CN111784268A

CN111784268A - Identification object determination method and device, electronic equipment and computer storage medium

Info

Publication number: CN111784268A
Application number: CN202010789762.XA
Authority: CN
Inventors: 季芸; 卓兴翔; 吴云阁; 吴远; 吴辉斌
Original assignee: Rajax Network Technology Co Ltd
Current assignee: Rajax Network Technology Co Ltd
Priority date: 2020-08-07
Filing date: 2020-08-07
Publication date: 2020-10-16

Abstract

The embodiment of the disclosure discloses a method and a device for determining an identification object, an electronic device and a computer storage medium, wherein the method for determining the identification object comprises the following steps: determining a set of identification objects; calculating the speed corresponding to the identification object in the identification object set; and when the speed corresponding to the identification object meets a first preset condition, determining that the identification object is a target identification object. The technical scheme is simple to implement, and can quickly and effectively identify the drifting GPS positioning point, so that the positioning track can be effectively corrected, correct data support is provided for subsequent decisions such as path planning and logistics scheduling, the correctness of position positioning, path data acquisition and path planning is guaranteed, and the correctness, effectiveness and efficiency of subsequent operations such as logistics scheduling are improved.

Description

Identification object determination method and device, electronic equipment and computer storage medium

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to a method and an apparatus for identifying an object, an electronic device, and a computer storage medium.

Background

With the development of internet technology, more and more service providers provide information through internet platforms, and many internet services need logistics distributors to distribute, so that the logistics scheduling quality is of great importance to the improvement of distribution efficiency and the service quality of the internet platforms. In logistics scheduling, the accuracy of the distribution path data of a distributor is decisive for the collection of subsequent path planning training data and the accuracy of a path planning result, in the prior art, a GPS positioning device is usually installed at the distributor to periodically collect the real-time position of the distributor, so as to generate a distribution path when the distributor executes a distribution task, and the obtained GPS positioning data can also be used as an important data source for detecting the behavior of the distributor. However, in practical applications, due to the influence of errors such as satellite orbit geometric position errors, satellite clock errors, receiver clock errors, troposphere and ionosphere errors, multipath effect errors, satellite selection availability errors, and sudden change errors caused by other environments or receiving systems, the GPS positioning points often drift, which seriously affects the correctness of the positioning of the distributors, the acquisition of path data, and the path planning, and therefore, the drifting GPS positioning points need to be accurately identified to improve the accuracy of the positioning of the distributors, and correct data support is provided for the subsequent decisions such as path planning and logistics scheduling.

Disclosure of Invention

The embodiment of the disclosure provides a method and a device for determining an identification object, electronic equipment and a computer storage medium.

In a first aspect, an embodiment of the present disclosure provides a method for determining an identified object.

Specifically, the method for determining the identification object includes:

determining a set of identification objects;

calculating the speed corresponding to the identification object in the identification object set;

and when the speed corresponding to the identification object meets a first preset condition, determining that the identification object is a target identification object.

With reference to the first aspect, in a first implementation manner of the first aspect, the determining a set of identifying objects includes:

acquiring a marked object sequence, wherein the marked object sequence comprises one or more marked objects arranged according to a marked object generation time sequence;

calculating the generation time difference between adjacent identification objects according to the generation time of the identification objects;

and determining the combination formed by the identification objects with the generation time difference smaller than a preset time difference threshold value as the identification object set.

With reference to the first aspect and the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the calculating a speed corresponding to a token object in the token object set includes:

calculating the average speed between adjacent identification objects in the identification object set;

and determining the average speed between the adjacent identification objects as the speed corresponding to the identification object in the adjacent identification objects.

With reference to the first aspect, the first implementation manner of the first aspect, and the second implementation manner of the first aspect, in a third implementation manner of the first aspect, the calculating an average speed between adjacent identification objects in the identification object set includes:

acquiring the position and the generation time of the identification object in the adjacent identification object;

calculating the distance between the adjacent identification objects according to the positions of the identification objects;

calculating the time difference between the adjacent identification objects according to the generation time of the identification objects;

and dividing the distance by the time difference to obtain the average speed between the adjacent identification objects.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, and the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the distance is a minimum spherical distance.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, and the fourth implementation manner of the first aspect, in a fifth implementation manner of the first aspect, when a speed corresponding to the identification object meets a first preset condition, the determining that the identification object is a target identification object includes:

