CN117292339A

CN117292339A - Lane group guide line generation method, device, equipment and readable storage medium

Info

Publication number: CN117292339A
Application number: CN202210693469.2A
Authority: CN
Inventors: 刘国亮; 湛逸飞
Original assignee: Beijing Co Wheels Technology Co Ltd
Current assignee: Beijing Co Wheels Technology Co Ltd
Priority date: 2022-06-17
Filing date: 2022-06-17
Publication date: 2023-12-26

Abstract

The present disclosure relates to a lane group guide line generation method, apparatus, device, and readable storage medium. The lane group data are acquired from the high-precision road network, so that the acquired lane group data are more accurate, the contours of the lane groups are identified according to the shape points of the lane lines included in the lane group data, the identified contours of the lane groups are more accurate, the contours of the lane groups are spatially divided to obtain the preset number of polygons, the centroids of each polygon in the preset number of polygons are sequentially connected according to the direction of the lane groups to generate the guide lines of the lane groups, the guide lines of the lane groups are generated by utilizing the high-precision map, the generated guide lines of the lane groups can represent the shape and the direction trend of the lane groups, so that the lane group characteristics of the original high-precision map can be better kept, the problem that part of users do not like the high-precision map can be solved, the problem that the high-precision map is slower in loading and the waiting time of users is longer can be solved, the requirements of users can be better met, and the user experience is improved.

Description

Lane group guide line generation method, device, equipment and readable storage medium

Technical Field

The disclosure relates to the technical field of data processing, and in particular relates to a lane group guide line generation method, a lane group guide line generation device, lane group guide line generation equipment and a readable storage medium.

Background

With rapid development of vehicle technology, high-precision maps have also become increasingly important.

Accurate position information in the high-precision map can assist the sensor to identify objects, rich road experience information is obtained in advance, and the sub-meter-level lane positioning provided by the sensor can better improve vehicle safety, so that the sensor is an indispensable important reference frame for realizing intelligent driving.

However, in some application scenarios, the high-precision map cannot meet the needs of the user. For example, some users dislike using high-precision maps, or the amount of data that needs to be loaded for high-precision maps is large, loading is slow, and waiting time for users is long, resulting in poor user experience.

Disclosure of Invention

In order to solve the technical problems, the disclosure provides a method, a device, equipment and a readable storage medium for generating lane group guide lines, which can solve the problem that part of users do not like a high-precision map and can also solve the problem that the high-precision map is loaded slowly and the waiting time of the users is long, thereby better meeting the demands of the users and improving the user experience.

In a first aspect, an embodiment of the present disclosure provides a lane group guidance line generating method, including:

obtaining lane group data from a high-precision road network, wherein the lane group comprises at least one lane in the same direction, and the lane group data comprises shape points of lane lines in the lane group corresponding to the lane group data and the direction of the lane group;

identifying the outline of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data;

space segmentation is carried out on the contour of the lane group to obtain a preset number of polygons;

and sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group.

In a second aspect, an embodiment of the present disclosure provides a lane group guide line generating apparatus including:

the lane group data comprises shape points of lane lines in the lane group corresponding to the lane group data and the direction of the lane group;

the recognition module is used for recognizing the outline of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data;

The generation module is used for carrying out space division on the contour of the lane group to obtain a preset number of polygons; and sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group.

In a third aspect, an embodiment of the present disclosure provides an electronic device, including:

a memory;

a processor; and

a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method according to the first aspect.

In a fourth aspect, embodiments of the present disclosure provide a computer-readable storage medium having stored thereon a computer program for execution by a processor to implement the method of the first aspect.

In a fifth aspect, the disclosed embodiments also provide a computer program product comprising a computer program or instructions which, when executed by a processor, implements a lane group guideline generation method as described above.

