Vehicle track data processing method, electronic equipment and storage medium

Abstract

The invention discloses a vehicle track data processing method, electronic equipment and a storage medium. The method comprises the following steps: acquiring track data of a target frame and N frames before and after the target frame; judging whether the target frame trajectory data is wrong or not according to each frame trajectory data and determining an error type when an error exists; if not, taking the next frame of the target frame as a new target frame, and returning to execute the step of obtaining the target frame and the track data of N frames before and after the target frame; and if yes, updating the target frame trajectory data based on the error type and each frame trajectory data, and returning to execute the step of judging whether the target frame trajectory data is wrong or not according to each frame trajectory data and determining the error type when the error exists. The correctness of the target frame trajectory data is judged through the trajectory data before and after the target frame, error data can be found, the trajectory data before and after the target frame is adjacent to the target frame trajectory data, the difference degree is small, and the error data in the target frame trajectory data can be effectively modified in an auxiliary mode.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle trajectory data processing, and in particular to a vehicle trajectory data processing method, electronic equipment and storage medium. Background Art

[0002] Urban transportation plays a vital role in social and economic development. With the rapid development of the economy and the continuous improvement of people's living standards, vehicles have become a means of transportation that every household can use. Its convenience and comfort have brought great convenience to people's lives, but the incidence of traffic congestion and traffic violations has also increased year by year, especially at complex traffic intersections, such as cross intersections, M-shaped intersections, or intersections with high driving difficulty. This poses a threat to travel safety and has attracted great attention from the transportation department. A lot of manpower and material resources have been invested in monitoring complex traffic intersections, analyzing and processing images and videos to achieve tasks such as detection, identification and tracking of target vehicles.

[0003] However, traffic intersections have problems such as large scene range, large number of vehicles, and serious occlusion between vehicles. Existing image or video acquisition equipment is also difficult to meet the requirements of large-scale and high-precision detection. Therefore, when monitoring vehicles at intersections, vehicle data is prone to missing or abnormal problems, which affects the tracking and detection of vehicles. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a vehicle trajectory data processing method to solve the problem of vehicle trajectory data processing.

[0005] In a first aspect, the present invention provides a vehicle trajectory data processing method, comprising:

[0006] Obtain the trajectory data of the target frame and N frames before and after the target frame;

[0007] Determine whether the target frame trajectory data is erroneous according to each frame trajectory data and determine the error type when an error exists;

[0008] If not, the frame after the target frame is used as a new target frame, and the process returns to the step of obtaining the trajectory data of the target frame and the N frames before and after the target frame;

[0009] If so, the target frame trajectory data is updated based on the error type and each frame trajectory data, and the process returns to the step of determining whether the target frame trajectory data is erroneous according to each frame trajectory data and determining the error type when an error exists.

[0010] In a second aspect, the present invention provides a vehicle trajectory data processing device, comprising:

[0011] A trajectory data acquisition module is used to acquire trajectory data of a target frame and N frames before and after the target frame;

[0012] The error judgment module is used to judge whether the target frame trajectory data is wrong according to each frame trajectory data and determine the error type when there is an error; if not, the content of the sliding module is executed; if so, the content of the correction module is executed;

[0013] The sliding module is used to take the next frame of the target frame as the new target frame and return the content of the execution trajectory data acquisition module;

[0014] The correction module is used to update the target frame trajectory data based on the error type and each frame trajectory data, and return the content of the error judgment module.

[0015] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle trajectory data processing method described in the first aspect of the present invention.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle trajectory data processing method described in the first aspect of the present invention when executed.

[0020] The vehicle trajectory data processing method provided by the embodiment of the present invention obtains the trajectory data of the target frame and each N frame before and after the target frame; judges whether the target frame trajectory data is wrong and determines the error type when there is an error according to the trajectory data of each frame; if not, the next frame of the target frame is used as the new target frame, and returns to execute the step of obtaining the trajectory data of the target frame and each N frame before and after the target frame; if so, the target frame trajectory data is updated based on the error type and the trajectory data of each frame, and returns to execute the step of judging whether the target frame trajectory data is wrong and determining the error type when there is an error according to the trajectory data of each frame. By judging the correctness of the target frame trajectory data by the trajectory data before and after the target frame, errors such as data missing and abnormality can be discovered in time, and the trajectory data before and after the target frame is adjacent to the target frame trajectory data, so the difference between the data is very small, so the target frame trajectory data can be updated based on the error type and the trajectory data of each frame, so as to avoid the occurrence of vehicle data missing or abnormal problems and affect the tracking detection of the vehicle. In addition, this scheme adopts a multi-round detection mechanism to check the errors in the target frame trajectory data, which can ensure that the errors of the target frame trajectory data are fully detected and corrected.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a flow chart of a vehicle trajectory data processing method provided by an embodiment of the present invention;

[0024] Figure 2 is a flow chart of a vehicle trajectory data processing method provided by an embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of a blind area data missing scenario provided by an embodiment of the present invention;

[0026] Figure 4 is a schematic diagram of a point data missing scenario provided by an embodiment of the present invention;

[0027] Figure 5 This is a schematic diagram of a target frame trajectory data coordinate error scenario provided by an embodiment of the present invention;

[0028] Figure 6 It is a schematic diagram of a target frame trajectory data deflection angle error scenario provided by an embodiment of the present invention;

[0029] Figure 7 is a structural schematic diagram of a vehicle trajectory data processing device provided by an embodiment of the present invention;

[0030] Figure 8 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0032] An embodiment of the present invention provides a vehicle trajectory data processing method, which can be applied to the case of processing vehicle trajectory data at a traffic intersection. The method can be executed by a vehicle trajectory data processing device, which can be implemented in the form of hardware and / or software, and the vehicle trajectory data processing device can be configured in an electronic device. It should be noted that the driving speed of the vehicle in the present invention must be within the prescribed urban driving speed range. For example, the urban driving speed range is within 60km / h, that is, the applicable scenario of the solution of the present invention is medium and low speed conditions.

