CN113868555A

CN113868555A - Track retrieval method, device, equipment and storage medium

Info

Publication number: CN113868555A
Application number: CN202111145667.7A
Authority: CN
Inventors: 李哲男; 张天宇; 赵辉; 蒋冰
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2021-09-28
Filing date: 2021-09-28
Publication date: 2021-12-31

Abstract

The present disclosure provides a trajectory retrieval method, apparatus, device and storage medium, which relate to the field of computer technology, in particular to the field of artificial intelligence, and specifically to the technical fields of computer vision, intelligent search and intelligent transportation. The specific implementation scheme is as follows: mapping the area to be retrieved to a standard plane, and carrying out grid coding on the mapped standard plane by adopting a preset curve; determining a target coding array of the area to be retrieved according to a grid coding result associated with the area to be retrieved; and determining target track data associated with the target coding array according to the target coding array and the index relation between the original track data and the original coding array. The efficiency and accuracy of track retrieval can be improved.

Description

Track retrieval method, device, equipment and storage medium

Technical Field

The present disclosure relates to the field of computer technology, and more particularly to the field of artificial intelligence, and more particularly to the field of computer vision, intelligent search, and intelligent transportation technologies.

Background

With the development of internet technology, the positioning technology of the mobile terminal is more and more widely applied. Since mobile terminals generate one trace point every second, various mobile terminals can generate hundreds of billions of trace points every day, which presents a huge challenge to spatial location-based trace retrieval.

Disclosure of Invention

The disclosure provides a track retrieval method, a track retrieval device, a track retrieval equipment and a storage medium.

According to an aspect of the present disclosure, there is provided a trajectory retrieval method including:

mapping the area to be retrieved to a standard plane, and carrying out grid coding on the mapped standard plane by adopting a preset curve;

determining a target coding array of the area to be retrieved according to a grid coding result associated with the area to be retrieved;

and determining target track data associated with the target coding array according to the target coding array and the index relation between the original track data and the original coding array.

According to another aspect of the present disclosure, there is provided an electronic device including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the trajectory retrieval method of any of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform a trajectory retrieval method of any one of the embodiments of the present disclosure.

According to the technology disclosed by the invention, the efficiency and the accuracy of track retrieval are improved. Provides a new idea for searching the space trajectory.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

fig. 1 is a flowchart of a trajectory retrieval method provided according to an embodiment of the present disclosure;

FIG. 2A is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure;

fig. 2B is a schematic diagram illustrating a curve filling effect of standard planes at different trellis encoding precisions provided according to an embodiment of the present disclosure;

fig. 2C is a schematic diagram of a trellis encoding result provided according to an embodiment of the present disclosure;

FIG. 3A is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure;

FIG. 3B is a schematic diagram illustrating an index relationship between original track data and original encoded data according to an embodiment of the disclosure;

FIG. 4A is a schematic diagram of a target coding array and an original coding array provided in accordance with an embodiment of the present disclosure;

FIG. 4B is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure;

FIG. 5A is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure;

FIG. 5B is a conceptual framework diagram of trajectory retrieval provided in accordance with an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of a trajectory retrieval device provided in accordance with an embodiment of the present disclosure;

fig. 7 is a block diagram of an electronic device for implementing a trajectory retrieval method of an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

Fig. 1 is a flowchart of a trajectory retrieval method provided according to an embodiment of the present disclosure. The embodiment of the disclosure is suitable for retrieving the original track data in the area to be retrieved, and is particularly suitable for retrieving the original track data in the area to be retrieved from a large amount of original track data. The method can be executed by a track retrieval device, which can be implemented in software and/or hardware and can be integrated in an electronic device with a track retrieval function. As shown in fig. 1, the track retrieval method provided in this embodiment may include:

s101, mapping the area to be retrieved to a standard plane, and carrying out grid coding on the mapped standard plane by adopting a preset curve.

