Vehicle trajectory processing method and device and related equipment

Abstract

The application provides a vehicle driving track processing method and device and related equipment, the method comprises: obtaining M positioning information and corresponding M positioning coordinates reported by a vehicle, each positioning information comprises vehicle speed information and latitude and longitude information of the vehicle at the corresponding positioning coordinate; determining N abnormal positioning coordinates in the M positioning coordinates based on at least one of distance information and the vehicle speed information, the distance information is the distance between any two adjacent positioning coordinates, and the distance information is determined based on at least the latitude and longitude information; filtering out the N abnormal positioning coordinates in the M positioning coordinates to obtain K positioning coordinates; and generating a driving track corresponding to the K positioning coordinates. In this way, the accuracy of the driving track of the vehicle can be improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method, apparatus and related equipment for processing vehicle driving trajectory. Background Technology

[0002] Currently, during vehicle operation, the vehicle's position is typically determined via satellite, and the vehicle's trajectory is then based on the satellite positioning data. However, network conditions and satellite positioning accuracy can affect the accuracy of the positioning points, resulting in an inaccurate final vehicle trajectory.

[0003] It is evident that in related technologies, positioning errors result in poor accuracy in obtaining vehicle trajectories. Summary of the Invention

[0004] This invention provides a vehicle trajectory processing method, apparatus, and related equipment, which can solve the problem of poor accuracy in the obtained vehicle trajectory due to positioning deviation in related technologies.

[0005] To solve the above problems, the present invention is implemented as follows:

[0006] In a first aspect, embodiments of the present invention provide a vehicle driving trajectory processing method, executed by a network-side device, the method comprising:

[0007] Obtain M location information points and corresponding M location coordinates reported by the vehicle. Each location information point includes the vehicle's speed information and latitude and longitude information at the corresponding location coordinates.

[0008] Based on at least one of the distance information and the vehicle speed information, N abnormal positioning coordinates are determined from the M positioning coordinates, wherein the distance information is the distance between any two adjacent positioning coordinates, and the distance information is determined at least based on the latitude and longitude information;

[0009] Filter out the N abnormal positioning coordinates from the M positioning coordinates to obtain K positioning coordinates;

[0010] Generate a driving trajectory corresponding to the K positioning coordinates.

[0011] Secondly, embodiments of the present invention provide a vehicle driving trajectory processing device, including a processor and a transceiver, and the device further includes:

[0012] The acquisition module is used to acquire M location information and M corresponding location coordinates reported by the vehicle. Each location information includes the vehicle speed information and latitude and longitude information of the vehicle at the corresponding location coordinates.

[0013] The determination module is used to determine N abnormal positioning coordinates from the M positioning coordinates based on at least one of distance information and vehicle speed information, wherein the distance information is the distance between any two adjacent positioning coordinates, and the distance information is determined at least based on the latitude and longitude information;

[0014] The filtering module is used to filter out the N abnormal positioning coordinates from the M positioning coordinates to obtain K positioning coordinates;

[0015] The generation module is used to generate the driving trajectory corresponding to the K positioning coordinates.

[0016] Thirdly, embodiments of the present invention also provide a communication device, including: a transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; the processor is configured to read the program in the memory to implement the steps in the method described in the first aspect above.

[0017] Fourthly, embodiments of the present invention also provide a readable storage medium for storing a program, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0018] In this embodiment of the invention, M location information pieces and corresponding M location coordinates reported by the vehicle are acquired. Each location information piece includes the vehicle's speed and latitude / longitude information at the corresponding location coordinates. Based on at least one of the distance information and the speed information, N abnormal location coordinates are determined from the M location coordinates. The distance information is the distance between any two adjacent location coordinates, and the distance information is determined at least based on the latitude / longitude information. The N abnormal location coordinates from the M location coordinates are filtered out to obtain K location coordinates. A driving trajectory corresponding to the K location coordinates is generated. By removing the N abnormal location coordinates from the M location coordinates, the obtained trajectory is made closer to the actual driving scenario of the vehicle, thereby improving the accuracy of the vehicle's driving trajectory and achieving precise trajectory correction. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the structure of a network system to which embodiments of the present invention can be applied;

[0021] Figure 2This is a flowchart illustrating the vehicle trajectory processing method provided in an embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of the vehicle trajectory processing device provided in an embodiment of the present invention;

[0023] Figure 4 This is a schematic diagram of the structure of the communication device provided in an embodiment of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] In the embodiments of this invention, the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, 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 is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices. Additionally, the use of "and / or" in this invention indicates at least one of the connected objects, such as A and / or B and / or C, representing seven possibilities: including A alone, B alone, C alone, both A and B present, both B and C present, both A and C present, and A, B, and C present.