when the speed corresponding to the identification object is equal to or greater than a preset speed threshold, determining that the identification object is the target identification object;

and when the speed corresponding to the identification object is smaller than the preset speed threshold, determining whether the identification object is the target identification object based on the speed parameter of a preset window where the identification object is located.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, and the fifth implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the determining, based on the speed parameter of the preset object window in which the identification object is located, whether the identification object is the target identification object includes:

determining a preset object window where the identification object is located;

calculating the mean value and the standard deviation of the corresponding speeds of all the identification objects in the preset object window;

and when the speed, the mean value and the standard deviation corresponding to the identification object meet a second preset condition, determining the identification object as the target identification object.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, and the sixth implementation manner of the first aspect, in a seventh implementation manner of the first aspect, the identification object is a detected GPS data point.

With reference to the first aspect, the first implementation manner of the first aspect, the second implementation manner of the first aspect, the third implementation manner of the first aspect, the fourth implementation manner of the first aspect, the fifth implementation manner of the first aspect, the sixth implementation manner of the first aspect, and the seventh implementation manner of the first aspect, in an eighth implementation manner of the first aspect, the embodiment of the present disclosure further includes:

performing at least one of the following according to the target identification object:

route planning, traffic control, traffic guidance, traffic restrictions, or adjusting navigation data.

In a second aspect, an apparatus for determining an identified object is provided in the embodiments of the present disclosure.

Specifically, the apparatus for determining an identification object includes:

a first determination module configured to determine a set of identifying objects;

the calculating module is configured to calculate the speed corresponding to the identification object in the identification object set;

the second determination module is configured to determine that the identification object is a target identification object when the speed corresponding to the identification object meets a first preset condition.

With reference to the second aspect, in a first implementation manner of the second aspect, the first determining module is configured to:

With reference to the second aspect and the first implementation manner of the second aspect, in a second implementation manner of the second aspect, the computing module is configured to:

With reference to the second aspect, the first implementation manner of the second aspect, and the second implementation manner of the second aspect, in a third implementation manner of the second aspect, the calculating an average velocity between adjacent identification objects in the identification object set is configured to:

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, and the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the distance is a minimum spherical distance.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, and the fourth implementation manner of the second aspect, in a fifth implementation manner of the second aspect, the second determining module is configured to:

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, and the fifth implementation manner of the second aspect, in a sixth implementation manner of the second aspect, the determining, based on the speed parameter of the preset object window in which the identification object is located, whether the identification object is a part of the target identification object is configured to:

determining a preset object window where the identification object is located;

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, and the sixth implementation manner of the second aspect, in a seventh implementation manner of the second aspect, the identification object is a detected GPS data point.

With reference to the second aspect, the first implementation manner of the second aspect, the second implementation manner of the second aspect, the third implementation manner of the second aspect, the fourth implementation manner of the second aspect, the fifth implementation manner of the second aspect, the sixth implementation manner of the second aspect, and the seventh implementation manner of the second aspect, in an eighth implementation manner of the second aspect, the embodiment of the present disclosure further includes:

an execution module configured to execute at least one of the following according to the target identification object:

In a third aspect, the disclosed embodiments provide an electronic device, comprising a memory and at least one processor, wherein the memory is configured to store one or more computer instructions, and wherein the one or more computer instructions are executed by the at least one processor to implement the method steps of the above-mentioned identification object determination method.

In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium for storing computer instructions for an identifying object determining apparatus, where the computer instructions include computer instructions for executing the identifying object determining method to determine an identifying object for the identifying object determining apparatus.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

the technical scheme firstly determines a GPS positioning point set to be analyzed, and realizes the identification of the drifting GPS positioning point by means of the speed corresponding to the GPS positioning point in the set. The technical scheme is simple to implement, and can quickly and effectively identify the drifting GPS positioning point, so that the positioning track can be effectively corrected, correct data support is provided for subsequent decisions such as path planning and logistics scheduling, the correctness of position positioning, path data acquisition and path planning is guaranteed, and the correctness, effectiveness and efficiency of subsequent operations such as logistics scheduling are improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:

fig. 1 illustrates a flow diagram of a method of identifying an object according to an embodiment of the present disclosure;

FIG. 2 shows a schematic diagram of a GPS fix preset object window according to an embodiment of the present disclosure;

FIG. 3 illustrates a diagram of a drifting GPS fix point identification result according to an embodiment of the present disclosure;

fig. 4 illustrates a block diagram of a structure of an identification object determination apparatus according to an embodiment of the present disclosure;

FIG. 5 shows a block diagram of an electronic device according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of a computer system suitable for implementing the identification object determination method according to an embodiment of the present disclosure.

