WO2024040500A1 - Coloring method and apparatus for three-dimensional road surface, and storage medium, electronic device and vehicle - Google Patents

Abstract

Disclosed in the present application are a coloring method and apparatus for a three-dimensional road surface, and a storage medium, an electronic device and a vehicle, which can solve the problem of the generation of a road edge line being time-consuming and inaccurate. The method comprises: performing a restoration operation on a three-dimensional road surface according to a preset distance, and curved-surface parameters of the three-dimensional road surface, so as to generate a first three-dimensional road surface point cloud; according to the pose of each frame of road image in the first three-dimensional road surface point cloud, determining a second three-dimensional road surface point cloud corresponding to the road image, wherein the second three-dimensional road surface point cloud comprises three-dimensional road surface points, the distances from which to the pose of the road image are less than or equal to the preset spacing, in the first three-dimensional road surface point cloud; projecting the second three-dimensional road surface point cloud to the corresponding road image, so as to obtain a projection point cloud in the road image; and coloring, by means of a target color, target three-dimensional road surface points, which correspond to target projection points, in the first three-dimensional road surface point cloud, so as to display a road edge of the three-dimensional road surface in a highlighted manner, wherein the target projection points comprise projection points, which are located in a target area, in a projection point cloud of each frame of road image.

Description

Three-dimensional road surface coloring method, device, storage medium, electronic equipment and vehicle Technical field

The present application relates to the field of automotive technology, specifically, to a three-dimensional road surface coloring method, device, storage medium, electronic equipment and vehicle.

Background technique

Electronic maps are maps that are stored and consulted digitally using computer technology. When people are walking, riding, or driving, they can get the route to their destination by consulting the electronic map, and they can also navigate in real time by turning on the intelligent navigation function. In order to improve user experience and improve the accuracy of electronic map query, it has gradually developed from two-dimensional electronic maps to three-dimensional electronic maps. One of the most critical aspects of generating a three-dimensional electronic map is generating a three-dimensional road surface. In related technologies, lidar is mainly relied on to collect radar point clouds to generate three-dimensional road surfaces. In order to improve accuracy and efficiency when performing quality inspections and corrections on pavement elements such as stop lines, sidewalks, and diversion strips based on this three-dimensional road surface, road edge lines can be generated in the three-dimensional road surface as reference lines.

Methods for generating road edge lines in related technologies mainly include: obtaining each frame of road image collected by the camera of the collection vehicle when collecting radar point clouds based on the lidar of the collection vehicle; perceiving the road edge line in each frame of road image; based on each frame The ground parameter of a pixel on the road edge line in the road image is projected onto the three-dimensional road surface to obtain a projection point, and with the projection point as the center and the ground parameter of the road image as the normal vector, a plane containing the projection point is fitted. ; Project the pixel point onto the corresponding plane, and the intersection point with the plane is the point of the road edge line in the three-dimensional road surface. However, when part of the curved surface of the three-dimensional road surface has a slope, but the fitted plane does not have a slope, directly using the intersection point as the point of the road edge line will lead to inaccuracy. In order to improve the accuracy, you can find nearby surfaces based on the intersection point and gradually iterate to the correct position. However, this blind iteration method is not only time-consuming, but also may not find the correct surface.

Contents of the invention

This application provides a three-dimensional road surface coloring method, device, storage medium, electronic equipment and vehicle, which can solve the problem of time-consuming and inaccurate generation of road edge lines.

The specific technical solutions are as follows:

In a first aspect, embodiments of the present application provide a three-dimensional road surface coloring method, which method includes:

According to the preset spacing and the surface parameters of the three-dimensional road surface, a restoration operation is performed on the three-dimensional road surface to generate a first three-dimensional road point cloud, wherein the three-dimensional road surface is an uncolored three-dimensional road surface fitted based on the original radar point cloud. ;

According to the position and orientation of each frame of road image in the first three-dimensional road point cloud, the second three-dimensional road point cloud corresponding to the road image is determined, wherein the road image is the original radar collected by the laser radar of the collection vehicle. When the point cloud is generated, in the road image collected by the camera of the collecting vehicle, the second three-dimensional road point cloud is included in the first three-dimensional road point cloud, and the distance from the pose of the road image is less than or equal to a predetermined distance. Set the distance between the three-dimensional road points;

Project the second three-dimensional road point cloud to the corresponding road image to obtain the projected point cloud in the road image;

Coloring the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the road edge of the three-dimensional road surface, wherein the target projection point includes the road in each frame Projection points located within a target area in the projection point cloud of the image, the target area including pixels having the same abscissa as the static road edge line perceived in the road image and a difference in ordinates within a preset difference range In the constituted area, the target three-dimensional road point includes a three-dimensional road point that has a direct mapping relationship with the target projection point, or the elevation of the three-dimensional road point that has a direct mapping relationship with the target projection point is preset. 3D pavement points obtained after height.

It can be seen from the above solution that after restoring the uncolored three-dimensional road surface to the first three-dimensional road point cloud, the embodiment of the present application can project the second three-dimensional road point cloud near the road image into the road image to obtain the projection point cloud, and Directly color the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point located in the target area in the projection point cloud into the target color, wherein the target area includes a static road edge line that is transverse to the perceived static road edge in the road image. An area composed of pixels with the same coordinates and a difference in ordinates within a preset difference range. The target 3D road points include 3D road points that have a direct mapping relationship with the target projection point or are obtained by raising the elevation of these 3D road points. 3D waypoint. It can be seen from this that in the embodiment of the present application, the second three-dimensional road point cloud in the three-dimensional road surface is directly projected onto the two-dimensional road image, and the road edge line perceived in the road image and its nearby projection points and the three-dimensional road point points are used. The mapping relationship directly determines the three-dimensional road points of the road edge line and colors them. Therefore, the embodiment of the present application does not need to construct a plane, and does not involve the problem of inconsistency between the plane and the three-dimensional road slope. Therefore, there is no need to iteratively search for nearby curved surfaces, and thus both Improving the generation efficiency of road edge lines can also improve the accuracy.