The area to be retrieved in this embodiment is an area that needs to be retrieved for the track. The area to be retrieved can be determined according to a track retrieval request sent by a retrieval demand party. Alternatively, the track retrieval request may directly include the area to be retrieved, for example, a certain city in city a. The track retrieval request may also include location information for determining the area to be retrieved, and the area to be retrieved is determined according to the location information. For example, if at least three position points are given, an area surrounded by the at least three position points may be used as the area to be retrieved; if a retrieval center, a retrieval radius and the like are given, taking the retrieval center as a central point, and taking an area within the range of the retrieval radius as an area to be retrieved.

The standard plane of the embodiment may be a two-dimensional plane obtained by performing dimensionality reduction expansion on a three-dimensional sphere plane of the earth. The embodiment may be that the three-dimensional sphere plane of the earth is expanded into a standard plane, that is, the standard plane includes all the regions on the earth; the three-dimensional sphere plane can also be expanded into a plurality of standard planes, for example, each area on the earth can be projected onto 6 faces of the circumscribed cube of the earth, so as to obtain 6 square standard planes. That is, each standard plane includes a part of the region on the earth, and the 6 standard planes combined together can include all the regions on the earth. The specific selection of several standard planes can be determined according to actual requirements.

The preset curve of the present embodiment is a preselected curve having the characteristics of dimension reduction, stability, continuity, etc. The preset curve is preferably a hilbert curve in this embodiment. Because the Hilbert curve can effectively reduce the dimension of a multidimensional space, when the Hilbert curve is an n (n tends to infinity) order curve, the position points on the curve tend to be stable basically, and the problem that the whole standard plane is filled and has no position mutation can be solved. Therefore, the present embodiment selects the hilbert curve as the preset curve, which can improve the accuracy of the trellis encoding of the standard plane. For example, compared with a Z-order curve, the method well solves the problem that the retrieval result is inaccurate when the data is close to one-dimensional distance but far from two-dimensional distance in the case of abrupt change of the corner position sequence.

Optionally, in this embodiment, according to a mapping relationship between a three-dimensional spherical surface of the earth and a standard plane, a region to be retrieved is mapped from the three-dimensional spherical surface to a two-dimensional standard plane, and then a preset region is used to perform mesh coding on the mapped standard plane, specifically, a preset curve may be used to perform curve filling on the standard plane mapped with the region to be retrieved, so as to divide the standard plane into a plurality of small meshes, and then each divided small mesh is coded, for example, an S2 algorithm may be used to code, so as to obtain a coding result corresponding to each small mesh, that is, one small mesh corresponds to one coding array.

It should be noted that, in this embodiment, if the three-dimensional sphere plane of the earth corresponds to a plurality of standard planes, in this embodiment, a standard plane including the area to be retrieved needs to be selected from the plurality of standard planes, and then the operation in this step needs to be performed based on the standard plane. In this embodiment, the coding array corresponding to each grid may at least include: the grid number of the grid, the identifier of the standard plane containing the area to be retrieved, and the like.

And S102, determining a target coding array of the area to be retrieved according to the grid coding result associated with the area to be retrieved.

Optionally, in this embodiment, a standard plane to be mapped to the region to be retrieved is already subjected to mesh division, and each mesh after division is subjected to mesh encoding, that is, an encoding array is obtained for each mesh. At this time, the grid associated with the to-be-retrieved area mapped to the standard plane, that is, the grid corresponding to the to-be-retrieved area in the standard plane, may be determined, and the grid coding result corresponding to the grid, that is, the coding array of the corresponding grid, is used as the target coding array of the to-be-retrieved area.

It should be noted that, when the precision of the standard plane division in S101 is sufficiently small, it can be approximately considered that the area to be retrieved may be composed of a plurality of divided grids, and the number of the plurality of coding groups of the plurality of grids is the target coding array of the area to be retrieved.

S103, determining target track data associated with the target coding array according to the target coding array and the index relation between the original track data and the original coding array.