Detailed Description

Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.

In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.

It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

The technical scheme provided by the embodiment of the disclosure firstly determines a GPS positioning point set to be analyzed, and realizes the identification of the drifting GPS positioning point by means of the speed corresponding to the GPS positioning point in the set. The technical scheme is simple to implement, and can quickly and effectively identify the drifting GPS positioning point, so that the positioning track can be effectively corrected, correct data support is provided for subsequent decisions such as path planning and logistics scheduling, the correctness of position positioning, path data acquisition and path planning is guaranteed, and the correctness, effectiveness and efficiency of subsequent operations such as logistics scheduling are improved.

Fig. 1 shows a flowchart of a method for identifying an object according to an embodiment of the present disclosure, as shown in fig. 1, the method for identifying an object includes the following steps S101 to S103:

in step S101, a set of identification objects is determined;

in step S102, calculating a speed corresponding to the identification object in the identification object set;

in step S103, when the speed corresponding to the identification object meets a first preset condition, it is determined that the identification object is a target identification object.

As mentioned above, with the development of internet technology, more and more service providers provide information through internet platforms, and many internet services require logistics distributors to distribute, so the logistics scheduling quality is very important for improving the distribution efficiency and the service quality of the internet platforms. In logistics scheduling, the accuracy of the distribution path data of a distributor is decisive for the collection of subsequent path planning training data and the accuracy of a path planning result, in the prior art, a GPS positioning device is usually installed at the distributor to periodically collect the real-time position of the distributor, so as to generate a distribution path when the distributor executes a distribution task, and the obtained GPS positioning data can also be used as an important data source for detecting the behavior of the distributor. However, in practical applications, due to the influence of errors such as satellite orbit geometric position errors, satellite clock errors, receiver clock errors, troposphere and ionosphere errors, multipath effect errors, satellite selection availability errors, and sudden change errors caused by other environments or receiving systems, the GPS positioning points often drift, which seriously affects the correctness of the positioning of the distributors, the acquisition of path data, and the path planning, and therefore, the drifting GPS positioning points need to be accurately identified to improve the accuracy of the positioning of the distributors, and correct data support is provided for the subsequent decisions such as path planning and logistics scheduling.

In the prior art, for the condition of GPS positioning point drift, a Kalman filtering processing mode is usually adopted, the Kalman filtering is the commonly used optimal estimation in the combined navigation data processing, when a system model and an observation model of combined navigation are determined, the resolving precision is high, but the Kalman filtering excessively depends on the statistical characteristics of system noise and observation noise, so that the method is more suitable for a linear system. In order to increase the processing capacity of a nonlinear system, an Extended Kalman Filter (EKF) algorithm is usually used, but both Kalman and EKF assume that an error model of the system is gaussian distributed, and in an actual scene, GPS positioning is easily affected by an external environment to generate sudden changes, so that a statistical characteristic of observation noise is seriously deviated from an actual situation, thereby affecting the optimal estimation of Kalman and EKF, and causing filtering divergence in serious cases.

For the condition of sudden change of the GPS positioning data, the common methods include particle filtering, Adaptive Kalman Filter (AKF), and Adaptive Robust Kalman Filter (ARKF). The method mainly estimates the statistical characteristics of observation noise through the statistic of measurement information, wherein the particle filter needs a large amount of samples to continuously update the parameters of a particle filter model, and the calculation amount is large; the covariance of the measurement information of the AKF algorithm is obtained through maximum likelihood estimation, the inhibition effect is limited, and an accumulated error exists; the ARKF algorithm constructs an equivalent covariance matrix according to the idea of selecting weight filtering, and the method is simple and effective, but is limited by observation information. In addition, a GPS data processing method suitable for a special scene such as road network matching may be used. However, in practical application, the distributor involves various irregular variable movements such as stationary waiting, walking and riding during distribution, and is a highly complex nonlinear system, and obviously, the Kalman and EKF methods based on the error model assumption of gaussian distribution are not suitable for GPS data processing of the distributor; in addition, due to the complexity of the distribution paths and the moving tracks of the distributors, the feasibility of the method for correcting the deviation through road network matching in a special passing area is greatly reduced.