In a first possible implementation of the first aspect, before projecting the second three-dimensional road point cloud to the corresponding road image and obtaining the projected point cloud in the road image, the method Also includes:

Convert the second three-dimensional road point cloud from the station center coordinate system to the camera coordinate system;

Filter invalid three-dimensional road points in the second three-dimensional road point cloud under the camera coordinate system, wherein the invalid three-dimensional road points include three-dimensional road points with elevations outside the target elevation range, and forward coordinates less than or equal to 0. 3D pavement points;

Projecting the second three-dimensional road point cloud to the corresponding road image and obtaining the projected point cloud in the road image includes:

Project the filtered second three-dimensional road point cloud in the camera coordinate system to the corresponding road image to obtain the projected point cloud in the road image.

It can be seen from the above solution that the embodiment of the present application can remove the road sections above and below the bridge or layered above and below the bridge by filtering out the three-dimensional road points whose elevation is outside the target elevation range, thereby making the obtained projection point cloud more accurate. By filtering out the previous Three-dimensional road points with coordinates less than or equal to 0 can be filtered out three-dimensional road points located outside the camera's shooting field of view, thereby reducing the amount of data converted from the camera coordinate system to the image coordinate system and improving the efficiency of road edge generation.

In a second possible implementation manner of the first aspect, the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point is colored into a target color to highlight the three-dimensional road surface. Before the road edge, the method also includes:

Filter invalid projection points in the projection point cloud, where the invalid projection points include projection points located outside the image coordinate system, projection points located below the hood line of the collection vehicle, and projection points located on the static road edge line Projection points above and above the dynamic road edge lines.

It can be seen from the above solution that the embodiment of the present application can improve the accuracy of the projected point cloud by filtering out projection points outside the drivable area (that is, invalid projection points), thereby not only improving the accuracy of generating road edges, but also improving the subsequent Accuracy in generating colored pavement or semantically segmented pavement.

In a third possible implementation manner of the first aspect, coloring the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into a target color includes:

Determine three-dimensional road points in the first three-dimensional road point cloud that meet preset conditions as the target three-dimensional road points, and color the target three-dimensional road points into the target color;

Wherein, the preset conditions include any one of the following:

Three-dimensional road points in the first three-dimensional road point cloud that have a direct mapping relationship with the target projection point;

The three-dimensional road point obtained after raising the elevation of the three-dimensional road point with a direct mapping relationship by the preset height;

The three-dimensional road points with a direct mapping relationship are filtered based on the drivable area point cloud. The drivable area point cloud includes the filtered projection point cloud, which is located by the vehicle cover. Lines, three-dimensional road points in the first three-dimensional road point cloud corresponding to projection points in the area enclosed by the static road edge line and the dynamic road edge line;

After filtering the three-dimensional road points with a direct mapping relationship based on the drivable area point cloud, the remaining three-dimensional road points are obtained by raising the elevation of the preset height.

It can be seen from the above solution that by raising the elevation in the embodiment of the present application, the drawn road edge can avoid blocking the original road landmarks, and the three-dimensional road points in the road can be filtered out through the drivable area point cloud, thereby improving the accuracy and accuracy of the road edge. Display of results.

In a fourth possible implementation manner of the first aspect, after filtering invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, the method further includes:

According to the target distance of each three-dimensional road point to be processed in the filtered second three-dimensional road point cloud in the camera coordinate system, the weight value corresponding to the three-dimensional road point to be processed is calculated, where the target The distance is the target distance between the transverse coordinate and the forward coordinate of the three-dimensional road point to be processed, and the target distance has a negative correlation with the weight value;

After filtering invalid projection points in the projection point cloud, the method further includes:

In the case where there is only one valid projection point corresponding to one three-dimensional road point in the first three-dimensional road point cloud, the three-dimensional road point in the first three-dimensional road point cloud corresponding to the valid projection point is colored into the above-mentioned The color value of a valid projection point, wherein the valid projection point is a projection point included in the filtered projection point cloud;

When there are multiple valid projection points corresponding to the same three-dimensional road point in the first three-dimensional road point cloud, perform a weighted calculation on the color values and the weight values of the multiple valid projection points, and The three-dimensional road points corresponding to the plurality of valid projection points are colored into weighted color values, wherein each of the plurality of valid projection points is located in a different road image.

It can be seen from the above solution that the embodiment of the present application can realize the coloring of the three-dimensional road surface by coloring the three-dimensional road points in the first three-dimensional road point cloud corresponding to the effective projection point. For example, when the road image is a color image, it can be obtained Colored pavement, when the road image is a semantic segmentation image, the semantic segmentation of the pavement can be obtained. And when coloring the three-dimensional road surface, weighted calculations can also be performed based on the weight value determined by the distance information, thereby improving the accuracy of the three-dimensional road surface coloring.

In a second aspect, embodiments of the present application provide a three-dimensional road surface coloring device. The device includes:

A restoration unit, configured to restore the three-dimensional road surface according to the preset spacing and the surface parameters of the three-dimensional road surface, and generate a first three-dimensional road surface point cloud, wherein the three-dimensional road surface is fitted based on the original radar point cloud. Uncolored three-dimensional pavement;

Determining unit, configured to determine the second three-dimensional road point cloud corresponding to the road image according to the position and orientation of each frame of the road image in the first three-dimensional road point cloud, wherein the road image is the lidar of the collection vehicle When collecting the original radar point cloud, the road image collected by the camera of the collecting vehicle, the second three-dimensional road point cloud is included in the first three-dimensional road point cloud, and the pose of the road image Three-dimensional road points whose distance is less than or equal to the preset distance;

A projection unit configured to project the second three-dimensional road point cloud to the corresponding road image to obtain the projected point cloud in the road image;

A coloring unit configured to color the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the road edge of the three-dimensional road surface, wherein the target projection point includes Projection points located within a target area in the projection point cloud of the road image in each frame. The target area includes the same abscissa as the static road edge line perceived in the road image and the difference between the ordinates is within a preset difference. The area composed of pixel points within the range, the target three-dimensional road point includes a three-dimensional road point that has a direct mapping relationship with the target projection point, or the three-dimensional road point that will have a direct mapping relationship with the target projection point. The three-dimensional road points obtained by raising the elevation to a preset height.