[0026] Please see Figure 1 , Figure 1 This is a structural diagram of a network system to which embodiments of the present invention can be applied, such as... Figure 1 As shown, it includes a data transmitting device 11 and a data receiving device 12.

[0027] The data transmitting device 11 and the data receiving device 12 can communicate with each other. The data transmitting device 11 sends ciphertext information (Ciphertext Block) to the data receiving device 12.

[0028] In practical applications, the data transmitting device 11 can be a terminal (also known as a user equipment (UE)) and the data receiving device 12 can be a network-side device; or, the data transmitting device 11 can be a network-side device and the data receiving device 12 can be a terminal, but it is not limited to these.

[0029] The terminal can be a mobile phone, tablet computer, laptop computer, personal digital assistant (PDA), mobile internet device (MID), wearable device, or vehicle-mounted device, etc. Network-side equipment can be base stations, access and mobility management functions (AMF), trunk lines, access points, or other network elements, etc.

[0030] The vehicle trajectory processing method provided in the embodiments of the present invention will be described below.

[0031] See Figure 2 , Figure 2 This is one of the flowcharts illustrating the vehicle trajectory processing method provided in this embodiment of the invention. Figure 2 The vehicle trajectory processing method shown can be executed by network-side devices.

[0032] like Figure 2 As shown, the vehicle trajectory processing method may include the following steps:

[0033] Step 201: Obtain M location information and corresponding M location coordinates reported by the vehicle. Each location information includes the vehicle speed and latitude and longitude information at the corresponding location coordinates.

[0034] In this step, M is an integer greater than 2, and the M location information and the corresponding M location coordinates can be reported by the vehicle within a preset time period.

[0035] For example, if the preset time period is from 2:00 PM to 2:30 PM, then if a user wants to obtain the vehicle's driving trajectory from 2:00 PM to 2:30 PM, then all location information reported by the vehicle during that period will be retrieved. Each location information may also include the time the vehicle reported the location, the corresponding latitude and longitude, and the vehicle's speed at that location coordinate.

[0036] The latitude and longitude information of the vehicle at the corresponding positioning point can be understood as the positioning coordinates of the vehicle at the corresponding positioning point.

[0037] Step 202: Based on at least one of the distance information and the vehicle speed information, determine N abnormal positioning coordinates among the M positioning coordinates.

[0038] In this step, N is an integer greater than 0. Abnormal positioning coordinates can be understood as positioning coordinate points with poor positioning accuracy.

[0039] In this embodiment, vehicle speed, distance, and other information can be used to determine the instantaneous speed of the vehicle, the distance between adjacent positioning coordinates, and continuous positioning coordinates. Then, based on the determined instantaneous speed, the distance between adjacent positioning coordinates, and continuous positioning coordinates, abnormal positioning coordinates among M positioning coordinates can be filtered to improve the accuracy of the vehicle's driving trajectory.

[0040] Among them, distance information can be understood as the distance between any two adjacent positioning coordinates, and distance information can be determined at least based on latitude and longitude information, that is, it can be determined based on positioning coordinates.

[0041] For example, for any two adjacent location coordinates, the distance between them can be calculated using the vehicle's speed and the corresponding travel time. For instance, if the vehicle reports its location information at coordinate A at 2:12 AM and at coordinate B at 2:14 AM, and coordinates A and B are adjacent, and the vehicle travels from A to B at a constant speed of 50 km / h, the distance between them can be calculated based on the relationship between speed and time.

[0042] Additionally, the distance between any two adjacent location coordinates can be obtained based on the vehicle's own odometer system. For example, when a vehicle reports location information, the distance between the current location coordinate and the previous location coordinate can be obtained, i.e., the distance the vehicle traveled from the previous location coordinate to the current location coordinate. This travel distance is then added to the location information corresponding to the current location coordinate, so that network-side devices can obtain the distance between the current location coordinate and the previous location coordinate through the location information.

[0043] Step 203: Filter out the N abnormal positioning coordinates from the M positioning coordinates to obtain K positioning coordinates.

[0044] In this step, K = MN, which means filtering out abnormal positioning coordinates from the M positioning coordinates to remove them, thus obtaining K positioning coordinates.

[0045] Step 204: Generate the driving trajectory corresponding to the K positioning coordinates.

[0046] In this step, the vehicle's trajectory within a preset time period can be generated by sequentially connecting K positioning coordinates.

[0047] The connection order of the K positioning coordinates can be determined according to the chronological order of their positioning times. Furthermore, the positioning time of a coordinate can be referenced to the reporting time of its positioning information.