The lane group guide line generation method, device, equipment and readable storage medium provided by the embodiment of the disclosure are used for acquiring lane group data from a high-precision road network, wherein the lane group comprises at least one lane in the same direction, the lane group data comprises shape points of lane lines in the lane group corresponding to the lane group data and the direction of the lane group, and the contour of the lane group is identified according to the shape points of the lane lines in the lane group corresponding to the lane group data. Further, the contours of the lane groups are spatially segmented to obtain a preset number of polygons. And sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group. Because the lane group data is acquired from the high-precision road network, the acquired lane group data is more accurate, the contour of the lane group is identified according to the shape points of the lane lines in the lane group corresponding to the lane group data, the identified lane group contour is more accurate, the contour of the lane group is further subjected to space division to obtain a preset number of polygons, the centroid of each polygon in the preset number of polygons is sequentially connected according to the direction of the lane group, the guide line of the lane group is generated, the lane group guide line is generated by utilizing the high-precision map, the generated lane group guide line can represent the shape and the direction trend of the lane group, so that the lane group characteristics of the original high-precision map can be better kept, the problem that partial users do not like the high-precision map can be solved, the data volume of the generated lane group guide line is smaller, the problem that the high-precision map is loaded more slowly, the waiting time of the users is longer can be solved, the requirements of the users are better met, and the user experience is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.

In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.

Fig. 1 is a flowchart of a lane group guidance line generation method provided in an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a lane group provided by an embodiment of the present disclosure;

FIG. 3 is a flow chart of a lane group guideline generation method provided in another embodiment of the present disclosure;

FIG. 4 is a flow chart of a lane group guideline generation method provided in another embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a lane group guidance wire generating apparatus according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.

Detailed Description

In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.

The embodiment of the disclosure provides a lane group guide line generating method, and the method is described below with reference to specific embodiments.

Fig. 1 is a flowchart of a lane group guidance line generating method according to an embodiment of the present disclosure. The method can be applied to a scene where a high-precision map cannot be used, and can also be applied to a scene where a lane group guide line is generated using a high-precision map. It can be appreciated that the lane group guidance line generation method provided by the embodiment of the present disclosure may also be applied in other scenarios.

The following describes a lane group guidance wire generating method shown in fig. 1, which includes the following specific steps:

s101, lane group data are obtained from a high-precision road network, the lane group comprises at least one lane in the same direction, and the lane group data comprise shape points of lane lines in the lane group corresponding to the lane group data and the direction of the lane group.

For example, the electronic device obtains lane group data from a high-definition road network. The lane group comprises at least one lane in the same direction, and the lane group data comprises shape points of lane lines in the lane group corresponding to the lane group data and the direction of the lane group. As shown in fig. 2, the lane group includes three lanes, the arrow indicates the direction of the lane group, a dotted line or a solid line is arranged between the lanes, two sides of the lanes are road surface edges, and the lane line includes the dotted line or the solid line between the lanes and also includes the lane edges. The lane line is composed of points, and the shape points of the lane line are all points forming the lane line, and the points can represent the length, the width and the curvature of the lane line.

S102, identifying the outline of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data.

After lane group data are acquired, the electronic equipment identifies the outline of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data. Specifically, the electronic device identifies the contour of the lane group according to some outermost points among the shape points of the lane lines in the lane group corresponding to the lane group data. For example, a lane group of length 20 meters and width 5 meters has a contour that approximates a rectangle.

Optionally, the electronic device may identify the contour of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data based on a scatter point contour algorithm. The scattered point contour algorithm is a simple and effective algorithm for rapidly extracting the contour, overcomes the defect that the contour is inaccurate due to the fact that the contour is extracted by the point cloud contour extraction algorithm according to boundary characteristics, and can rapidly and accurately identify the contour.

S103, performing space segmentation on the contour of the lane group to obtain a preset number of polygons.

After the contour of the lane group is identified, the electronic equipment performs space division on the contour of the lane group to obtain a preset number of polygons. For example, the electronic device performs spatial segmentation on the contour of the lane group based on a binary spatial segmentation tree algorithm to obtain a preset number of polygons. Therefore, some complex polygonal outlines can be divided into some simpler polygons, and subsequent processing is facilitated.

S104, according to the direction of the lane group, connecting the mass centers of each polygon in the preset number of polygons in sequence to generate a guide line of the lane group.

After the preset number of polygons are obtained, the mass centers of each polygon in the preset number of polygons are sequentially connected according to the direction of the lane group, so that a guide line of the lane group is generated, and the lane group guide line can represent the shape and the direction trend of the lane group.