In a first possible implementation manner of the second aspect, the device further includes:

A coordinate system conversion unit configured to project the second three-dimensional road point cloud to the corresponding road image and obtain the projected point cloud in the road image, converting the second three-dimensional road point cloud from Convert the station center coordinate system to the camera coordinate system;

The first filtering unit is used to filter invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, where the invalid three-dimensional road points include three-dimensional road points with elevations outside the target elevation range, previous Three-dimensional road points with coordinates less than or equal to 0;

The projection unit is configured to project the filtered second three-dimensional road point cloud in the camera coordinate system to the corresponding road image to obtain the projected point cloud in the road image.

In a second possible implementation manner of the second aspect, the device further includes:

A second filtering unit configured to filter all target three-dimensional road points in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the road edge of the three-dimensional road surface. Invalid projection points in the projection point cloud, wherein the invalid projection points include projection points located outside the image coordinate system, projection points located below the hood line of the collection vehicle, and projection points located above the static road edge line Projection points and projection points above dynamic road edge lines.

In a third possible implementation manner of the second aspect, the coloring unit is configured to determine a three-dimensional road point in the first three-dimensional road point cloud that satisfies a preset condition as the target three-dimensional road point, and The target three-dimensional road surface points are colored into the target color;

Wherein, the preset conditions include any one of the following:

Three-dimensional road points in the first three-dimensional road point cloud that have a direct mapping relationship with the target projection point;

The three-dimensional road point obtained after raising the elevation of the three-dimensional road point with a direct mapping relationship by the preset height;

The three-dimensional road points with a direct mapping relationship are filtered based on the drivable area point cloud. The drivable area point cloud includes the filtered projection point cloud, which is located by the vehicle cover. Lines, three-dimensional road points in the first three-dimensional road point cloud corresponding to projection points in the area enclosed by the static road edge line and the dynamic road edge line;

After filtering the three-dimensional road points with a direct mapping relationship based on the drivable area point cloud, the remaining three-dimensional road points are obtained by raising the elevation of the preset height.

In a fourth possible implementation manner of the second aspect, the device further includes:

A computing unit configured to, after filtering the invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, calculate the filtered second three-dimensional road point cloud in the camera coordinate system. The target distance of each three-dimensional road point to be processed is calculated, and the weight value corresponding to the three-dimensional road point to be processed is calculated, where the target distance is between the lateral coordinate and the forward coordinate of the three-dimensional road point to be processed. The target distance has a negative correlation with the weight value;

The coloring unit is also configured to, after filtering the invalid projection points in the projection point cloud, when there is only one valid projection point corresponding to a three-dimensional road point in the first three-dimensional road point cloud, The three-dimensional road points in the first three-dimensional road point cloud corresponding to the effective projection points are colored into the color values of the effective projection points, wherein the effective projection points are included in the filtered projection point cloud. Projection points; when there are multiple valid projection points corresponding to the same three-dimensional road point in the first three-dimensional road point cloud, weight the color values and the weight values of the multiple valid projection points. Calculate and color the three-dimensional road points corresponding to the plurality of valid projection points into weighted color values, wherein each of the plurality of valid projection points is located in a different road image.

The three-dimensional road surface coloring device provided by the embodiment of the present application, after restoring the uncolored three-dimensional road surface to the first three-dimensional road surface point cloud, can project the second three-dimensional road surface point cloud near the road image into the road image to obtain projection points. cloud, and directly color the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point located in the target area into the target color, where the target area includes the static road perceived in the road image The area composed of pixels with the same abscissa coordinate of the edge line and the difference between the ordinates within the preset difference range. The target 3D pavement points include 3D pavement points that have a direct mapping relationship with the target projection point or the elevation of these 3D pavement points is adjusted. 3D waypoints obtained after high. It can be seen from this that in the embodiment of the present application, the second three-dimensional road point cloud in the three-dimensional road surface is directly projected onto the two-dimensional road image, and the road edge line perceived in the road image and its nearby projection points and the three-dimensional road point points are used. The mapping relationship directly determines the three-dimensional road points of the road edge line and colors them. Therefore, the embodiment of the present application does not need to construct a plane, and does not involve the problem of inconsistency between the plane and the three-dimensional road slope. Therefore, there is no need to iteratively search for nearby curved surfaces, and thus both Improving the generation efficiency of road edge lines can also improve the accuracy.

In a third aspect, embodiments of the present application provide a storage medium on which a computer program is stored. When the program is executed by a processor, the method described in any possible implementation of the first aspect is implemented.

In a fourth aspect, embodiments of the present application provide an electronic device. The electronic device includes:

one or more processors;

a storage device for storing one or more programs,

When one or more programs are executed by one or more processors, the electronic device implements the method described in any possible implementation manner of the first aspect.

In a fifth aspect, embodiments of the present application provide a vehicle, which includes the device as described in any possible implementation of the second aspect, or the electronic device as described in the fourth aspect.

Description of drawings

In order to more clearly explain the embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without exerting creative efforts.

Figure 1 is a schematic flow chart of a three-dimensional road surface coloring method provided by an embodiment of the present application;

Figure 2 is a schematic diagram of the coordinate system provided by the embodiment of the present application;

Figure 3 is an example diagram of an invalid projection point and a valid projection point provided by an embodiment of the present application;

Figure 4 is a block diagram of a three-dimensional road surface coloring device provided by an embodiment of the present application;

Figure 5 is a schematic structural diagram of a vehicle provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

It should be noted that, as long as there is no conflict, the embodiments and features in the embodiments of this application can be combined with each other. The terms "including" and "having" and any variations thereof in the embodiments and drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes Other steps or units inherent to such processes, methods, products or devices.

