CN114840626A

CN114840626A - High-precision map data processing method, driving navigation method and related device

Info

Publication number: CN114840626A
Application number: CN202210524589.XA
Authority: CN
Inventors: 杨帅
Original assignee: Apollo Intelligent Connectivity Beijing Technology Co Ltd
Current assignee: Apollo Intelligent Connectivity Beijing Technology Co Ltd
Priority date: 2022-05-13
Filing date: 2022-05-13
Publication date: 2022-08-02

Abstract

The invention provides a high-precision map data processing method, a driving navigation method and a related device, relates to the technical field of artificial intelligence such as a vehicle networking, an intelligent cabin, a high-precision map and automatic driving, and can be applied to intelligent traffic scenes. The method comprises the following steps: acquiring first high-precision map data describing lane area map information in a point and line form; performing curve smoothing processing on line data in the first high-precision map data to obtain second high-precision map data; and performing dimension-raising operation on the second high-precision map data to construct third high-precision map data for describing the lane area map information in a surface and/or three-dimensional form. Compared with three-dimensional map data directly obtained through inclination measurement during aerial photography, the method can remarkably reduce the data volume of the third high-precision map data under the condition of ensuring the precision, so that the performance of vehicle-mounted hardware equipment is better matched, and lane-level navigation with higher immersion sense can be provided for a user driving an automatic driving vehicle.

Description

High-precision map data processing method, driving navigation method and related device

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to the field of artificial intelligence technologies such as car networking, intelligent cockpit, high-precision maps, and automatic driving, and can be applied to intelligent traffic scenes, and in particular, to a high-precision map data processing method, a driving navigation method, and a corresponding apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

Background

With the rapid development of the automatic driving technology, the data products of the high-precision map are continuously iterated and perfected, and the iteration direction mainly faces to two angles of precision improvement and stereoscopic impression enhancement.

Because the actual use object of the high-precision map is the hardware equipment of the automatic driving vehicle, and the high-dimensional high-precision map data acquired by conventional aerial photography in a tilted photogrammetry mode has huge data volume, the storage capacity and the calculation performance of the vehicle-mounted hardware equipment can not meet the actual automatic driving requirement.

Disclosure of Invention

The embodiment of the disclosure provides a high-precision map data processing method, a driving navigation method, corresponding devices, electronic equipment, a computer readable storage medium and a computer program product.

In a first aspect, an embodiment of the present disclosure provides a high-precision map data processing method, including: acquiring first high-precision map data describing map information of a lane area in a point and line form; performing curve smoothing processing on line data in the first high-precision map data to obtain second high-precision map data; and performing dimension-raising operation on the second high-precision map data to construct third high-precision map data for describing the lane area map information in a surface and/or three-dimensional form.

In a second aspect, an embodiment of the present disclosure provides another high-precision map data processing method, including: acquiring first high-precision map data describing lane area map information in a point and line form; performing curve smoothing processing on line data in the first high-precision map data to obtain second high-precision map data; performing dimension-increasing operation on the second high-precision map data to construct third high-precision map data describing the map information of the lane area in a surface and/or three-dimensional form; acquiring first standard map data describing map information of other areas in a dot and line form; wherein the accuracy of the first standard map data is lower than that of the first high-accuracy map data, and the map information of other areas is map information of other areas except the lane area; performing dimension-increasing operation on the first standard map data to construct second standard map data which describe map information of other areas in a planar and/or three-dimensional form; and fusing the second standard map data and the third high-precision map data to obtain the map data of the whole area.

In a third aspect, an embodiment of the present disclosure provides a driving navigation method, including: determining a current position in response to receiving a driving navigation request; presenting driving navigation information corresponding to the current position based on the third high-precision map data or the full-area map data; the third high-precision map data is obtained according to the high-precision map data processing method described in any implementation manner of the first aspect, and the full-area map data is obtained according to the high-precision map data processing method described in any implementation manner of the second aspect.

In a fourth aspect, an embodiment of the present disclosure provides a high-precision map data processing apparatus, including: a first high-precision map data acquisition unit configured to acquire first high-precision map data describing lane area map information in the form of points and lines; a curve smoothing unit configured to perform curve smoothing on line data in the first high-precision map data to obtain second high-precision map data; and a first dimension-raising operation unit configured to perform a dimension-raising operation on the second high-precision map data to construct third high-precision map data describing the lane area map information in a planar and/or three-dimensional stereoscopic form.

In a fifth aspect, another high-precision map data processing apparatus provided in an embodiment of the present disclosure includes: a first high-precision map data acquisition unit configured to acquire first high-precision map data describing lane area map information in the form of points and lines; a curve smoothing unit configured to perform curve smoothing on line data in the first high-precision map data to obtain second high-precision map data; a first dimension-increasing operation unit configured to perform a dimension-increasing operation on the second high-precision map data to construct third high-precision map data describing lane area map information in a planar and/or three-dimensional stereoscopic form; a first standard map data acquisition unit configured to acquire first standard map data describing other regional map information in dot and line form; wherein the accuracy of the first standard map data is lower than that of the first high-accuracy map data, and the map information of other areas is map information of other areas except the lane area; a second dimension-increasing operation unit configured to perform dimension-increasing operation on the first standard map data to construct second standard map data describing map information of other areas in a planar and/or three-dimensional stereoscopic form; and the map data fusion unit is configured to fuse the second standard map data and the third high-precision map data to obtain the full-area map data.

In a sixth aspect, an embodiment of the present disclosure provides a driving navigation apparatus, including: a current position determination unit configured to determine a current position in response to receiving a driving navigation request; a driving navigation information providing unit configured to present driving navigation information corresponding to the current position based on the third high-precision map data or the full-area map data; wherein the third high-precision map data is obtained according to the high-precision map data processing device described in any one of the fourth aspects, and the full-area map data is obtained according to the high-precision map data processing device described in any one of the fifth aspects.

