CN111191597B - System and method for extracting road structure based on vector line - Google Patents
System and method for extracting road structure based on vector line Download PDFInfo
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- CN111191597B CN111191597B CN201911401191.1A CN201911401191A CN111191597B CN 111191597 B CN111191597 B CN 111191597B CN 201911401191 A CN201911401191 A CN 201911401191A CN 111191597 B CN111191597 B CN 111191597B
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Abstract
The invention discloses a system and a method for extracting a road structure based on vector lines. Wherein the method is configured to obtain vector line data of a high precision map; extracting at least one selected road structure and/or at least one suspected road structure in the vector line data according to at least one previously acquired standard road structure model, and marking the suspected road structure; judging whether at least one marked suspected road structure is a candidate road structure; after judging that the marked suspected road structure is a candidate road structure, extracting the candidate road structure; the selected road structure and/or the candidate road structure are/is corrected and/or supplemented. The method can automatically extract the standardized pre-selected road structure according to the standardized standard road structure model, mark the non-standardized suspected road structure, and further process the suspected road structure in a screening way, thereby improving the extraction efficiency and precision compared with the road structure extraction means which only depends on operator screening in the prior art.
Description
Technical Field
The invention relates to the technical field of measurement and control, in particular to a system and a method for extracting a road structure based on a vector line.
Background
With the complication of traffic networks and the diversification of vehicle types; the requirement for the refinement of the high-precision electronic map is higher and higher.
When high-precision maps are applied to the field of automatic driving, it is necessary to provide position and topology information based on roads and lanes. Then, it is necessary to extract structural information such as intersections and lane changes, such as intersections at ordinary traffic lights, when making a high-precision map.
In the prior art, a method for extracting road structure information such as intersections, lane increase and decrease with high precision is generally based on original data such as laser point cloud or based on shape lines extracted from the original data. And then the operator manually confirms the position of the change of the road structure and extracts the road structure. The method is limited by manual operation of operators, so that the operation process is complicated, the consumed time is long, and due to different technical backgrounds of the operators, high-precision data made by the operators may have differences, and the data requirements of high-precision maps cannot be met.
Disclosure of Invention
The embodiment of the invention at least discloses a road structure extraction method based on vector lines. The method disclosed by the embodiment can automatically extract the standardized pre-selected road structure according to the standardized standard road structure model, mark the non-standardized suspected road structure, and further process the suspected road structure in a screening way, so that the extraction efficiency and the extraction precision are improved compared with the road structure extraction means which is only screened by operators in the prior art.
To achieve the above, the method is configured to acquire vector line data of a high-precision map; extracting at least one selected road structure and/or at least one suspected road structure in the vector line data according to at least one previously acquired standard road structure model, and marking the suspected road structure; judging whether the suspected road structure of at least one mark is a candidate road structure; after the suspected road structure marked is judged to be a candidate road structure, extracting the candidate road structure; -correcting and/or supplementing said pre-selected road structure and/or said candidate road structure.
In some embodiments of the present disclosure, the method is configured with: acquiring a first candidate road image of the candidate road structure; and selecting at least one first candidate road image as a sample, and correcting the standard road structure model.
In some embodiments of the present disclosure, the method is configured with: generating a road-prior image of the corrected and/or supplemented road-prior structure; and selecting at least one of the first selected road images as a sample, and correcting the standard road structure model.
In some embodiments of the present disclosure, the method is configured with: generating a second candidate road image of the corrected and/or supplemented candidate road structure; and selecting at least one second candidate road image as a sample, and correcting the standard road structure model.
In some embodiments disclosed herein, obtaining the prior-selected road structure is configured to: acquiring at least one vector line in the vector line data; acquiring a starting point coordinate of the vector line; acquiring a starting point coordinate set of all vector lines; acquiring a starting point coordinate in at least one first preset area through the starting point coordinate set; distinguishing a starting point scene type of the starting point coordinates in the first preset area according to the starting point coordinates and the types corresponding to the vector lines; and intercepting a first vector line segment corresponding to the starting point coordinate in the first preset area, and extracting the first vector line segment as the prior road structure according to the standard road structure model and the starting point scene type.