[0033] Figure 1 A flow chart of a vehicle trajectory data processing method provided by an embodiment of the present invention, such as Figure 1 As shown, the vehicle trajectory data processing method includes:

[0034] S101, obtaining trajectory data of a target frame and N frames before and after the target frame.

[0035] A radar is installed at the traffic intersection, and the radar collection range is set as the target monitoring range. The trajectory data is the point cloud data of the vehicles in the traffic intersection collected by the laser radar. Optionally, the radar frequency is 25Hz, and the sampling period is 40ms. The sampling period is the time interval between two adjacent samples, that is, the interval between two adjacent frames of trajectory data. After collecting the point cloud data, the point cloud data must first be preprocessed to remove noise and clutter. Then, a connection relationship is established between the point cloud and the ground objects, and the ground objects are classified and extracted on this basis.

[0036] The trajectory data may include time, vehicle ID, lane, vehicle model information, vehicle speed, coordinates, and deflection angle, etc. The vehicle ID may be the vehicle license plate number, or a tag ID generated when a newly added vehicle is identified, or a combination of a license plate number and a tag ID.

[0037] It should be noted that one frame of trajectory data usually includes trajectory data of multiple vehicles at the same time. For example, in one frame of trajectory data obtained at time A, the number of vehicle IDs (vehicles) is 80, and in one frame of trajectory data obtained at time B, the number of vehicle IDs (vehicles) is 120. The time, lane, vehicle model information, speed, coordinates, and deflection angle corresponding to each vehicle ID are the data associated with the vehicle ID.

[0038] N is a positive integer greater than or equal to 1, the target frame is the Tth frame, the N frames before the target frame are the TNth frame, the TN-1th frame... the T-1th frame, and the N frames after the target frame are the T+1th frame... the T+N-1th frame, and the T+Nth frame. The purpose of obtaining the trajectory data of the target frame and the N frames before and after the target frame is that the trajectory data of the N frames before and after the target frame are the trajectory data adjacent to the trajectory data of the target frame. Under medium and low speed conditions, the difference between the adjacent trajectory data and the trajectory data of the target frame is very small. Therefore, on the one hand, the correctness of the trajectory data of the target frame can be checked based on the adjacent trajectory data, and on the other hand, the erroneous trajectory data of the target frame can be corrected based on the adjacent trajectory data.

[0039] Optionally, 1≤N≤3. The purpose of this setting is that at most the trajectory data of 3 frames before and after the target frame can be obtained to update the target frame trajectory data. Considering that the vehicle's coordinates, deflection angle, lane, speed, etc. may change at any time, the difference between trajectory data with a large frame number difference is also large. If trajectory data with a large difference is used to correct the target frame trajectory data, it will bring a large error and cannot achieve the purpose of correcting the error of the target frame trajectory data. Therefore, in order to reduce the error, the value of N is minimized under the premise of correcting the error of the target frame trajectory data.

[0040] S102: judging whether the target frame trajectory data is erroneous according to each frame trajectory data and determining the error type when an error exists.

[0041] If not, execute S103, and if so, execute S104.

[0042] The trajectory data may include time, vehicle ID, lane, vehicle model information, speed, coordinates and deflection angle, etc. When data is missing, it is usually because at least one vehicle ID in the target frame trajectory data is lost. When data anomalies occur, it is usually because there is an error in the posture (coordinates and deflection angle) corresponding to a vehicle ID in the target frame trajectory data. This is because there may be blind spots during radar detection, and radar monitoring is susceptible to interference. In general, it is determined whether the target frame trajectory data is wrong based on each frame trajectory data, specifically to detect the data integrity and posture correctness of the target frame trajectory data.

[0043] Regarding blind spots, if affected by obstruction or angle problems, the electromagnetic waves emitted by the radar cannot reach the target vehicle to be detected, and the trajectory data of the target vehicle cannot be detected, that is, there is a radar detection blind spot. For example, in one case, there is a green belt or bridge pier at the traffic intersection, and the range where the green belt or bridge pier is located may form a detection blind spot. In another case, when a larger vehicle blocks a smaller vehicle, when the smaller vehicle is taken as the detection object, the area where the larger vehicle is located is the detection blind spot, which will cause the trajectory data of the smaller vehicle to be missing.

[0044] Regarding the susceptibility of radar to interference, radar signals are easily affected by various electromagnetic interferences, weather conditions, etc., resulting in false alarms or missed alarms, reducing the accuracy of reconnaissance, and easily resulting in erroneous detection results, that is, data such as vehicle speed and posture are prone to errors.