According to the method, lane group data are obtained from a high-precision road network, the lane group comprises at least one lane in the same direction, the lane group data comprise shape points of lane lines in the lane group corresponding to the lane group data and directions of the lane group, and the outline of the lane group is identified according to the shape points of the lane lines in the lane group corresponding to the lane group data. Further, the contours of the lane groups are spatially segmented to obtain a preset number of polygons. And sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group. Because the lane group data is acquired from the high-precision road network, the acquired lane group data is more accurate, the contour of the lane group is identified according to the shape points of the lane lines in the lane group corresponding to the lane group data, the identified lane group contour is more accurate, the contour of the lane group is further subjected to space division to obtain a preset number of polygons, the centroid of each polygon in the preset number of polygons is sequentially connected according to the direction of the lane group, the guide line of the lane group is generated, the lane group guide line is generated by utilizing the high-precision map, the generated lane group guide line can represent the shape and the direction trend of the lane group, so that the lane group characteristics of the original high-precision map can be better kept, the problem that partial users do not like the high-precision map can be solved, the data volume of the generated lane group guide line is smaller, the problem that the high-precision map is loaded more slowly, the waiting time of the users is longer can be solved, the requirements of the users are better met, and the user experience is improved.

On the basis of the above embodiment, the acquiring lane group data includes: determining the at least one lane in the high-definition road network; and obtaining lane group data corresponding to the at least one lane.

In some embodiments, the electronic device determines the at least one lane in the high-definition road network, and further obtains lane group data corresponding to the at least one lane. The lane group comprises at least one lane in the same direction, and the lane group data comprises shape points of lane lines in the lane group corresponding to the lane group data and the direction of the lane group.

Optionally, the identifying the contour of the lane group according to the shape point of the lane line in the lane group corresponding to the lane group data includes: determining the boundary of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data; and determining the outline of the lane group according to the boundary of the lane group.

In this embodiment, after lane group data is acquired, the electronic device determines a boundary of a lane group according to shape points of lane lines in the lane group corresponding to the lane group data. For example, the electronic device identifies some shape points at the outermost periphery among the shape points of the lane lines in the lane group corresponding to the lane group data as target shape points, and the electronic device determines the boundary of the lane group according to the target shape points. Further, the electronic device determines the outline of the lane group according to each boundary of the lane group. The contour of the lane group can be rectangular or complex polygonal.

The embodiment of the disclosure obtains lane group data corresponding to the at least one lane by determining the at least one lane in the high-precision road network. Further, determining the boundary of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data, and determining the outline of the lane group according to the boundary of the lane group. And carrying out space segmentation on the contour of the lane group to obtain a preset number of polygons. And sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group. The electronic equipment identifies some shape points at the outermost periphery of the shape points of the lane lines in the lane group corresponding to the lane group data as target shape points, and determines the boundary of the lane group according to the target shape points. Further, the electronic equipment determines the outline of the lane group according to each boundary of the lane group, can better determine the outline of the lane group, can better generate lane group guide lines according to the outline of the lane group, and generates lane group guide lines by utilizing the high-precision map, so that the lane group characteristics of the original high-precision map are better kept, the problem that part of users do not like the high-precision map can be solved, the generated lane group guide lines are smaller in data size and faster in loading, and therefore the problem that the high-precision map is slower in loading and longer in waiting time of users can be solved, the requirements of the users are better met, and the user experience is improved.

Fig. 3 is a flowchart of a lane group guidance line generating method according to another embodiment of the present disclosure, as shown in fig. 3, the method includes the following steps:

s301, lane group data are obtained from a high-precision road network, the lane group comprises at least one lane in the same direction, and the lane group data comprise shape points of lane lines in the lane group corresponding to the lane group data and the direction of the lane group.

Specifically, the implementation process and principle of S301 and S101 are identical, and will not be described herein.

S302, forming a shape point set by the shape points of the lane lines in the lane group corresponding to the lane group data.

For example, the lane group data corresponds to a plurality of shape points of the lane lines in the lane group, and the electronic device may form a shape point set from the shape points.

In this step, the lane group data includes shape point data of all lane lines, and these shape point data may be formed into one point set N.

