Driving track processing method and device, computer equipment and readable storage medium

Abstract

The invention relates to a driving track processing method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring track associated data corresponding to each original track point in an original track; for any original track point, determining a stability parameter corresponding to the original track point according to the track association data corresponding to the original track point and the weight coefficient corresponding to each track association data; determining whether the original track point is a target noisy point or not according to a size relationship between the stability parameter corresponding to the original track point and a preset stability threshold value corresponding to the original track; and under the condition that the original track point is the target noisy point, eliminating the target noisy point. By adopting the method, the track processing precision can be improved.

Description

Technical Field

[0001] The present application relates to the field of trajectory processing technology, and in particular to a driving trajectory processing method, device, computer equipment and readable storage medium. Background Art

[0002] In the process of processing the driving trajectory of automobile logistics transportation, it is usually based on the distance threshold filtering method and the speed threshold method. For example, the distance threshold filtering method sets a unified upper limit of the distance between adjacent trajectory points (such as 100 meters), and then compares the distance between each pair of adjacent trajectory points to eliminate trajectory points that exceed the upper limit. This method is simple and easy to implement, with low calculation cost, and is suitable for initial logistics transportation that does not require high trajectory accuracy.

[0003] However, when dealing with complex and ever-changing automobile logistics trajectory data, its limitations gradually become apparent and need to be addressed urgently. Summary of the invention

[0004] Based on this, it is necessary to provide a driving trajectory processing method, device, computer equipment and readable storage medium that can improve the trajectory processing accuracy in response to the above technical problems.

[0005] In a first aspect, the present application provides a driving trajectory processing method, comprising:

[0006] Obtaining trajectory association data corresponding to each original trajectory point in the original trajectory;

[0007] For any original trajectory point, according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data, the stability parameter corresponding to the original trajectory point is determined;

[0008] Determine whether the original trajectory point is a target noise point according to the magnitude relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory;

[0009] When the original trajectory point is a target noise point, the target noise point is removed.

[0010] In one embodiment, the trajectory association data includes motion state data and signal state data; the weight coefficient includes a first weight coefficient corresponding to the motion state data and a second weight coefficient corresponding to the signal state data; accordingly, according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data, the stability parameter corresponding to the original trajectory point is determined, including:

[0011] Determine a first stability parameter corresponding to the original trajectory point according to the motion state data corresponding to the original trajectory point and the first weight coefficient;

[0012] Determine a second stability parameter corresponding to the original trajectory point according to the signal state data corresponding to the original trajectory point and the second weight coefficient;

[0013] A stability parameter corresponding to the original trajectory point is determined according to the first stability parameter and the second stability parameter.

[0014] In one embodiment, the motion state data includes position data and speed data, and the position data includes coordinate position and horizontal position; accordingly, determining the first stability parameter corresponding to the original trajectory point according to the motion state data corresponding to the original trajectory point and the first weight coefficient includes:

[0015] Determine the distance influence parameter corresponding to the original trajectory point according to the coordinate position of the original trajectory point and the coordinate position of the adjacent trajectory point corresponding to the original trajectory point;

[0016] Determine the slope influence parameter corresponding to the original trajectory point according to the horizontal position of the original trajectory point and the horizontal positions of the adjacent trajectory points corresponding to the original trajectory point;

[0017] Determine a speed influence parameter corresponding to the original trajectory point according to the speed data of the original trajectory point and the speed data of the adjacent trajectory points corresponding to the original trajectory point;

[0018] A first stability parameter corresponding to the original trajectory point is determined according to at least one of the distance influencing parameter, the slope influencing parameter and the speed influencing parameter, and a weight coefficient corresponding to the selected parameter.

[0019] In one embodiment, the adjacent track point includes a front adjacent track point and a rear adjacent track point; accordingly, according to the coordinate position of the original track point and the coordinate position of the adjacent track point corresponding to the original track point, determining the distance influence parameter corresponding to the original track point includes:

[0020] Determine a first spacing according to the coordinate position of the original trajectory point and the coordinate position of the previous adjacent trajectory point corresponding to the original trajectory point;

[0021] Determine a second spacing according to the coordinate position of the original trajectory point and the coordinate position of the adjacent trajectory point after the original trajectory point corresponds;

[0022] A distance influence parameter corresponding to the original trajectory point is determined according to the first distance and / or the second distance.