[0048] For example, if we set the symbol for the positioning coordinates to P, then K positioning coordinates can be represented as P1, P2, ... P K Furthermore, the positioning time corresponding to each positioning coordinate can be represented as T1, T2, ..., T. K And in T1, T2, ... T K If the arrangement order represents the chronological order, then the K positioning coordinates are arranged in the order of P1, P2, ..., P... K The elements are connected in sequence to generate the corresponding driving trajectory.

[0049] It should be noted that the positioning coordinates in this invention represent the coordinate values ​​of the vehicle at that positioning point, and the positioning coordinates of the vehicle can be represented by latitude and longitude values.

[0050] In this embodiment, by removing N abnormal positioning coordinates from the M positioning coordinates, the obtained trajectory is made closer to the actual driving scenario of the vehicle, thereby improving the accuracy of the vehicle's driving trajectory and achieving precise trajectory correction.

[0051] Optionally, determining N abnormal positioning coordinates from the M positioning coordinates based on at least one of distance information and vehicle speed information includes:

[0052] If the vehicle speed information and / or distance information corresponding to the first positioning coordinate among the M positioning coordinates meet the first preset condition, the first positioning coordinate is determined to be an abnormal positioning coordinate.

[0053] The M positioning coordinates further include a second positioning coordinate, which is the preceding positioning coordinate of the first positioning coordinate. The first preset condition includes at least one of the following:

[0054] The vehicle speed corresponding to the first positioning coordinate and the vehicle speed corresponding to the second positioning coordinate are both zero, and the distance between the first positioning coordinate and the second positioning coordinate is less than the first distance;

[0055] The vehicle speeds corresponding to the first and second positioning coordinates are both less than the first speed, and the distance between the first and second positioning coordinates is less than the second distance.

[0056] The first positioning coordinate belongs to a first coordinate set. The first coordinate set includes L consecutive third positioning coordinates among the M positioning coordinates corresponding to vehicle speeds greater than a second vehicle speed, and the vehicle speed of the positioning coordinate preceding the third positioning coordinate is greater than the second vehicle speed, where L is less than or equal to a first preset value;

[0057] The first positioning coordinate belongs to a second coordinate set. The second coordinate set includes H consecutive fourth positioning coordinates among the M positioning coordinates, and the distance between the fourth positioning coordinate and the positioning coordinate preceding it is greater than a third distance, where H is less than or equal to a second preset value;

[0058] The first distance is less than the second distance, the second distance is less than the third distance, the first vehicle speed is less than the second vehicle speed, and both L and H are positive integers.

[0059] In this embodiment, through the above determination conditions, the abnormal positioning coordinates among the M positioning coordinates can be accurately screened out, thereby improving the accuracy of determining the driving trajectory.

[0060] Moreover, by filtering out the abnormal positioning coordinates, the smoothness of the driving trajectory can be ensured, and the operation efficiency of trajectory generation can be improved.

[0061] For example, set the current point (the first positioning coordinate) as Pn, the previous point (the second positioning coordinate) as Pn-1, the vehicle speed at the current positioning coordinate as Vn, set the first vehicle speed as Vmin, set the second vehicle speed as Vmax, set the first distance as 50 meters, set the second distance as Dmin, and set the third distance as Dmax. Then, when the first positioning coordinate meets the first preset condition, it is determined that the first positioning coordinate is an abnormal positioning coordinate. Among them, the first preset condition includes at least one of the following:

[0062] a. If the speeds of the current point and the previous point are equal to 0 and the distance between the two points is less than 50m, that is, Vn&Vn-1 = 0 and Dis(Pn - Pn-1) < 50m, then filter Pn;

[0063] b. If the speeds of the current point and the previous point are less than Vmin and the straight-line distance between the two points is less than Dmin, that is, Vn&Vn-1 < Vmin and Dis(Pn - Pn-1) < Dmin, then filter Pn;

[0064] c. If the speeds of the current point and the previous point are greater than Vmax and the number of consecutive abnormal points is less than or equal to m, that is, Vn&Vn-1 > Vmax and the number of such consecutive abnormal points is less than or equal to L, then filter the current point. If the number of consecutive points is greater than L, then do not filter;

[0065] d. If the distance between the current point and the previous point is greater than Dmax and the number of consecutive outliers is less than or equal to m, i.e., Dis(Pn-Pn-1)>Vmax and the number of such consecutive outliers is less than or equal to H, then filter the current point; if the number of consecutive outliers is greater than H, then do not filter.

[0066] Understandably, for non-freighter motor vehicles, Vmin can be set to 12km / h, Dmin to 100m, Vmax to 150km / h, Dmax to 100km, and L and H can both be set to 6.

[0067] Optionally, generating the driving trajectory corresponding to the K positioning coordinates includes:

[0068] Connect the start coordinates and end coordinates of the K positioning coordinates with a straight line, obtain the distances from the other positioning coordinates (excluding the start coordinates and end coordinates) to the straight line, and obtain the corresponding maximum distance value.

