CN113298910A - Method, apparatus and storage medium for generating traffic sign line map - Google Patents

Method, apparatus and storage medium for generating traffic sign line map Download PDF

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CN113298910A
CN113298910A CN202110528222.0A CN202110528222A CN113298910A CN 113298910 A CN113298910 A CN 113298910A CN 202110528222 A CN202110528222 A CN 202110528222A CN 113298910 A CN113298910 A CN 113298910A
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traffic sign
grid
sign line
point cloud
map
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何叶
曾清喻
李友浩
王玉斌
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Apollo Intelligent Technology Beijing Co Ltd
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Apollo Intelligent Technology Beijing Co Ltd
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Priority to PCT/CN2022/092141 priority patent/WO2022237821A1/en
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    • G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract

The present disclosure provides a method, an apparatus, and a storage medium for generating a traffic sign line map, which relate to the field of computer technology, and more particularly, to the fields of automatic driving, autonomous parking, intelligent transportation, computer vision, and electronic maps. The specific implementation scheme is as follows: based on a grid map corresponding to a preset geographic area, mapping each frame of point cloud data into the grid map according to multi-frame point cloud data of a traffic sign line in the preset geographic area, increasing a state value of a grid unit with the point cloud data, wherein the more times the point cloud data are mapped to the grid unit, the larger the state value of the grid unit is, the higher the possibility that the traffic sign line passes through the grid unit is, and generating the traffic sign line map of the preset geographic area according to the grid unit of which the state value is greater than a preset threshold value. The method and the device can reduce the calculation amount for generating the traffic sign line map and improve the generation efficiency, accuracy and consistency of the map.

Description

Method, apparatus and storage medium for generating traffic sign line map
Technical Field
The present disclosure relates to the fields of automatic driving, autonomous parking, intelligent transportation, computer vision, electronic maps, and the like in computer technology, and in particular, to a method, an apparatus, and a storage medium for generating a traffic sign line map.
Background
With the development of the automatic driving technology, sensors such as cameras and radars surrounding the body of the automatic driving vehicle are basically standard. In order to utilize the surrounding environment information obtained by the sensors to the maximum, it is an effective means to restore and reconstruct the traffic sign line (such as lane line, ground arrow, sidewalk, etc.) in the environmental road to generate a traffic sign line map.
In the related art, most of the schemes for generating the traffic sign line map output the segments of the traffic sign line in a segmented manner by a curve clustering and fitting method based on the acquired position information of the vehicle and the point set data of the traffic sign line observed for many times, and the segments of the traffic sign line are spliced to obtain the complete traffic sign line map, and the accuracy and consistency of the traffic sign line map are low.
Disclosure of Invention
The present disclosure provides a method, apparatus, and storage medium for generating a traffic sign line map.
According to a first aspect of the present disclosure, there is provided a method of generating a traffic sign line map, comprising:
acquiring multi-frame point cloud data of a traffic sign line in a preset geographic area;
mapping each frame of point cloud data to a grid map corresponding to the preset geographic area, wherein the grid map comprises a plurality of grid units;
increasing the state value of the grid unit corresponding to each frame of point cloud data;
and generating a traffic sign line map of the preset geographic area according to the grid unit with the state value larger than the preset threshold value.
According to a second aspect of the present disclosure, there is provided an apparatus for generating a traffic sign line map, comprising:
the point cloud data acquisition module is used for acquiring multi-frame point cloud data of a traffic sign line in a preset geographic area;
the data point mapping module is used for mapping each frame of point cloud data to a grid map corresponding to the preset geographic area, and the grid map comprises a plurality of grid units;
the grid map updating module is used for increasing the state value of a grid unit corresponding to each frame of point cloud data;
and the traffic sign line map generating module is used for generating a traffic sign line map of the preset geographic area according to the grid unit of which the state value is greater than the preset threshold value.
According to a third aspect of the present disclosure, there is provided an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.
According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the first aspect.
According to a fifth aspect of the present disclosure, there is provided a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of an electronic device can read the computer program, execution of the computer program by the at least one processor causing the electronic device to perform the method of the first aspect.
The method for generating the traffic sign line map improves the accuracy of the traffic sign line map.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an example scene diagram of a method of generating a traffic sign line map in which embodiments of the present disclosure may be implemented;
fig. 2 is a flowchart of a method for generating a traffic sign line map according to a first embodiment of the present disclosure;
fig. 3 is a flowchart of a method for generating a map of a traffic sign line according to a second embodiment of the present disclosure;
fig. 4 is an exemplary diagram of a traffic sign line map provided by a third embodiment of the present disclosure;
fig. 5 is a schematic diagram of an apparatus for generating a traffic sign line map according to a third embodiment of the present disclosure;
fig. 6 is a schematic diagram of an apparatus for generating a traffic sign line map according to a fourth embodiment of the present disclosure;
fig. 7 is a block diagram of an electronic device for implementing a method of generating a traffic sign line map provided by 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.