[0023] In one embodiment, the signal state data includes signal strength and signal accuracy; accordingly, determining the second stability parameter corresponding to the original trajectory point according to the signal state data corresponding to the original trajectory point and the second weight coefficient includes:

[0024] Determine the intensity impact data corresponding to the original trajectory point according to the signal intensity corresponding to the original trajectory point and the weight coefficient corresponding to the signal intensity;

[0025] Determine the accuracy impact data corresponding to the original trajectory point according to the signal accuracy corresponding to the original trajectory point and the weight coefficient corresponding to the signal accuracy;

[0026] A second stability parameter corresponding to the original trajectory point is determined according to the strength influence data and / or the accuracy influence data.

[0027] In one embodiment, determining whether the original trajectory point is a target noise point according to a magnitude relationship between a stability parameter corresponding to the original trajectory point and a preset stability threshold corresponding to the original trajectory includes:

[0028] When the stability parameter of the original trajectory point exceeds a preset stability threshold corresponding to the original trajectory, the original trajectory is determined to be a candidate noise point;

[0029] When the positional relationship between the candidate noise point and the adjacent trajectory point of the candidate noise point is not within the preset area, the original trajectory point is determined to be the target noise point.

[0030] In one of the embodiments, before determining whether the original trajectory point is a target noise point according to the magnitude relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory, the method further includes:

[0031] The preset stability threshold corresponding to the original trajectory is determined according to the magnitude relationship between the stability parameters corresponding to the original trajectory points in the original trajectory and the number of the original trajectory points in the original trajectory.

[0032] In a second aspect, the present application also provides a driving trajectory processing device, comprising:

[0033] A data acquisition module, used to acquire trajectory association data corresponding to each original trajectory point in the original trajectory;

[0034] A first determination module is used to determine, for any original trajectory point, a stability parameter corresponding to the original trajectory point according to trajectory association data corresponding to the original trajectory point and a weight coefficient corresponding to each trajectory association data;

[0035] A second determination module is used to determine whether the original trajectory point is a target noise point according to the size relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory;

[0036] The trajectory processing module is used to remove the target noise point when the original trajectory point is the target noise point.

[0037] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0038] Obtaining trajectory association data corresponding to each original trajectory point in the original trajectory;

[0039] For any original trajectory point, according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data, the stability parameter corresponding to the original trajectory point is determined;

[0040] Determine whether the original trajectory point is a target noise point according to the magnitude relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory;

[0041] When the original trajectory point is a target noise point, the target noise point is removed.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0043] Obtaining trajectory association data corresponding to each original trajectory point in the original trajectory;

[0044] For any original trajectory point, according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data, the stability parameter corresponding to the original trajectory point is determined;

[0045] Determine whether the original trajectory point is a target noise point according to the magnitude relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory;

[0046] When the original trajectory point is a target noise point, the target noise point is removed.

[0047] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0048] Obtaining trajectory association data corresponding to each original trajectory point in the original trajectory;

[0049] For any original trajectory point, according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data, the stability parameter corresponding to the original trajectory point is determined;

[0050] Determine whether the original trajectory point is a target noise point according to the magnitude relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory;

[0051] When the original trajectory point is a target noise point, the target noise point is removed.

[0052] The above-mentioned driving trajectory processing method, device, computer equipment and readable storage medium determine the stability parameter corresponding to the original trajectory point based on the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data, and determine whether the original trajectory point is a target noise point based on the size relationship between the stability parameter corresponding to each original trajectory point and the preset stability threshold corresponding to the original trajectory, and remove the target noise point if the original trajectory point is a target noise point. In the above process, since the stability coefficient corresponding to each original trajectory point is determined based on the corresponding trajectory association data and the weight coefficient corresponding to each association data, the stability coefficient corresponding to each original trajectory point can better characterize the stability of the corresponding original trajectory point. The target noise point determined based on the size relationship between the stability parameter corresponding to each original trajectory point and the preset stability threshold corresponding to the original trajectory is more accurate, thereby improving the trajectory processing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A schematic diagram of a flow chart of a driving trajectory processing method in one embodiment;

[0055] Figure 2 A schematic flow chart of a stability parameter determination step in one embodiment;

[0056] Figure 3 A schematic diagram of a flow chart of a target noise point determination step in one embodiment;

[0057] Figure 4 A schematic diagram of a flow chart of a driving trajectory processing method in another embodiment;

[0058] Figure 5 is a structural block diagram of a driving trajectory processing device in one embodiment;

[0059] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0061] In one embodiment, Figure 1 As shown, a driving trajectory processing method is provided. This embodiment takes the method applied to a terminal as an example for illustration. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0062] S110, obtaining trajectory association data corresponding to each original trajectory point in the original trajectory.