Figure 1 is a schematic flow chart of a three-dimensional road surface coloring method. This method can be applied to electronic equipment or computer equipment, and specifically can be applied to vehicles or servers. The method can include the following steps:

S110: According to the preset spacing and the surface parameters of the three-dimensional road surface, perform a restoration operation on the three-dimensional road surface to generate a first three-dimensional road point cloud.

Among them, the three-dimensional road surface is an uncolored three-dimensional road surface fitted based on the original radar point cloud. The embodiments of this application do not limit the method of generating a three-dimensional road surface based on the original radar point cloud. For example, you can first filter out the radar point cloud about the road surface from the original radar point cloud, and then perform horizontal plane direction fitting on the filtered radar point cloud. , and finally perform vertical fitting to generate a three-dimensional road surface as a three-dimensional road surface.

The distance between adjacent three-dimensional road points in the first three-dimensional road point cloud is a preset distance. The preset distance can be the same as the distance of the original radar point cloud, or it can be different, for example, it can be 0.5m. Both the three-dimensional road surface and the first three-dimensional road surface point cloud can be in the station center coordinate system (east-north-celestial coordinate system ENU), or they can be converted from the world coordinate system to the station center coordinate system.

S120: Determine the second three-dimensional road point cloud corresponding to the road image based on the position and orientation of each frame of road image in the first three-dimensional road point cloud.

Among them, the road image is the road image collected by the camera of the collection vehicle when the lidar of the collection vehicle collects the original radar point cloud. Road images can be collected through multiple trips by a collection vehicle and/or thinned out, and a reasonable amount of data can be retained. The embodiment of this application does not limit the installation angle and installation position of the camera on the collection vehicle. The second three-dimensional road point cloud includes three-dimensional road points in the first three-dimensional road point cloud that are less than or equal to a preset distance from the pose of the road image. Pose includes position and posture. The preset distance can be determined based on the final generated road edge accuracy. For example, when the preset distance is 25m, the second three-dimensional road point cloud corresponding to the road image can be the second three-dimensional road point cloud within the circular area defined with the center point of the road image as the center and 25m as the radius. .

It should be added that in order to improve the efficiency of road edge generation, embodiments of the present application can also first divide the first three-dimensional road point cloud into multiple area blocks, and then perform the step of "according to each frame of road image on the multiple area blocks in parallel". The pose in the area block is used to determine the second three-dimensional road point cloud corresponding to the road image," and subsequent steps. Among them, the blocking principle can be: traverse the first three-dimensional road point cloud, when the number of traversed point clouds reaches the upper limit, stop traversing, and determine the traversed point clouds to be the same area block, and then continue to traverse the untraversed point clouds. The first three-dimensional road point cloud is traversed using this method until all three-dimensional road points in the first three-dimensional road point cloud are traversed.

S130: Project the second three-dimensional road point cloud to the corresponding road image to obtain the projected point cloud in the road image.

This step can first convert the second three-dimensional road point cloud from the station center coordinate system to the camera coordinate system, and then convert it from the camera coordinate system to the image coordinate system, thereby realizing the projection of the second three-dimensional road point cloud to the road image and obtaining the road image. Projection point cloud in .

S140: Color the target three-dimensional road surface point in the first three-dimensional road surface point cloud corresponding to the target projection point into the target color to highlight the road edge of the three-dimensional road surface.

Among them, the target projection points include projection points located in the target area in the projection point cloud of each frame of the road image. The target area includes the same abscissa as the static road edge line perceived in the road image and the difference in the ordinate is within the preset difference range. The area composed of pixels. Static road edge lines include road fences and other fixed dividing lines used to distinguish roads from non-roads, while dynamic road edge lines are the rear edges of vehicles in front of the collection vehicle, so there may or may not be dynamic road edge lines. The preset difference range can be determined based on the final generated road edge accuracy, for example, it can be 5 pixels. The target color includes colors other than the color of the road surface, especially colors that are significantly different from the color of the road surface, for example, it can be red, green, etc. The method for perceiving static road edge lines and dynamic road edge lines mentioned in the following embodiments may be: labeling at least one of these three types of lines on a large number of historical road images in advance, and then using the history data containing the labeling information. The road image is used for model training to obtain a target detection model, and finally the target detection model is used to detect lines in the road image to be sensed. Among them, the target detection model can be a CNN (Convolutional Neural Network, convolutional neural network) model.

The target three-dimensional road surface points include three-dimensional road surface points that have a direct mapping relationship with the target projection point, or three-dimensional road surface points that are obtained after raising the elevation of the three-dimensional road surface point that has a direct mapping relationship with the target projection point by a preset height. The three-dimensional road surface point that has a direct mapping relationship with the target projection point means that the target projection point and the three-dimensional road surface point are the same point in different coordinate systems. The preset height can be determined based on the final generated road edge accuracy.

Specifically, the three-dimensional road points in the first three-dimensional road point cloud that meet the preset conditions can be determined as the target three-dimensional road points, and the target three-dimensional road points can be colored into the target color;

Among them, the preset conditions include any of the following:

Three-dimensional road points in the first three-dimensional road point cloud that have a direct mapping relationship with the target projection point;

The three-dimensional pavement point obtained after raising the elevation of the three-dimensional pavement point with a direct mapping relationship by a preset height;

The three-dimensional road points with direct mapping relationships are filtered based on the drivable area point cloud. The drivable area point cloud includes the filtered projection point cloud, which is located between the collected vehicle cover line and the static road edge line. Three-dimensional road points in the first three-dimensional road point cloud corresponding to projection points in the area enclosed by the dynamic road edge lines;

After filtering the three-dimensional road points with direct mapping relationships based on the drivable area point cloud, the three-dimensional road points obtained by raising the elevation of the remaining three-dimensional road points by a preset height.

In the embodiment of this application, raising the elevation can prevent the drawn road edge from blocking the original road landmarks. The three-dimensional road points in the road can be filtered out through the drivable area point cloud, thereby improving the accuracy and display effect of the road edge.