The nouns to which this disclosure relates will be explained first:
odds (odds): statistically, it is the ratio of the probability of an event occurring to the probability of the event not occurring. If the probability of an event occurring is p, then the probability of the event occurring is p/(1-p).
The present disclosure provides a method, apparatus, and storage medium for generating a traffic sign line map. The method is applied to the fields of automatic driving, autonomous parking, intelligent traffic, computer vision, electronic maps and the like in the computer technology, so that the accuracy and consistency of the traffic sign line map are improved.
The method for generating the traffic sign line map provided by the disclosure can be specifically applied to any one of the following scenes for constructing the traffic sign line map in a certain geographic area:
one application scenario is: and constructing a traffic sign line map of a road in a certain city, wherein the traffic sign line map at least comprises the position information of the traffic sign lines such as a lane line, a sidewalk, a guide arrow and the like on the road. And in the running process of the vehicle, determining the position of the traffic sign line according to the traffic sign line map, and controlling the vehicle to run according to the position of the traffic sign line.
Another application scenario is as follows: and constructing a traffic sign line map of the ground in the parking lot, wherein the traffic sign line map at least comprises position information of traffic sign lines such as vehicle position lines, lane lines and guide arrows in the parking lot. When the method is applied to autonomous parking, the position of the vehicle position line is determined according to the traffic sign line map in response to an autonomous parking instruction, and the vehicle is controlled to perform autonomous parking according to the position of the vehicle position line.
In addition, the method for generating the traffic sign line map may also be applied to other scenes, and is not limited specifically here.
In the related technology, most of the schemes for generating the traffic sign line map output the segments of the traffic sign line in a segmented manner by a curve clustering and fitting method based on the acquired position information of the vehicle and the point set data of the traffic sign line observed for many times, and the segments of the traffic sign line are spliced to obtain the complete traffic sign line map. Because the actual road contains various traffic sign lines corresponding to different curve types, only a certain type or certain types of curve parameter models are adopted, the traffic sign lines of other curve types cannot be accurately fitted, the error of the traffic sign line map is large due to the condition of error identification, and the consistency of the traffic sign line map is poor (such as poor straightness of a lane line, poor smoothness of a bent part and the like) due to the splicing process.
Fig. 1 is an exemplary scene diagram of a method for generating a traffic sign line map according to an embodiment of the present disclosure, and exemplarily, as shown in fig. 1, in a data acquisition stage, during a vehicle 10 is traveling in a preset geographic area, an image acquisition device 11 mounted on the vehicle 10 acquires image data in the preset geographic area, and a positioning device 12 mounted on the vehicle 10 acquires pose data of the vehicle 10. In the data processing stage, the electronic device 20 acquires traffic sign line point cloud data corresponding to each frame of image according to the acquired image data and pose data of the vehicle to obtain multi-frame point cloud data of the traffic sign line; and generating a traffic sign line map of a preset geographic area according to the multi-frame point cloud data of the traffic sign line.
The image capturing device may be a device for capturing an image on a vehicle, and may be a camera, a laser radar, or the like, and the positioning device may be a device for positioning a vehicle pose on the vehicle, which is not specifically limited herein.
Fig. 2 is a flowchart of a method for generating a traffic sign line map according to a first embodiment of the present disclosure. As shown in fig. 2, the method comprises the following specific steps:
step S201, obtaining multi-frame point cloud data of the traffic sign line in the preset geographic area.
In order to construct a traffic sign line map in a preset geographic area, point cloud data of the traffic sign line in the preset geographic area needs to be acquired, and the traffic sign line map is generated based on the point cloud data of the traffic sign line.
Each frame of point cloud data of the traffic sign line comprises position information of a plurality of data points of the traffic sign line.
For example, based on the scenario shown in fig. 1, in the data acquisition stage, during the vehicle driving in the preset geographic area, the image acquisition device mounted on the vehicle acquires image data in the preset geographic area, and the positioning device mounted on the vehicle acquires pose data of the vehicle. The electronic equipment acquires image data and pose data of vehicles in a preset geographic area, and determines point cloud data of a traffic sign line corresponding to each frame of image according to the image data and the pose data of the vehicles in the preset geographic area.