In a seventh aspect, an embodiment of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to implement the high-precision map data processing method as described in any one of the implementations of the first aspect and/or the high-precision map data processing method as described in any one of the implementations of the second aspect and/or the vehicle navigation method as described in any one of the implementations of the third aspect when executed.

In a sixth aspect, the disclosed embodiments provide a non-transitory computer-readable storage medium storing computer instructions for enabling a computer to implement the high-precision map data processing method described in any implementation manner of the first aspect and/or the high-precision map data processing method described in any implementation manner of the second aspect and/or the driving navigation method described in any implementation manner of the third aspect.

In a seventh aspect, the present disclosure provides a computer program product including a computer program, which when executed by a processor can implement the steps of the high-precision map data processing method described in any implementation manner of the first aspect and/or the high-precision map data processing method described in any implementation manner of the second aspect and/or the driving navigation method described in any implementation manner of the third aspect.

According to the high-precision map data processing method provided by the embodiment of the disclosure, when first high-precision map data describing lane area map information in a point and line form is acquired, smoothness of line data is improved through curve smoothing processing, and then dimension increasing is performed on a zero-dimensional point and a one-dimensional line, so that third high-precision map data represented by a two-dimensional surface and a three-dimensional stereo form is obtained. Since the first high-precision map data contains only the low-dimensional map information of the lane area and other useless details for lane-level navigation are removed, the data amount of the finally obtained third high-precision map data can be significantly reduced even by the dimension-increasing operation, so that the performance of the on-vehicle hardware equipment is better matched, and the lane-level navigation with higher immersion can be provided for the user driving the autonomous vehicle.

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

Other features, objects and advantages of the disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:

FIG. 1 is an exemplary system architecture to which the present disclosure may be applied;

fig. 2 is a flowchart of a high-precision map data processing method according to an embodiment of the present disclosure;

fig. 3 is a flowchart of a method for performing a dimension-increasing operation on a lane guardrail line according to an embodiment of the disclosure;

fig. 4 is a schematic flow chart illustrating a dimension-increasing operation performed on a lane guardrail line according to an embodiment of the disclosure;

fig. 5 is a flowchart of a method for performing a dimension-increasing operation on a lane boundary according to an embodiment of the present disclosure;

fig. 6 is a flowchart of another high-precision map data processing method provided in the embodiment of the present disclosure;

fig. 7 is a block diagram of a high-precision map data processing apparatus according to an embodiment of the present disclosure;

fig. 8 is a block diagram of another high-precision map data processing apparatus according to an embodiment of the present disclosure;

fig. 9 is a block diagram of a driving navigation apparatus according to an embodiment of the present disclosure;

fig. 10 is a schematic structural diagram of an electronic device suitable for executing a high-precision map data processing method and/or a driving navigation method according to 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. It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict.

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.

Fig. 1 illustrates an exemplary system architecture 100 to which embodiments of the high-precision map data processing method, the driving navigation method, and corresponding apparatus, electronic devices, and computer-readable storage media of the present disclosure may be applied.

As shown in fig. 1, the system architecture 100 may include a ground survey vehicle 101, a map server 102, and an autonomous vehicle 103. Data transmission paths are established between the ground measuring vehicle 101, the map server 102 and the automatic driving vehicle 103, such as a wireless network or other types.

The ground survey vehicle 101 is provided with various map data measuring devices such as a millimeter wave radar, a laser scanner, a camera, and the like, so as to collect high-precision map data of a travel area by continuous travel; the map server 102 is configured to process raw map data collected by the map measuring vehicle 101, so as to obtain target high-precision map data that can provide a greater picture sense and immersion sense for a large number of drivers of the autonomous vehicle 103 and that matches the performance of on-vehicle hardware devices, and thus provide driving navigation based on the target high-precision map data.

The ground survey vehicle 101, the map server 102, and the autonomous vehicle 103 may be installed with various applications for implementing information communication therebetween, such as an original map data collection application, a high-precision map generation application, and a driving navigation application.

The map server 102 may provide various services through various built-in applications, for example, a high-precision map generation application that can generate high-dimensional high-precision map data based on low-dimensional high-precision map data may be provided, and the map server 102 may implement the following effects when running the high-precision map generation application: firstly, receiving original high-precision map data acquired by a ground measuring vehicle 101 for a lane area; then, extracting first high-precision map data which are related to the key information of lane navigation and are represented by points and lines from the original high-precision map data; then, performing curve smoothing processing on line data in the first high-precision map data to obtain second high-precision map data; and finally, performing dimension-raising operation on the second high-precision map data to construct third high-precision map data for describing the map information of the lane area in a planar and/or three-dimensional form.

It should be noted that the original high-precision map data may be acquired from the ground measuring vehicle 101 in real time, or may be stored in advance in a local storage unit of the map server 102 in various ways. Thus, when the map server 102 detects that such data is already stored locally (e.g., a mapping task remaining before beginning processing), it may choose to retrieve such data directly from locally, in which case the example system architecture 100 may also not include the ground measuring vehicle 101.

After the map server 102 generates the third high-precision map data by the built-in high-precision map application, the third high-precision map data may be transmitted to each autonomous vehicle 103 that requires the map for driving navigation by the built-in data transmission application.

Furthermore, in order to optimize the viewing experience of passengers, standard map data of map information of other areas except the lane area can be fused on the basis of the third high-precision map data to fill the surrounding background information of lane-level navigation, and finally, the map data of the whole area can be obtained.

It should be understood that the number of ground measuring vehicles, map servers, and autonomous vehicles in FIG. 1 are merely illustrative. There may be any number of ground survey vehicles, map servers, and autonomous vehicles, as desired for implementation.