In some embodiments disclosed herein, obtaining the prior-selected road structure is configured to: acquiring at least one vector line in the vector line data; acquiring the end point coordinates of the vector line; acquiring a terminal coordinate set of all vector lines; acquiring an end point coordinate in at least one second preset area throughout the start point coordinate set; distinguishing the end point scene type of the end point coordinate in the second preset area according to the end point coordinate and the type corresponding to the vector line; and intercepting a second vector line segment corresponding to the terminal point coordinate in the second preset area, and extracting the second vector line segment as the prior road structure according to the standard road structure model and the terminal point scene type.
In some embodiments of the present disclosure, the obtaining of the suspected road structure is configured to: acquiring the starting point coordinate which does not belong to the selected road structure as a candidate starting point coordinate, and acquiring the end point coordinate as a candidate end point coordinate; and generating the suspected road structure according to the coordinate track between the candidate starting point coordinate and the candidate ending point coordinate.
In some embodiments of the present disclosure, the suspected road structure marked by the determination is the candidate road structure, and the determination is configured to: displaying the marked at least one suspected road structure; and manually screening at least one suspected road structure as the candidate road structure.
The embodiment of the invention at least discloses a road structure extraction system based on vector lines. The system comprises a vector line data module, an automatic identification module, an auxiliary identification module and a correction identification module; the vector line data module is configured to obtain vector line data of a high-precision map; the automatic identification module is configured to extract at least one pre-selected road structure and/or at least one suspected road structure in the vector line data according to at least one previously acquired standard road structure model, and mark the suspected road structure; the auxiliary identification module is configured to determine whether the suspected road structure of at least one mark is a candidate road structure, and extract the candidate road structure after determining that the suspected road structure of the mark is a candidate road structure; the revision identification module is configured to revise and/or supplement the prior road structure and/or the candidate road structure.
In some embodiments of the present disclosure, the system includes a model modification module; the secondary identification module is configured with: acquiring a first candidate road image of the candidate road structure; the revision identification module is configured to: generating a first selected road image of the first selected road structure after correction and/or supplementation and a second candidate road image of the candidate road structure; the model modification module is configured to; and correcting the standard road structure model according to the first candidate road image, the second candidate road image and the selected road image.
In view of the above, other features and advantages of the disclosed exemplary embodiments will become apparent from the following detailed description of the disclosed exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of an embodiment in which a method is performed;
FIG. 2 is a flow chart of an embodiment of a method performed after optimization;
FIG. 3 is a flow chart of the method executed after optimization in the embodiment;
fig. 4 is a flowchart in which S100 is executed in the embodiment.
Fig. 5 is a block diagram of the system in the embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
The embodiment discloses a road structure extraction method based on vector lines. The method of the present embodiment is performed at some standardized server and/or computing device.
The server and/or computing device is implemented in this embodiment with at least a memory and a processor. The memory mainly comprises a program storage area and a data storage area; the storage program area may store an operating system (for example, an android operating system, abbreviated as "android system", or an ios operating system, or another operating system, where the operating system may also be abbreviated as "system"), and an application program (for example, a sound playing function, an image playing function, etc.) required by at least one function. And, the storage data area may store data created according to the use of the electronic terminal, including related setting information or use condition information of the displayed application, etc., which are referred to in the embodiments of the present application. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, and other volatile solid state storage devices.
The server and/or the computing device acquires laser point clouds obtained by a vehicle through a laser scanner and extracts vector line data based on the laser point clouds before executing the method disclosed by the embodiment. The vector line data is processed as shown in fig. 1 when the method disclosed in the present embodiment is performed.
S100, according to a preset standard road structure model or the combination of at least two standard road structure models, a selected road structure in the vector line data is automatically extracted, and a suspected road structure is marked.
S200 provides an operable first display window to display the marked suspected road structures, so that the operator can determine whether each marked suspected road structure is a candidate road structure through the first display window.
S300, after determining that a suspected road structure is a candidate road structure, an operator manually extracts the candidate road structure through the first display window.
S400 provides a second display window operable to display the automatically extracted first-selected road structure and the manually extracted candidate road structure. And then the operator observes and corrects the first selected road structure and/or the candidate road structure through the second display window.
After the server and/or the computing equipment executes the process of the method, the selected road structure can be automatically extracted through the standard road structure model, and then the candidate road structure is manually screened by an operator; compared with the prior art, the automatic extraction of the road structure selected in advance and the marking of the suspected road structure can be realized through the standardized standard road structure model, and the extraction efficiency and the accuracy are improved.
