can be regrouped based on whether the determined data is vehicle turning data, to obtain a third vehicle driving data subset corresponding to the vehicle turning data and a fourth vehicle driving data subset corresponding to non-vehicle turning data. As shown in Table 5, it is a vehicle driving data table carrying vehicle turning data. In this table, the vehicle driving data corresponding to labels 1, 2, 4, 5, and 6 is the third vehicle driving data subset, and the vehicle driving data corresponding to labels 3, 7, 8, and 9 is the fourth vehicle driving data subset. Correspondingly, the vehicle driving data corresponding to labels 1 and 2 is continuous turning data, and the vehicle driving data corresponding to labels 4, 5, and 6 is continuous turning data.

[0129] Table 5 Vehicle driving data table carrying vehicle turning data

[0130]

[0131]

[0132]

[0133] In another embodiment, the present application can also implement the function of determining continuous turning data through hive-sql scripts, which may specifically include:

[0134] First, determine the first sorting field and the second sorting field according to the data acquisition time of each piece of vehicle driving data. The specific implementation process can be:

[0135] First, use the row_number sorting window function preset in the script to sort the vehicle driving data in ascending order according to the data collection time. Correspondingly, the vehicle can be grouped first through the built-in row_number function in Hive: row_number() over(partition by vehicle order by collection time asc) to obtain the vehicle driving data set corresponding to the vehicle. Then, sort the vehicle driving data set determined by vehicle classification in ascending order according to the data collection time to obtain the first sorting field corresponding to each vehicle driving data of each vehicle. Then use the row_number sorting window function to group according to whether the driving speed is 0 and sort again in ascending order according to the data collection time. Correspondingly, through the built-in row_number function in Hive: row_number() over(partition by vehicle, whether the speed is 0 order by collection time asc), each vehicle and whether the speed is 0 can be grouped first, and then sorted in ascending order according to the collection time, so as to obtain the sequential sorting of the vehicle driving data with a speed of 0 for each vehicle and the sequential sorting of the vehicle driving data with a speed not equal to 0 for each vehicle, that is, the second sorting field corresponding to the vehicle driving data set.

[0136] Then, determine the continuous driving data group according to the first sorting field and the second sorting field. The specific implementation process can be as follows:

[0137] After obtaining the two sorting fields, the difference in sorting can be calculated. Among them, the records with the same difference and a speed not equal to 0 are the continuous driving data groups.

[0138] After determining the continuous driving data group, determine the driving direction angle difference between the vehicle driving data in each continuous driving data group, and then determine the vehicle turning data according to the determined driving direction angle difference. The specific implementation process can be as follows:

[0139] Continuing with the data in Table 1-5 above as an example, it can be obtained that the vehicle driving data corresponding to labels 1-2 is a continuous driving data group, the vehicle driving data corresponding to labels 4-6 is a continuous driving data group, and the vehicle driving data corresponding to labels 8-9 is a continuous driving data group. Then, based on the obtained continuous driving data group, the following process can be further carried out:

[0140] For the vehicle driving data in the continuous driving data set, the driving direction angle difference between each vehicle driving data and the next vehicle driving data (i.e., adjacent vehicle driving data) can be calculated. For example: Vehicle driving data 1-2 are continuous driving data. If the driving direction angle difference between vehicle driving data 1 and the next vehicle driving data 2 is 20, then the adjacent angle difference of vehicle driving data 1 is 20. Vehicle driving data 2 is the last vehicle driving data reported continuously, and there is no adjacent next vehicle driving data, so the angle difference is null. Correspondingly, this step can be achieved by using the window function lead, sorting in ascending order by the data collection time, obtaining the direction angle of the next vehicle driving data, and then taking the difference with the direction angle of the current vehicle driving data.