The original trajectory data is data formed by a series of ordered two-dimensional longitude and latitude coordinate points, and each longitude and latitude coordinate point is acquired by a mobile terminal (such as a mobile phone, a vehicle-mounted device, a wearable device and the like) in real time by using a Global Navigation Satellite System (GNNS). Each moving process of each mobile device forms a set of original track data. The original coding array of this embodiment is obtained by coding the original track data, and the specific coding process may be similar to the process of determining the target coding array of the region to be retrieved, for example, mapping the original track data into a standard plane, performing mesh coding on the mapped standard plane by using a preset curve, and determining the original coding array of the original track data according to a mesh coding result associated with the original track data. The specific determination process will be described in detail in the following embodiments.

It should be noted that, in this embodiment, an index relationship is established between the original trace data and the original coding array obtained by coding the original trace data, such as "original coding array — original trace data". And the original track data and the corresponding index relationship (i.e. the index relationship between the original track data and the original coding array) can be stored in the track database in advance.

Optionally, in this embodiment, an original coding array corresponding to the target coding array may be retrieved from the track database according to the target coding array (for example, an original coding array consistent with the target coding array is found), that is, the original coding array to be retrieved at this time; and then, determining original track data corresponding to the original coding array to be retrieved at the time, namely target track data to be retrieved at the time, based on the index relationship between the original track data and the original coding array stored in the track database.

According to the scheme of the embodiment of the disclosure, a preset curve is adopted to perform grid coding on a standard plane which is mapped with the area to be retrieved to determine a target coding array corresponding to the area to be retrieved, and then original track data corresponding to the target coding array is retrieved to serve as the target track data based on the index relation between the original track data and the original coding array. The scheme of the embodiment provides a new method for carrying out grid coding on position points based on a preset curve, solves the problem that track retrieval is inaccurate due to the fact that the one-dimensional distance is short but the actual two-dimensional distance is long after coding in the existing geographic Hash (Geo Hash) coding method, and improves efficiency and accuracy of track retrieval. Provides a new idea for searching the space trajectory.

FIG. 2A is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure; fig. 2B is a schematic diagram illustrating a curve filling effect of standard planes at different trellis encoding precisions provided according to an embodiment of the present disclosure; fig. 2C is a schematic diagram of a trellis encoding result provided according to an embodiment of the present disclosure. On the basis of the above embodiments, the present embodiment further explains in detail how to "map the region to be retrieved into the standard plane, and perform mesh encoding on the mapped standard plane by using the preset curve". As shown in fig. 2A-2C, the track retrieval method provided in this embodiment may include:

s201, determining a standard plane and grid coding precision corresponding to the area to be retrieved.

The mesh coding precision may be the fineness of mesh division of a preset standard plane, and the higher the mesh coding precision is, the finer the divided mesh is. Preferably, the trellis encoding precision of the present embodiment is up to 30 levels, and the coverage range is from 0.7cm to 85000000 km. And more selectable levels are set, so that the change of two adjacent levels is relatively smooth, and the problem of difficulty in level selection can be well avoided.

Optionally, in this embodiment, the optional standard plane is a standard plane of 6 squares obtained by projecting all points on the three-dimensional sphere of the earth onto 6 faces of the circumscribed cube. When the standard plane corresponding to the area to be retrieved is determined from the selectable 6 standard planes, if the track retrieval request sent by the retrieval demand party contains the standard plane corresponding to the plane to be retrieved, the determination can be directly performed according to the track retrieval request; otherwise, which of the 6 projected standard planes contains the area to be retrieved can be judged, and which standard plane is taken as the standard plane of the area to be retrieved.

Optionally, in this embodiment, when determining the mesh coding precision corresponding to the area to be retrieved, if the trajectory retrieval request sent by the retrieval demander includes the mesh coding precision, the determination may be directly performed according to the trajectory retrieval request at this time; otherwise, a system default trellis encoding accuracy or the like may be selected.

S202, the area to be retrieved is mapped into a standard plane, a preset curve is filled in the standard plane according to the grid coding precision, and the grid formed after the curve is filled is coded.