[0069] Based on the maximum distance value, determine R positioning coordinates from the K positioning coordinates that satisfy the second preset condition, where R is an integer greater than 0;

[0070] Filtering out R positioning coordinates from the K positioning coordinates yields S positioning coordinates;

[0071] Generate a driving trajectory corresponding to the S positioning coordinates.

[0072] In this embodiment, S = KR, and the positioning coordinates can be thinned based on the K positioning coordinates to filter out unnecessary positioning coordinates from the K positioning coordinates, that is, to filter out positioning coordinates that meet the second preset condition from the K positioning coordinates, so as to reduce unnecessary positioning coordinates and improve the computational efficiency of the final generated driving trajectory.

[0073] Furthermore, by thinning out unnecessary positioning coordinates, the resulting driving trajectory can be made closer to the actual driving scenario of the vehicle.

[0074] Specifically, the system can compare the maximum distance value with a preset distance value to determine whether the positioning coordinates meet the second preset condition. For example, if the maximum distance value is less than the preset distance value, then all positioning coordinates except the start and end coordinates are filtered out from the K positioning coordinates, that is, only the start and end coordinates are retained, and the line connecting the start and end coordinates is taken as the vehicle's corresponding driving trajectory within a preset time period.

[0075] In addition, if the maximum distance value is greater than or equal to the preset distance value, the positioning coordinates corresponding to the maximum distance value are retained, and the positioning coordinates are divided into two parts with the positioning coordinates as the boundary. The judgment logic of the maximum distance value and the preset distance value is recursively applied until all positioning coordinates are included in the analysis and calculation, so as to obtain R positioning coordinates that satisfy the second preset condition out of K positioning coordinates.

[0076] For example, the K positioning coordinates include positioning coordinate 1, positioning coordinate 2, positioning coordinate 3, positioning coordinate 4 and positioning coordinate 5, with positioning coordinate 1 being the starting coordinate, positioning coordinate 5 being the ending coordinate, and the line connecting positioning coordinate 1 and positioning coordinate 5 being the target straight line.

[0077] In one example, the distance from positioning coordinate 2 to the target line is 10 meters, the distance from positioning coordinate 3 to the target line is 13 meters, and the distance from positioning coordinate 4 to the target line is 19 meters. That is, the maximum distance value corresponding to positioning coordinates 2, 3, and 4 is 19 meters. And the preset distance value can be set to 20 meters, so that the maximum distance value is less than the preset distance value. This means that positioning coordinates 2, 3, and 4 can be filtered out, and only positioning coordinates 1 and 5 can be retained. The line connecting positioning coordinates 1 and 5 is used as the vehicle's corresponding driving trajectory within the preset time period.

[0078] In another example, the distance from positioning coordinate 2 to the target line is 17 meters, the distance from positioning coordinate 3 to the target line is 23 meters, and the distance from positioning coordinate 4 to the target line is 16 meters. That is, the maximum distance value corresponding to positioning coordinates 2, 3, and 4 is 23 meters. And the preset distance value can be set to 20 meters. That is, if the maximum distance value is greater than the preset distance value, then positioning coordinate 3 is retained. And positioning coordinates 1, 2, 3, 4, and 5 are divided into two parts with positioning coordinate 3 as the boundary. The other positioning coordinates are analyzed and calculated to determine the positioning coordinates that need to be filtered out and improve the calculation efficiency of the final generated driving trajectory.

[0079] Optionally, the M location information and the corresponding M location coordinates are reported by the vehicle within a preset time period;

[0080] After generating the driving trajectory corresponding to the K positioning coordinates, the method further includes:

[0081] If target location information is obtained after the preset time period, the driving trajectory is updated based on the location coordinates corresponding to the target location information.

[0082] The target location information refers to location information whose reporting time falls within the preset time period.

[0083] In this embodiment, the target location information can be understood as the target location information that cannot be reported to the network side device within its corresponding preset time period due to network latency or other reasons. Therefore, after obtaining the target location information, the driving trajectory can be updated by the location coordinates corresponding to the target location information to make the obtained driving trajectory more accurate.

[0084] It is understood that the target positioning information in this embodiment can be one or multiple positioning coordinates, that is, the target positioning information is a collection of multiple positioning information.

[0085] Further optionally, updating the driving trajectory based on the positioning coordinates corresponding to the target positioning information includes:

[0086] The reporting time of the target location information is obtained;

[0087] Based on the reporting time, determine the sorting relationship of the positioning coordinates corresponding to the target positioning information among the K positioning coordinates;

[0088] Based on the sorting relationship, the positioning coordinates corresponding to the target positioning information are added to the sequence corresponding to the K positioning coordinates, and a sequence of K+1 positioning coordinates is obtained;

[0089] Generate the driving trajectory corresponding to the K+1 positioning coordinates.