Further, fig. 2 illustrates that the server and/or the computing device generates a first candidate road image of the candidate road structure displayed in the first display window when the candidate road structure is extracted by the operator in the method S300 disclosed in the present embodiment; meanwhile, in S500 following the above-described flow, all the first candidate road images are selected as samples for correcting the standard road structure model.
Further, fig. 3 illustrates that after the operator corrects the first-chosen road structure and the candidate road structure in the method S400 disclosed in the embodiment, the server and/or the computing device generates the first-chosen road image of the corrected first-chosen road structure and the first candidate road image of the corrected candidate road structure displayed in the second display window. In S500, all of the first candidate road image, the second candidate road image, and the first selected road image are selected as samples for correcting the standard road structure model.
Fig. 4 shows a flow of acquiring the pre-selected road structure when the server and/or the computing device executes S100 disclosed in this embodiment.
S111, acquiring a start point coordinate and an end point coordinate of the vector line under a Cartesian rectangular coordinate system.
S112 obtains the start point coordinate set and the end point coordinate set of all vector lines.
S113 goes through the start point coordinate set to obtain the start point coordinates in at least one first preset area.
S114, distinguishing the starting point scene type of the starting point coordinate in the first preset area according to the starting point coordinate and the type of the corresponding vector line, wherein the starting point scene type comprises a boundary starting point, a lane increasing starting point, a diversion intersection starting point, an intersection starting point and the like.
S115, a first vector line segment corresponding to the starting point coordinate in the first preset area is intercepted, and the first vector line segment is extracted as a road structure to be selected first according to the standard road structure model and the starting point scene type.
S116 goes through the start point coordinate set to obtain the end point coordinate in at least one second preset region.
And S117, distinguishing the end point scene type of the end point coordinate in the second preset area according to the end point coordinate and the type of the corresponding vector line, wherein the end point scene type is an end point at the boundary, a lane reduction end point, an end point at a confluence intersection and an end point at an intersection.
S118, a second vector line segment corresponding to the terminal point coordinate in the second preset area is intercepted, and the second vector line segment is extracted as a road structure to be selected first according to the standard road structure model and the terminal point scene type.
The server and/or the computing device obtains the flow of the suspected road structure when executing S100 disclosed in the present embodiment.
S121, acquiring a starting point coordinate which does not belong to the road selecting structure in advance as a candidate starting point coordinate, and acquiring an end point coordinate as a candidate end point coordinate.
And S122, generating a suspected road structure according to the coordinate track between the candidate starting point coordinates and the candidate ending point coordinates.
To further illustrate the main flow of the method of the present embodiment. Fig. 5 illustrates a system for extracting a road structure based on vector lines according to the present embodiment. The system comprises a vector line data module, an automatic identification module, an auxiliary identification module, a correction identification module and a model correction module.
The vector line data module is configured to obtain vector line data of a high-precision map.
The automatic identification module is configured to extract at least one pre-selected road structure and/or at least one suspected road structure in the vector line data according to at least one previously acquired standard road structure model, and to mark the suspected road structure.
The auxiliary identification module is configured to determine whether the at least one marked suspected road structure is a candidate road structure, and extract the candidate road structure after determining that the marked suspected road structure is a candidate road structure. And acquiring a first candidate road image of the candidate road structure.
The revised identification module is configured to revise and/or supplement the selected road structure and the candidate road structure. And generating a first-selected-road image of the corrected and/or supplemented first-selected-road structure and a second candidate-road image of the candidate-road structure.
The model modification module is configured to modify the standard road structure model based on the first candidate road image, the second candidate road image, and the first selected road image.
The present embodiment is described in detail above. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is simple, and the related points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
The embodiments are described in a progressive mode in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the apparatuses disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is simple, and for related points, reference may be made to the description of the method.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the various examples have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It should also be noted that, in this specification, 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. Also, 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 phrases "comprising a component of' 8230; \8230;" does not exclude the presence of additional like elements in the process, method, article, or apparatus that comprises the element.