S303, for any two shape points in the shape point set, if the distance between the two shape points is smaller than a preset threshold value, determining two target points from a perpendicular bisector of a connecting line between the two shape points, wherein the distance between each target point and any one shape point in the two shape points is one half of the preset threshold value.

For any two shape points in the set of shape points, if the distance between the two shape points is greater than or equal to a preset threshold, the shape points are excluded. Thus, some outliers, which are some shape points in the lane group data that do not represent lane lines, such as lines of roadside parking spaces, some mesh lines, and the like, can be eliminated, and the data processing amount is reduced. And if the distance between the two shape points is smaller than a preset threshold value, determining two target points from the perpendicular bisector of the connecting line between the two shape points, wherein the distance between each target point and any one of the two shape points is one half of the preset threshold value. The preset threshold is twice the radius, the fineness of the boundary is determined by the preset threshold, and the smaller the preset threshold is, the finer the boundary is, so that the obtained boundary is more accurate. Two circles can be determined by passing two shape points and under the condition of a certain radius. Since the centers of the two circles are on the perpendicular bisector of the line between the two shape points and the distances from the two shape points to the centers of the circles are equal to the radius, the two circles can be determined.

For example, the smaller the discrimination radius R, the higher the accuracy of the identified contour boundary is. Assuming that N points exist in the point set N, selecting any two points P1 and P2 from the N points, and when the distance between the P1 and the P2 is smaller than 2R, drawing a circle with the radius R by passing through the P1 and the P2; when the distance between P1 and P2 is greater than or equal to 2R, discarding.

S304, determining two circles by taking the two target points as circle centers and taking one half of the preset threshold value as radius.

After determining the two target points, the electronic device determines the two circles by taking the two target points as circle centers and taking one half of a preset threshold value as a radius. The two circles determined are symmetrical about the line connecting the two shape points and also symmetrical about the perpendicular bisector of the line connecting the two shape points.

When the distance between P1 and P2 is smaller than 2R, a circle with the radius R is drawn through P1 and P2. It will be appreciated by those skilled in the art that when the radius is determined, two circles can be determined over two points P1, P2.

And S305, if any one of the two circles does not contain other shape points except the two shape points, determining the two shape points as boundary point data.

If no other shape points than the two shape points are contained in either of the two circles, it is explained that the two shape points are already outermost points, i.e., the two shape points are determined to be boundary point data. If no other points are contained within the circle drawn over P1, P2, the points P1, P2 are boundary points.

Optionally, any two shape points in the n shape points in the shape point set are combined to form (n-1))/2 line segments, and the line segments are judged in the above process, so that a boundary point data set formed by multiple groups of boundary point data can be determined, and one group of boundary point data comprises two shape points.

S306, determining the boundary of the lane group according to the boundary point data in the shape point set.

After determining that the two shape points are boundary point data, the electronic equipment determines the boundary of the lane group according to the boundary point data in the shape point set. For example, the boundary points are connected by smooth line segments to obtain the boundary of the lane group. The line P1P2 connecting the boundary points P1, P2 is the boundary of the lane group.

Specifically, S306 may be implemented by S3061, S3062:

s3061, determining boundary lines of the lane groups according to boundary point data in the shape point set.

After the two shape points are determined to be the boundary point data, the electronic equipment connects the two boundary points, and the boundary line of the lane group is determined. Optionally, the electronic device connects each obtained set of boundary point data to determine the boundary line of the lane group.

S3062, determining the boundary of the lane group according to the boundary line of the lane group.

After determining the boundary line of the lane group, the electronic equipment determines the boundary of the lane group according to the boundary line of the lane group.

S307, determining the outline of the lane group according to the boundary of the lane group.

In some embodiments, the electronic device performs smoothing on the boundary of the lane group to obtain the contour of the lane group. The contour of the lane group obtained after the smoothing process may be rectangular or complex polygonal.

S308, performing space segmentation on the contour of the lane group to obtain a preset number of polygons.

In some embodiments, the preset number is one third of the number of sides of a polygon made up of the contours of the lane groups; the space division is performed on the contour of the lane group to obtain a preset number of polygons, including: judging whether the number of polygons formed after space division is one third of the number of sides of the polygon formed by the outlines of the lane groups; if yes, obtaining the preset number of polygons and stopping segmentation.