Optionally, after determining the standard plane and the mesh coding precision corresponding to the area to be retrieved, the embodiment may map the area to be retrieved to the standard plane, then fill a preset curve in the standard plane according to the mesh coding precision (e.g., 30 levels) corresponding to the area to be retrieved, divide the standard plane into a plurality of meshes after the curve is filled, and then sequentially code each mesh to obtain the coding array cell corresponding to each mesh.

For example, fig. 2B shows an effect diagram of filling hilbert curves (i.e., preset curves) in the standard plane under different mesh coding accuracies, where the higher the mesh accuracy is, the denser the hilbert curves are filled in the standard plane, and accordingly, the finer the mesh is divided into the standard plane. The coding array shown in fig. 2C may be regarded as a coding array corresponding to a grid divided after filling the hilbert curve in the standard plane under the 30-level grid precision in fig. 2B. The code array is 64 bits, wherein the first three bits represent the standard plane number corresponding to the area to be retrieved, namely 101, the first position of the code array from back to front, which is not 0, is the array terminator. That is, the position before the end character of the array is the valid character of the coding array. Note that the valid character is 33 bits when the trellis encoding precision is 30 levels, and the valid character is 27 bits when the trellis encoding precision is 24 levels.

Optionally, the embodiment may also convert the 64-bit binary code array into a decimal code array for subsequent quick retrieval.

S203, determining a target coding array of the area to be retrieved according to the grid coding result associated with the area to be retrieved.

S204, determining target track data associated with the target coding array according to the target coding array and the index relation between the original track data and the original coding array.

According to the scheme of the embodiment of the invention, the number of the selectable standard planes and the number of the selectable grid coding precisions are multiple, the standard plane and the grid coding precision corresponding to the area to be retrieved are firstly determined, then the grid coding is carried out on the standard plane which maps the area to be retrieved by adopting the preset curve based on the grid coding precision, the target coding array corresponding to the area to be retrieved is determined, and then the original track data corresponding to the target coding array is retrieved as the target track data based on the index relationship between the original track data and the original coding array. According to the scheme of the embodiment, when the position points are subjected to the grid coding based on the preset curve, a proper standard plane and the grid coding precision can be selected according to actual requirements, the grid coding fineness is improved, and then the track retrieval accuracy is improved.

FIG. 3A is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure; fig. 3B is a schematic diagram of an index relationship between original track data and original encoded data according to an embodiment of the disclosure. In an embodiment of the present disclosure, an index relationship between original track data and original encoded data includes: the reverse index relationship between the original coding array and the original track number, and the forward index relationship between the original track number and the original track data.

For example, as shown in fig. 3B, the inverted index relationship between a set of original coding arrays and the original track number is: 3869277663051577529- [ Trace 1, Trace 2, Trace 3, Trace 4], wherein a set of positive index relationships between the original trace code and the original trace data is: track 1-original track data 1. It should be noted that fig. 3B shows the conversion of a 64-bit binary original coded array into a decimal original coded array. In this embodiment, the reverse index relationship between the 64-bit binary original coding array and the track original track number may also be directly established, which is not limited.

On the basis of the above embodiments, the present embodiment further explains in detail how to "determine the target track data associated with the target coding array according to the target coding array and the index relationship between the original track data and the original coding array". As shown in fig. 3A-3B, the track retrieval method provided in this embodiment may include:

s301, mapping the area to be retrieved to a standard plane, and carrying out grid coding on the mapped standard plane by adopting a preset curve.

S302, determining a target coding array of the area to be retrieved according to the grid coding result associated with the area to be retrieved.

S303, determining the target track number associated with the target coding array according to the target coding array and the inverted index relation between the original coding array and the original track number.