Referring to fig. 2, fig. 2 is a flowchart of a high-precision map data processing method according to an embodiment of the disclosure, where the process 200 includes the following steps:

step 201: acquiring first high-precision map data describing lane area map information in a point and line form;

this step is intended to acquire, by an execution subject of the high-precision map data processing method (for example, the map server 102 shown in fig. 1), first high-precision map data describing lane area map information in the form of points and lines, that is, the first high-precision map data is constituted of low-dimensional data such as point data and line data, and the low dimension is with respect to high-dimensional data constituted of face data and three-dimensional data.

The first high-precision map data can be extracted from original high-precision map data acquired from various acquisition devices erected on a ground measuring vehicle on a lane area related to a driving road surface, and the point data in the first high-precision map data can be point cloud data acquired by scanning the lane area through a laser scanner erected on the ground measuring vehicle, can be certain specific points in complete point cloud data, can also be certain data points sensed by a millimeter wave radar, and can even be certain key points extracted from an image shot by a vehicle-mounted camera, such as certain points representing lane marks, front and rear vehicles and obstacles; the line data in the first high-precision map data may be obtained by connecting or fitting a plurality of points representing the same object in the point cloud data, or may be extracted or extracted from a side of an object (for example, a boundary line of a lane) recorded in an image captured by the vehicle-mounted camera.

Step 202: performing curve smoothing processing on line data in the first high-precision map data to obtain second high-precision map data;

on the basis of step 201, this step is intended to perform curve smoothing processing on line data in the first high-precision map data by the execution subject described above. The reason why the curve smoothing process is performed on the line data in the first high-precision map data is that the data dimension is relatively low due to the acquisition mode and the acquisition height of the ground measuring vehicle, so that some lines obtained by direct drawing or fitting are not smooth, and the error is further amplified when the uneven lines are subjected to lifting dimension to form a surface or further lifting dimension to form a three-dimensional stereogram. Therefore, the purpose of curve smoothing is to eliminate as much error as possible in the subsequent upscaling operation of low-dimensional data.

Step 203: and performing dimension-raising operation on the second high-precision map data to construct third high-precision map data for describing the lane area map information in a surface and/or three-dimensional form.

On the basis of step 202, this step is intended to construct third high-precision map data describing lane area map information in a planar and/or three-dimensional stereoscopic form by performing an up-dimensional operation on the second high-precision map data by the execution subject described above. The data dimension of the second high-precision map data is improved through dimension-raising processing, and the low-dimensional lane area map data which are originally expressed as points and lines are raised and dimensioned into high-dimensional lane area map data which are more in line with the actual perception of a user and are expressed in a surface and/or three-dimensional form.

In the dimension-up process using the low-dimensional line data as the starting point of the dimension-up operation and the high-dimensional three-dimensional shape data as the target point of the dimension-up operation, the whole dimension-up operation can be divided into two parts which are sequentially performed, that is, the dimension-up operation is firstly performed based on the line data as the plane data, and then the plane data is performed the dimension-up operation as the three-dimensional shape data.

Naturally, it is necessary to rely on the dimension-increasing parameters such as the plane extending direction and the plane extending amount for accurately increasing the line data to the plane data in the dimension-increasing process, and similarly, the dimension-increasing parameters such as the height extending direction and the height extending amount for increasing the plane data to the three-dimensional stereo configuration data in the dimension-increasing process.

Similarly, the dimension-lifting operation related to other starting points and other target points can be adaptively adjusted according to the dimension-lifting thought, so that the dimension-lifting operation has pertinence, and the accuracy of a dimension-lifting result is improved.

In order to understand how to perform three-dimensional operations specifically, the present disclosure will also present a specific implementation manner for the following two different dimension-increasing objects, respectively:

referring to fig. 3, fig. 3 is a flowchart of a method for performing a dimension-increasing operation on a lane fence line according to an embodiment of the present disclosure, that is, a specific implementation manner of the dimension-increasing operation provided for the lane fence line in the second high-precision map data, where the flowchart 300 includes the following steps:

step 301: determining a plane extension direction and a first extension amount of a lane guardrail line;

the lane guardrail line is a line used for indicating a stereoscopic lane guardrail, namely only necessary position and trend information of the stereoscopic lane guardrail is reserved. Therefore, when performing a maintenance-up operation on the lane-guardrail line, it is necessary to first determine a planar extension direction and a first extension amount of the lane-guardrail line for guiding how to correctly generate a lane-guardrail surface based on the lane-guardrail line.

When determining the planar extension direction and the first extension of the lane barrier line, there are generally three ways: 1) when the lane guardrail line is abstracted from the upper edge of the lane guardrail surface showing the trend of the lane guardrail, the plane extending direction only comprises a downward extending direction, and the first extending amount is the length from the upper edge to the lower edge; 2) when the lane guardrail line is abstracted from a center line of the lane guardrail surface showing the trend of the lane guardrail, the plane extending direction simultaneously comprises an upward extending direction and a downward extending direction, and the first extending amount is the length from the center line to the upper edge or the lower edge respectively; 3) when the lane guardrail line is abstracted from the lower edge of the lane guardrail surface showing the trend of the lane guardrail, the plane extending direction only comprises the upward extending direction, and the first extending amount is the length from the lower edge to the upper edge.

Step 302: extending the lane guardrail line along the plane extension direction by a first extension amount to obtain a lane guardrail surface;

in step 301, the lane protecting line is extended by a first extension amount along the plane extension direction by the executing body to obtain a lane protecting surface. That is, by extending the correct extension amount in the correct extension direction, the correct lane fence surface is obtained based on the lane fence line.

Step 303: determining the height extension direction and the second extension amount of the lane guardrail surface;

on the basis that the lane guard surface has been obtained in step 302, this step is intended to further determine the height extension direction and the second extension amount of the lane guard surface from the above-described execution body. I.e. the height extension direction and the second extension amount, are the up-dimensional parameters for determining the correct up-dimension of the two-dimensional plane into the three-dimensional stereo morphology.