[0045] The trajectory data of each N frame before and after the target frame are the trajectory data adjacent to the trajectory data of the target frame. The difference between the adjacent trajectory data and the trajectory data of the target frame is small, so the correctness of the trajectory data of the target frame can be verified based on the adjacent trajectory data. Before using the trajectory data of each frame for analysis, it is usually necessary to preprocess the trajectory data, which includes steps such as data cleaning, standardization, and normalization to ensure the quality and consistency of the data.

[0046] Specifically, multiple specified types of trajectory features can be extracted from each frame trajectory data; each type of trajectory feature is clustered, and specifically, the density of the trajectory feature can be calculated to form a cluster. When the trajectory feature of the target frame is isolated or located in a low-density area, it means that the trajectory feature of the target frame is abnormal, that is, the trajectory data of the target frame is abnormal. When the trajectory feature of the target frame is missing, it can be said that the trajectory data of the target frame is missing.

[0047] S103: Use the frame following the target frame as a new target frame.

[0048] When there is no error in the target frame trajectory data, there is no need to update (correct) the target frame trajectory data, and the next frame data can be tested. After executing S103, the process returns to execute S101: obtaining the trajectory data of the target frame and each of the N frames before and after the target frame. In this way, the correctness of each frame trajectory data can be tested.

[0049] It can be known that the trajectory data before the target frame trajectory data are all correct trajectory data, specifically, they may be trajectory data that is determined to be correct for the first time, or trajectory data that is updated and determined to be correct for the last time.

[0050] S104: Update the target frame trajectory data based on the error type and each frame trajectory data.

[0051] When there is an error in the target frame trajectory data, the difference between the adjacent trajectory data and the target frame trajectory data is small, so the target frame trajectory data can be updated in combination with other adjacent frame trajectory data before and after the target frame. Specifically, when the error type is data missing or data abnormal, since the trajectory data before the target frame are all correct trajectory data, the trajectory data before the target frame can be used to fill the target frame trajectory data with data to achieve the purpose of correction. It is also possible to combine the mean of the X (1≤X≤N) frames before the target frame and the X frames after to obtain the missing or abnormal values ​​in the target frame trajectory data. It is also possible to combine the mean of the Y (1≤Y≤N) frames before the target frame and the frame after to obtain the missing or abnormal values ​​in the target frame trajectory data. There are many methods for updating the wrong target trajectory data, and the above description is only used as an example. Specifically, when the trajectory data of a certain vehicle ID is missing or wrong, it is necessary to correct and update it according to the trajectory data of the same vehicle ID in other frames.

[0052] After executing S104, the process returns to execute S102: judging whether the target frame trajectory data is wrong according to each frame trajectory data and determining the error type when an error exists. The function of returning to execute S102 is to:

[0053] The vehicle trajectory data processing method provided by the embodiment of the present invention obtains the trajectory data of the target frame and each N frame before and after the target frame; judges whether the target frame trajectory data is wrong and determines the error type when there is an error according to the trajectory data of each frame; if not, the next frame of the target frame is used as the new target frame, and returns to execute the step of obtaining the trajectory data of the target frame and each N frame before and after the target frame; if so, the target frame trajectory data is updated based on the error type and the trajectory data of each frame, and returns to execute the step of judging whether the target frame trajectory data is wrong and determining the error type when there is an error according to the trajectory data of each frame. By judging the correctness of the target frame trajectory data by the trajectory data before and after the target frame, errors such as data missing and abnormality can be discovered in time, and the trajectory data before and after the target frame is adjacent to the target frame trajectory data, so the difference between the data is very small, so the target frame trajectory data can be updated based on the error type and the trajectory data of each frame, so as to avoid the occurrence of vehicle data missing or abnormal problems and affect the tracking detection of the vehicle. In addition, this scheme adopts a multi-round detection mechanism to check the errors in the target frame trajectory data, which can ensure that the errors of the target frame trajectory data are fully detected and corrected.

[0054] In an optional embodiment, the vehicle trajectory data processing method further includes: determining, for the vehicle ID in the trajectory data of the target frame and N frames after the target frame, whether the vehicle ID is a newly added vehicle ID; if so, marking the entry time of the newly added vehicle ID.

[0055] In an optional embodiment, the vehicle ID in the trajectory data is marked with the first appearance time, and the vehicle trajectory data processing method further includes: for each frame of trajectory data, the duration of each vehicle ID is calculated according to the current time and the first appearance time of each vehicle ID; the vehicle ID whose duration reaches the preset duration threshold is regarded as an invalid vehicle ID; the invalid vehicle ID and the data associated with the invalid vehicle ID are deleted from each frame of trajectory data. The vehicle corresponding to the trajectory data with a longer duration usually has left the traffic intersection, so there is no need to continue monitoring the trajectory data of the vehicle. At this time, the vehicle ID of the vehicle is an invalid vehicle ID and the corresponding data is deleted. The advantage of such a setting is that the trajectory data with a longer duration can be cleaned up to improve the processing efficiency of the trajectory data and reduce resource occupation. The preset duration threshold is the normal driving duration of the vehicle in the traffic intersection (including driving duration and parking duration), which can be set according to the size of the traffic intersection, the historical vehicle stay duration, traffic flow, etc. For example, the preset duration threshold can be 2 minutes.

[0056] In an optional embodiment, the trajectory data includes vehicle ID, coordinates and deflection angle, Figure 2 is a flow chart of a method for error detection of target frame trajectory data, such as Figure 2As shown, S102: judging whether the target frame trajectory data is erroneous according to each frame trajectory data and determining the error type when an error occurs, including:

[0057] S21, calculating the intersection of the vehicle ID of the previous frame trajectory data of the target frame and the trajectory data of the next N frames of the target frame to obtain the intersection vehicle ID.