The embodiment may be to find an original coding array (i.e., an original coding array to be retrieved) that is consistent with the target coding array, and use an original track number corresponding to the original coding array to be retrieved as a target track number associated with the target coding array based on an inverted index relationship between the original coding array and the original track number. For example, if the target coding array is 3869277663051577530, it can be seen from the inverted index relationship between the original coding array and the original track number shown in fig. 3B that the target track coding array is identical to the original coding array of the second row, so track 2, track 5 and track 6 corresponding to the original coding array 3869277663051577530 of the second row are taken as the target track numbers associated with the target coding array.

S304, determining the target track data associated with the target track number according to the target track number and the forward index relationship between the original track number and the original track data.

After the target track number is determined, the original track data corresponding to the target track number may be searched for as target track data associated with the target track number based on the forward index relationship between the original track number and the original track data.

For example, after determining that the target track numbers associated with the target coding array are track 2, track 5, and track 6, it can be seen from the forward index relationship between the original track numbers and the original track data shown in fig. 3B that the original track data 2 corresponding to the track 2, the original track data 5 corresponding to the track 5, and the original track data 6 corresponding to the track 6 are the target track data associated with the target track numbers.

According to the scheme of the embodiment, the preset curve is adopted to carry out grid coding on the standard plane which is mapped with the area to be retrieved to determine the target coding array corresponding to the area to be retrieved, then based on the index relation between the original track data and the original coding array, when the original track data corresponding to the target coding array is retrieved, the track number is retrieved based on the reverse index relation, then the track data is retrieved based on the forward index relation, and meanwhile, the reverse index and the forward index are introduced to carry out track retrieval, so that the track retrieval efficiency is greatly improved.

Fig. 4A is a schematic diagram of a target coding array and an original coding array provided according to an embodiment of the present disclosure. The target coding array is a 24-level coding array, namely the coding precision of the target coding array is 24 levels; the original coding array is a 30-level coding array, that is, the coding precision of the original coding array is 30 levels. The present embodiment preferably sets the encoding precision of the original encoding array to the highest precision level, and the precision of the target encoding array may be set according to the precision of the retrieval demander, and is usually less than or equal to the highest encoding precision.

FIG. 4B is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure; on the basis of the above embodiments, the present embodiment further explains in detail how to determine target track data associated with a target coding array according to the target coding array and the index relationship between the original track data and the original coding array when the trellis coding accuracy of the target coding array is smaller than the trellis coding accuracy of the original coding array. As shown in fig. 4A-4B, the track retrieval method provided in this embodiment may include:

s401, the area to be retrieved is mapped to a standard plane, and the mapped standard plane is subjected to grid coding by adopting a preset curve.

S402, determining a target coding array of the area to be retrieved according to the grid coding result associated with the area to be retrieved.

S403, determining the original coding array associated with the target coding array according to the inclusion relationship between the target coding array and the original coding array.

Optionally, in the embodiment of the present disclosure, for the same region, the coding array with low coding precision includes a coding array with high coding precision, for example, as shown in fig. 4B, the first 24 bits of the target coding array at level 24 are identical to the first 24 bits of the original coding array at level 30, that is, it is stated that the target coding array at level 24 includes the original coding array at level 30.

Therefore, when the target coding array is lower than the coding precision of the original coding array, the present embodiment may select the original coding array included in the target coding array from the original coding arrays as the original coding array associated with the target coding array. Specifically, the last bit at the end of the target coding array is searched forward to find the first position which is not 0, that is, the array terminator, and the effective character before the array terminator is obtained; and finding the original coding array with the same effective characters from the first bit in the original coding array as the original coding array contained in the target coding array, namely the original coding array associated with the target coding array. For example, the original coding array shown in FIG. 4A may be used as the original coding array associated with the target coding array.

S404, determining the target track number associated with the target coding array according to the original coding array associated with the target coding array and the inverted index relation between the original coding array and the original track number.

For example, the present embodiment may retrieve, based on the inverted index relationship between the original coding array and the original track number, the original coding array corresponding to the target coding array as the target track number associated with the target coding array.

S405, determining target track data associated with the target track number according to the target track number and the forward index relationship between the original track number and the original track data.