[0063] Among them, the original trajectory can be a car driving trajectory, and the original trajectory can be collected and acquired based on the Global Positioning System (GPS); it can also be obtained based on monitoring by a road monitoring system; it can also be obtained based on positioning sensors set on the vehicle. This application does not impose any limitation on the method of obtaining the original trajectory.

[0064] The trajectory association data can be used to characterize the state of each original trajectory point in the original trajectory, for example, it can be used to characterize the motion state, distribution state, and change state of each original trajectory point.

[0065] Exemplarily, the trajectory association data corresponding to each original trajectory point may be carried in the original trajectory, and the trajectory association data corresponding to each original trajectory point may be directly acquired while acquiring the original trajectory.

[0066] S120 , for any original trajectory point, determine a stability parameter corresponding to the original trajectory point according to trajectory association data corresponding to the original trajectory point and a weight coefficient corresponding to each trajectory association data.

[0067] Among them, each track-related data corresponds to a different weight coefficient, which can be determined based on manual experience, or determined through a large number of experiments, or can be set based on user needs. This application does not impose any limitation on the method for determining the weight coefficient corresponding to each track-related data.

[0068] Illustratively, in this embodiment, for any original trajectory point, the product of different trajectory association data corresponding to the original trajectory point and the corresponding weight coefficient can be determined, and the sum of different products is used as the stability coefficient corresponding to the original trajectory point.

[0069] Exemplarily, the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data may also be input into a pre-trained stability parameter determination model to obtain the stability parameter corresponding to the original trajectory point.

[0070] S130, determining whether the original trajectory point is a target noise point according to a magnitude relationship between a stability parameter corresponding to the original trajectory point and a preset stability threshold corresponding to the original trajectory.

[0071] Among them, the preset stability threshold corresponding to the original trajectory can be determined based on manual experience or through a large number of experiments, and this application does not impose any limitation on this.

[0072] In order to make the preset stability threshold match the original trajectory more closely and improve the accuracy of the target noise point determination, in an optional embodiment, different original trajectories correspond to different preset stability thresholds. For example, the preset stability threshold corresponding to the original trajectory can be determined based on the magnitude relationship of the stability parameters corresponding to each original trajectory point in the original trajectory and the number of original trajectory points in the original trajectory.

[0073] For example, the stability parameters corresponding to different original trajectory points are sorted from small to large, and the preset stability threshold corresponding to the original trajectory point is determined according to the position of the different stability parameters in the sorting result. In order to make the process of determining the preset stability threshold more specific, a specific determination method is provided: the number of original trajectory points is N, that is, there are N stability parameters, and the result after sorting from small to large is: , where SN is the stability parameter corresponding to the Nth original trajectory point. In the sorting result, the median is M. If N is an odd number, then ; If N is an even number, then ; The first quartile Q1 is ; The third quartile Q3 is Furthermore, the preset stability threshold is determined based on the following formula:

[0074] ;

[0075] Where T is the preset stability threshold; M is the median; Q3 is the third quartile; Q1 is the first quartile.

[0076] Exemplarily, in this embodiment, the original trajectory point corresponding to the stability parameter greater than the preset stability threshold may be used as the target noise point.

[0077] S140: When the original trajectory point is a target noise point, remove the target noise point.

[0078] In the above driving trajectory processing method, the stability parameter corresponding to the original trajectory point is determined based on the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data, and based on the size relationship between the stability parameter corresponding to each original trajectory point and the preset stability threshold corresponding to the original trajectory, it is determined whether the original trajectory point is a target noise point, and if the original trajectory point is a target noise point, the target noise point is eliminated. In the above process, since the stability coefficient corresponding to each original trajectory point is determined based on the corresponding trajectory association data and the weight coefficient corresponding to each association data, the stability coefficient corresponding to each original trajectory point can better characterize the stability of the corresponding original trajectory point. Based on the size relationship between the stability parameter corresponding to each original trajectory point and the preset stability threshold corresponding to the original trajectory, the target noise point determined is more accurate, thereby improving the trajectory processing accuracy.

[0079] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the trajectory association data includes motion state data and signal state data; the weight coefficient includes a first weight coefficient corresponding to the motion state data, and a second weight coefficient corresponding to the signal state data; in this case, the process of determining the stability parameter corresponding to the original trajectory point according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data is refined.