Step 304: extending the surface of the lane guardrail along the height extension direction by a second extension amount to obtain a three-dimensional lane guardrail;

on the basis of step 303, this step is similar to step 302, and the right stereoscopic lane guardrail is obtained based on the lane guardrail surface by extending the right extending amount towards the right extending direction.

Step 305: generating third high-precision map data containing a stereoscopic lane guardrail;

on the basis of step 304, this step is intended to generate third high-precision map data containing a stereo lane guardrail from the execution subject described above. It should be noted that the third high-precision map data usually includes other lane related data such as a lane surface in addition to the stereo lane fence, and this embodiment only aims at the stereo lane fence portion, and when the third high-precision map data also includes other lane related data, the third high-precision map data also includes a corresponding dimension-raising operation portion.

That is, in this embodiment, through steps 301 to 305, taking a low-dimensional lane guardrail line as an example, a dimension-increasing implementation scheme is provided, in which dimension-increasing is performed from a line to a plane, and dimension-increasing is performed from a plane to a three-dimensional form, on the basis of ensuring the direction of the lane guardrail, dimension-increasing operation is performed from low-dimensional data, so that useless detail data carried by high-dimensional data can be prevented from being directly acquired, and further, the perception of a user is improved while the data volume is significantly reduced, and the performance of vehicle-mounted hardware equipment is better matched.

Further, since the lane barriers are not only straight lines, but also are usually broken lines at the intersection, that is, two connected lane barrier lines, when the dimension-increasing operation is performed according to the above embodiment, a connection gap is easily formed between the respectively constructed lane barrier surfaces, thereby affecting the subsequent dimension-increasing operation. In response to this problem, the present disclosure further provides an improvement:

responding to the existence of a connecting gap between the two target lane guardrail surfaces, respectively extending the edge lines of the target lane guardrail surfaces to obtain intersection points of the extended edge lines; the two target lane guardrail surfaces are obtained by performing dimension increasing operation on two connected target lane guardrail lines respectively;

and splicing the two target lane guardrail surfaces into a complete new lane guardrail surface based on the intersection point.

In order to facilitate understanding of the repairing operation of the connecting gap, reference may also be made to a flow chart of the maintenance-up operation performed on the lane guardrail line shown in fig. 4, that is, fig. 4 shows, step by step, how to perform the maintenance-up operation on the lane guardrail line to finally obtain the stereoscopic lane guardrail, in a manner indicated by an arrow:

1) representing coordinates of two endpoints of a line segment representing the lane guardrail line in a pre-constructed three-dimensional space coordinate system, and then connecting the two endpoints to obtain the lane guardrail line;

2) calculating two temporary points on a plumb line of the lane guardrail line according to the coordinates of the middle point and the two end points of the lane guardrail line, determining the extending direction of the line corresponding to the two temporary points as the direction of the plumb line, taking the direction of the plumb line as the plane extending direction, and finally determining four new end points for forming a lane guardrail surface by combining with a first extending amount;

3) and sequentially connecting the four new end points to obtain the lane guardrail surface. At the moment, the fact that the connection gaps exist on the lane guardrail surfaces constructed respectively based on two connected lane guardrail lines with different directions is found;

4) when the connecting gap is repaired, an angular bisector N for calculating an included angle between an extension line A' of the guardrail line of the lane A and the guardrail line of the lane B is specifically used, and a line formed by N1 and N2 is a plumb line of N;

5) and according to the plumb line N1N2 as a connecting line for connecting two roadway surfaces, splicing to obtain a complete new roadway guardrail surface. In principle, the method is consistent with the method of extending the intersection point of the edge line;

6) and determining the plumb line of the new lane guardrail plane according to the same mode as the step 2), determining the plumb line of the new lane guardrail plane according to the plumb line, taking the plumb line as the height extension direction, and finally determining each endpoint for forming the three-dimensional lane guardrail by combining with the second extension amount.

Unlike the dimension-increasing operation for the lane guardrail line shown in fig. 3-4, fig. 5 is a flowchart of a method for performing the dimension-increasing operation on the lane boundary provided by the embodiment of the present disclosure, and the process 500 includes the following steps for a specific dimension-increasing operation provided by the lane boundary in the second high-precision map data:

step 501: determining two adjacent and parallel target lane boundaries;

lane boundaries, as the name implies, are boundaries between two adjacent lanes, i.e. the regions from one side of the lane boundary to the other side of the adjacent lane boundary, are regions to which the same lane belongs. Due to this characteristic, only using low dimensional data such as lane boundaries can actually provide accurate lane level navigation, but the perception to the user is poor because no detail is included.

This step is intended to determine two adjacent and parallel target lane boundaries from the execution body.

Step 502: respectively connecting the upper edges and the lower edges of the two target lane boundaries in the vertical direction of the target lane boundaries to obtain a closed lane surface;

in step 501, the step is to connect the upper edge and the lower edge of the two target lane boundaries in the vertical direction of the target lane boundaries by the execution body to obtain a closed lane surface.

Namely, the closed lane surface showing the lane width is obtained by closing the lower edge of the upper edge.

According to the above operation, an independent lane surface can be obtained for each lane. Of course, in order to avoid that a plurality of lane surfaces actually belong to the same large road surface, a large road surface may be formed based on the outermost lane boundary of the multiple parallel lanes, and divided into a plurality of lane surfaces according to other lane boundaries included therein.

Step 503: third high-precision map data including the lane surface of each lane is generated.

In addition to step 502, this step is intended to generate third high-precision map data including the lane surface of each lane by the execution subject described above. It should be noted that the third high-precision map data usually includes other lane related data such as a lane guard rail entity, a driving sign, a roadside sign, and the like, besides the lane surface, but since the embodiment is directed to the portion of the lane surface, the other portions are not expanded together.