According to the scheme of the embodiment of the disclosure, an original coding array of original track data can be generated based on higher coding precision, when the coding precision of a target coding array of a region to be retrieved is lower than that of the original coding array, the embodiment may be that the target coding array with low precision is positioned to the original coding array with high precision based on the inclusion relationship between the target coding array and the original coding array, then the target track number associated with the target coding array is determined based on the inverted index relationship between the original coding array and the original track number, and the target track data associated with the target track number is determined based on the forward index relationship between the original track number and the original track data. Therefore, when the encoding precision of the retrieval region is low, high-precision original track data can be retrieved, and the track retrieval precision is improved.

FIG. 5A is a flow chart of another trajectory retrieval method provided in accordance with an embodiment of the present disclosure; fig. 5B is a conceptual framework diagram of trajectory retrieval provided in accordance with an embodiment of the present disclosure. The present embodiment further explains in detail how to "construct an index relationship between original track data and original code data" based on the above-described embodiments. As shown in fig. 5A-5B, the track retrieval method provided in this embodiment may include:

s501, mapping the original track data to a standard plane, and carrying out grid coding on the mapped standard plane by adopting a preset curve.

Specifically, the process of mapping the original trajectory data to the standard plane and performing mesh coding on the mapped standard plane by using the preset curve in this step is similar to the process of mapping the area to be retrieved to the standard plane and performing mesh coding on the mapped standard plane by using the preset curve as described in the above embodiment. For example, it may be determined the standard plane and the mesh encoding precision corresponding to the original trajectory data. And mapping the original track data into a standard plane, filling a preset curve in the standard plane according to the grid coding precision, and coding the grid formed after the curve is filled. The specific implementation process has been described in the above embodiments, and is not described herein again.

Optionally, in order to improve the precision of the trajectory retrieval, the embodiment may set the trellis encoding precision corresponding to the original trajectory data to be the highest trellis encoding precision, such as 30 levels.

S502, determining an original coding array of the original track data according to the grid coding result associated with the original track data.

Specifically, the process of determining the original coding array of the original track data according to the grid coding result associated with the original track data in this step is similar to the process of determining the target coding array of the to-be-retrieved area according to the grid coding result associated with the to-be-retrieved area and described in the above embodiment, and is not repeated here.

It should be noted that, because the original track data of this embodiment is composed of a plurality of track points, each track point is associated with a mesh coding result, the mesh coding results associated with different track points may be the same or different, and this embodiment may be implemented by summarizing the mesh coding results associated with each track point in the original track data to obtain an original coding array of the original track data, that is, one original track data corresponds to at least one original coding array.

S503, establishing an index relationship between the original track data and the original encoding data.

Specifically, the present embodiment may directly establish a reverse index relationship between the original coding array and the original track data, and may also establish a reverse index relationship between the original coding array and the original track number, and a forward index relationship between the original track number and the original track data.

Optionally, as shown in fig. 5B, in this embodiment, after the original track data is encoded and the index relationship between the original track data and the original encoded data set is established, a data warehousing operation is performed, that is, the established index relationship and the original track data are stored in the track database.

S504, the area to be retrieved is mapped into a standard plane, and the mapped standard plane is subjected to grid coding by adopting a preset curve.

And S505, determining a target coding array of the area to be retrieved according to the grid coding result associated with the area to be retrieved.

S506, determining target track data associated with the target coding array according to the target coding array and the index relation between the original track data and the original coding array.

For example, as shown in fig. 5B, when performing track retrieval, the present embodiment may query, in the track database, an index relationship between original track data corresponding to the target coding array and the original coding array based on the target coding array determined in S504-S505, and determine target track data associated with the target coding array based on the query to the index relationship.

According to the scheme of the embodiment of the disclosure, when the original track data is processed, the original track data is mapped to the standard plane of the area to be searched as well as the position point of the area to be searched, and each position point in the original track data is coded based on the preset curve. After encoding, an index relationship between the original track data and the original encoding data is established, so that the original track data contained in the area to be retrieved can be conveniently and quickly retrieved in the follow-up process.