[0141] Furthermore, for each vehicle driving data in the continuous driving data, the driving direction angle difference of any vehicle driving data with an interval duration within a preset time threshold can be calculated. Here, for the convenience of explanation, the time interval threshold is set to 2S. For example: Vehicle driving data 4-6 are continuous driving data. If the interval durations between vehicle driving data 4 and vehicle driving data 5, 6 are within 2S, then the driving direction angle differences between vehicle driving data 4 and vehicle driving data 4, 5, 6 are calculated as 0, 20, 30 respectively; the driving direction angle differences between vehicle driving data 5 and vehicle driving data 5, 6 are 0, 10 respectively. The driving direction angle difference between vehicle driving data 6 and vehicle driving data 6 is 0. This step is achieved by performing a Cartesian join intersection association on the original table data A and the original table data A' (the data content is exactly the same as that of table A) based on the sorting difference field (the same difference means a continuous driving), filtering out the data where the reporting time of A' < the reporting time of A and the reporting time of A' - the reporting time of A > the time, and then taking the angle difference to obtain the result. For example, if the sorting differences of vehicle driving data 1 and vehicle driving data 2 are the same, after performing a Cartesian association on the original table data A and the original table data A' based on the sorting difference, vehicle driving data 1 in table A is associated with vehicle driving data 1 and vehicle driving data 2 in table A' respectively, and vehicle driving data 2 in table A is associated with vehicle driving data 1 and vehicle driving data 2 in table A' respectively. Vehicle driving data 1 and 2 obtain 4 rows of data through the Cartesian product association, and then filter out the data where the reporting time of A' < the reporting time of A and the reporting time of A' - the reporting time of A > the time through the where condition, leaving 3 pieces of data, which are the associated data of vehicle driving data 1 in table A - vehicle driving data 1 in table A', vehicle driving data 1 in table A - vehicle driving data 2 in table A', and vehicle driving data 2 in table A - vehicle driving data 2 in table A'. That is, taking the angle of the corresponding vehicle driving data in table A' - the angle of the corresponding vehicle driving data in table A can obtain the angle difference.

[0142] In addition, through the foregoing steps, the driving direction angle difference between each vehicle driving data and any vehicle driving data within the interval time range can be obtained. The vehicle driving data is grouped using group by, and the maximum driving direction angle difference determined in each continuous driving data is obtained through the max function. Exemplarily, the driving direction angle difference between vehicle driving data 1 and adjacent vehicle driving data 2 can be obtained as 20, and the driving direction angle differences between vehicle driving data 1 and each vehicle driving data (vehicle driving data 1, vehicle driving data 2) during a continuous driving within the interval time range are 0 and 20 respectively. After grouping by vehicle driving data and taking the maximum driving direction angle difference, the maximum driving direction angle difference of vehicle driving data 1 is the maximum value 20 among 20, 0, and 20. Then, by judging the maximum driving direction angle difference of each vehicle driving data, those greater than the angle difference threshold can be determined as vehicle turning data. Exemplarily, the angle difference threshold can be set to 25 degrees. Therefore, vehicle driving data 4, 5, and 6 can be marked as vehicle turning data.

[0143] After determining the vehicle turning data, the continuous turning data can be further determined. The specific implementation process can be as follows:

[0144] The row_number sorting window function can be used to sort the vehicle driving data in ascending order according to the data collection time, and then the row_number sorting window function is used to group the vehicle driving data according to whether it is vehicle turning data and re-sort it in ascending order according to the data collection time. After obtaining two sorting values, the difference of the sorting is calculated. Among them, the records with the same difference and being the driving data of turning vehicles are continuous turning data.

[0145] Based on the same idea, the embodiments of this specification also provide a device corresponding to the above method. Figure 5 As shown in the structural schematic diagram of the vehicle turning data processing device provided by the embodiments of the present invention, Figure 5 The device provided in this embodiment may include:

[0146] An acquisition module 501, configured to acquire a vehicle driving data set, where the vehicle driving data set includes multiple vehicle driving data, and each vehicle driving data includes a data collection time.