That is, in this embodiment, through steps 501 to 503, taking a lane boundary of a low-dimensional vehicle as an example, a dimension-increasing implementation scheme taking line dimension-increasing as a plane is provided, and by performing dimension-increasing operation on low-dimensional data, useless detail data carried by high-dimensional data can be prevented from being directly acquired, so that the user perception is improved, the data size is also significantly reduced, and the performance of vehicle-mounted hardware equipment is better matched.

The lane area may also include other related map data such as traffic lights, driving signs, direction signs, roadside signs, and the like, and the dimension increasing operation may be completed after adaptive adjustment by referring to the dimension increasing modes embodied in the two embodiments, which is not described herein any more.

In order to match the computational performance of the in-vehicle hardware devices of the autonomous vehicle, the high-precision map data provided by the above-described embodiments include only the lane area, i.e., the remaining map information that is not useful for lane-level navigation is completely discarded, and although the computational performance requirements of the in-vehicle hardware devices can be reduced to the maximum extent, the perception of the user driving the autonomous vehicle is not affected. To this end, the present embodiment further provides a flowchart of another high-precision map data processing method through fig. 6, where the flowchart 600 includes the following steps:

step 601: acquiring first high-precision map data describing lane area map information in a point and line form;

step 602: performing curve smoothing processing on line data in the first high-precision map data to obtain second high-precision map data;

step 603: performing dimension-increasing operation on the second high-precision map data to construct third high-precision map data describing the map information of the lane area in a surface and/or three-dimensional form;

step 604: acquiring first standard map data describing map information of other areas in a dot and line form;

wherein the standard map data has a map accuracy lower than that of the first high-accuracy map data. This is because the key of the lane-level navigation is the high-precision map data of the lane area, and the map data of the other areas except the lane area is not the necessary data, so the data amount can be reduced by reducing the precision requirement, for example, the precision error of the standard map data can be on the order of meters, even on the order of tens of meters.

Step 605: performing dimension-increasing operation on the first standard map data to construct second standard map data which describe map information of other areas in a planar and/or three-dimensional form;

in this step, the dimension increasing operation performed on the first standard map may be performed in the dimension increasing manner described in the above embodiment. However, it should be noted that, in some scenarios, the operation of obtaining the second standard map data based on the first standard map data may also be performed by another execution subject, and in this case, the execution subject only needs to execute step 606.

Step 606: and fusing the second standard map data and the third high-precision map data to obtain the map data of the whole area.

Step 605 performs similar dimension-increasing operation on the first standard map data, so that the second standard map data and the third high-precision map data can have a fusion basis due to the same data dimension, and finally, the full-area map data is obtained through fusion.

When the integrated full-area map data is used for providing lane-level navigation service for the automatic driving vehicle, the third high-precision map data serves as a main information providing source for lane-level navigation, and the second standard map data is more favorable for serving as a complement to other map information near a lane, such as the outline of surrounding buildings, a green water system, a far sign and the like, so that the perception and the immersion of a user are improved.

Furthermore, in order to ensure that the fused full-area map data does not have errors at certain positions of the viaduct and the positions with space overlapping conditions, the height information of the high-precision map data and the standard map data at the connecting positions can be processed uniformly, and the unified height information can be simply understood.

On the basis of any of the above embodiments, correctly performing the dimension-increasing operation is a basis for ensuring that a screen effect that can be presented by finally obtained third high-precision map data or full-area map data, and then, in order to ensure that the dimension-increasing operation can be correctly executed as much as possible, the present disclosure further provides an implementation scheme for how to obtain correct dimension-increasing parameters through the following embodiments:

acquiring a first live-action image corresponding to the lane area and a second live-action image corresponding to other areas;

and determining a dimension-increasing parameter when the dimension-increasing operation is performed on the second high-precision map data by using the first live-action image, for example: a plane extension direction, a height extension direction, a first extension amount and a second extension amount corresponding to the lane guardrail line;

and determining a dimension-increasing parameter when the dimension-increasing operation is performed on the first standard map data by using the second live-action image.

Namely, rich image information contained in the live-action image helps to obtain more accurate upscaling parameters.

The above embodiments all use a map server (e.g., map server 102 shown in fig. 1) as an execution subject, and how to generate the third high-precision map data and the full-area map data is illustrated at a multi-level, and the following describes how to change the angle to an autonomous vehicle (e.g., autonomous vehicle 103 shown in fig. 1) to provide lane-level navigation using the third high-precision map data or the full-area map data at the vehicle end.

A driving navigation method comprises the following steps:

determining a current position in response to receiving a driving navigation request;

and presenting the driving navigation information corresponding to the current position based on the third high-precision map data or the full-area map data.

Namely, when the automatic driving vehicle receives a driving navigation request, the current position of the vehicle is determined firstly, and then the third high-precision map data or the full-area map data is called to present the driving navigation information corresponding to the current position. That is, the third high-precision map data or the full-area map data is map data that matches the performance of the in-vehicle hardware device obtained by the scheme provided by the above-described embodiment.

With further reference to fig. 7-9, as an implementation of the above-described method embodiments, the present disclosure provides two different high-precision map data processing apparatus and an apparatus embodiment of a driving navigation apparatus, respectively. Among them, one embodiment of the high-precision map data processing device corresponds to the embodiment of the high-precision map data processing method shown in fig. 2, another embodiment of the high-precision map data processing device corresponds to the embodiment of the high-precision map data processing method shown in fig. 6, and the embodiment of the driving navigation device corresponds to the embodiment of the driving navigation method. The device can be applied to various electronic equipment.