On the other hand, due to the fact that the behavior of the distributor and the positioning devices have certain differences and are influenced by complex environments, the positioning data acquired by the positioning devices such as mobile phone GPS sensors sensing various scenes on the distribution link of the distributor are complex. Meanwhile, due to the fact that the number of distributors is large and the acquisition frequency of the positioning data is high, the positioning data generated every day can reach the GB or even TB scale, and the large-scale positioning data is available, therefore, the collected off-line time sequence GPS original data needs to be effectively and efficiently analyzed, a drifting GPS positioning data set is provided, and then the GPS positioning data set is generated to serve as basic data of each follow-up algorithm and service. Under the circumstances, a simple, efficient and effective method for identifying a lightweight drifting GPS positioning point is needed to realize fast processing of massive GPS positioning data.

In view of the above drawbacks, in this embodiment, a method for identifying a landmark object is proposed, which first determines a set of GPS fixes to be analyzed and identifies a drifting GPS fix by means of the velocities corresponding to the GPS fixes in the set. The technical scheme is simple to implement, and can quickly and effectively identify the drifting GPS positioning point, so that the positioning track can be effectively corrected, correct data support is provided for subsequent decisions such as path planning and logistics scheduling, the correctness of position positioning, path data acquisition and path planning is guaranteed, and the correctness, effectiveness and efficiency of subsequent operations such as logistics scheduling are improved.

In an optional implementation manner of this embodiment, the identification object refers to an object that is generated through an identification behavior, and may be normal, correct, or abnormal or wrong, and is provided with a generation time correspondingly, where the identification behavior may be, for example, a GPS positioning behavior, at this time, the identification object may be a detected GPS data point, that is, a GPS positioning point, the GPS positioning point may be a correct GPS positioning point, or an abnormal GPS positioning point that is affected by an error and has drifted, and the generation time corresponding to the GPS positioning point is time for generating the GPS positioning point. Of course, the identification behavior may also be other identification behaviors, which are not specifically limited in the present disclosure, but for convenience of description, the technical solution of the present disclosure is explained and explained below by taking the identification behavior as a GPS positioning behavior and taking an identification object as a GPS positioning point as an example.

In an optional implementation manner of this embodiment, the set of identification objects refers to a set formed by identification objects to be analyzed, which need to be analyzed to identify whether an abnormal identification object exists therein, that is, a target identification object.

In an optional implementation manner of this embodiment, the speed corresponding to the identification object refers to a state parameter corresponding to the identification object and capable of characterizing a position relationship between a certain identification object and another identification object, especially an adjacent identification object. For example, if a certain identification object has a fast speed, which means that the identification object is at least far away from the adjacent identification object, the identification object is likely to be an abnormal identification object.

In an optional implementation manner of this embodiment, the step S101, that is, the step of determining the set of identification objects, may include the following steps:

The GPS device normally generates GPS fix points at a fixed frequency, for example, every 2 seconds, thereby obtaining a sequence of GPS fix points, and in the sequence of GPS fix points, the GPS fix points are arranged in order from the morning to the evening according to the generation time. However, in practical applications, due to reasons such as that a distributor turns off a GPS device, a failure of the GPS device, and the like, the GPS positioning data cannot be acquired for a long time or the acquired GPS positioning data have a long interval, and if the GPS positioning point sequence is considered as an object, the missing or long-interval GPS positioning data may interfere with identification and judgment of an abnormal GPS positioning point in the GPS positioning point sequence, thereby possibly causing misjudgment of the abnormal GPS positioning point. For example, if a certain GPS positioning point sequence includes 200 GPS positioning points, the first 100 GPS positioning points are GPS positioning points generated according to a fixed frequency of 2 seconds, but after the 100 th GPS positioning point is generated, the GPS positioning device has a short fault, and returns to normal after 20 seconds, and then the GPS positioning point is generated according to a fixed frequency of 2 seconds, then there is a time difference of 20 seconds between the generation time of the 101 th GPS positioning point and the generation time of the 100 th GPS positioning point, if the above is described: if the speed corresponding to a certain identification object is fast, that means that the identification object is at least far away from the adjacent identification object, the identification object is likely to be an abnormal identification object, and then the 101 th GPS positioning point will be determined as an abnormal GPS positioning point, but actually the GPS positioning point is not an abnormal GPS positioning point but a normal GPS positioning point, that is, at this time, the abnormal GPS positioning point is misjudged.