[0058] The target frame is the Tth frame, and the intersection vehicle ID is the vehicle ID that appears in the trajectory data of the T-1th frame and in any frame from the T+1th frame to the T+Nth frame.

[0059] S22: Determine whether all the intersection vehicle IDs exist in the target frame trajectory data.

[0060] If yes, execute S25, if no, execute S24.

[0061] According to the driving rules of vehicles at traffic intersections, under normal circumstances, the data associated with each vehicle ID is continuous. If the intersection vehicle IDs all exist in the target frame trajectory data, it means that there is no data missing problem in the target frame trajectory data. Then, the correctness of the position and posture of each vehicle ID in the target frame trajectory data is further verified, that is, S25 is executed.

[0062] If any intersection vehicle ID does not exist in the target frame trajectory data, it indicates that there is a data missing problem in the target frame trajectory data, and the data missing type in the target frame trajectory data is further verified, that is, S24 is executed.

[0063] S23, taking the intersection vehicle ID that does not exist in the target frame trajectory data as the target missing vehicle ID.

[0064] Since the intersection vehicle ID appears both before and after the target frame trajectory data, but does not appear in the target frame trajectory data, it means that the data associated with the vehicle ID is missing in the target frame trajectory data. In this case, the intersection vehicle ID is used as the target missing vehicle ID.

[0065] It should be noted that, when there are target missing vehicle IDs, the number of target missing vehicle IDs may be one or more.

[0066] S24, determining the error type of the target frame trajectory data according to the appearance position of the target missing vehicle ID in the trajectory data of the next N frames of the target frame.

[0067] Specifically, it includes: judging whether the target missing vehicle ID appears in the trajectory data of the next frame of the target frame; if so, determining that the error type of the target frame trajectory data is point data missing; if not, determining that the error type of the target frame trajectory data is blind area data missing. That is, when the target missing vehicle ID is missing in two consecutive frames of trajectory data, it is blind area data missing, and when the target missing vehicle ID is missing in only one frame (target frame) of trajectory data, it is point data missing.

[0068] Figure 3 A schematic diagram of a blind area data missing scenario is shown in Figure 3 As shown in part A, N=2, the target missing vehicle ID is C2, the Tth frame is the target frame, the trajectory data of the Tth frame and the T+1th frame do not include the target missing vehicle ID (C2), and the error type of the target frame trajectory data is blind area data missing.

[0069] Figure 4 A schematic diagram of a point data missing scenario is shown in Figure 2. Figure 4 As shown in part A, N=2, the target missing vehicle ID is C2, the Tth frame is the target frame, the trajectory data of the Tth frame does not include the target missing vehicle ID (C2), but the trajectory data of the T+1th frame includes the target missing vehicle ID, then the error type of the target frame trajectory data is point data missing.

[0070] S25 . For each vehicle ID of the target frame, determine whether the target frame trajectory data is erroneous and the error type when an error is determined based on the coordinates and deflection angles of the target frame and the frames before and after the target frame.

[0071] by Figure 3 Taking part A as an example, the Tth frame is the target frame, and the coordinates and deflection angles corresponding to the vehicle ID in the trajectory data of the T-1th frame, the Tth frame, and the T+1th frame are obtained, that is, three frames of pose data.

[0072] Optionally, when verifying the correctness of the position and posture of the vehicle ID, first determine whether the coordinates corresponding to the vehicle ID in the target frame trajectory data are wrong. If not, further determine whether the deflection angle corresponding to the vehicle ID in the target frame trajectory data is wrong.

[0073] In one example, determining whether the coordinates corresponding to a vehicle ID in target frame trajectory data are wrong includes: for each vehicle ID in the target frame, obtaining the first coordinate of a previous frame of the target frame and the second coordinate of the target frame, and obtaining the speed of the vehicle with the vehicle ID in the target frame; calculating the spatial distance between the first coordinate and the second coordinate; calculating the theoretical displacement distance of the vehicle with the vehicle ID according to the speed of the vehicle in the target frame; determining whether the spatial distance is greater than the theoretical displacement distance; if so, determining that the error type of the target frame trajectory data is a coordinate error.

[0074] The theoretical displacement distance can be calculated based on the speed of the vehicle in the target frame and the radar acquisition cycle. For example, the speed of the vehicle in the target frame is 60km / h, and the radar acquisition cycle is 40ms. The distance traveled by the vehicle in the interval between two frames is 0.65m, and the theoretical displacement distance can be set to 0.65m. Since the data before the target frame are all correct data, the coordinates of the previous frame of the target frame are used as the reference point for the displacement distance of the vehicle in the target frame to ensure the accuracy of data calculation. When the spatial distance between the coordinates of the vehicle of the vehicle ID in the target frame and its coordinates in the previous frame of the target frame is greater than the theoretical displacement distance, it can be determined that the coordinates of the vehicle ID in the target frame are wrong, that is, the error type of the target frame trajectory data is a coordinate error.