For example, the electronic device may further obtain point cloud data in a preset geographic area scanned by the laser radar, and extract the point cloud data of the traffic sign line from the point cloud data in the preset geographic area.
Illustratively, multi-frame point cloud data of the traffic sign lines in the preset geographic area can be generated in advance by other equipment and stored. The electronic equipment can also directly acquire multi-frame point cloud data of the traffic sign line in the preset geographic area from other equipment.
Step S202, mapping each frame of point cloud data to a grid map corresponding to a preset geographic area, wherein the grid map comprises a plurality of grid units; and increasing the state value of the grid unit corresponding to each frame of point cloud data.
The grid map comprises a plurality of grid cells, and the state value of each grid cell is used for representing probability information of a traffic sign line passing through the grid cell.
And sequentially traversing each frame of point cloud data after obtaining the multi-frame point cloud data of the traffic sign line in the preset geographic area, updating the state value of each grid unit in the grid map according to each frame of point cloud data, and finishing updating the grid map after traversing the point cloud data. For example, if there are N frames of point cloud data, the grid map is updated N times, where N is a positive integer.
For each frame of point cloud data, the point cloud data is mapped into a grid map, that is, each data point included in the point cloud data is mapped into the grid map, and a grid unit in which each data point falls is determined.
For any grid cell, if a data point in the frame of point cloud data falls into the grid cell, it indicates that there is a pixel point of a traffic sign line in a position corresponding to the grid cell in an image corresponding to the frame of point cloud data, and it can be considered that the probability that the traffic sign line passes through the grid cell is high based on the frame of image, so that the state value of the grid cell is increased.
In this step, the grid cell having the point cloud data refers to a grid cell in which at least one data point in the frame of point cloud data falls. A grid cell without point cloud data refers to a grid cell into which none of the data points in the frame of point cloud data falls. For a grid cell with point cloud data, the state value of the grid cell is increased, while for a grid cell without point cloud data, the state value of the grid cell is kept unchanged.
Traversing each frame of point cloud data, when updating the grid map according to each frame of point cloud data, the state value of the grid unit with the point cloud data is increased, the state value of the grid unit without the point cloud data is unchanged, after traversing all the point cloud data, the times of mapping the point cloud data to the grid unit are more, the state value of the grid unit is larger, and the possibility that the traffic sign line passes through the grid unit is higher.
And S203, generating a traffic sign line map of a preset geographic area according to the grid unit with the state value larger than the preset threshold value.
In the step, according to a preset threshold value, grid cells with state values larger than the preset threshold value are extracted from the grid map, and according to the grid cells with the state values larger than the preset threshold value, a traffic sign line map of a preset geographic area is generated.
The preset threshold may be set and adjusted according to the needs of the actual application scenario, and is not specifically limited herein.
In the embodiment, based on the grid map corresponding to the preset geographic area and the multi-frame point cloud data of the traffic sign line in the preset geographic area, each frame of point cloud data is mapped into the grid map by traversing each frame of point cloud data, and the state value of the grid unit with the point cloud data is increased, while the state value of the grid unit without the point cloud data is kept unchanged. After traversing all the point cloud data, the more times the point cloud data is mapped to the grid cell, the larger the state value of the grid cell is, and the higher the possibility that the traffic sign line passes through the grid cell is. And generating a traffic sign line map of a preset geographic area according to the grid unit with the state value larger than the preset threshold value, and generating the traffic sign line map through a series of addition operations, so that the calculation amount is greatly reduced, and the map generation efficiency is improved. Meanwhile, the whole map is generated at one time, the mistaken identification and splicing processes caused by curve fitting and splicing are avoided, the method is suitable for scenes constructed by various different maps, and the map accuracy and consistency are improved.
Fig. 3 is a flowchart of a method for generating a traffic sign line map according to a second embodiment of the present disclosure. On the basis of the first embodiment, in this embodiment, the state value of the grid cell may be probability information that the traffic sign line passes through the grid cell, and the initial value of the state value of the grid cell is 0.
As shown in fig. 3, the method comprises the following specific steps:
s301, acquiring images in a preset geographic area acquired by the vehicle, and acquiring pose data when the vehicle acquires the images.
In this embodiment, based on the scenario shown in fig. 1, in the data acquisition stage, in the process that the vehicle travels in the preset geographic area, the image acquisition device mounted on the vehicle acquires image data in the preset geographic area. The image data may include a plurality of frames of images, among others.