As shown in fig. 7, the high-precision map data processing apparatus 700 of the present embodiment may include: a first high-precision map data acquisition unit 701, a curve smoothing unit 702, and a first dimension-increasing operation unit 703. Wherein the first high-precision map data acquisition unit 701 is configured to acquire first high-precision map data describing lane area map information in the form of points and lines; a curve smoothing unit 702 configured to perform curve smoothing on line data in the first high-precision map data to obtain second high-precision map data; a first dimension-increasing operation unit 703 configured to perform a dimension-increasing operation on the second high-precision map data to construct third high-precision map data describing the lane area map information in a planar and/or three-dimensional stereoscopic form.

In the present embodiment, in the high-precision map data processing apparatus 700: the detailed processing of the first high-precision map data obtaining unit 701, the curve smoothing processing unit 702, and the first dimension-increasing operation unit 703 and the technical effects thereof can refer to the related descriptions of step 201 and step 203 in the corresponding embodiment of fig. 2, which are not described herein again.

In some optional implementations of the present embodiment, the first dimension-increasing unit 703 may include a first dimension-increasing subunit configured to perform a dimension-increasing operation on the second high-precision map data, and construct third high-precision map data describing the lane area map information in a three-dimensional stereo form, and the first dimension-increasing subunit may be further configured to:

determining the plane extension direction and the first extension amount of the lane guardrail line aiming at the lane guardrail line in the second high-precision map data;

extending the lane guardrail line along the plane extension direction by a first extension amount to obtain a lane guardrail surface;

determining the height extension direction and the second extension amount of the lane guardrail surface;

extending the surface of the lane guardrail along the height extension direction by a second extension amount to obtain a three-dimensional lane guardrail;

third high-precision map data containing a stereo lane guardrail is generated.

In some optional implementations of the present embodiment, the high-precision map data processing apparatus 700 may further include:

the edge line extension unit is configured to respond to the existence of a connecting gap between two target lane guardrail surfaces, respectively extend the edge lines of the target lane guardrail surfaces and obtain intersection points of the extended edge lines; the two target lane guardrail surfaces are obtained by performing dimension increasing operation on two connected target lane guardrail lines respectively;

and the connecting gap repairing unit is configured to splice the two target lane guardrail surfaces into a complete new lane guardrail surface based on the intersection point.

In some optional implementations of the present embodiment, the first ascending dimension operation unit 703 may include a second ascending dimension operation subunit configured to perform an ascending dimension operation on the second high-precision map data, and construct third high-precision map data describing the lane area map information in a surface form, and the second ascending dimension operation subunit may be further configured to:

determining two adjacent and parallel target lane boundaries for lane boundaries in the second high-precision map data;

respectively connecting the upper edges and the lower edges of the two target lane boundaries in the vertical direction of the target lane boundaries to obtain a closed lane surface;

third high-precision map data including the lane surface of each lane is generated.

a first live-action image acquisition unit configured to acquire a first live-action image corresponding to the lane area;

and a first dimension-increasing parameter determination unit configured to determine a dimension-increasing parameter when the dimension-increasing operation is performed on the second high-precision map data using the first live-action image.

As shown in fig. 8, the high-precision map data processing apparatus 800 of the present embodiment may include: a first high-precision map data acquisition unit 801, a curve smoothing processing unit 802, a first ascending dimension operation unit 803, a first standard map data acquisition unit 804, a second ascending dimension operation unit 805, and a map data fusion unit 806. Wherein the first high-precision map data acquisition unit 801 is configured to acquire first high-precision map data describing lane area map information in the form of points and lines; a curve smoothing unit 802 configured to perform curve smoothing on line data in the first high-precision map data to obtain second high-precision map data; a first dimension-raising operation unit 803 configured to perform a dimension-raising operation on the second high-precision map data to construct third high-precision map data describing lane area map information in a planar and/or three-dimensional stereoscopic form; a first standard map data acquisition unit 804 configured to acquire first standard map data describing other regional map information in dot and line form; wherein the accuracy of the first standard map data is lower than that of the first high-accuracy map data, and the map information of other areas is map information of other areas except the lane area; a second ascending-dimension operation unit 805 configured to perform ascending-dimension operation on the first standard map data to construct second standard map data describing map information of other areas in a planar and/or three-dimensional stereoscopic form; and a map data fusion unit 806 configured to fuse the second standard map data and the third high-precision map data to obtain full-area map data.

In the present embodiment, in the high-precision map data processing apparatus 800: the detailed processing and the technical effects of the first high-precision map data obtaining unit 801, the curve smoothing processing unit 802, the first dimension-increasing operation unit 803, the first standard map data obtaining unit 804, the second dimension-increasing operation unit 805, and the map data fusion unit 806 can refer to the related descriptions of step 601 and step 606 in the corresponding embodiment of fig. 6, which are not described herein again.

In some optional implementations of the present embodiment, the first dimension-increasing operation unit 803 may include a first dimension-increasing subunit configured to perform a dimension-increasing operation on the second high precision map data, and construct third high precision map data describing the lane area map information in a three-dimensional stereo form, and the first dimension-increasing subunit may be further configured to:

and generating third high-precision map data containing the stereoscopic lane guardrail.

In some optional implementations of the present embodiment, the high precision map data processing apparatus 800 may further include:

and a height information unifying unit configured to unify the height information of the second high-precision map data and the first standard map data at the connected position before the ascending operation is performed on the first standard map data.

first and second live-action image acquisition units configured to acquire a first live-action image corresponding to a lane region and a second live-action image corresponding to another region;

a first dimension-increasing parameter determination unit configured to determine a dimension-increasing parameter when a dimension-increasing operation is performed on the second high-precision map data using the first live-action image;

and a second dimension-increasing parameter determination unit configured to determine a dimension-increasing parameter at the time of performing a dimension-increasing operation on the first standard map data using the second live-action image.