[0090] In this embodiment, the reporting time of the target positioning information can be obtained, and the sorting relationship of the positioning coordinates corresponding to the target positioning information among the K positioning coordinates can be determined based on the reporting time. Then, the positioning coordinates corresponding to the target positioning information are added to the K positioning coordinates, and the sorting of the K+1 positioning coordinates is obtained. The driving trajectory corresponding to the K+1 positioning coordinates is then updated and generated to improve the accuracy of the obtained driving trajectory.

[0091] For example, the system can batch process the data (i.e., target location information) uploaded the previous day at a set time each day, and can use the device number corresponding to the vehicle as a reference, as well as the timestamp of the uploaded data to recalculate the mileage for the day and update the driving trajectory.

[0092] Specifically, take the timestamp Tk of the supplementary transmission data of device i, and traverse the actual sequence of the daily positioning coordinates P1 to Pn corresponding to Tk as T1 to Tn; when Tx < Tk < T(x + 1), stop traversing; recalculate the mileage of Tk, that is, the mileage of Tx plus the distance between Tx and Tk, assign k as x + 1, and record the mileage of Pk as Mk; recalculate the mileage of P(k + 1), P(k + 2)...P(n + 1) according to the mileage calculation method, that is, M(k + 1), P(k + 2)...P(n + 1), and the data of M1, M2...Mk remains unchanged; the mileage of any segment of the trajectory of the device is the mileage value obtained by subtracting the starting point from the ending point or the maximum mileage value minus the minimum mileage value in this segment of the trajectory.

[0093] Among them, the mileage calculation method can be based on the mileage value of the current point being the straight-line distance between the current point and the previous point plus the mileage value of the previous point, that is, the mileage value of the current point is Mile(n) = Mile(n - 1) + Dis(Pn - Pn - 1). Because it is a cumulative calculation method for continuous points, the mileage value of the trajectory within a certain period of time is the maximum mileage value minus the minimum mileage value among all the positioning points of this segment of the trajectory, that is, Mile = Max(mile) - Min(mile).

[0094] The vehicle driving trajectory processing method provided by the embodiments of the present invention obtains M positioning information reported by the vehicle and the corresponding M positioning coordinates. Each positioning information includes the vehicle speed information and longitude and latitude information at the corresponding positioning coordinates; based on at least one of the distance information and the vehicle speed information, N abnormal positioning coordinates among the M positioning coordinates are determined. The distance information is the distance between any two adjacent positioning coordinates, and the distance information is at least determined based on the longitude and latitude information; filter out the N abnormal positioning coordinates among the M positioning coordinates to obtain K positioning coordinates; generate a driving trajectory corresponding to the K positioning coordinates. In this way, by removing the N abnormal positioning coordinates among the M positioning coordinates, the obtained trajectory is closer to the actual driving scenario of the vehicle, thereby improving the accuracy of the vehicle driving trajectory and achieving accurate trajectory correction.

[0095] The following is a specific description of an embodiment of the present invention:

[0096] Step 1: Receive the positioning data uploaded by the in-vehicle device, including information such as message time, speed, and positioning.

[0097] Step 2: Judge that if the message time corresponding to the current positioning information is earlier than the message time corresponding to the previous positioning information, then execute Step 2.1; otherwise, execute Step 2.2.

[0098] Step 2.1: Mark the current positioning information as supplementary transmission data.

[0099] Step 2.2: Mark the current positioning information as real-time data;

[0100] Step 3: Select a continuous series of positioning points P0, P1...Pn within a period of time to form a trajectory, and judge each positioning point. There are the following four situations;

[0101] Step 3.1: If the speed between the current point and the previous point is equal to 0 and the distance between the two points is less than 50m, then filter Pn;

[0102] Step 3.2: If the speed between the current point and the previous point is less than Vmin and the straight-line distance between the two points is less than Dmin, then filter Pn;

[0103] Step 3.3: If the speed between the current point and the previous point is greater than Vmax and the number of consecutive abnormal points is less than or equal to m, and such consecutive abnormal points are less than or equal to m, then filter the current point. If the number of consecutive points is greater than m, then do not filter;

[0104] Step 3.4: If the distance between the current point and the previous point is greater than Dmax and the number of consecutive abnormal points is less than or equal to m, and such consecutive abnormal points are less than or equal to m, then filter the current point. If the number of consecutive points is greater than m, then do not filter;

[0105] Among them, the value of m can be 6.