[0147] A processing module 502, configured to sort the vehicle driving data set based on the data collection time to determine a first sorting field corresponding to each vehicle driving data.

[0148] The processing module 502 is further configured to group the vehicle driving data set based on a preset grouping rule, and sort the grouped vehicle driving data to determine a second sorting field corresponding to each vehicle driving data.

[0149] In this embodiment, the processing module 502 is further configured to:

[0150] Group the vehicle travel data set based on the travel speed corresponding to each vehicle to obtain a first vehicle travel data subset and a second vehicle travel data subset.

[0151] Sort the vehicle travel data in the first vehicle travel data subset and the second vehicle travel data subset respectively based on the data collection time, and determine a second sorting field corresponding to each vehicle travel data.

[0152] The processing module 502 is further configured to perform grouping processing on the vehicle travel data set according to the first sorting field and the second sorting field to obtain at least one continuous travel data group.

[0153] In this embodiment, the processing module 502 is further configured to:

[0154] Determine a first difference between the first sorting field and the second sorting field corresponding to each vehicle travel data.

[0155] Determine the vehicle travel data with a travel speed greater than the preset speed and the same first difference as a continuous travel data group.

[0156] The processing module 502 is further configured to, for each continuous travel data group, determine a travel direction angle difference corresponding to the vehicle travel data in the continuous travel data group, obtain a target travel direction angle difference that is not less than the preset angle difference threshold in the travel direction angle difference, and then set the vehicle travel data corresponding to the target travel direction angle difference as vehicle turning data.

[0157] In addition, in another embodiment, the processing module 502 is further configured to:

[0158] For each continuous travel data group, determine a travel direction angle difference corresponding to the vehicle travel data in the continuous travel data group to obtain a first travel direction angle difference set.

[0159] Obtain the largest travel direction angle difference from the first travel direction angle difference set to obtain a first maximum travel direction angle difference.

[0160] If the first maximum travel direction angle difference is not less than the preset angle difference threshold, set the vehicle travel data corresponding to the first maximum travel direction angle difference as vehicle turning data.

[0161] In addition, in another embodiment, the processing module 502 is further configured to:

[0162] For each of the continuous driving data groups, determine the interval duration between each vehicle driving data according to the data acquisition time included in each vehicle driving data in the continuous driving data group.

[0163] Obtain the target vehicle driving data with the interval duration within a preset duration threshold to obtain a target vehicle driving data set.

[0164] Determine the corresponding driving direction angle difference between each target vehicle driving data in the target vehicle driving data set to obtain a second driving direction angle difference set.

[0165] Obtain the maximum driving direction angle difference from the second driving direction angle difference set to obtain a second maximum driving direction angle difference.

[0166] If the second maximum driving direction angle difference is not less than a preset angle difference threshold, set the vehicle driving data corresponding to the second maximum driving direction angle difference as vehicle turning data.

[0167] In addition, in another embodiment, the processing module 502 is further configured to:

[0168] Group and sort the vehicle driving data set based on whether the vehicle driving data is vehicle turning data, and determine a third sorting field corresponding to each vehicle driving data.

[0169] Determine a second difference between a first sorting field and a third sorting field corresponding to each vehicle driving data.

[0170] Determine the vehicle driving data with the same second difference and being vehicle turning data as continuous turning data.

[0171] In this embodiment, the processing module 502 is further configured to:

[0172] Group the vehicle driving data set based on whether the vehicle driving data is vehicle turning data to obtain a third vehicle driving data subset and a fourth vehicle driving data subset.

[0173] Sort the vehicle driving data in the third vehicle driving data subset and the fourth vehicle driving data subset respectively based on the data acquisition time, and determine a third sorting field corresponding to each vehicle driving data.

[0174] The device provided by the embodiment of the present invention can implement the method of the above Figure 2 shown embodiment. The implementation principle and technical effects are similar, and will not be elaborated here.