As shown in fig. 9, the car navigation device 900 of the present embodiment may include: current position determination section 901 and driving navigation information providing section 902. Wherein, the current position determining unit 901 is configured to determine the current position in response to receiving the driving navigation request; and a driving navigation information providing unit 902 configured to present driving navigation information corresponding to the current position based on the third high-precision map data or the full-area map data.

In the present embodiment, the car navigation device 900: the specific processing of the current position determining unit 901 and the driving navigation information providing unit 902 and the technical effects brought by the processing can respectively correspond to the related descriptions in the method embodiments, and are not described herein again.

The present embodiment exists as an apparatus embodiment corresponding to the above method embodiment, and the high-precision map data processing apparatus and the driving navigation apparatus provided in the present embodiment acquire first high-precision map data describing lane area map information in the form of points and lines, improve the smoothness of the line data by curve smoothing processing, and then perform dimension raising on zero-dimensional points and one-dimensional lines to obtain third high-precision map data represented in a two-dimensional surface and three-dimensional stereo form. Since the first high-precision map data contains only the low-dimensional map information of the lane area and other useless details for lane-level navigation are removed, the data amount of the finally obtained third high-precision map data can be significantly reduced even by the dimension-increasing operation, so that the performance of the on-vehicle hardware equipment is better matched, and the lane-level navigation with higher immersion can be provided for the user driving the autonomous vehicle.

According to an embodiment of the present disclosure, the present disclosure also provides an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to implement the high-precision map data processing method or the driving navigation method described in any of the above embodiments when executed.

According to an embodiment of the present disclosure, the present disclosure further provides a readable storage medium storing computer instructions for enabling a computer to implement the high-precision map data processing method or the driving navigation method described in any of the above embodiments when executed.

According to an embodiment of the present disclosure, the present disclosure also provides a computer program product, which when executed by a processor can implement the high-precision map data processing method or the driving navigation method described in any of the above embodiments.

FIG. 10 illustrates a schematic block diagram of an example electronic device 1000 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 processing, cellular phones, 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. 10, the apparatus 1000 includes a computing unit 1001 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)1002 or a computer program loaded from a storage unit 1008 into a Random Access Memory (RAM) 1003. In the RAM 1003, various programs and data necessary for the operation of the device 1000 can also be stored. The calculation unit 1001, the ROM 1002, and the RAM 1003 are connected to each other by a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.

A number of components in device 1000 are connected to I/O interface 1005, including: an input unit 1006 such as a keyboard, a mouse, and the like; an output unit 1007 such as various types of displays, speakers, and the like; a storage unit 1008 such as a magnetic disk, an optical disk, or the like; and a communication unit 1009 such as a network card, a modem, a wireless communication transceiver, or the like. The communication unit 1009 allows the device 1000 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.

Computing unit 1001 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated 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 1001 executes the respective methods and processes described above, such as a high-precision map data processing method or a driving navigation method. For example, in some embodiments, the high-precision map data processing method or the vehicle navigation method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 1008. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 1000 via ROM 1002 and/or communications unit 1009. When the computer program is loaded into the RAM 1003 and executed by the computing unit 1001, one or more steps of the high-precision map data processing method or the vehicle navigation method described above may be performed. Alternatively, in other embodiments, the computing unit 1001 may be configured to perform the high-precision map data processing method or the driving navigation 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), 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 may be a cloud Server, which is also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service extensibility in the conventional physical host and Virtual Private Server (VPS) service.

According to the technical scheme of the embodiment of the disclosure, the low-dimensional original high-precision map data acquired by the ground measuring vehicle for the lane area is selected, and the high-dimensional high-precision map data capable of improving the immersion feeling is obtained through the dimension increasing operation after curve smoothing processing. Because the ground survey car the collection height is limited, compare the three-dimensional map data that take photo by plane and directly obtain through the slope measurement, can show the data bulk that reduces the high-accuracy map data of target that constructs under the circumstances of guaranteeing the precision to the performance of better matching on-vehicle hardware equipment, and then can provide the lane level navigation that the sense of immersion is higher for the user who drives the autopilot vehicle.

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, 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, depending on 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 high-precision map data processing method comprises the following steps:

acquiring first high-precision map data describing lane area map information in a point and line form;

performing curve smoothing processing on line data in the first high-precision map data to obtain second high-precision map data;

and performing dimension-raising operation on the second high-precision map data to construct third high-precision map data for describing the lane area map information in a surface and/or three-dimensional form.

2. The method of claim 1, wherein performing a dimension-up operation on the second high-precision map data to construct third high-precision map data describing the lane area map information in a three-dimensional stereo modality comprises:

determining a plane extension direction and a first extension amount of a lane guardrail line in the second high-precision map data;

extending the lane guardrail line along the plane extension direction by the first extension amount to obtain a lane guardrail surface;

determining a height extension direction and a second extension amount of the lane guardrail surface;

extending the lane guardrail surface along the height extension direction by the second extension amount to obtain a three-dimensional lane guardrail;

3. The method of claim 2, further comprising:

responding to the existence of a connecting gap between two target lane guardrail surfaces, respectively extending the edge lines of the target lane guardrail surfaces to obtain intersection points of the extended edge lines; the two target lane guardrail surfaces are obtained by performing dimension increasing operation on two connected target lane guardrail lines respectively;

4. The method according to claim 1, wherein performing an upscaling operation on the second high-precision map data to construct third high-precision map data describing the lane area map information in a surface form includes:

5. The method of any of claims 1-4, further comprising:

acquiring a first live-action image corresponding to the lane area;

and determining a dimension-increasing parameter when dimension-increasing operation is carried out on the second high-precision map data by using the first live-action image.