[0075] Figure 5 This is a schematic diagram of a target frame trajectory data coordinate error scenario, such as Figure 5 As shown in the before part, A, B, and C are the coordinates corresponding to the trajectory data of the T-2, T-1, and T frames respectively. The T frame is the target frame, then B is the first coordinate of the T-1 frame, and C is the second coordinate of the T frame. Figure 5 It can be seen that the spatial distance d2 between BC is much larger than the spatial distance d1 between AB. This phenomenon is usually abnormal, that is, the data is wrong. Assume Figure 5 If d2 in is greater than the theoretical displacement distance, the error type of the trajectory data of the Tth frame is coordinate error.

[0076] In one example, determining a deflection angle error corresponding to a vehicle ID in target frame trajectory data includes: respectively calculating a difference in deflection angle between a target frame and a frame before the target frame, and a difference in deflection angle between a frame after the target frame and the target frame, to obtain a first angle difference and a second angle difference; determining whether the difference between the first angle difference and the second angle difference is within a preset difference range; if not, determining that the error type of the target frame trajectory data is a deflection angle error.

[0077] When a vehicle is driving at a traffic intersection, it is in a medium or low speed condition. Then, each frame of trajectory data of the same vehicle gradually changes over time, that is, the difference in the deflection angles in the trajectory data adjacent or close to each other at the time of acquisition is also small. It can be seen that when a vehicle is driving at a traffic intersection, the change amplitude of the deflection angles of adjacent frames is also usually within a certain range. Then, the difference between the deflection angle difference between the target frame and the previous frame (the first angle difference) and the deflection angle difference between the next frame and the target frame (the second angle difference) also needs to be within a preset difference range. Exemplarily, the difference range is -120° to 120°. Therefore, it is possible to determine whether the target frame trajectory data has a deflection angle error by the degree of difference in the deflection angle change between the first deflection angle, the second deflection angle, and the third deflection angle.

[0078] Figure 6This is a schematic diagram of a target frame trajectory data deflection angle error scenario, such as Figure 6 As shown in the before part, A, B, and C are the coordinates corresponding to the T-1, T, and T+1 frame trajectory data respectively, and the deflection angles are 30°, 100°, and 20° respectively. The T frame is the target frame, the deflection angle difference between BA (the first angle difference) is 70°, and the deflection angle difference between CB (the second angle difference) is -80°. Assuming that the difference range is -120° to 120°, the difference between the two angle differences is not within the difference range, and the deflection angle corresponding to the vehicle ID in the target frame trajectory data is wrong.

[0079] In an optional embodiment, the target frame trajectory data is updated based on the error type and each frame trajectory data, including: if the error type is point data missing, the target frame trajectory data is filled with data according to the previous frame or next frame trajectory data of the target frame; if the error type is blind area data missing, the target frame trajectory data is filled with data according to the previous frame trajectory data of the target frame.

[0080] When point data is missing, the trajectory data of the previous frame or the next frame of the target frame are filled with data, so the trajectory data of the target frame can be filled with data according to the trajectory data of the previous frame or the next frame of the target frame. Considering that the trajectory data between the target frames is verified or updated, it is preferred that Figure 4 As shown in part B, the target frame trajectory data can be filled with data according to the previous frame trajectory data of the target frame; based on the same reason, if the error type is blind area data missing, such as Figure 3 As shown in part B, the trajectory data of the previous frame of the target frame can also be used to fill the trajectory data of the target frame. In addition, if the error type is blind area data missing, since the next frame of the target frame is also data missing, the trajectory data of the previous frame of the target frame can also be used to fill the trajectory data of the next frame of the target frame.

[0081] In an optional embodiment, N≥2, the Tth frame is taken as the target frame, and the target frame trajectory data is updated based on the error type and the trajectory data of each frame, including: if the error type is a coordinate error, for the target frame vehicle ID associated with the erroneous coordinates, the theoretical displacement distance of the Tth frame, the coordinates of the T-1th frame, and the deflection angles of other frames except the T-1th frame and the Tth frame are obtained to obtain an auxiliary deflection angle; the coordinate range of the coordinates of the Tth frame is set according to the theoretical displacement distance corresponding to the Tth frame and the coordinates of the T-1th frame; the erroneous coordinates of the Tth frame are modified according to the coordinate range and the auxiliary deflection angle; if the error type is a deflection angle error, the erroneous deflection angle of the Tth frame is modified according to the coordinates in the trajectory data of each frame.

[0082] When the coordinates are wrong, the wrong coordinates in the target frame trajectory data are modified according to the distance theoretical value, that is, for the same vehicle (ID), the distance difference between the coordinates of the target frame and the coordinates of the previous frame is limited to within the theoretical displacement distance, then the coordinates of the target frame after correction can be multiple, such as Figure 5 As shown in the after part of , the coordinate range is the point on the circle with the coordinate B of the previous frame (T-1 frame) as the center and the theoretical displacement distance as the radius. When the corrected coordinates of the target frame are located at different points, the deflection angle corresponding to the coordinates is also different. Therefore, the deflection angle of the target frame can be limited first, and the coordinates can be determined by combining the deflection angle. The deflection angles of other frames except the T-1 frame and the T frame are used as auxiliary deflection angles. The auxiliary deflection angles represent the characteristics of the deflection angles of the vehicle with the vehicle ID in the vicinity of the target frame. The vehicle belongs to the medium and low speed vehicle condition and the radar acquisition cycle is also short. The deflection angle of the target frame is similar to the characteristics of these auxiliary deflection angles. Therefore, the deflection angle of the target frame can be determined by combining the auxiliary deflection angles. Among them, since the coordinates of the T frame are not determined, the deflection angle of the T-1 frame is also not determined, and it cannot be used to calculate the deflection angle of the T frame.