In consideration of the above possibility of erroneous determination, in this embodiment, the GPS positioning point sequence, i.e., the set of identification objects, which is the basis of the determination of the abnormal GPS positioning point is regenerated based on the generation time difference between the adjacent identification objects in the identification object sequence. Specifically, firstly, a tag object sequence, that is, a relatively complete tag object sequence, is obtained, where the tag object sequence includes one or more tag objects arranged according to a tag object generation time sequence; then, calculating the generation time difference between adjacent identification objects according to the generation time of the identification objects; and finally, determining the combination formed by the identification objects with the generation time difference smaller than a preset time difference threshold value as the identification object set. The preset time difference threshold value can be set according to the requirements of practical application, and the specific value of the preset time difference threshold value is not specifically limited by the disclosure. For example, if the normal time difference between the GPS positioning points is 2 seconds, that is, the GPS device generates GPS positioning points at regular time intervals of 2 seconds, the preset time difference threshold may be set to 10 seconds, that is, the GPS positioning points with the time difference between adjacent GPS positioning points in the GPS positioning point sequence being less than 10 seconds may be taken as objects to be analyzed together, that is, these GPS positioning points all fall into the subsequent analyzed GPS positioning point set.

In an optional implementation manner of this embodiment, the identified object sequence may include one or more identified object sets, and when the identified object sequence includes a plurality of identified object sets, the identification of the target identified object may be performed on each identified object set according to the above scheme.

In an optional implementation manner of this embodiment, the step S102, that is, the step of calculating the speed corresponding to the identification object in the identification object set, may include the following steps:

In order to effectively obtain the speed corresponding to the identification object in the identification object set to determine the position relationship between a certain identification object and other identification objects, such as adjacent identification objects, in this embodiment, first, an average speed between adjacent identification objects in the identification object set is calculated; and then, determining the average speed between the adjacent identification objects as the speed corresponding to the designated identification object in the adjacent identification objects, wherein the designated identification object can be determined and set according to the requirements of practical application, and the disclosure does not specially limit the speed. For example, the average speed between two adjacent identification objects may be both used as the speed corresponding to the previous identification object in the adjacent identification objects, or both may be used as the speed corresponding to the next identification object in the adjacent identification objects.

In an optional implementation manner of this embodiment, the step of calculating an average velocity between adjacent identification objects in the identification object set may include the following steps:

In this embodiment, the average speed between the adjacent identification objects in the identification object set is calculated by using the positions and the generation times of the identification objects in the adjacent identification objects, specifically, the positions and the generation times of the identification objects in the adjacent identification objects are firstly obtained; then calculating the distance between the adjacent identification objects according to the positions of the identification objects; calculating the time difference between the adjacent identification objects according to the generation time of the identification objects; and finally, dividing the distance by the time difference to obtain the average speed between the adjacent identification objects.

In an optional implementation manner of this embodiment, the distance is a minimum spherical distance, and in this implementation, it is assumed that the position information of the adjacent tagged objects a and B are (lat) respectively_A，lon_A) And (lat)_B，lon_B) And the time difference between identifying objects a and B is t, then the minimum spherical distance between identifying objects a and B can be expressed as:

d＝2Racsinf，

wherein, R is the radius of the earth,

the average velocity between adjacent identifying objects a and B can be expressed as:

v＝d/t。

of course, the distance may be selected to be other distances, and the present disclosure is not particularly limited to the specific selection of the distance calculation method.

In an optional implementation manner of this embodiment, in step S103, that is, when the speed corresponding to the identification object meets the first preset condition, the step of determining that the identification object is the target identification object may include the following steps:

In the above, the speed corresponding to the identification object can represent the position relationship between the identification object and other identification objects, especially between adjacent identification objects, for example, if the speed corresponding to a certain identification object is fast, it indicates that the identification object is at least far away from the adjacent identification object, and then the identification object is likely to be an abnormal identification object. Specifically, if the speed corresponding to the identification object is equal to or greater than a preset speed threshold, determining that the identification object is an abnormal identification object, that is, the target identification object; and if the speed corresponding to the identification object is smaller than the preset speed threshold, determining whether the identification object is an abnormal identification object, namely the target identification object, based on the speed parameter of a preset window where the identification object is located. The preset speed threshold may be set according to a requirement of an actual application, for example, the preset speed threshold may be set to a maximum traveling speed that can be reached by a carrier that generates the identification object, such as 20 m/s, and if a speed corresponding to a certain identification object is equal to or greater than the preset speed threshold, it is considered that the identification object is not likely to be obtained by normal traveling of the carrier that generates the identification object, so that it may be determined that the identification object is an abnormal identification object, that is, the target identification object.