[0080] See also Figure 2 The steps for determining the stability parameters shown include:

[0081] S210, determining a first stability parameter corresponding to the original trajectory point according to the motion state data corresponding to the original trajectory point and a first weight coefficient.

[0082] The motion state data includes position data and speed data, and the position data includes coordinate position and horizontal position. The first stability parameter can characterize the stability of the original trajectory point in the motion state dimension.

[0083] In an optional embodiment, the distance influence parameter corresponding to the original trajectory point can be determined according to the coordinate position of the original trajectory point and the coordinate position of the adjacent trajectory point corresponding to the original trajectory point; the slope influence parameter corresponding to the original trajectory point can be determined according to the horizontal position of the original trajectory point and the horizontal position of the adjacent trajectory point corresponding to the original trajectory point; the speed influence parameter corresponding to the original trajectory point can be determined according to the speed data of the original trajectory point and the speed data of the adjacent trajectory point corresponding to the original trajectory point; the first stability parameter corresponding to the original trajectory point can be determined according to at least one of the distance influence parameter, the slope influence parameter and the speed influence parameter, and the weight coefficient corresponding to the selected parameter.

[0084] The distance influence parameter can be used to characterize the influence of the distance between the original trajectory point and the adjacent trajectory point on the first stability parameter.

[0085] Exemplarily, the adjacent trajectory points include a front adjacent trajectory point and a rear adjacent trajectory point. Accordingly, the distance influence parameter corresponding to the original trajectory point can be determined in the following manner: a first spacing is determined according to the coordinate position of the original trajectory point and the coordinate position of the front adjacent trajectory point corresponding to the original trajectory point; a second spacing is determined according to the coordinate position of the original trajectory point and the coordinate position of the rear adjacent trajectory point corresponding to the original trajectory point; and a distance influence parameter corresponding to the original trajectory point is determined according to the first spacing and / or the second spacing.

[0086] For an original trajectory point, the distance influence parameter corresponding to the original trajectory point can be the distance between the original trajectory point and its previous adjacent trajectory point; it can also be the distance between the original trajectory point and its subsequent adjacent trajectory point; it can also be the weighted sum of the distance between the original trajectory point and its previous adjacent trajectory point and the distance between the original trajectory point and its subsequent adjacent trajectory point.

[0087] Taking the coordinate position of the original trajectory point as (lon1, lat1) and the coordinate position of its previous adjacent trajectory point as (lon2, lat2) as an example, the distance between the original trajectory point and its previous adjacent trajectory point can be determined by the following formula:

[0088] ;

[0089] Where d is the distance between the original trajectory point and its previous adjacent trajectory point; lon1 is the longitude of the original trajectory point; lat1 is the latitude of the original trajectory point; lon2 is the longitude of the previous adjacent trajectory point of the original trajectory point; lat2 is the latitude of the previous adjacent trajectory point of the original trajectory point; and R is the average radius of the earth.

[0090] Exemplarily, the slope influence parameter corresponding to the original trajectory point may be determined in the following manner: the slope influence parameter corresponding to the original trajectory point may be determined according to the horizontal position of the original trajectory point and the horizontal positions of adjacent trajectory points corresponding to the original trajectory point.

[0091] For an original trajectory point, the slope influence parameter corresponding to the original trajectory point can be the slope between the original trajectory point and its previous adjacent trajectory point; it can also be the slope between the original trajectory point and its subsequent adjacent trajectory point; it can also be the weighted sum of the distance between the original trajectory point and its previous adjacent trajectory point and the slope between the original trajectory point and its subsequent adjacent trajectory point.

[0092] For example, obtain the heights h1 and h2 of adjacent trajectory points, calculate the horizontal distance x between the two points, and the calculation process of x is the same as the calculation process of the distance d between adjacent trajectory points. Assume that the positions of the two trajectory points are (lon1, lat1) and (lon2, lat2) respectively, calculate the horizontal distance x between the two points according to the Haversing formula, and then calculate the slope between adjacent trajectory points based on the following formula:

[0093] ;

[0094] In the formula, is the slope between adjacent trajectory points; h1 and h2 are the heights of adjacent trajectory points respectively; x is the horizontal distance between adjacent trajectory points.