[0083] Specifically, the erroneous coordinates in the Tth frame are modified according to the coordinate range and the auxiliary deflection angle, including: calculating the mean of the auxiliary deflection angles to obtain the average deflection angle; obtaining a vector with the coordinates of the T-1th frame as the starting point and the angle with the deflection angle reference direction as the average deflection angle as the first vector; and modifying the corresponding erroneous coordinates in the Tth frame according to the intersection of the first vector and the coordinate range.

[0084] like Figure 5 As shown in the after part of , N = 2, then the trajectory data before and after the T-th frame are 2 frames respectively, and the auxiliary deflection angles are the T-2 frame, T+1 frame and T+2 frame respectively, α1, α2, α3, and the average value of the three auxiliary deflection angles is calculated to obtain the average deflection angle αt. The vector with the coordinates of the T-1th frame as the starting point and the angle with the deflection angle reference direction as the average deflection angle αt is the first vector H. The intersection of the first vector H and the coordinate range is the corrected coordinate.

[0085] Specifically, the erroneous deflection angle in the target frame trajectory data is modified according to the coordinates in the trajectory data of each frame, including: for the vehicle ID associated with the erroneous deflection angle, obtaining the coordinates of the Tth frame and the M frames before and after the Tth frame to obtain the reference coordinates, M≤N; connecting the reference coordinates in sequence to obtain a plurality of second vectors; determining the angle between each second vector and the reference direction of the deflection angle, and taking the average of all the angles as the deflection angle of the target frame vehicle ID in the Tth frame.

[0086] like Figure 6As shown in the after part of , M = 1, the Tth frame is the target frame, the trajectory data before and after the Tth frame are 1 frame respectively, the reference coordinates are A, B, C, D respectively, assuming that the deflection angles of AB, BC, and CD are 30°, 25°, and 20° respectively, and the average value of the three reference deflection angles is 25°, so the deflection angle of the vehicle ID in the Tth frame is 25°.

[0087] Of course, when N=3, M can also be 2 or 3. In addition, the coordinates of the previous frame and the next two frames of the target frame can also be taken as reference coordinates. The specific setting is based on actual needs, and the present invention is not limited to this.

[0088] In general, the vehicle trajectory data processing method in the present invention is as follows (without corresponding figures):

[0089] A1. Obtain trajectory data of the target frame and N frames before and after the target frame.

[0090] A2. Determine whether there is data missing in the target frame.

[0091] If there is missing data, execute A3 to analyze the specific type of missing data. If there is no missing data, execute A4 to analyze the correctness of the coordinates.

[0092] A3. Analyze the specific types of missing data and obtain the error types when data is missing.

[0093] A6 is executed after A3 to fill in data.

[0094] A4. Analyze the coordinate correctness of the target frame to determine whether the coordinates are correct.

[0095] If the coordinates are correct, execute A5 to analyze the deflection angle. If the coordinates are wrong, execute A6 to correct the coordinates.

[0096] A5. Analyze the correctness of the deflection angle of the target frame to determine whether the deflection angle is correct.

[0097] If the deflection angle is correct, execute A7; if the deflection angle is incorrect, execute A6 to correct the deflection angle.

[0098] A6. Correct the target frame trajectory data according to the error type and each frame trajectory data, and return to execute A2.

[0099] A7. Determine if the target frame trajectory data is correct or has been corrected, and then go to the next frame trajectory data.

[0100] By detecting and correcting (or filling) each frame of trajectory data from the aspects of data integrity and posture correctness, and performing layer-by-layer detection and correction on the trajectory data, it can be ensured that the problems of data missing and data anomalies are effectively solved.

[0101] Corresponding to the vehicle trajectory data processing method in the present invention, the present invention also provides a vehicle trajectory data processing device, Figure 7 FIG. 1 is a schematic diagram of the structure of a vehicle trajectory data processing device. Figure 7 As shown, the vehicle trajectory data processing device includes:

[0102] The trajectory data acquisition module 701 is used to acquire the trajectory data of the target frame and N frames before and after the target frame;

[0103] The error judgment module 702 is used to judge whether the target frame trajectory data is wrong according to each frame trajectory data and determine the error type when there is an error; if not, the content of the sliding module is executed; if so, the content of the correction module is executed;

[0104] The sliding module 703 is used to take the next frame of the target frame as a new target frame and return the content of the execution trajectory data acquisition module;

[0105] The correction module 704 is used to update the target frame trajectory data based on the error type and each frame trajectory data, and return the content of the error judgment module.

[0106] Optionally, the trajectory data includes vehicle ID, coordinates and deflection angle, and the error judgment module 702 includes:

[0107] The intersection vehicle ID calculation submodule is used to calculate the intersection of the vehicle ID of the previous frame trajectory data of the target frame and the next N frames trajectory data of the target frame to obtain the intersection vehicle ID;

[0108] The intersection vehicle ID judgment submodule is used to judge whether the intersection vehicle IDs all exist in the target frame trajectory data; if not, the content of the target missing vehicle ID determination submodule is executed; if so, the content of the second error type judgment submodule is executed;

[0109] A target missing vehicle ID determination submodule is used to use the intersection vehicle ID that does not exist in the target frame trajectory data as the target missing vehicle ID;

[0110] A first error type determination submodule is used to determine the error type of the target frame trajectory data according to the appearance position of the target missing vehicle ID in the trajectory data of the next N frames of the target frame;

[0111] The second error type judgment submodule is used to judge whether the target frame trajectory data is wrong and determine the error type when an error occurs according to the coordinates and deflection angles of the target frame and the frames before and after the target frame for each vehicle ID of the target frame.