[0106] Step 4: Connect the starting point P0 and the ending point Pn of the trajectory to form a straight line, and set a threshold N. Calculate the distances from all other points on the trajectory to this straight line respectively, and take the maximum value disMax. Judge that if disMax < N, then execute Step 4.1, otherwise execute Step 4.2;

[0107] Step 4.1: Filter out all data except the starting point and the ending point;

[0108] Step 4.2: Take this point as the boundary, divide the trajectory into two parts to form two trajectories, and re-substitute into Step 4 for calculation;

[0109] Step 5: Perform cumulative calculation on the mileage values of each positioning point, then the mileage value of this section of the trajectory is Mile = Max(mile) - Min(mile);

[0110] Step 6: Use a scheduled task every day to process the supplementary transmission data of the previous day. Judge that if there is supplementary transmission data, then execute Step 6.1, otherwise execute Step 6.2;

[0111] Step 6.1: Repeat Step 5;

[0112] Step 6.2: End the process.

[0113] Thus, by employing a comprehensive judgment strategy that combines instantaneous velocity, straight-line distance between adjacent points, and the number of consecutive points, the technical effect of accurately identifying abnormal location coordinates can be achieved; and by using a distance threshold comparison method for thinning, the technical effect of drawing the trajectory with fewer points can be achieved while ensuring trajectory smoothness; in addition, by using a scheme to mark and correct the supplementary data, the technical effects of trajectory integrity and accurate mileage calculation can also be achieved.

[0114] See Figure 3 , Figure 3 This is a structural diagram of the vehicle trajectory processing device provided in an embodiment of the present invention. Figure 3 As shown, the device 300 includes:

[0115] The acquisition module 301 is used to acquire M location information and M corresponding location coordinates reported by the vehicle. Each location information includes the vehicle speed information and latitude and longitude information of the vehicle at the corresponding location coordinates.

[0116] The determining module 302 is used to determine N abnormal positioning coordinates among the M positioning coordinates based on at least one of distance information and vehicle speed information, wherein the distance information is the distance between any two adjacent positioning coordinates, and the distance information is determined at least based on the latitude and longitude information;

[0117] Filtering module 303 is used to filter out N abnormal positioning coordinates from the M positioning coordinates to obtain K positioning coordinates;

[0118] The generation module 304 is used to generate the driving trajectory corresponding to the K positioning coordinates.

[0119] Optionally, the determining module 302 is specifically used to determine the first positioning coordinate as an abnormal positioning coordinate when the vehicle speed information and / or distance information corresponding to the first positioning coordinate among the M positioning coordinates meet the first preset condition;

[0120] The M positioning coordinates further include a second positioning coordinate, which is the preceding positioning coordinate of the first positioning coordinate. The first preset condition includes at least one of the following:

[0121] The vehicle speed corresponding to the first positioning coordinate and the vehicle speed corresponding to the second positioning coordinate are both zero, and the distance between the first positioning coordinate and the second positioning coordinate is less than the first distance;

[0122] The vehicle speeds corresponding to the first and second positioning coordinates are both less than the first speed, and the distance between the first and second positioning coordinates is less than the second distance.

[0123] The first positioning coordinate belongs to the first coordinate set, which includes L consecutive third positioning coordinates from the M positioning coordinates where the vehicle speed is greater than the second vehicle speed, and the vehicle speed of the preceding positioning coordinate of the third positioning coordinate is greater than the second vehicle speed, and L is less than or equal to a first preset value.

[0124] The first positioning coordinate belongs to the second coordinate set, which includes H consecutive fourth positioning coordinates from the M positioning coordinates, and the distance between the fourth positioning coordinate and the previous positioning coordinate is greater than the third distance, and H is less than or equal to the second preset value.

[0125] The first distance is less than the second distance, the second distance is less than the third distance, the first vehicle speed is less than the second vehicle speed, and L and H are both positive integers.

[0126] Optionally, the generation module 304 includes:

[0127] The first acquisition unit is used to connect the start coordinates and end coordinates of the K positioning coordinates into a straight line, acquire the distances from the other positioning coordinates (excluding the start coordinates and the end coordinates) to the straight line, and obtain the corresponding maximum distance value.

[0128] The first determining unit is used to determine R positioning coordinates among the K positioning coordinates that satisfy the second preset condition based on the maximum distance value, where R is an integer greater than 0;

[0129] A filtering unit is used to filter out R positioning coordinates from the K positioning coordinates to obtain S positioning coordinates;

[0130] The first generation unit is used to generate the driving trajectory corresponding to the S positioning coordinates.

[0131] Optionally, the M location information and the corresponding M location coordinates are reported by the vehicle within a preset time period;

[0132] The device 300 further includes:

[0133] The update module is used to update the driving trajectory based on the positioning coordinates corresponding to the target positioning information when the target positioning information is obtained at a time after the preset time period.

[0134] The target location information refers to location information whose reporting time falls within the preset time period.