Claims (9)
1. A road structure extraction method based on vector lines is characterized in that,
the method is configured to:
acquiring vector line data of a high-precision map;
extracting at least one selected road structure and/or at least one suspected road structure in the vector line data according to at least one previously acquired standard road structure model, and marking the suspected road structure;
obtaining the select-ahead road structure configured to: acquiring at least one vector line in the vector line data; acquiring a starting point coordinate of the vector line;
acquiring a starting point coordinate set of all vector lines; acquiring a starting point coordinate in at least one first preset area throughout the starting point coordinate set; distinguishing a starting point scene type of the starting point coordinates in the first preset area according to the starting point coordinates and the types corresponding to the vector lines; intercepting a first vector line segment corresponding to the starting point coordinate in the first preset area, and extracting the first vector line segment as the prior road selection structure according to the standard road structure model and the starting point scene type;
judging whether the suspected road structure of at least one mark is a candidate road structure;
after the suspected road structure marked is judged to be a candidate road structure, extracting the candidate road structure;
correcting and/or supplementing the pre-selected road structure and/or the candidate road structure.
2. The vector-line-based road structure extraction method according to claim 1, wherein the method is configured with:
acquiring a first candidate road image of the candidate road structure;
and selecting at least one first candidate road image as a sample, and correcting the standard road structure model.
3. The vector-line-based road structure extraction method according to claim 1, wherein the method is configured with:
generating a corrected and/or supplemented prior road image of the prior road structure;
and selecting at least one of the first selected road images as a sample, and correcting the standard road structure model.
4. The vector-line-based road structure extraction method according to claim 1, wherein the method is configured with:
generating a second candidate road image of the corrected and/or supplemented candidate road structure;
and selecting at least one second candidate road image as a sample, and correcting the standard road structure model.
5. The vector-line-based road structure extraction method according to claim 1, wherein the pre-selected road structure is obtained and configured to: acquiring at least one vector line in the vector line data;
acquiring the end point coordinates of the vector line;
acquiring a terminal coordinate set of all vector lines;
acquiring a terminal coordinate in at least one second preset area after traversing the starting point coordinate set; distinguishing the end point scene type of the end point coordinate in the second preset area according to the end point coordinate and the type corresponding to the vector line;
and intercepting a second vector line segment corresponding to the terminal point coordinate in the second preset area, and extracting the second vector line segment as the prior road structure according to the standard road structure model and the terminal point scene type.
6. The vector-line-based road structure extraction method according to claim 5, wherein the suspected road structure is obtained by being configured to: acquiring the starting point coordinate which does not belong to the selected road structure as a candidate starting point coordinate, and acquiring the end point coordinate as a candidate end point coordinate;
and generating the suspected road structure according to the coordinate track between the candidate starting point coordinate and the candidate ending point coordinate.
7. The vector-line-based road structure extraction method according to claim 1, wherein the suspected road structure of the judgment mark is the candidate road structure, and is configured to: displaying the marked at least one suspected road structure;
and manually screening at least one suspected road structure as the candidate road structure.
8. A road structure extraction system based on vector lines is characterized in that,
the system comprises a vector line data module, an automatic identification module, an auxiliary identification module and a correction identification module;
the vector line data module is configured to obtain vector line data of a high-precision map;
the automatic identification module is configured to extract at least one pre-selected road structure and/or at least one suspected road structure in the vector line data according to at least one previously acquired standard road structure model, and mark the suspected road structure;
the obtaining the prior road structure is configured to obtain at least one vector line in the vector line data; acquiring a starting point coordinate of the vector line;
acquiring a starting point coordinate set of all vector lines; acquiring a starting point coordinate in at least one first preset area through the starting point coordinate set; distinguishing a starting point scene type of the starting point coordinate in the first preset area according to the starting point coordinate and the type corresponding to the vector line; intercepting a first vector line segment corresponding to the starting point coordinate in the first preset area, and extracting the first vector line segment as the prior road structure according to the standard road structure model and the starting point scene type;
the auxiliary identification module is configured to determine whether the at least one marked suspected road structure is a candidate road structure, and extract the candidate road structure after determining that the marked suspected road structure is a candidate road structure;
the revision identification module is configured to revise and/or supplement the prior road structure and/or the candidate road structure.
9. The vector-line-based road structure extraction system according to claim 8, wherein the system includes a model modification module;
the secondary identification module is configured with:
acquiring a first candidate road image of the candidate road structure;
the revision identification module is configured to:
generating a first selected road image of the first selected road structure after correction and/or supplementation and a second candidate road image of the candidate road structure;
the model revision module is configured to;
and correcting the standard road structure model according to the first candidate road image, the second candidate road image and the selected road image.
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