[0095] Exemplarily, the speed influence parameter corresponding to the original trajectory point can be determined in the following manner: the speed influence parameter corresponding to the original trajectory point is determined based on the speed data of the original trajectory point and the speed data of the adjacent trajectory points corresponding to the original trajectory point; wherein the speed influence parameter may include at least one of speed and acceleration.

[0096] For example, the instantaneous speed can be determined by the following method: the distance d between adjacent trajectory points is known, and the time interval between the two points is combined (obtained from timestamp difference), according to the formula Determine the instantaneous speed.

[0097] The acceleration can be determined as follows: Based on the instantaneous velocities v1 and v2 of adjacent trajectory points, for adjacent time intervals , calculate the acceleration a: , the same applies to deceleration.

[0098] Further, in this embodiment, the first stability parameter corresponding to the original trajectory point can be determined according to at least one of the distance influencing parameter, the slope influencing parameter and the speed influencing parameter, and the weight coefficient corresponding to the selected parameter. Exemplarily, different influencing parameters correspond to different weight coefficients. In this embodiment, the weighted sum of different influencing parameters can be used as the first stability parameter.

[0099] S220, determining a second stability parameter corresponding to the original trajectory point according to the signal state data corresponding to the original trajectory point and the second weight coefficient.

[0100] The signal status data includes signal strength and signal accuracy, and both the signal strength and signal accuracy can be obtained when the original trajectory points are obtained.

[0101] Accordingly, in some embodiments, the intensity influence data corresponding to the original trajectory point can be determined based on the signal strength corresponding to the original trajectory point and the weight coefficient corresponding to the signal strength; the accuracy influence data corresponding to the original trajectory point can be determined based on the signal accuracy corresponding to the original trajectory point and the weight coefficient corresponding to the signal accuracy; the second stability parameter corresponding to the original trajectory point can be determined based on the intensity influence data and / or the accuracy influence data.

[0102] Specifically, in this embodiment, the precision value corresponding to the original trajectory point can be directly used as the precision influence data; the intensity value corresponding to the original trajectory point can be directly used as the intensity influence data.

[0103] S230: Determine a stability parameter corresponding to the original trajectory point according to the first stability parameter and the second stability parameter.

[0104] Exemplarily, in this embodiment, the weighted sum of the first stability parameter and the second stability parameter may be used as the stability parameter corresponding to the original trajectory point.

[0105] In the above embodiment, a specific method for determining the stability parameter is provided. The stability parameter includes a first stability parameter and a second stability parameter, so that the stability parameter has more reference significance.

[0106] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the process of determining whether the original trajectory point is a target noise point based on the magnitude relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory is described in detail.

[0107] See also Figure 3 The target noise determination steps shown include:

[0108] S310: When the stability parameter of the original trajectory point exceeds a preset stability threshold corresponding to the original trajectory, determine that the original trajectory is a candidate noise point.

[0109] Among them, the candidate noise point is the original trajectory point that may be the target noise point.

[0110] S320: Determine the original trajectory point as a target noise point when the positional relationship between the candidate noise point and the adjacent trajectory point of the candidate noise point is not within a preset area.

[0111] For example, in this embodiment, the target noise point can be selected from the original trajectory points in the following manner: for the noise point candidate point P, obtain its adjacent trajectory points P before and after prev and P next Calculate P prev and P nextThe distance d between the connecting lines and the angle between them and the horizontal According to the trajectory data, the normal distance range of the corresponding road section is calculated [d min , d max ] and the angle range [θ min ,θ max If d is not in [d min , d max ], or Not in [θ min ,θ max ], and then check the slopes of the three points (the original trajectory point and its preceding adjacent trajectory point and the following adjacent trajectory point). During normal driving, the slope changes gently. If deleting P causes a sudden change in the slope, the original trajectory point P is determined to be a non-target noise point; otherwise, it is determined to be a target noise point.

[0112] In the above embodiment, original trajectory points whose stability parameters exceed the preset stability threshold are taken as candidate noise points, and a method for determining target noise points from the candidate noise points is provided, so that the selected target noise points are more accurate.

[0113] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the driving trajectory processing method provided by the present application is introduced in detail.

[0114] See also Figure 4 The driving trajectory processing method shown includes:

[0115] S401, obtaining trajectory association data corresponding to each original trajectory point in the original trajectory;

[0116] S402, for any original trajectory point, determining a first spacing according to a coordinate position of the original trajectory point and a coordinate position of a previous adjacent trajectory point corresponding to the original trajectory point;

[0117] S403, determining a second distance according to the coordinate position of the original trajectory point and the coordinate position of the adjacent trajectory point corresponding to the original trajectory point;

[0118] S404: Determine a distance influence parameter corresponding to the original trajectory point according to the first distance and / or the second distance.