[0175] Figure 6 is a schematic hardware structure diagram of a vehicle turning data processing device provided by an embodiment of the present invention. AsFigure 6 As shown in the figure, the device 600 provided in this embodiment includes at least one processor 601 and a memory 602. Among them, the processor 601 and the memory 602 are connected through a bus 603.

[0176] In the specific implementation process, at least one processor 601 executes the computer-executable instructions stored in the memory 602, so that at least one processor 601 executes the method in the above method embodiment.

[0177] For the specific implementation process of the processor 601, reference can be made to the above method embodiment. The implementation principle and technical effects are similar, and will not be elaborated here in this embodiment.

[0178] In the above Figure 6 In the shown embodiment, it should be understood that the processor may be a central processing unit (English: Central Processing Unit, abbreviated: CPU), or other general-purpose processors, digital signal processors (English: Digital Signal Processor, abbreviated: DSP), application-specific integrated circuits (English: Application SpecificIntegrated Circuit, abbreviated: ASIC), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly embodied as being executed and completed by a hardware processor, or executed and completed by a combination of hardware and software modules in the processor.

[0179] The memory may include high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one disk memory.

[0180] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0181] This embodiment of the present invention also provides a computer-readable storage medium, in which computer-executable instructions are stored. When the processor executes the computer-executable instructions, the vehicle turning data processing method in the above method embodiment is implemented.

[0182] An embodiment of the present invention also provides a computer program product, including a computer program which, when executed by a processor, implements the vehicle turning data processing method as described above.

[0183] The above-mentioned computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk or an optical disc. The readable storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0184] An exemplary readable storage medium is coupled to the processor, enabling the processor to read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in a device.

[0185] Those of ordinary skill in the art can understand that all or part of the steps to implement the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including those of the above method embodiments; and the foregoing storage medium includes various media that can store program codes, such as ROM, RAM, magnetic disks or optical discs.

[0186] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for processing vehicle turning data, characterized in that, Including: Obtain a vehicle driving dataset, where the vehicle driving dataset includes a plurality of vehicle driving data, and each vehicle driving data contains a data acquisition moment; Sort the vehicle driving dataset based on the data acquisition moment, and determine a first sorting field corresponding to each vehicle driving data; Group the vehicle driving dataset based on a preset grouping rule, and sort the grouped vehicle driving data to determine a second sorting field corresponding to each vehicle driving data; Perform a grouping process on the vehicle driving dataset according to the first sorting field and the second sorting field to obtain at least one continuous driving data group; For each continuous driving data group, determine the driving direction angle difference corresponding to each vehicle driving data in the continuous driving data group, obtain a target driving direction angle difference that is not less than a preset angle difference threshold in the driving direction angle difference, and then set the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data; Group the vehicle driving dataset based on whether the vehicle driving data is vehicle turning data to obtain a third vehicle driving data subset and a fourth vehicle driving data subset; Sort the vehicle driving data in the third vehicle driving data subset and the fourth vehicle driving data subset respectively based on the data acquisition moment, and determine a third sorting field corresponding to each vehicle driving data; Determine a second difference between the first sorting field and the third sorting field corresponding to each vehicle driving data; Determine the vehicle driving data with the same second difference and being vehicle turning data as continuous turning data.

2. The method according to claim 1, characterized in that, If each vehicle driving data includes the driving speed corresponding to the vehicle, then the grouping the vehicle driving dataset based on a preset grouping rule, and sorting the grouped vehicle driving data to determine a second sorting field corresponding to each vehicle driving data includes: Group the vehicle driving dataset based on the driving speed corresponding to each vehicle to obtain a first vehicle driving data subset and a second vehicle driving data subset; Sort the vehicle driving data in the first vehicle driving data subset and the second vehicle driving data subset respectively based on the data acquisition moment, and determine a second sorting field corresponding to each vehicle driving data.