6. A high-precision map data processing method comprises the following steps:

performing dimension-increasing operation on the second high-precision map data to construct third high-precision map data which describe the map information of the lane area in a surface and/or three-dimensional form;

acquiring first standard map data describing map information of other areas in a dot and line form; wherein the accuracy of the first standard map data is lower than that of the first high-accuracy map data, and the other-area map information is map information of an area other than the lane area;

performing dimension-increasing operation on the first standard map data to construct second standard map data which describe the map information of the other areas in a planar and/or three-dimensional form;

and fusing the second standard map data and the third high-precision map data to obtain the map data of the whole area.

7. The method of claim 6, wherein performing a dimension-up operation on the second high-precision map data to construct third high-precision map data describing the lane area map information in a three-dimensional stereo modality comprises:

generating third high-precision map data containing the stereoscopic lane guardrail.

8. The method of claim 7, further comprising:

9. The method according to claim 6, wherein performing an upscaling operation on the second high-precision map data to construct third high-precision map data describing the lane area map information in a surface form includes:

10. The method of claim 6, wherein prior to performing the upscaling operation on the first standard map data, further comprising:

unifying height information of the second high-precision map data and the first standard map data at a connected position.

11. The method according to any one of claims 6-10, further comprising:

acquiring a first live-action image corresponding to the lane area and a second live-action image corresponding to the other area;

determining a dimension-increasing parameter when dimension-increasing operation is carried out on the second high-precision map data by using the first live-action image;

12. A driving navigation method comprises the following steps:

presenting driving navigation information corresponding to the current position based on third high-precision map data or full-area map data; the third high-precision map data is obtained according to the high-precision map data processing method of any one of claims 1 to 5, and the full-area map data is obtained according to the high-precision map data processing method of any one of claims 6 to 11.

13. A high-precision map data processing apparatus comprising:

a first high-precision map data acquisition unit configured to acquire first high-precision map data describing lane area map information in the form of points and lines;

a curve smoothing unit configured to perform curve smoothing on line data in the first high-precision map data to obtain second high-precision map data;

and a first dimension-raising operation unit configured to perform a dimension-raising operation on the second high-precision map data to construct third high-precision map data describing the lane area map information in a planar and/or three-dimensional stereoscopic form.

14. The apparatus according to claim 13, wherein the first dimension-raising operation unit includes a first dimension-raising subunit configured to perform a dimension-raising operation on the second high-precision map data, construct third high-precision map data that describes the lane area map information in a three-dimensional stereoscopic form, the first dimension-raising subunit being further configured to:

15. The apparatus of claim 14, further comprising:

16. The apparatus according to claim 13, wherein the first ascending dimension operation unit includes a second ascending dimension operation subunit configured to perform an ascending dimension operation on the second high-precision map data, constructing third high-precision map data describing the lane area map information in a surface form, the second ascending dimension operation subunit being further configured to:

determining two adjacent and parallel target lane boundaries for the lane boundaries in the second high-precision map data;

17. The apparatus of any of claims 13-16, further comprising:

a first dimension-increasing parameter determination unit configured to determine a dimension-increasing parameter when a dimension-increasing operation is performed on the second high-precision map data using the first live-action image.

18. A high-precision map data processing apparatus comprising:

a first dimension-increasing operation unit configured to perform a dimension-increasing operation on the second high-precision map data, and construct third high-precision map data describing the lane area map information in a planar and/or three-dimensional stereoscopic form;

a first standard map data acquisition unit configured to acquire first standard map data describing other regional map information in dot and line form; wherein the accuracy of the first standard map data is lower than that of the first high-accuracy map data, and the other-area map information is map information of an area other than the lane area;

a second dimension-increasing operation unit configured to perform a dimension-increasing operation on the first standard map data to construct second standard map data describing the other area map information in a planar and/or three-dimensional stereoscopic form;

a map data fusion unit configured to fuse the second standard map data and the third high-precision map data to obtain full-area map data.

19. The apparatus of claim 18, wherein the first dimension-raising operation unit includes a first dimension-raising subunit configured to perform a dimension-raising operation on the second high-precision map data, to construct third high-precision map data describing the lane area map information in a three-dimensional stereo form, the first dimension-raising subunit being further configured to:

20. The apparatus of claim 19, further comprising:

21. The apparatus according to claim 18, wherein the first ascending dimension operation unit includes a second ascending dimension operation subunit configured to perform an ascending dimension operation on the second high-precision map data, constructing third high-precision map data describing the lane area map information in a surface form, the second ascending dimension operation subunit being further configured to:

22. The apparatus of claim 18, further comprising:

an altitude information unifying unit configured to unify altitude information of the second high-precision map data and the first standard map data at a connected position before performing a dimension-up operation on the first standard map data.

23. The method according to any one of claims 18-22, further comprising:

first and second live-action image acquiring units configured to acquire a first live-action image corresponding to the lane region and a second live-action image corresponding to the other region;

a second dimension-increasing parameter determination unit configured to determine a dimension-increasing parameter when a dimension-increasing operation is performed on the first standard map data using the second live-action image.

24. A driving navigation device, comprising:

a current position determination unit configured to determine a current position in response to receiving a driving navigation request;

a driving navigation information providing unit configured to present driving navigation information corresponding to the current position based on third high-precision map data or full-area map data; wherein the third high precision map data is obtained according to the high precision map data processing device of any one of claims 13-17, and the full area map data is obtained according to the high precision map data processing device of any one of claims 18-23.

25. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the high-precision map data processing method of any one of claims 1-5 and/or the high-precision map data processing method of any one of claims 6-11 and/or the method of driving navigation of claim 12.

26. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the high-precision map data processing method of any one of claims 1 to 5 and/or the high-precision map data processing method of any one of claims 6 to 11 and/or the driving navigation method of claim 12.

27. A computer program product comprising a computer program which, when executed by a processor, carries out the steps of the high precision map data processing method of any one of claims 1 to 5 and/or the high precision map data processing method of any one of claims 6 to 11 and/or the method of driving navigation of claim 12.