[0119] S405, determining a slope influence parameter corresponding to the original trajectory point according to the horizontal position of the original trajectory point and the horizontal positions of adjacent trajectory points corresponding to the original trajectory point;

[0120] S406, determining a speed influence parameter corresponding to the original trajectory point according to the speed data of the original trajectory point and the speed data of the adjacent trajectory points corresponding to the original trajectory point;

[0121] S407, determining a first stability parameter corresponding to the original trajectory point according to at least one of the distance influencing parameter, the slope influencing parameter and the speed influencing parameter, and a weight coefficient corresponding to the selected parameter;

[0122] S408, determining intensity influence data corresponding to the original trajectory point according to the signal intensity corresponding to the original trajectory point and the weight coefficient corresponding to the signal intensity;

[0123] S409, determining the accuracy impact data corresponding to the original trajectory point according to the signal accuracy corresponding to the original trajectory point and the weight coefficient corresponding to the signal accuracy;

[0124] S410, determining a second stability parameter corresponding to the original trajectory point according to the strength influence data and / or the accuracy influence data;

[0125] S411, determining a stability parameter corresponding to the original trajectory point according to the first stability parameter and the second stability parameter;

[0126] S412, determining a preset stability threshold corresponding to the original trajectory according to a magnitude relationship between stability parameters corresponding to each original trajectory point in the original trajectory and the number of original trajectory points in the original trajectory;

[0127] S413, when the stability parameter of the original trajectory point exceeds a preset stability threshold corresponding to the original trajectory, determining the original trajectory as a candidate noise point;

[0128] S414: Determine the original trajectory point as a target noise point when the positional relationship between the candidate noise point and the adjacent trajectory point of the candidate noise point is not within a preset area.

[0129] S415: When the original trajectory point is a target noise point, remove the target noise point.

[0130] It should be noted that in order to ensure that the driving trajectory is uninterrupted after removing the target noise points, the continuity of the trajectory can be ensured in the following ways: Construct a noise point index set to record the noise point index to be removed. Traverse all trajectory points that have been judged as noise points again, and add the index of the trajectory point that is finally determined to be a noise point to this auxiliary list. Process them one by one from the last element of the set, accurately locate the position of each noise point index in the original trajectory data, and then remove it from the original data set. If you encounter continuous noise points, you need to define the starting and ending indexes of this continuous noise point segment in the original data, and remove the entire noise point segment at one time, so as to avoid the risk of accidentally deleting valid trajectory points and ensure the integrity and accuracy of the original trajectory data.

[0131] After noise removal, there will be discontinuous areas in the original trajectory. At this time, search for adjacent and normal trajectory points. Let the front normal trajectory point be A, its coordinates are (x1, y1), and the back normal trajectory point be B, its coordinates are (x2, y2). For the Kth vacant position, calculate the relative distance ratio r from the point x1 k =k / n+1, calculate the coordinates of the vacant position according to the linear interpolation formula, the horizontal coordinate x=x1+r k *(x2-x1), ordinate y=y1+r k *(y2-y1). Use these calculated coordinates to fill in the gaps one by one, and repair the continuity of the trajectory after removing the target noise.

[0132] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0133] Based on the same inventive concept, the embodiment of the present application also provides a driving trajectory processing device for implementing the driving trajectory processing method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more driving trajectory processing device embodiments provided below can refer to the limitations of the driving trajectory processing method above, and will not be repeated here.

[0134] In an exemplary embodiment, Figure 5 As shown, a driving trajectory processing device is provided, including: a data acquisition module 510, a first determination module 520, a second determination module 530 and a trajectory processing module 540, wherein:

[0135] A data acquisition module 510 is used to acquire trajectory association data corresponding to each original trajectory point in the original trajectory;

[0136] A first determination module 520 is used to determine, for any original trajectory point, a stability parameter corresponding to the original trajectory point according to trajectory association data corresponding to the original trajectory point and a weight coefficient corresponding to each trajectory association data;

[0137] A second determination module 530, configured to determine whether the original trajectory point is a target noise point according to a magnitude relationship between a stability parameter corresponding to the original trajectory point and a preset stability threshold corresponding to the original trajectory;

[0138] The trajectory processing module 540 is used to remove the target noise point when the original trajectory point is the target noise point.