3. The method according to claim 1, wherein If each vehicle driving data includes the driving speed corresponding to the vehicle, then the performing a grouping process on the vehicle driving dataset according to the first sorting field and the second sorting field to obtain at least one continuous driving data group includes: Determine a first difference between the first sorting field and the second sorting field corresponding to each vehicle driving data; Determine the vehicle driving data with the driving speed greater than a preset speed and the same first difference as a continuous driving data group.

4. The method according to claim 1, wherein For each of the continuous driving data groups, determining a corresponding driving direction angle difference between vehicle driving data in the continuous driving data group, obtaining a target driving direction angle difference that is not less than a preset angle difference threshold in the driving direction angle differences, and then setting the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data, includes: For each of the continuous driving data groups, determining a corresponding driving direction angle difference between vehicle driving data in the continuous driving data group to obtain a first set of driving direction angle differences; Obtaining the maximum driving direction angle difference from the first set of driving direction angle differences to obtain a first maximum driving direction angle difference; If the first maximum driving direction angle difference is not less than the preset angle difference threshold, setting the vehicle driving data corresponding to the first maximum driving direction angle difference as vehicle turning data.

5. The method according to claim 1, characterized in that, For each of the continuous driving data groups, determining a corresponding driving direction angle difference between vehicle driving data in the continuous driving data group, obtaining a target driving direction angle difference that is not less than a preset angle difference threshold in the driving direction angle differences, and then setting the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data, includes: For each of the continuous driving data groups, determining an interval duration between vehicle driving data based on the data acquisition time included in each vehicle driving data in the continuous driving data group; Obtaining target vehicle driving data with the interval duration within a preset duration threshold to obtain a target vehicle driving data set; Determining a corresponding driving direction angle difference between target vehicle driving data in the target vehicle driving data set to obtain a second set of driving direction angle differences; Obtaining the maximum driving direction angle difference from the second set of driving direction angle differences to obtain a second maximum driving direction angle difference; If the second maximum driving direction angle difference is not less than the preset angle difference threshold, setting the vehicle driving data corresponding to the second maximum driving direction angle difference as vehicle turning data.

6. A vehicle turning data processing device, characterized in that, Includes: An acquisition module, configured to acquire a vehicle driving data set, where the vehicle driving data set includes a plurality of vehicle driving data, and each vehicle driving data includes a data acquisition time; A processing module, configured to sort the vehicle driving data set based on the data acquisition time, and determine a first sorting field corresponding to each vehicle driving data; The processing module is further configured to group the vehicle driving data set based on a preset grouping rule, and sort the grouped vehicle driving data, and determine a second sorting field corresponding to each vehicle driving data; The processing module is further configured to perform a grouping process on the vehicle driving data set according to the first sorting field and the second sorting field to obtain at least one continuous driving data group; The processing module is further configured to, for each of the continuous driving data groups, determine the corresponding driving direction angle difference between the vehicle driving data in the continuous driving data group, obtain the target driving direction angle difference that is not less than a preset angle difference threshold in the driving direction angle difference, and then set the vehicle driving data corresponding to the target driving direction angle difference as vehicle turning data; group the vehicle driving data set based on whether the vehicle driving data is vehicle turning data to obtain a third vehicle driving data subset and a fourth vehicle driving data subset; sort the vehicle driving data in the third vehicle driving data subset and the fourth vehicle driving data subset respectively based on the data acquisition time to determine the third sorting field corresponding to each vehicle driving data; determine the second difference between the first sorting field and the third sorting field corresponding to each vehicle driving data; and determine the vehicle driving data with the same second difference and being vehicle turning data as continuous turning data.

7. A vehicle turning data processing device, characterized in that, Comprising: At least one processor and a memory; The memory stores computer execution instructions; The at least one processor executes the computer execution instructions stored in the memory, so that the at least one processor executes the vehicle turning data processing method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Computer execution instructions are stored in the computer-readable storage medium, and when the processor executes the computer execution instructions, the vehicle turning data processing method according to any one of claims 1 to 5 is implemented.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the vehicle turning data processing method according to any one of claims 1 to 5 is implemented.

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