For example, let the number of sides of the polygon surrounded by the lane outline be m, and space-cut the polygon surrounded by the lane outline by using a binary space-division tree (bsp tree) algorithm until the number of polygons formed after cutting is m/3.

S309, according to the direction of the lane group, connecting the mass centers of each polygon in the preset number of polygons in sequence to generate a guide line of the lane group.

The embodiment of the disclosure obtains lane group data from a high-precision road network, wherein the lane group data comprises at least one lane in the same direction, the lane group data comprises shape points of lane lines in the lane group corresponding to the lane group data, and the direction of the lane group, and the shape points of the lane lines in the lane group corresponding to the lane group data form a shape point set. For any two shape points in the shape point set, if the distance between the two shape points is smaller than a preset threshold value, two target points are determined from a perpendicular bisector of a connecting line between the two shape points, and the distance between each target point and any one shape point in the two shape points is one half of the preset threshold value. And then, respectively determining two circles by taking the two target points as circle centers and taking one half of the preset threshold value as radius. And if any one of the two circles does not contain other shape points except the two shape points, determining the two shape points as boundary point data, and determining the boundary of the lane group according to the boundary point data in the shape point set. Further, determining the contour of the lane group according to the boundary of the lane group, and performing space segmentation on the contour of the lane group to obtain a preset number of polygons. And sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group. For any two shape points in the set of shape points, the disclosed embodiments exclude the shape points if the distance between the two shape points is greater than or equal to a preset threshold. In this way, outliers can be eliminated, reducing data throughput. And if the distance between the two shape points is smaller than a preset threshold value, determining two target points from the perpendicular bisector of the connecting line between the two shape points, wherein the distance between each target point and any one of the two shape points is one half of the preset threshold value. The preset threshold is twice of the radius, the fineness of the boundary is determined by the preset threshold, the smaller the preset threshold is, the finer the boundary is, the more accurate the obtained boundary is, and the generated lane group guide line is further accurate.

Fig. 4 is a flowchart of a lane group guidance line generating method according to another embodiment of the present disclosure, as shown in fig. 4, the method includes the following steps:

s401, determining the at least one lane in the high-precision road network.

In some embodiments, the electronic device determines the at least one lane in the high-definition road network. As shown in fig. 2, there is a dotted line or a solid line between the lanes, and the two sides of the lane group are road surface edges, and the lane line includes the dotted line or the solid line between the lanes and also includes the lane edges.

S402, lane group data corresponding to the at least one lane are acquired.

After determining the at least one lane in the high-precision road network, the electronic equipment acquires lane group data corresponding to the at least one lane. The lane group data comprises shape points of lane lines in a lane group corresponding to the lane group data and directions of the lane group. The lane line is composed of points, and the shape points of the lane line are all points forming the lane line, and the points can represent the length, the width and the curvature of the lane line.

S403, identifying the outline of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data.

Specifically, the implementation process and principle of S403 and S102 are consistent, and will not be described herein.

S404, performing space division on the polygon formed by the outlines of the lane groups.

After the contour of the lane group is identified, the electronic equipment performs space division on the contour of the lane group. For example, the electronic device spatially segments the contour of the lane group based on a binary spatial segmentation tree algorithm. Therefore, some complex polygonal outlines can be divided into some simpler polygons, and subsequent processing is facilitated.

S405, judging whether the number of polygons formed after space division is a preset number.

The electronic equipment judges whether the number of polygons formed after space division is a preset number. If the number of polygons formed after the space division is a preset number, S406 is performed, otherwise S404 is performed.

S406, if yes, obtaining the preset number of polygons and stopping segmentation.

If the number of polygons formed after the space division is a preset number, obtaining the preset number of polygons and stopping the division.

S407, determining the mass center of each polygon in the preset number of polygons.

After obtaining the preset number of polygons, the electronic device determines the centroid of each polygon in the preset number of polygons. For example, the electronic device calculates a centroid of each polygon of the preset number of polygons.

S408, according to the direction of the lane group, connecting the mass centers of each polygon in the preset number of polygons in sequence to generate a guide line of the lane group.