In addition, the embodiment of the present application can also uniformly color the three-dimensional road points corresponding to the drivable area point cloud into a certain color (different from the target color) to generate a drivable area road surface in the three-dimensional road surface, so that it can be realized based on the drivable area. Pavement can correct the three-dimensional map generated by other methods and other functions.

The three-dimensional road surface coloring method provided by the embodiment of the present application, after restoring the uncolored three-dimensional road surface to the first three-dimensional road surface point cloud, can project the second three-dimensional road surface point cloud near the road image into the road image to obtain projection points. cloud, and directly color the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point located in the target area into the target color, where the target area includes the static road perceived in the road image The area composed of pixels with the same abscissa coordinate of the edge line and the difference between the ordinates within the preset difference range. The target 3D pavement points include 3D pavement points that have a direct mapping relationship with the target projection point or the elevation of these 3D pavement points is adjusted. 3D waypoints obtained after high. It can be seen from this that in the embodiment of the present application, the second three-dimensional road point cloud in the three-dimensional road surface is directly projected onto the two-dimensional road image, and the road edge line perceived in the road image and its nearby projection points and the three-dimensional road point points are used. The mapping relationship directly determines the three-dimensional road points of the road edge line and colors them. Therefore, the embodiment of the present application does not need to construct a plane, and does not involve the problem of inconsistency between the plane and the three-dimensional road slope. Therefore, there is no need to iteratively search for nearby curved surfaces, and thus both Improving the generation efficiency of road edge lines can also improve the accuracy.

In one implementation, in order to increase the accuracy of the projected point cloud and improve the efficiency of road edge generation, the embodiment of the present application projects the second three-dimensional road point cloud to the corresponding road image to obtain the projected point cloud in the road image. , you can first convert the second 3D road point cloud from the station center coordinate system to the camera coordinate system, then filter the invalid 3D road points in the second 3D road point cloud in the camera coordinate system, and finally filter the filtered 3D road points in the camera coordinate system. The second three-dimensional road surface point cloud is projected to the corresponding road image to obtain the projected point cloud in the road image.

Among them, invalid three-dimensional road points include three-dimensional road points whose elevation is outside the target elevation range and three-dimensional road points whose forward coordinates are less than or equal to 0. The target elevation range can be [0,3m].

As shown in Figure 2, the x-axis, y-axis and z-axis constitute the camera coordinate system with the camera optical center as the origin. The z-axis is the forward coordinate axis, the y-axis is the coordinate axis used to represent elevation, and the x-axis is horizontal. Axis. The u-axis (horizontal axis) and v-axis (vertical axis) constitute the image coordinate system, and the z-axis passes through the center of the image coordinate system.

The three-dimensional road surface coloring method provided by the embodiment of the present application can remove the road sections above and below the bridge or layered above and below the bridge by filtering out the three-dimensional road points whose elevation is outside the target elevation range, thereby making the obtained projected point cloud more accurate. Filtering out three-dimensional road points with forward coordinates less than or equal to 0 can filter out three-dimensional road points located outside the camera's shooting field of view, thereby reducing the amount of data converted from the camera coordinate system to the image coordinate system and improving the efficiency of road edge generation.

In one implementation, in order to improve the accuracy of generating road edges, embodiments of the present application may color the target three-dimensional road points in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the three-dimensional Before the road edge of the road surface, invalid projection points in the projection point cloud are filtered. Invalid projection points include projection points located outside the image coordinate system, projection points located below the cover line of the collection vehicle, and projection points located above the static road edge line. Projection points and projection points above dynamic road edge lines. As shown in Figure 3, the shaded part is the valid projection point area, and the area formed by the valid projection points inside this area can be called the drivable area, and the non-shaded part is the invalid projection point area. Valid projection points are projection points other than invalid projection points in the projection point cloud.

It should be added that filtering invalid projection points in the projection point cloud can not only improve the accuracy of generating road edges, but also improve the accuracy of subsequent generation of colored pavement or semantic segmentation of pavement.

In one implementation, after filtering the invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, the embodiment of the present application can also filter each of the second three-dimensional road point cloud in the camera coordinate system. The target distance of the three-dimensional road point to be processed is calculated, and the weight value corresponding to the three-dimensional road point to be processed is calculated. The target distance is the target distance between the transverse coordinate and the forward coordinate of the three-dimensional road point to be processed. The target distance and the weight are There is a negative correlation between the values; after filtering the invalid projection points in the projection point cloud, when there is only one valid projection point corresponding to a three-dimensional road point in the first three-dimensional road point cloud, the first three-dimensional road point corresponding to the valid projection point will be The three-dimensional pavement points in the pavement point cloud are colored into the color values of the effective projection points, where the effective projection points are the projection points included in the filtered projection point cloud; when there are multiple valid projection points corresponding to the first three-dimensional road point cloud In the case of the same three-dimensional road point, weighted calculations are performed on the color values and weight values of multiple valid projection points, and the three-dimensional road points corresponding to the multiple valid projection points are colored into weighted color values, where multiple Each of the valid projection points is located in a different road image.

When the road image used in the embodiment of the present application is an original color road image collected by a camera, the three-dimensional road surface generated after coloring in the embodiment of the present application is a colored road surface; when the road image used in the embodiment of the present application is an original color road image When the image is a semantically segmented image, the three-dimensional road surface generated after coloring in this embodiment of the present application is a semantically segmented road surface. Colored pavement is a pavement that has the same color as the road surface in the real world; semantic segmentation pavement is a three-dimensional pavement that semantically separates the landmark part and non-landmark part of the road. Pavement landmarks refer to the use of lines, arrows, text, etc. on the road surface to convey guidance to traffic participants. Signs showing restrictions, warnings and other traffic information.

In addition, the embodiment of the present application can also uniformly color the uncolored three-dimensional road points in the three-dimensional road surface into a certain color (such as gray) to highlight the color of the road surface.

The three-dimensional road surface coloring method provided by the embodiment of the present application can realize the coloring of the three-dimensional road surface by coloring the three-dimensional road surface points in the first three-dimensional road surface point cloud corresponding to the effective projection point. For example, when the road image is a color image , the colored road surface can be obtained, and when the road image is a semantic segmentation image, the semantic segmentation road surface can be obtained. And when coloring the three-dimensional road surface, weighted calculations can also be performed based on the weight value determined by the distance information, thereby improving the accuracy of the three-dimensional road surface coloring.