[0139] In one embodiment, the trajectory-associated data includes motion state data and signal state data; the weight coefficient includes a first weight coefficient corresponding to the motion state data and a second weight coefficient corresponding to the signal state data; accordingly, the first determination module 520 includes a first determination unit, which is used to determine the first stability parameter corresponding to the original trajectory point according to the motion state data and the first weight coefficient corresponding to the original trajectory point; a second determination unit, which is used to determine the second stability parameter corresponding to the original trajectory point according to the signal state data and the second weight coefficient corresponding to the original trajectory point; and a third determination unit, which is used to determine the stability parameter corresponding to the original trajectory point according to the first stability parameter and the second stability parameter.

[0140] In one embodiment, the motion state data includes position data and speed data, and the position data includes coordinate position and horizontal position; accordingly, the first determination unit includes a first determination subunit, which is used to determine the distance influence parameter corresponding to the original trajectory point according to the coordinate position of the original trajectory point and the coordinate position of the adjacent trajectory point corresponding to the original trajectory point; a second determination subunit, which is used to determine the slope influence parameter corresponding to the original trajectory point according to the horizontal position of the original trajectory point and the horizontal position of the adjacent trajectory point corresponding to the original trajectory point; a third determination subunit, which is used to determine the speed influence parameter corresponding to the original trajectory point according to the speed data of the original trajectory point and the speed data of the adjacent trajectory point corresponding to the original trajectory point; and a fourth determination subunit, which is used to determine the first stability parameter corresponding to the original trajectory point according to at least one of the distance influence parameter, the slope influence parameter and the speed influence parameter, and the weight coefficient corresponding to the selected parameter.

[0141] In one embodiment, the adjacent trajectory points include front adjacent trajectory points and rear adjacent trajectory points; accordingly, the first determining subunit is specifically used to determine the first spacing according to the coordinate position of the original trajectory point and the coordinate position of the front adjacent trajectory point corresponding to the original trajectory point; determine the second spacing according to the coordinate position of the original trajectory point and the coordinate position of the rear adjacent trajectory point corresponding to the original trajectory point; determine the distance influence parameter corresponding to the original trajectory point according to the first spacing and / or the second spacing.

[0142] In one embodiment, the signal status data includes signal strength and signal accuracy; accordingly, the second determination unit includes a fifth determination subunit, which is used to determine the strength influence data corresponding to the original trajectory point according to the signal strength corresponding to the original trajectory point and the weight coefficient corresponding to the signal strength; a sixth determination subunit, which is used to determine the accuracy influence data corresponding to the original trajectory point according to the signal accuracy corresponding to the original trajectory point and the weight coefficient corresponding to the signal accuracy; and a seventh determination subunit, which is used to determine the second stability parameter corresponding to the original trajectory point according to the strength influence data and / or the accuracy influence data.

[0143] In one embodiment, the second determination module 530 includes a fourth determination unit, which is used to determine that the original trajectory is a candidate noise point when the stability parameter of the original trajectory point exceeds a preset stability threshold corresponding to the original trajectory; and a fifth determination unit, which is used to determine that the original trajectory point is a target noise point when the positional relationship between the candidate noise point and the adjacent trajectory points of the candidate noise point is not within a preset area.

[0144] In one embodiment, the driving trajectory processing device also includes a third determination module, which is used to determine a preset stability threshold corresponding to the original trajectory based on the size relationship between the stability parameters corresponding to each original trajectory point in the original trajectory and the number of original trajectory points in the original trajectory.

[0145] Each module in the above-mentioned driving trajectory processing device can be implemented in whole or in part by software, hardware or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0146] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a driving trajectory processing method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0147] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0148] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0149] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0150] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0151] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0152] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0153] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A driving trajectory processing method, characterized in that: The method comprises: Obtaining trajectory association data corresponding to each original trajectory point in the original trajectory; For any original trajectory point, determine the stability parameter corresponding to the original trajectory point according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each of the trajectory association data; Determining whether the original trajectory point is a target noise point according to a magnitude relationship between a stability parameter corresponding to the original trajectory point and a preset stability threshold corresponding to the original trajectory; In the case where the original trajectory point is a target noise point, the target noise point is removed.