Specifically, the implementation process and principle of S408 and S104 are identical, and will not be described herein.

According to the embodiment of the disclosure, the lane group data corresponding to the at least one lane is obtained by determining the at least one lane in the high-precision road network, and the contour of the lane group is identified according to the shape points of the lane lines in the lane group corresponding to the lane group data. Further, space division is performed on the polygons formed by the outlines of the lane groups, and whether the number of the polygons formed after the space division is a preset number is judged. If yes, obtaining the preset number of polygons and stopping segmentation. And further determining the mass center of each polygon in the preset number of polygons, and sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group. After space division is carried out on the polygons formed by the outlines of the lane groups, judgment is carried out, whether the number of the polygons formed after the space division is a preset number is judged, if so, the polygons with the preset number are obtained, and the division is stopped; otherwise, continuing to space-divide the polygons formed by the outlines of the lane groups until the number of the polygons formed after space division is a preset number. The contour of the lane group is divided into a preset number of polygons, the mass center of each polygon is further determined, the mass centers of each polygon in the preset number of polygons are sequentially connected according to the direction of the lane group, the guide line of the lane group is generated, the generated lane group guide line better represents the shape and direction trend of the lane group, the generated lane group guide line is more accurate, the lane group guide line is generated by utilizing the high-precision map, the lane group characteristics of the original high-precision map can be better kept, the problem that part of users do not like the high-precision map can be solved, the data amount of the generated lane group guide line is smaller, the loading speed is higher, the problem that the loading speed of the high-precision map is longer for users can be solved, the requirements of users are better met, and the user experience is improved.

Fig. 5 is a schematic structural diagram of a lane group guidance wire generating apparatus according to an embodiment of the present disclosure. The lane group guide generating apparatus may be a server as described in the above embodiment, or the lane group guide generating apparatus may be a part or component in the server. The lane group guide line generating apparatus provided by the embodiment of the present disclosure may execute the processing flow provided by the lane group guide line generating method embodiment, as shown in fig. 5, the lane group guide line generating apparatus 50 includes: an acquisition module 51, an identification module 52, a generation module 53; the obtaining module 51 is configured to obtain lane group data from a high-precision road network, where the lane group includes at least one lane in the same direction, and the lane group data includes shape points of lane lines in the lane group corresponding to the lane group data, and a direction of the lane group; the identifying module 52 is configured to identify a contour of the lane group according to shape points of lane lines in the lane group corresponding to the lane group data; the generating module 53 is configured to spatially divide the contour of the lane group to obtain a preset number of polygons; and sequentially connecting the mass centers of each polygon in the preset number of polygons according to the direction of the lane group to generate a guide line of the lane group.

Optionally, the acquiring module 51 is specifically configured to, when acquiring lane group data: determining the at least one lane in the high-definition road network; and obtaining lane group data corresponding to the at least one lane.

Optionally, the identifying module 52 is specifically configured to, when identifying the contour of the lane group according to the shape point of the lane line in the lane group corresponding to the lane group data: determining the boundary of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data; and determining the outline of the lane group according to the boundary of the lane group.

Optionally, the identifying module 52 is specifically configured to, when determining the boundary of the lane group according to the shape point of the lane line in the lane group corresponding to the lane group data: forming a shape point set by shape points of lane lines in the lane group corresponding to the lane group data; for any two shape points in the shape point set, if the distance between the two shape points is smaller than a preset threshold value, determining two target points from a perpendicular bisector of a connecting line between the two shape points, wherein the distance between each target point and any one shape point in the two shape points is one half of the preset threshold value; respectively taking the two target points as circle centers and taking one half of the preset threshold value as radius to determine two circles; if any one of the two circles does not contain other shape points except the two shape points, determining the two shape points as boundary point data; and determining the boundary of the lane group according to the boundary point data in the shape point set.

Optionally, when the identifying module 52 determines the boundary of the lane group according to the boundary point data in the shape point set, the identifying module is specifically configured to: determining boundary lines of the lane groups according to boundary point data in the shape point set; and determining the boundary of the lane group according to the boundary line of the lane group.