Preferably, in the embodiment of the present disclosure, a high-throughput communication interface, that is, a representational state transfer style interface Restful API, may be specially configured to implement communication between the retrieval system and the retrieval demanding party. Specifically, a track retrieval request containing an area to be retrieved, which is sent by a retrieval demand party, is received through a representational state transfer style interface Restful API; and/or feeding back the target track data to the retrieval demand side through the Restful API. The embodiment realizes the communication between the retrieval system and the retrieval demand party based on the Restful API with high throughput performance, and the setting has the advantages of improving the communication efficiency and having stronger universality.

Fig. 6 is a schematic structural diagram of a trajectory retrieval device according to an embodiment of the present disclosure. The embodiment of the disclosure is suitable for retrieving the original track data in the area to be retrieved, and is particularly suitable for retrieving the original track data in the area to be retrieved from a large amount of original track data. The device can be implemented by software and/or hardware, and the device can implement the track retrieval method described in any embodiment of the disclosure. As shown in fig. 6, the trajectory retrieval device includes:

the mapping and coding module 601 is configured to map a region to be retrieved to a standard plane, and perform mesh coding on the mapped standard plane by using a preset curve;

a target array determining module 602, configured to determine a target coding array of the to-be-retrieved area according to a trellis coding result associated with the to-be-retrieved area;

a target track determining module 603, configured to determine, according to the target coding array and an index relationship between the original track data and the original coding array, target track data associated with the target coding array.

Further, the mapping and encoding module 601 is specifically configured to:

determining a standard plane and grid coding precision corresponding to a region to be retrieved;

and mapping the area to be retrieved to a standard plane, filling a preset curve in the standard plane according to the grid coding precision, and coding the grid formed after the curve is filled.

Further, the index relationship between the original track data and the original encoding data set includes: the reverse index relationship between the original coding array and the original track number, and the forward index relationship between the original track number and the original track data.

Further, the target track determining module 603 includes:

the track number indexing unit is used for determining a target track number associated with the target coding array according to the target coding array and the inverted index relation between the original coding array and the original track number;

and the track data indexing unit is used for determining the target track data associated with the target track number according to the target track number and the forward index relationship between the original track number and the original track data.

Further, if the trellis encoding precision of the target encoding array is smaller than the trellis encoding precision of the original encoding array, the track number index unit is specifically configured to:

determining an original coding array associated with a target coding array according to the inclusion relation between the target coding array and the original coding array;

and determining the target track number associated with the target coding array according to the original coding array associated with the target coding array and the inverted index relationship between the original coding array and the original track number.

Further, the trajectory retrieval device further includes:

the mapping and encoding module 601 is further configured to map the original trajectory data to a standard plane, and perform mesh encoding on the mapped standard plane by using a preset curve;

the original array determining module is used for determining an original coding array of the original track data according to a grid coding result associated with the original track data;

and the index relation establishing module is used for establishing the index relation between the original track data and the original coding array.

Further, the preset curve is a hilbert curve.

Further, the trajectory retrieval device further comprises a communication module, and the communication module is configured to:

receiving a track retrieval request containing a to-be-retrieved area sent by a retrieval demand party through a representational state transfer style interface Restful API; and/or the presence of a gas in the gas,

and feeding back the target track data to a retrieval demand side through a Restful API.

The product can execute the method provided by any embodiment of the disclosure, and has corresponding functional modules and beneficial effects of the execution method.

In the technical scheme of the disclosure, any related track data is acquired, stored, applied and the like, and the requirements of related laws and regulations are met, and the good custom of the public order is not violated.

The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.

FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 7, the device 700 comprises a computing unit 701, which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM)702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.

Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

Computing unit 701 may be a variety of general purpose and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 701 executes the respective methods and processes described above, such as the trajectory retrieval method. For example, in some embodiments, the trajectory retrieval method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of a computer program may be loaded onto and/or installed onto device 700 via ROM 702 and/or communications unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the trajectory retrieval method described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the trajectory retrieval method by any other suitable means (e.g. by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

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

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome. The server may also be a server of a distributed system, or a server incorporating a blockchain.

Artificial intelligence is the subject of research that makes computers simulate some human mental processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), both at the hardware level and at the software level. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing, and the like; the artificial intelligence software technology mainly comprises a computer vision technology, a voice recognition technology, a natural language processing technology, a machine learning/deep learning technology, a big data processing technology, a knowledge map technology and the like.

Cloud computing (cloud computing) refers to a technology system that accesses a flexibly extensible shared physical or virtual resource pool through a network, where resources may include servers, operating systems, networks, software, applications, storage devices, and the like, and may be deployed and managed in a self-service manner as needed. Through the cloud computing technology, high-efficiency and strong data processing capacity can be provided for technical application and model training of artificial intelligence, block chains and the like.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A trajectory retrieval method, comprising:

2. The method according to claim 1, wherein the mapping the area to be retrieved to a standard plane and the mesh encoding of the mapped standard plane by using a preset curve comprises:

3. The method of claim 1, wherein the indexing between the original track data and the original encoded array comprises: the reverse index relationship between the original coding array and the original track number, and the forward index relationship between the original track number and the original track data.

4. The method of claim 3, wherein the determining the target track data associated with the target coding array according to the target coding array and an index relationship between the original track data and the original coding array comprises:

determining a target track number associated with the target coding array according to the target coding array and an inverted index relation between the original coding array and the original track number;

and determining the target track data associated with the target track number according to the target track number and the forward index relationship between the original track number and the original track data.

5. The method of claim 4, wherein if the trellis encoding precision of the target encoding array is smaller than the trellis encoding precision of the original encoding array, determining the target track number associated with the target encoding array according to the target encoding array and the inverted index relationship between the original encoding array and the original track number comprises:

6. The method of claim 1, further comprising:

mapping the original track data into a standard plane, and carrying out grid coding on the mapped standard plane by adopting a preset curve;

determining an original coding array of the original track data according to a grid coding result associated with the original track data;

and establishing an index relationship between the original track data and the original encoding array.

7. The method according to any of claims 1-6, wherein the preset curve is a Hilbert curve.

8. The method of claim 1, further comprising:

9. A trajectory retrieval device comprising:

the mapping coding module is used for mapping the area to be retrieved to a standard plane and carrying out grid coding on the mapped standard plane by adopting a preset curve;

the target array determining module is used for determining a target coding array of the area to be retrieved according to the grid coding result associated with the area to be retrieved;

and the target track determining module is used for determining target track data associated with the target coding array according to the target coding array and the index relationship between the original track data and the original coding array.

10. The apparatus of claim 9, wherein the map coding module is specifically configured to:

11. The apparatus of claim 9, wherein the indexing relationship between the original track data and the original encoded array comprises: the reverse index relationship between the original coding array and the original track number, and the forward index relationship between the original track number and the original track data.

12. The apparatus of claim 11, wherein the target trajectory determination module comprises:

13. The apparatus of claim 12, wherein if the trellis encoding precision of the target encoding array is less than the trellis encoding precision of the original encoding array, the track number indexing unit is specifically configured to:

14. The apparatus of claim 9, further comprising:

the mapping and coding module is also used for mapping the original track data into a standard plane and carrying out grid coding on the mapped standard plane by adopting a preset curve;

15. The apparatus according to any one of claims 9-14, wherein the preset curve is a hilbert curve.

16. The apparatus of claim 9, further comprising a communication module to:

17. An electronic device, comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the trajectory retrieval method of any of claims 1-8.

18. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the trajectory retrieval method according to any one of claims 1 to 8.

19. A computer program product comprising a computer program which, when executed by a processor, implements a trajectory retrieval method according to any one of claims 1-8.