2. The method according to claim 1, characterized in that The trajectory association data includes motion state data and signal state data; the weight coefficient includes a first weight coefficient corresponding to the motion state data and a second weight coefficient corresponding to the signal state data; accordingly, determining the stability parameter corresponding to the original trajectory point according to the trajectory association data corresponding to the original trajectory point and the weight coefficient corresponding to each trajectory association data includes: determining a first stability parameter corresponding to the original trajectory point according to the motion state data corresponding to the original trajectory point and the first weight coefficient; determining a second stability parameter corresponding to the original trajectory point according to the signal state data corresponding to the original trajectory point and the second weight coefficient; A stability parameter corresponding to the original trajectory point is determined according to the first stability parameter and the second stability parameter.

3. The method according to claim 2, characterized in that The motion state data includes position data and speed data, and the position data includes coordinate position and horizontal position; accordingly, determining the first stability parameter corresponding to the original trajectory point according to the motion state data corresponding to the original trajectory point and the first weight coefficient includes: Determine a distance influence parameter corresponding to the original trajectory point according to the coordinate position of the original trajectory point and the coordinate position of an adjacent trajectory point corresponding to the original trajectory point; Determine a slope influence parameter corresponding to the original trajectory point according to the horizontal position of the original trajectory point and the horizontal positions of adjacent trajectory points corresponding to the original trajectory point; Determine a speed influence parameter corresponding to the original trajectory point according to the speed data of the original trajectory point and the speed data of an adjacent trajectory point corresponding to the original trajectory point; The first stability parameter corresponding to the original trajectory point is determined according to at least one of the distance influencing parameter, the slope influencing parameter and the speed influencing parameter, and a weight coefficient corresponding to the selected parameter.

4. The method according to claim 3, characterized in that The adjacent track points include a front adjacent track point and a rear adjacent track point; accordingly, determining the distance influence parameter corresponding to the original track point according to the coordinate position of the original track point and the coordinate position of the adjacent track point corresponding to the original track point includes: Determine a first spacing according to the coordinate position of the original trajectory point and the coordinate position of the previous adjacent trajectory point corresponding to the original trajectory point; Determine a second spacing according to the coordinate position of the original trajectory point and the coordinate position of the adjacent trajectory point corresponding to the original trajectory point; A distance influence parameter corresponding to the original trajectory point is determined according to the first distance and / or the second distance.

5. The method according to claim 2, characterized in that: The signal state data includes signal strength and signal accuracy; accordingly, determining the second stability parameter corresponding to the original trajectory point according to the signal state data corresponding to the original trajectory point and the second weight coefficient includes: Determining intensity influence data corresponding to the original trajectory point according to the signal intensity corresponding to the original trajectory point and the weight coefficient corresponding to the signal intensity; Determining the precision impact data corresponding to the original trajectory point according to the signal precision corresponding to the original trajectory point and the weight coefficient corresponding to the signal precision; A second stability parameter corresponding to the original trajectory point is determined according to the strength influence data and / or the accuracy influence data.

6. The method according to any one of claims 1 to 5, characterized in that The determining whether the original trajectory point is a target noise point according to a magnitude relationship between a stability parameter corresponding to the original trajectory point and a preset stability threshold corresponding to the original trajectory includes: When the stability parameter of the original trajectory point exceeds a preset stability threshold corresponding to the original trajectory, determining the original trajectory as a candidate noise point; When the positional relationship between the candidate noise point and the adjacent trajectory point of the candidate noise point is not within a preset area, the original trajectory point is determined to be a target noise point.

7. The method according to any one of claims 1 to 5, characterized in that Before determining whether the original trajectory point is a target noise point according to the magnitude relationship between the stability parameter corresponding to the original trajectory point and the preset stability threshold corresponding to the original trajectory, the method further includes: The preset stability threshold corresponding to the original trajectory is determined according to the magnitude relationship between the stability parameters corresponding to the original trajectory points in the original trajectory and the number of the original trajectory points in the original trajectory.

8. A driving trajectory processing device, characterized in that: The device comprises: A data acquisition module, used to acquire trajectory association data corresponding to each original trajectory point in the original trajectory; A first determination module is used to determine, for any original trajectory point, a stability parameter corresponding to the original trajectory point according to trajectory association data corresponding to the original trajectory point and a weight coefficient corresponding to each of the trajectory association data; A second determination module, configured to determine whether the original trajectory point is a target noise point according to a magnitude relationship between a stability parameter corresponding to the original trajectory point and a preset stability threshold corresponding to the original trajectory; The trajectory processing module is used to remove the target noise point when the original trajectory point is the target noise point.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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