Corresponding to the above method embodiment, another embodiment of the present application provides a three-dimensional road surface coloring device. As shown in Figure 4, the device includes:

The restoration unit 21 is used to restore the three-dimensional road surface according to the preset spacing and the surface parameters of the three-dimensional road surface, and generate a first three-dimensional road surface point cloud, where the three-dimensional road surface is an uncolored image fitted based on the original radar point cloud. three-dimensional road surface;

The determination unit 22 is used to determine the second three-dimensional road point cloud corresponding to the road image according to the position and orientation of each frame of the road image in the first three-dimensional road point cloud, where the road image is the original radar point cloud collected by the lidar of the collection vehicle. When collecting the road image collected by the camera of the vehicle, the second three-dimensional road point cloud includes three-dimensional road points in the first three-dimensional road point cloud that are less than or equal to the preset distance from the position of the road image;

The projection unit 23 is used to project the second three-dimensional road point cloud to the corresponding road image to obtain the projected point cloud in the road image;

The coloring unit 24 is used to color the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the road edge of the three-dimensional road surface, wherein the target projection point includes each frame of the road image. The projection point in the projection point cloud is located in the target area. The target area includes the area composed of pixels with the same abscissa as the static road edge line perceived in the road image and the difference between the ordinates is within the preset difference range. The target three-dimensional road surface The points include three-dimensional pavement points that have a direct mapping relationship with the target projection point, or three-dimensional pavement points that are obtained by raising the elevation of the three-dimensional pavement point that has a direct mapping relationship with the target projection point by a preset height.

In a possible implementation, the device further includes:

A coordinate system conversion unit, used to convert the second three-dimensional road point cloud from the station center coordinate system to the camera coordinate system before projecting the second three-dimensional road point cloud to the corresponding road image and obtaining the projected point cloud in the road image;

The first filtering unit is used to filter invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, where the invalid three-dimensional road points include three-dimensional road points whose elevation is outside the target elevation range and whose forward coordinate is less than or equal to 0. three-dimensional road points;

The projection unit 23 is used to project the filtered second three-dimensional road point cloud in the camera coordinate system to the corresponding road image to obtain the projected point cloud in the road image.

In a possible implementation, the device further includes:

The second filtering unit is used to filter invalid projections in the projection point cloud before coloring the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into the target color to highlight the road edge of the three-dimensional road surface. Points, where invalid projection points include projection points located outside the image coordinate system, projection points located below the hood line of the collection vehicle, projection points located above the static road edge line, and projection points located above the dynamic road edge line.

In a possible implementation, the coloring unit 24 is used to determine the three-dimensional road points that meet the preset conditions in the first three-dimensional road point cloud as the target three-dimensional road points, and color the target three-dimensional road points into the target color;

Among them, the preset conditions include any of the following:

Three-dimensional road points in the first three-dimensional road point cloud that have a direct mapping relationship with the target projection point;

The three-dimensional pavement point obtained after raising the elevation of the three-dimensional pavement point with a direct mapping relationship by a preset height;

The three-dimensional road points with direct mapping relationships are filtered based on the drivable area point cloud. The drivable area point cloud includes the filtered projection point cloud, which is located between the collected vehicle cover line and the static road edge line. Three-dimensional road points in the first three-dimensional road point cloud corresponding to projection points in the area enclosed by the dynamic road edge lines;

After filtering the three-dimensional road points with direct mapping relationships based on the drivable area point cloud, the three-dimensional road points obtained by raising the elevation of the remaining three-dimensional road points by a preset height.

In a possible implementation, the device further includes:

A computing unit configured to, after filtering invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, target each to-be-processed three-dimensional road point in the filtered second three-dimensional road point cloud in the camera coordinate system. Distance, calculate the weight value corresponding to the three-dimensional road point to be processed, where the target distance is the target distance between the lateral coordinates and the forward coordinate of the three-dimensional road point to be processed, and the target distance has a negative correlation with the weight value;

The coloring unit 24 is also used to, after filtering the invalid projection points in the projection point cloud, when there is only one valid projection point corresponding to one three-dimensional road point in the first three-dimensional road point cloud, convert the valid projection point corresponding to the first The three-dimensional road points in the three-dimensional road point cloud are colored into the color values of the effective projection points, where the effective projection points are the projection points included in the filtered projection point cloud; when there are multiple effective projection points corresponding to the first three-dimensional road point cloud In the case of the same three-dimensional road point in , perform weighted calculations on the color values and weight values of multiple valid projection points, and color the three-dimensional road points corresponding to the multiple valid projection points into weighted color values, where Each of the valid projection points is located in a different road image.

The three-dimensional road surface coloring device provided by the embodiment of the present application, after restoring the uncolored three-dimensional road surface to the first three-dimensional road surface point cloud, can project the second three-dimensional road surface point cloud near the road image into the road image to obtain projection points. cloud, and directly color the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point located in the target area into the target color, where the target area includes the static road perceived in the road image The area composed of pixels with the same abscissa coordinate of the edge line and the difference between the ordinates within the preset difference range. The target 3D pavement points include 3D pavement points that have a direct mapping relationship with the target projection point or the elevation of these 3D pavement points is adjusted. 3D waypoints obtained after high. It can be seen from this that in the embodiment of the present application, the second three-dimensional road point cloud in the three-dimensional road surface is directly projected onto the two-dimensional road image, and the road edge line perceived in the road image and its nearby projection points and the three-dimensional road point points are used. The mapping relationship directly determines the three-dimensional road points of the road edge line and colors them. Therefore, the embodiment of the present application does not need to construct a plane, and does not involve the problem of inconsistency between the plane and the three-dimensional road slope. Therefore, there is no need to iteratively search for nearby curved surfaces, and thus both Improving the generation efficiency of road edge lines can also improve the accuracy.