In an optional implementation manner of this embodiment, the step of determining whether the identification object is the target identification object based on the speed parameter of the preset object window in which the identification object is located may include the following steps:

determining a preset object window where the identification object is located;

In this embodiment, when the speed corresponding to the identification object is less than the preset speed threshold and it cannot be determined whether the identification object is the target identification object according to the preset speed threshold, it is determined whether the identification object is the target identification object based on the speed parameter of the preset window in which the identification object is located. Specifically, a preset object window where the identification object is located is determined, where the size of the preset object window may be set according to the needs of practical applications, for example, the preset object window may be determined according to a reasonable feasibility change interval of the identification object, and assuming that the generation time interval of the GPS positioning points is 2 seconds, for a certain GPS positioning point, taking the certain GPS positioning point as a central point, and the duration 2 × 6 of the range corresponding to the left and right positioning points is 12 seconds as a reasonable behavior change time interval of a distributor, the preset object window may be set such that the GPS positioning point T1, T2, T3, T4, T5, T6, T7, T8, T9 are a part of a GPS positioning point set, for the GPS positioning point T5, the GPS T5 is taken as a central point, the ranges corresponding to the left and right positioning points are used as the preset object window, as shown by the dashed line frame in fig. 2; then calculating the mean value mu and the standard deviation sigma of the corresponding speeds of all the identification objects in the preset object window; if the speed, the mean value and the standard deviation corresponding to the identification object satisfy a second preset condition, for example, if the speed, the mean value and the standard deviation satisfy v_iIf μ > 3 σ, the identification object can be considered to deviate from the region formed by other identification objects, and then it can be determined that the identification object is an abnormal identification object, i.e. the target identification object. The second preset condition may also be set as another condition, as long as the second preset condition can represent the position association relationship between the identification object or the speed corresponding to the identification object and another identification object, such as an adjacent identification object.

In an optional implementation manner of this embodiment, the method further includes:

In this implementation, the target identification object determined above may be used as basic data for path planning, traffic control, traffic guidance, traffic restrictions, or adjusting navigation data. Taking path planning as an example, after determining an abnormal GPS positioning point, i.e. the target identification object, the abnormal GPS positioning point in the acquired GPS positioning points may be deleted, and then path planning may be performed using the remaining GPS positioning points as basic data.

Based on the above technical solution, the target identification object in the identification object set can be quickly and effectively identified, as shown in fig. 3, the GPS positioning points T4, T5, and T6 are finally identified drifting GPS positioning points.

The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.

Fig. 4 shows a block diagram of a structure of an identification object determination apparatus according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device by software, hardware, or a combination of both. As shown in fig. 4, the identification object determination apparatus includes:

a first determination module 401 configured to determine a set of identifying objects;

a calculating module 402 configured to calculate a speed corresponding to an identification object in the identification object set;

a second determining module 403, configured to determine that the identification object is a target identification object when the speed corresponding to the identification object satisfies a first preset condition.

In view of the above drawbacks, in this embodiment, a marker object determination device is proposed, which first determines a set of GPS fix points to be analyzed and enables identification of a drifting GPS fix point by means of the velocities corresponding to the GPS fix points in the set. The technical scheme is simple to implement, and can quickly and effectively identify the drifting GPS positioning point, so that the positioning track can be effectively corrected, correct data support is provided for subsequent decisions such as path planning and logistics scheduling, the correctness of position positioning, path data acquisition and path planning is guaranteed, and the correctness, effectiveness and efficiency of subsequent operations such as logistics scheduling are improved.