[0135] Optionally, the update module includes:

[0136] The second acquisition module is used to acquire the reporting time of the target location information;

[0137] The second determining unit is used to determine the sorting relationship of the positioning coordinates corresponding to the target positioning information among the K positioning coordinates based on the reporting time;

[0138] An adding module is used to add the positioning coordinates corresponding to the target positioning information to the sequence corresponding to the K positioning coordinates based on the sorting relationship, and obtain a sequence of K+1 positioning coordinates;

[0139] The second generation unit is used to generate the driving trajectory corresponding to the K+1 positioning coordinates.

[0140] Device 300 can implement the embodiments of the present invention. Figure 2 The various processes in the method embodiments, and the ways to achieve the same beneficial effects, will not be repeated here to avoid repetition.

[0141] This invention also provides a communication device. Please refer to [link to relevant documentation]. Figure 4 The communication device may include a processor 401, a memory 402, and a program 4021 stored in the memory 402 and capable of running on the processor 401.

[0142] In this invention, the communication device is a network-side device, and program 4021 can be implemented when executed by processor 401. Figure 2 Any steps in the corresponding method embodiments and the achievement of the same beneficial effects will not be repeated here.

[0143] Those skilled in the art will understand that all or part of the steps of the methods described in the above embodiments can be implemented by hardware related to program instructions, and the program can be stored in a readable medium. The present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, can implement the above-described methods. Figure 2 Any step in the corresponding method embodiment can achieve the same technical effect, and will not be repeated here to avoid repetition.

[0144] The storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0145] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A vehicle trajectory processing method, executed by a network-side device, characterized in that, The method includes: Obtain M location information points and corresponding M location coordinates reported by the vehicle. Each location information point includes the vehicle's speed information and latitude and longitude information at the corresponding location coordinates. Based on at least one of the distance information and the vehicle speed information, N abnormal positioning coordinates are determined from the M positioning coordinates, wherein the distance information is the distance between any two adjacent positioning coordinates, and the distance information is determined at least based on the latitude and longitude information; Filter out the N abnormal positioning coordinates from the M positioning coordinates to obtain K positioning coordinates; Generate a driving trajectory corresponding to the K positioning coordinates; Determining N abnormal positioning coordinates from the M positioning coordinates based on at least one of distance information and vehicle speed information includes: If the vehicle speed information and / or distance information corresponding to the first positioning coordinate among the M positioning coordinates meet the first preset condition, the first positioning coordinate is determined to be an abnormal positioning coordinate. The M positioning coordinates further include a second positioning coordinate, which is the preceding positioning coordinate of the first positioning coordinate. The first preset condition includes at least one of the following: The first positioning coordinate belongs to the first coordinate set, which includes L consecutive third positioning coordinates from the M positioning coordinates where the vehicle speed is greater than the second vehicle speed, and L is less than or equal to a first preset value. The first positioning coordinate belongs to the second coordinate set, which includes H consecutive fourth positioning coordinates from the M positioning coordinates, and the distance between the fourth positioning coordinate and the previous positioning coordinate is greater than the third distance, and H is less than or equal to the second preset value. If L is greater than the first preset value or H is greater than the second preset value, the first positioning coordinates are determined to be normal positioning coordinates.

2. The method according to claim 1, characterized in that, The first preset condition also includes at least one of the following: The vehicle speed corresponding to the first positioning coordinate and the vehicle speed corresponding to the second positioning coordinate are both zero, and the distance between the first positioning coordinate and the second positioning coordinate is less than the first distance; The vehicle speeds corresponding to the first and second positioning coordinates are both less than the first vehicle speed, and the distance between the first and second positioning coordinates is less than the second distance. The first distance is less than the second distance, the second distance is less than the third distance, and the first vehicle speed is less than the second vehicle speed.

3. The method according to claim 1 or 2, characterized in that, The generation of the driving trajectory corresponding to the K positioning coordinates includes: Connect the start coordinates and end coordinates of the K positioning coordinates with a straight line, obtain the distances from the other positioning coordinates (excluding the start coordinates and end coordinates) to the straight line, and obtain the corresponding maximum distance value. Based on the maximum distance value, determine R positioning coordinates among the K positioning coordinates that satisfy the second preset condition; Filtering out R positioning coordinates from the K positioning coordinates yields S positioning coordinates; Generate a driving trajectory corresponding to the S positioning coordinates.

4. The method according to claim 1 or 2, characterized in that, The M location information and the corresponding M location coordinates are reported by the vehicle within a preset time period; After generating the driving trajectory corresponding to the K positioning coordinates, the method further includes: If target location information is obtained after the preset time period, the driving trajectory is updated based on the location coordinates corresponding to the target location information. The target location information refers to location information whose reporting time falls within the preset time period.