Based on the above method embodiments, another embodiment of the present application provides a storage medium on which executable instructions are stored. When executed by a processor, the instructions cause the processor to implement the method described in any of the above embodiments.

Based on the above method embodiment, another embodiment of the present application provides an electronic device or computer device, including:

one or more processors;

a storage device for storing one or more programs,

Wherein, when the one or more programs are executed by the one or more processors, the electronic device or computer device is caused to implement the method described in any of the above embodiments.

Based on the above method embodiments, another embodiment of the present application provides a vehicle, which includes the device as described in any of the above embodiments, or includes the electronic device as described above.

As shown in Figure 5, the vehicle includes a CPU (Central Processing Unit, central processing unit) 31, a GPS (Global Positioning System, global positioning system) positioning device 32, a T-Box (Telematics Box, a remote information processor) 33, a V2X ( Vehicle-to-Everything (Internet of Vehicles) module 34, lidar 35 and camera 36. Among them, the GPS positioning device 32 is used to obtain the current geographical location of the vehicle; the T-Box 33 can be used as a gateway to communicate with the server; the CPU 31 can execute the three-dimensional road surface coloring method mentioned in the above embodiment; the laser radar 35 is used to collect the information in front of the vehicle. Radar point cloud; camera 36 is used to collect images of the road in front of the vehicle.

The above device embodiments correspond to the method embodiments and have the same technical effects as the method embodiments. For detailed description, please refer to the method embodiments. The device embodiment is obtained based on the method embodiment. For specific description, please refer to the method embodiment section and will not be described again here. Those of ordinary skill in the art can understand that the accompanying drawing is only a schematic diagram of an embodiment, and the modules or processes in the accompanying drawing are not necessarily necessary for implementing the present application.

Those of ordinary skill in the art can understand that the modules in the device in the embodiment may be distributed in the device in the embodiment according to the description of the embodiment, or may be correspondingly changed and located in one or more devices different from this embodiment. The modules of the above embodiments can be combined into one module, or further divided into multiple sub-modules.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent substitutions are made to some of the technical features; however, these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions in the embodiments of the present application.

Claims (13)

1. A three-dimensional road surface coloring method, characterized in that the method includes:

   According to the preset spacing and the surface parameters of the three-dimensional road surface, a restoration operation is performed on the three-dimensional road surface to generate a first three-dimensional road point cloud, wherein the three-dimensional road surface is an uncolored three-dimensional road surface fitted based on the original radar point cloud. ;

   According to the position and orientation of each frame of road image in the first three-dimensional road point cloud, the second three-dimensional road point cloud corresponding to the road image is determined, wherein the road image is the original radar collected by the laser radar of the collection vehicle. When the point cloud is generated, in the road image collected by the camera of the collecting vehicle, the second three-dimensional road point cloud is included in the first three-dimensional road point cloud, and the distance from the pose of the road image is less than or equal to a predetermined distance. Set the distance between the three-dimensional road points;

   Project the second three-dimensional road point cloud to the corresponding road image to obtain the projected point cloud in the road image;

   Coloring the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the road edge of the three-dimensional road surface, wherein the target projection point includes the road in each frame Projection points located within a target area in the projection point cloud of the image, the target area including pixels having the same abscissa as the static road edge line perceived in the road image and a difference in ordinates within a preset difference range In the constituted area, the target three-dimensional road point includes a three-dimensional road point that has a direct mapping relationship with the target projection point, or the elevation of the three-dimensional road point that has a direct mapping relationship with the target projection point is preset. 3D pavement points obtained after height.
2. The method according to claim 1, characterized in that, before projecting the second three-dimensional road point cloud to the corresponding road image and obtaining the projected point cloud in the road image, the method further include:

   Convert the second three-dimensional road point cloud from the station center coordinate system to the camera coordinate system;

   Filter invalid three-dimensional road points in the second three-dimensional road point cloud under the camera coordinate system, wherein the invalid three-dimensional road points include three-dimensional road points with elevations outside the target elevation range, and forward coordinates less than or equal to 0. 3D pavement points;

   Projecting the second three-dimensional road point cloud to the corresponding road image and obtaining the projected point cloud in the road image includes:

   Project the filtered second three-dimensional road point cloud in the camera coordinate system to the corresponding road image to obtain the projected point cloud in the road image.
3. The method of claim 2, wherein the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point is colored into a target color to highlight the three-dimensional road surface. Before road edge, the method also includes:

   Filter invalid projection points in the projection point cloud, where the invalid projection points include projection points located outside the image coordinate system, projection points located below the hood line of the collection vehicle, and projection points located on the static road edge line Projection points above and above the dynamic road edge lines.
4. The method of claim 3, wherein coloring the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into a target color includes:

   Determine three-dimensional road points in the first three-dimensional road point cloud that meet preset conditions as the target three-dimensional road points, and color the target three-dimensional road points into the target color;

   Wherein, the preset conditions include any one of the following:

   Three-dimensional road points in the first three-dimensional road point cloud that have a direct mapping relationship with the target projection point;

   The three-dimensional road point obtained after raising the elevation of the three-dimensional road point with a direct mapping relationship by the preset height;

   The three-dimensional road points with a direct mapping relationship are filtered based on the drivable area point cloud. The drivable area point cloud includes the filtered projection point cloud, which is located by the vehicle cover. Lines, three-dimensional road points in the first three-dimensional road point cloud corresponding to projection points in the area enclosed by the static road edge line and the dynamic road edge line;

   After filtering the three-dimensional road points with a direct mapping relationship based on the drivable area point cloud, the remaining three-dimensional road points are obtained by raising the elevation of the preset height.
5. The method according to claim 3 or 4, characterized in that, after filtering the invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, the method further includes:

   According to the target distance of each three-dimensional road point to be processed in the filtered second three-dimensional road point cloud in the camera coordinate system, the weight value corresponding to the three-dimensional road point to be processed is calculated, where the target The distance is the target distance between the transverse coordinate and the forward coordinate of the three-dimensional road point to be processed, and the target distance has a negative correlation with the weight value;