In an optional implementation manner of this embodiment, the first determining module 401 may be configured to:

In an optional implementation manner of this embodiment, the calculation module 402 may be configured to:

In an optional implementation manner of this embodiment, the calculating the average speed between adjacent identification objects in the identification object set may be configured to:

In an optional implementation manner of this embodiment, the distance is a minimum spherical distance, and in this implementation, it is assumed that the position information of the adjacent tagged objects a and B are (lat) respectively_A，lon_A) And (lat)_B，lon_B) Identifying a time difference between objects A and B as t, then identifying a minimum sphere between objects A and BThe face distance may be expressed as:

d＝2Racsinf，

wherein, R is the radius of the earth,

v＝d/t。

In an optional implementation manner of this embodiment, the second determining module 403 may be configured to:

In an optional implementation manner of this embodiment, the determining, based on the speed parameter of the preset object window in which the identification object is located, whether the identification object is part of the target identification object may be configured to:

determining a preset object window where the identification object is located;

In this embodiment, when the speed corresponding to the identification object is less than the preset speed threshold and it cannot be determined whether the identification object is the target identification object according to the preset speed threshold, it is determined whether the identification object is the target identification object based on the speed parameter of the preset window in which the identification object is located. Specifically, a preset object window where the identification object is located is determined, where the size of the preset object window may be set according to the needs of practical applications, for example, the preset object window may be determined according to a reasonable feasibility change interval of the identification object, and assuming that the generation time interval of the GPS positioning points is 2 seconds, for a certain GPS positioning point, taking the certain GPS positioning point as a central point, and the duration 2 × 6 of the range corresponding to the left and right positioning points is 12 seconds as a reasonable behavior change time interval of a distributor, the preset object window may be set as a GPS positioning point window formed by the left and right GPS positioning points and the certain GPS positioning point as a central point, as shown in fig. 2, the GPS positioning points T1, T2, T3, T4, T5, T6, T7, T8, and T3526 are shown in fig. 2,The T9 is a part of a GPS positioning point set, and for the GPS positioning point T5, the ranges corresponding to the left and right positioning points, which use the GPS positioning point T5 as a central point, are taken as the preset object window, as shown by the dashed line box in fig. 2; then calculating the mean value mu and the standard deviation sigma of the corresponding speeds of all the identification objects in the preset object window; if the speed, the mean value and the standard deviation corresponding to the identification object satisfy a second preset condition, for example, if the speed, the mean value and the standard deviation satisfy v_iIf μ > 3 σ, the identification object can be considered to deviate from the region formed by other identification objects, and then it can be determined that the identification object is an abnormal identification object, i.e. the target identification object. The second preset condition may also be set as another condition, as long as the second preset condition can represent the position association relationship between the identification object or the speed corresponding to the identification object and another identification object, such as an adjacent identification object.

In an optional implementation manner of this embodiment, the apparatus further includes:

The present disclosure also discloses an electronic device, fig. 5 shows a block diagram of an electronic device according to an embodiment of the present disclosure, and as shown in fig. 5, the electronic device 500 includes a memory 501 and a processor 502; wherein the content of the first and second substances,

the memory 501 is used to store one or more computer instructions, which are executed by the processor 502 to implement the above-described method steps.

As shown in fig. 6, the computer system 600 includes a processing unit 601 which can execute various processes in the above-described embodiments according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the system 600 are also stored. The processing unit 601, the ROM602, and the RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary. The processing unit 601 may be implemented as a CPU, a GPU, a TPU, an FPGA, an NPU, or other processing units.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.

As another aspect, the present disclosure also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above-described embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.

Claims

1. A method of identifying an object, comprising:

determining a set of identification objects;

2. The method of claim 1, the determining a set of identifying objects, comprising:

3. The method according to claim 1 or 2, wherein the calculating the speed corresponding to the identification object in the identification object set comprises:

4. The method of claim 3, wherein calculating an average velocity between adjacent identifying objects in the set of identifying objects comprises:

5. An identified object determining apparatus comprising:

6. The apparatus of claim 5, the first determination module configured to:

7. The apparatus of claim 5 or 6, the computing module configured to:

8. The apparatus of claim 7, the portion that calculates an average velocity between adjacent identifying objects in the set of identifying objects configured to:

9. An electronic device comprising a memory and at least one processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the at least one processor to implement the method steps of any one of claims 1-4.

10. A computer-readable storage medium having stored thereon computer instructions, characterized in that the computer instructions, when executed by a processor, carry out the method steps of any of claims 1-4.