[0112] Optionally, the first error type judgment submodule includes:

[0113] A position determination unit, used to determine whether the target missing vehicle ID appears in the trajectory data of the next frame of the target frame; if so, the content of the point data missing determination unit is executed; if not, the content of the blind area data missing determination unit is executed;

[0114] a point data missing determination unit, used to determine that the error type of the target frame trajectory data is point data missing;

[0115] The blind area data missing unit is used to determine that the error type of the target frame trajectory data is the blind area data missing.

[0116] Optionally, the correction module 704 includes:

[0117] A first correction submodule, configured to fill the target frame trajectory data with data according to the previous frame or next frame trajectory data of the target frame if the error type is point data missing;

[0118] The second correction submodule is used to fill the target frame trajectory data with data according to the previous frame trajectory data of the target frame if the error type is blind area data missing.

[0119] Optionally, the trajectory data also includes speed, and the second error type judgment submodule includes:

[0120] A data acquisition unit, for acquiring, for each vehicle ID of a target frame, a first coordinate of a previous frame of the target frame and a second coordinate of the target frame, and acquiring a speed of the vehicle of the vehicle ID in the target frame;

[0121] A spatial distance calculation unit, used to calculate the spatial distance between the first coordinate and the second coordinate;

[0122] A theoretical displacement distance calculation unit, used for calculating the theoretical displacement distance of the vehicle with the vehicle ID according to the speed of the vehicle in the target frame;

[0123] A distance judgment unit, used to judge whether the spatial distance is greater than the theoretical displacement distance; if so, the contents of the coordinate error determination unit are executed; if not, the contents of the angle difference calculation unit are executed;

[0124] A coordinate error determination unit, used to determine that the error type of the target frame trajectory data is a coordinate error;

[0125] An angle difference calculation unit is used to calculate the difference between the deflection angle of the target frame and the frame before the target frame, and the difference between the deflection angle of the frame after the target frame and the target frame, to obtain a first angle difference and a second angle difference;

[0126] An angle difference determination unit, used to determine whether the difference between the first angle difference and the second angle difference is within a preset difference range; if not, executing the content of the deflection angle error determination unit;

[0127] The deflection angle error determination unit is used to determine that the error type of the target frame trajectory data is a deflection angle error.

[0128] Optionally, N≥2, the Tth frame is taken as the target frame, and the correction module 704 further includes:

[0129] an auxiliary deflection angle determination submodule, for obtaining, if the error type is a coordinate error, the theoretical displacement distance of the Tth frame, the coordinates of the T-1th frame, and the deflection angles of other frames except the T-1th frame and the Tth frame for the vehicle ID associated with the erroneous coordinates, to obtain an auxiliary deflection angle;

[0130] A coordinate range determination submodule, used for setting the coordinate range of the coordinates of the Tth frame according to the theoretical displacement distance corresponding to the Tth frame and the coordinates of the T-1th frame;

[0131] A coordinate correction submodule, used for modifying the erroneous coordinates in the Tth frame according to the coordinate range and the auxiliary deflection angle;

[0132] The deflection angle correction submodule is used to modify the erroneous deflection angle of the Tth frame according to the coordinates in the trajectory data of each frame if the error type is a deflection angle error.

[0133] Optional, coordinate correction submodule, including:

[0134] an average deflection angle calculation unit, used to calculate the average of the auxiliary deflection angles to obtain an average deflection angle;

[0135] A first vector determination unit is used to obtain a vector with the coordinates of the T-1th frame as a starting point and an angle between the vector and the deflection angle reference direction as the average deflection angle as a first vector;

[0136] A coordinate correction unit is used to modify the corresponding erroneous coordinates in the Tth frame according to the intersection point of the first vector and the coordinate range.

[0137] Optional, deflection angle correction submodule, including:

[0138] A reference coordinate acquisition unit is used to acquire the coordinates of the Tth frame and the M frames before and after the Tth frame for the vehicle ID associated with the wrong deflection angle, and obtain the reference coordinates, M≤N;

[0139] A second vector acquisition unit, used for sequentially connecting the reference coordinates to obtain a plurality of second vectors;

[0140] An angle determination unit, used to determine the angle between each of the second vectors and a deflection angle reference direction;

[0141] The deflection angle correction unit is used to take the average of all angles as the deflection angle of the target frame vehicle ID in the Tth frame.

[0142] The vehicle trajectory data processing device provided in the embodiment of the present invention can execute the vehicle trajectory data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0143] Figure 8 A schematic diagram of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0144] like Figure 8 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0145] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0146] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 performs the various methods and processes described above, such as the vehicle trajectory data processing method.

[0147] In some embodiments, the vehicle trajectory data processing method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the vehicle trajectory data processing method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the vehicle trajectory data processing method in any other appropriate manner (e.g., by means of firmware).