   After filtering invalid projection points in the projection point cloud, the method further includes:

   In the case where there is only one valid projection point corresponding to one three-dimensional road point in the first three-dimensional road point cloud, the three-dimensional road point in the first three-dimensional road point cloud corresponding to the valid projection point is colored into the above-mentioned The color value of a valid projection point, wherein the valid projection point is a projection point included in the filtered projection point cloud;

   When there are multiple valid projection points corresponding to the same three-dimensional road point in the first three-dimensional road point cloud, perform a weighted calculation on the color values and the weight values of the multiple valid projection points, and The three-dimensional road points corresponding to the plurality of valid projection points are colored into weighted color values, wherein each of the plurality of valid projection points is located in a different road image.
6. A three-dimensional road surface coloring device, characterized in that the device includes:

   A restoration unit, configured to restore the three-dimensional road surface according to the preset spacing and the surface parameters of the three-dimensional road surface, and generate a first three-dimensional road surface point cloud, wherein the three-dimensional road surface is fitted based on the original radar point cloud. Uncolored three-dimensional pavement;

   Determining unit, configured to determine the second three-dimensional road point cloud corresponding to the road image according to the position and orientation of each frame of the road image in the first three-dimensional road point cloud, wherein the road image is the lidar of the collection vehicle When collecting the original radar point cloud, the road image collected by the camera of the collecting vehicle, the second three-dimensional road point cloud is included in the first three-dimensional road point cloud, and the pose of the road image Three-dimensional road points whose distance is less than or equal to the preset distance;

   A projection unit configured to project the second three-dimensional road point cloud to the corresponding road image to obtain the projected point cloud in the road image;

   A coloring unit configured to color the target three-dimensional road point in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the road edge of the three-dimensional road surface, wherein the target projection point includes The projected point in the projected point cloud of each frame of the road image is located in a target area. The target area includes the same abscissa as the static road edge line perceived in the road image and the difference between the ordinates is within a preset difference. The area composed of pixel points within the range, the target three-dimensional road point includes a three-dimensional road point that has a direct mapping relationship with the target projection point, or is located between the three-dimensional road point that will have a direct mapping relationship with the target projection point. The three-dimensional road points obtained by raising the elevation to a preset height.
7. The device according to claim 6, characterized in that the device further includes:

   A coordinate system conversion unit configured to project the second three-dimensional road point cloud to the corresponding road image and obtain the projected point cloud in the road image, converting the second three-dimensional road point cloud from Convert the station center coordinate system to the camera coordinate system;

   The first filtering unit is used to filter invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, where the invalid three-dimensional road points include three-dimensional road points with elevations outside the target elevation range, previous Three-dimensional road points with coordinates less than or equal to 0;

   The projection unit is configured to project the filtered second three-dimensional road point cloud in the camera coordinate system to the corresponding road image to obtain the projected point cloud in the road image.
8. The device of claim 7, further comprising:

   A second filtering unit configured to filter all target three-dimensional road points in the first three-dimensional road point cloud corresponding to the target projection point into a target color to highlight the road edge of the three-dimensional road surface. Invalid projection points in the projection point cloud, wherein the invalid projection points include projection points located outside the image coordinate system, projection points located below the hood line of the collection vehicle, and projection points located above the static road edge line Projection points and projection points above dynamic road edge lines.
9. The device according to claim 8, characterized in that the coloring unit is used to determine the three-dimensional road points that meet preset conditions in the first three-dimensional road point cloud as the target three-dimensional road points, and The target three-dimensional road surface points are colored into the target color;

   Wherein, the preset conditions include any one of the following:

   Three-dimensional road points in the first three-dimensional road point cloud that have a direct mapping relationship with the target projection point;

   The three-dimensional road point obtained after raising the elevation of the three-dimensional road point with a direct mapping relationship by the preset height;

   The three-dimensional road points with a direct mapping relationship are filtered based on the drivable area point cloud. The drivable area point cloud includes the filtered projection point cloud, which is located by the vehicle cover. Lines, three-dimensional road points in the first three-dimensional road point cloud corresponding to projection points in the area enclosed by the static road edge line and the dynamic road edge line;

   After filtering the three-dimensional road points with a direct mapping relationship based on the drivable area point cloud, the remaining three-dimensional road points are obtained by raising the elevation of the preset height.
10. The device according to claim 8 or 9, characterized in that the device further includes:

    A computing unit configured to, after filtering the invalid three-dimensional road points in the second three-dimensional road point cloud in the camera coordinate system, calculate the filtered second three-dimensional road point cloud in the camera coordinate system. The target distance of each three-dimensional road point to be processed is calculated, and the weight value corresponding to the three-dimensional road point to be processed is calculated, where the target distance is between the lateral coordinate and the forward coordinate of the three-dimensional road point to be processed. The target distance has a negative correlation with the weight value;

    The coloring unit is also configured to, after filtering the invalid projection points in the projection point cloud, when there is only one valid projection point corresponding to a three-dimensional road point in the first three-dimensional road point cloud, The three-dimensional road points in the first three-dimensional road point cloud corresponding to the effective projection points are colored into the color values of the effective projection points, wherein the effective projection points are included in the filtered projection point cloud. Projection points; when there are multiple valid projection points corresponding to the same three-dimensional road point in the first three-dimensional road point cloud, weight the color values and the weight values of the multiple valid projection points. Calculate and color the three-dimensional road points corresponding to the plurality of valid projection points into weighted color values, wherein each of the plurality of valid projection points is located in a different road image.
11. A storage medium with a computer program stored thereon, characterized in that when the program is executed by a processor, the method according to any one of claims 1-5 is implemented.
12. An electronic device, characterized in that the electronic device includes:

    one or more processors;

    a storage device for storing one or more programs,

    When the one or more programs are executed by the one or more processors, the electronic device is caused to implement the method according to any one of claims 1-5.
13. A vehicle, characterized in that the vehicle includes the device according to any one of claims 6-10, or the electronic device according to claim 12.

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