Optionally, the generating module 53 performs spatial segmentation on the contour of the lane group, and is specifically configured to: space-dividing the polygon formed by the outlines of the lane groups; judging whether the number of polygons formed after space division is a preset number or not; if yes, obtaining the preset number of polygons and stopping segmentation.

Optionally, the preset number is one third of the number of sides of a polygon formed by the outlines of the lane groups;

the generating module 53 performs spatial segmentation on the contour of the lane group, and is specifically configured to: judging whether the number of polygons formed after space division is one third of the number of sides of the polygon formed by the outlines of the lane groups; if yes, obtaining the preset number of polygons and stopping segmentation.

The lane group guidance wire generating device of the embodiment shown in fig. 5 may be used to implement the technical solution of the above method embodiment, and its implementation principle and technical effects are similar, and will not be described herein again.

Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure. The electronic device may be a server as described in the above embodiments. The electronic device provided in the embodiment of the present disclosure may execute the processing flow provided in the embodiment of the lane group guidance line generation method, as shown in fig. 6, the electronic device 60 includes: a memory 61, a processor 62, computer programs and a communication interface 63; wherein the processor 62, the memory 61 and the communication interface 63 are connected by a communication bus; the processor 62 is for executing one or more computer programs stored in the memory 61; the computer program is stored in the memory 61 and is configured to execute the lane group guide line generation method as described above by the processor 62.

In addition, the embodiment of the present disclosure also provides a computer-readable storage medium having stored thereon a computer program that is executed by a processor to implement the lane group guidance wire generating method described in the above embodiment.

Furthermore, the disclosed embodiments also provide a computer program product comprising a computer program or instructions which, when executed by a processor, implements the lane group guideline generation method as described above.

It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having 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. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.

The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to:

In addition, the electronic device may also perform other steps in the lane group guidance line generation method as described above.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts 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 flowchart or block diagrams may represent a module, segment, or 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 involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

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. The 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.

It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A lane group guide line generation method, comprising:

2. The method of claim 1, wherein the obtaining lane group data from the high-definition road network comprises:

determining the at least one lane in the high-definition road network;

and obtaining lane group data corresponding to the at least one lane.

3. The method of claim 2, wherein the identifying the contour of the lane group from the shape points of the lane lines in the lane group corresponding to the lane group data comprises:

Determining the boundary of the lane group according to the shape points of the lane lines in the lane group corresponding to the lane group data;

and determining the outline of the lane group according to the boundary of the lane group.

4. The method of claim 3, wherein the determining the boundary of the lane group from the shape points of the lane lines in the lane group corresponding to the lane group data comprises:

forming a shape point set by shape points of lane lines in the lane group corresponding to the lane group data;

for any two shape points in the shape point set, if the distance between the two shape points is smaller than a preset threshold value, determining two target points from a perpendicular bisector of a connecting line between the two shape points, wherein the distance between each target point and any one shape point in the two shape points is one half of the preset threshold value;

respectively taking the two target points as circle centers and taking one half of the preset threshold value as radius to determine two circles;

if any one of the two circles does not contain other shape points except the two shape points, determining the two shape points as boundary point data;

and determining the boundary of the lane group according to the boundary point data in the shape point set.

5. The method of claim 4, wherein the determining the boundary of the lane group from the boundary point data in the set of shape points comprises:

determining boundary lines of the lane groups according to boundary point data in the shape point set;

and determining the boundary of the lane group according to the boundary line of the lane group.

6. The method of claim 1, wherein the spatially segmenting the contour of the lane group to obtain a predetermined number of polygons comprises:

space-dividing the polygon formed by the outlines of the lane groups;

judging whether the number of polygons formed after space division is a preset number or not;

if yes, obtaining the preset number of polygons and stopping segmentation.

7. The method according to claim 6, wherein the preset number is one third of the number of sides of a polygon constituted by the contours of the lane groups;

the space division is performed on the contour of the lane group to obtain a preset number of polygons, including:

judging whether the number of polygons formed after space division is one third of the number of sides of the polygon formed by the outlines of the lane groups;

If yes, obtaining the preset number of polygons and stopping segmentation.

8. A lane group guide line generating apparatus, comprising:

9. An electronic device, comprising:

a memory;

a processor; and

a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any one of claims 1-7.

10. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method according to any of claims 1-7.