[0148] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0149] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0150] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0151] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0152] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0153] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0154] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0155] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle trajectory data processing method, characterized in that: include: Obtain the trajectory data of the target frame and N frames before and after the target frame; Determine whether the target frame trajectory data is erroneous according to each frame trajectory data and determine the error type when an error exists; If not, the frame after the target frame is used as a new target frame, and the process returns to the step of obtaining the trajectory data of the target frame and the N frames before and after the target frame; If so, the target frame trajectory data is updated based on the error type and each frame trajectory data, and the process returns to execute the step of determining whether the target frame trajectory data is erroneous according to each frame trajectory data and determining the error type when an error exists.

2. The vehicle trajectory data processing method according to claim 1, characterized in that: The trajectory data includes vehicle ID, coordinates and deflection angle. Judging whether the target frame trajectory data is wrong and the error type when an error occurs according to each frame trajectory data includes: Calculate the intersection of the vehicle ID of the trajectory data of the previous frame of the target frame and the trajectory data of the next N frames of the target frame to obtain the intersection vehicle ID; Determine whether the intersection vehicle IDs all exist in the target frame trajectory data; If not, the intersection vehicle ID that does not exist in the target frame trajectory data is used as the target missing vehicle ID; Determine the error type of the target frame trajectory data according to the appearance position of the target missing vehicle ID in the trajectory data of the next N frames of the target frame; If so, for each vehicle ID of the target frame, determine whether the target frame trajectory data is erroneous and the error type when an error is determined based on the coordinates and deflection angles of the target frame and the frames before and after the target frame.

3. The vehicle trajectory data processing method according to claim 2, characterized in that: Determining the error type of the target frame trajectory data according to the appearance position of the target missing vehicle ID in the trajectory data of the next N frames of the target frame includes: Determine whether the target missing vehicle ID appears in the trajectory data of the next frame of the target frame; If so, it is determined that the error type of the target frame trajectory data is point data missing; If not, it is determined that the error type of the target frame trajectory data is blind area data missing.

4. The vehicle trajectory data processing method according to claim 3, characterized in that: The target frame trajectory data is updated based on the error type and each frame trajectory data, including: If the error type is point data missing, then fill the target frame trajectory data with data according to the previous frame or next frame trajectory data of the target frame; If the error type is missing blind area data, the target frame trajectory data is filled with data according to the previous frame trajectory data of the target frame.

5. The vehicle trajectory data processing method according to claim 2, characterized in that: The trajectory data also includes speed. For each vehicle ID of the target frame, the target frame trajectory data is judged to be wrong and the error type when an error is determined based on the coordinates and deflection angles of the target frame and the frames before and after the target frame, including: For each vehicle ID of the target frame, obtain the first coordinate of the previous frame of the target frame and the second coordinate of the target frame, and obtain the speed of the vehicle with the vehicle ID in the target frame; Calculating a spatial distance between the first coordinate and the second coordinate; Calculate the theoretical displacement distance of the vehicle with the vehicle ID according to the speed of the vehicle in the target frame; Determining whether the spatial distance is greater than the theoretical displacement distance; If so, determine that the error type of the target frame trajectory data is a coordinate error; If not, respectively calculating the difference in deflection angle between the target frame and the frame before the target frame, and the difference in deflection angle between the frame after the target frame and the target frame, to obtain a first angle difference and a second angle difference; Determining whether a difference between the first angle difference and the second angle difference is within a preset difference range; If not, it is determined that the error type of the target frame trajectory data is a deflection angle error.

6. The vehicle trajectory data processing method according to claim 5, characterized in that: N≥2, taking the Tth frame as the target frame, updating the target frame trajectory data based on the error type and each frame trajectory data, including: If the error type is a coordinate error, for the vehicle ID associated with the erroneous coordinates, obtain the theoretical displacement distance of the Tth frame, the coordinates of the T-1th frame, and the deflection angles of other frames except the T-1th frame and the Tth frame to obtain an auxiliary deflection angle; Setting the coordinate range of the coordinates of the Tth frame according to the theoretical displacement distance corresponding to the Tth frame and the coordinates of the T-1th frame; Modify the erroneous coordinates in the Tth frame according to the coordinate range and the auxiliary deflection angle; If the error type is a deflection angle error, the error deflection angle of the Tth frame is modified according to the coordinates in the trajectory data of each frame.

7. The vehicle trajectory data processing method according to claim 6, characterized in that: Modifying the erroneous coordinates in the Tth frame according to the coordinate range and the auxiliary deflection angle includes: Calculating the mean of the auxiliary deflection angles to obtain an average deflection angle; Obtaining a vector with the coordinates of the T-1th frame as a starting point and an angle with the deflection angle reference direction as the average deflection angle as a first vector; The corresponding erroneous coordinates in the Tth frame are modified according to the intersection of the first vector and the coordinate range.

8. The vehicle trajectory data processing method according to claim 6, characterized in that: Modify the error deflection angle of the Tth frame according to the coordinates in the trajectory data of each frame, including: For the vehicle ID associated with the wrong deflection angle, obtain the coordinates of the Tth frame and the M frames before and after the Tth frame to obtain the reference coordinates, M≤N; Connecting the reference coordinates in sequence to obtain a plurality of second vectors; determining the angle between each of the second vectors and a deflection angle reference direction; The average of all angles is taken as the deflection angle of the target frame vehicle ID in the Tth frame.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle trajectory data processing method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle trajectory data processing method according to any one of claims 1 to 8 when executed.

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