5. The method according to claim 4, characterized in that, Updating the driving trajectory based on the positioning coordinates corresponding to the target positioning information includes: The reporting time of the target location information is obtained; Based on the reporting time, determine the sorting relationship of the positioning coordinates corresponding to the target positioning information among the K positioning coordinates; Based on the sorting relationship, the positioning coordinates corresponding to the target positioning information are added to the sequence corresponding to the K positioning coordinates, and a sequence of K+1 positioning coordinates is obtained; Generate the driving trajectory corresponding to the K+1 positioning coordinates.

6. A vehicle trajectory processing device, characterized in that, The device includes a processor and a transceiver, and further includes: The acquisition module is used to acquire M location information and M corresponding location coordinates reported by the vehicle. Each location information includes the vehicle speed information and latitude and longitude information of the vehicle at the corresponding location coordinates. The determination module is used to determine N abnormal positioning coordinates from the M positioning coordinates based on at least one of distance information and vehicle speed information, wherein the distance information is the distance between any two adjacent positioning coordinates, and the distance information is determined at least based on the latitude and longitude information; The filtering module is used to filter out the N abnormal positioning coordinates from the M positioning coordinates to obtain K positioning coordinates; The generation module is used to generate the driving trajectory corresponding to the K positioning coordinates; The determining module is specifically used to determine the first positioning coordinate as an abnormal positioning coordinate when the vehicle speed information and / or distance information corresponding to the first positioning coordinate among the M positioning coordinates meet the first preset condition. The M positioning coordinates further include a second positioning coordinate, which is the preceding positioning coordinate of the first positioning coordinate. The first preset condition includes at least one of the following: The first positioning coordinate belongs to the first coordinate set, which includes L consecutive third positioning coordinates from the M positioning coordinates where the vehicle speed is greater than the second vehicle speed, and L is less than or equal to a first preset value. The first positioning coordinate belongs to the second coordinate set, which includes H consecutive fourth positioning coordinates from the M positioning coordinates. The distance between the fourth positioning coordinate and the previous positioning coordinate is greater than the third distance, H is less than or equal to the second preset value, and L and H are both positive integers. If L is greater than the first preset value or H is greater than the second preset value, the first positioning coordinates are determined to be normal positioning coordinates.

7. The apparatus according to claim 6, characterized in that, The first preset condition also includes at least one of the following: The vehicle speed corresponding to the first positioning coordinate and the vehicle speed corresponding to the second positioning coordinate are both zero, and the distance between the first positioning coordinate and the second positioning coordinate is less than the first distance; The vehicle speeds corresponding to the first and second positioning coordinates are both less than the first vehicle speed, and the distance between the first and second positioning coordinates is less than the second distance. The first distance is less than the second distance, the second distance is less than the third distance, and the first vehicle speed is less than the second vehicle speed.

8. The apparatus according to claim 6 or 7, characterized in that, The generation module includes: The first acquisition unit is used to connect the start coordinates and end coordinates of the K positioning coordinates into a straight line, acquire the distances from the other positioning coordinates (excluding the start coordinates and end coordinates) to the straight line, and obtain the corresponding maximum distance value. The first determining unit is used to determine R positioning coordinates among the K positioning coordinates that satisfy the second preset condition based on the maximum distance value, where R is an integer greater than 0; A filtering unit is used to filter out R positioning coordinates from the K positioning coordinates to obtain S positioning coordinates; The first generation unit is used to generate the driving trajectory corresponding to the S positioning coordinates.

9. The apparatus according to claim 6 or 7, characterized in that, The M location information and the corresponding M location coordinates are reported by the vehicle within a preset time period; The device further includes: The update module is used to update the driving trajectory based on the positioning coordinates corresponding to the target positioning information when the target positioning information is obtained at a time after the preset time period. The target location information refers to location information whose reporting time falls within the preset time period.

10. The apparatus according to claim 9, characterized in that, The update module includes: The second acquisition module is used to acquire the reporting time of the target location information; The second determining unit is used to determine the sorting relationship of the positioning coordinates corresponding to the target positioning information among the K positioning coordinates based on the reporting time; An adding module is used to add the positioning coordinates corresponding to the target positioning information to the sequence corresponding to the K positioning coordinates based on the sorting relationship, and obtain a sequence of K+1 positioning coordinates; The second generation unit is used to generate the driving trajectory corresponding to the K+1 positioning coordinates.

11. A communication device, comprising: A transceiver, a memory, a processor, and a program stored in the memory and executable on the processor; characterized in that the processor is configured to read the program in the memory to implement the steps of the vehicle trajectory processing method as described in any one of claims 1 to 5.

12. A readable storage medium for storing a program, characterized in that, When the program is executed by the processor, it implements the steps of the vehicle trajectory processing method as described in any one of claims 1 to 5.

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