A loaded positioning device on the vehicle collects pose data of the vehicle. Wherein the pose data comprises pose data of the vehicle acquired at a plurality of times. And determining the pose data of the vehicle when each frame of image is acquired according to the timestamp of the image acquisition and the timestamp of the pose data of the vehicle.
The electronic equipment acquires multi-frame images in a preset geographic area acquired by the vehicle and pose data when the vehicle acquires the images.
The traffic sign line is arranged in the preset geographic area, and the collected multi-frame image can cover the traffic sign line in the preset geographic area.
In this embodiment, the preset geographic area is a geographic range of a traffic sign line map that needs to be acquired according to the requirements of a service scene. For example, if a city map is created, the predetermined geographic area may be the area where a city is located; if a parking lot map needs to be established, the preset geographic area may be an area where a parking lot is located, and the like. The preset geographic area may be set and adjusted according to the needs of the actual application scenario, and this embodiment is not specifically limited herein.
And S302, determining the coordinates of the mapping points of the pixel points of the traffic sign lines in the image under the vehicle body coordinate system.
In the step, each frame of image can be processed respectively, and according to each frame of image, the three-dimensional coordinates of the mapping points of the pixel points of the traffic sign lines in the image under the vehicle body coordinate system are determined.
This step in this embodiment can be implemented as follows:
determining pixel points of traffic sign lines in the image; and mapping the pixel points into mapping points under the vehicle body coordinate system according to the camera model corresponding to the image to obtain the coordinates of the mapping points.
Exemplarily, according to each frame of image, determining pixel coordinates of pixel points of the traffic sign line in the image in an image coordinate system; and mapping the pixel points into mapping points under the vehicle body coordinate system according to the camera model corresponding to the image to obtain the three-dimensional coordinates of the mapping points.
Specifically, each frame of image is subjected to image processing, the traffic sign line information in the image is extracted, the pixel points of the traffic sign line in the image are determined, and the pixel coordinates of the pixel points of the traffic sign line are further determined. And reversely projecting the pixel points into the physical world according to the camera model, so as to map the pixel points into the mapping points under the vehicle body coordinate system, and obtaining the three-dimensional coordinates of the mapping points of the pixel points of the traffic sign line under the vehicle body coordinate system.
In addition, in this step, any method in the prior art that converts two-dimensional coordinates of pixel points in an image into three-dimensional coordinates in a vehicle body coordinate system may be adopted, and this embodiment is not described herein again.
Step S303, projecting the mapping points to a world coordinate system according to pose data of the vehicle when acquiring the image to obtain the coordinates of the corresponding projection points; and generating a frame of point cloud data according to the three-dimensional coordinates of the projection points determined by each frame of image.
In the step, the mapping points are projected to a world coordinate system according to pose data when the vehicle collects images to obtain corresponding projection points and three-dimensional coordinates of the projection points, and a frame of point cloud data is formed according to the three-dimensional coordinates of the projection points determined by each frame of image.
After the three-dimensional coordinates of the mapping points of the pixel points of the traffic sign lines in the image under the vehicle body coordinate system are obtained, the mapping points of the pixel points of the traffic sign lines in the image under the vehicle body coordinate system are projected to the world coordinate system according to the pose of the vehicle when the image is collected, and the three-dimensional coordinates of the projection points and the projection points of the pixel points of the traffic sign lines in the image under the world coordinate system are obtained.
In this embodiment, a frame of point cloud data is formed according to the three-dimensional coordinates of the projection points determined for each frame of image.
In addition, in this step, any method in the prior art that converts the three-dimensional coordinates in the vehicle body coordinate system into the three-dimensional coordinates in the world coordinate system may be used, and this embodiment is not described herein again.
The above steps S301 to S303 are optional embodiments of obtaining multiple frames of point cloud data corresponding to a traffic sign line provided in this embodiment, and according to each frame of image and a pose of a vehicle when acquiring the image, by identifying a pixel point of the traffic sign line in the image, and converting a coordinate of the pixel point into a world coordinate system, obtaining three-dimensional coordinates of multiple corresponding data points after the pixel point of the traffic sign line is mapped to the world coordinate system, and using the three-dimensional coordinates as one frame of point cloud data of the traffic sign line, accurate point cloud data of the traffic sign line can be obtained, thereby providing a data base for generating an accurate traffic sign line map.
In another optional implementation manner of this embodiment, the electronic device may further obtain point cloud data in a preset geographic area scanned by the laser radar, and extract point cloud data of the traffic sign line from the point cloud data in the preset geographic area to obtain multiple types of point cloud data of the traffic sign line.
In another optional implementation manner of this embodiment, multi-frame point cloud data of the traffic sign line in the preset geographic area may also be generated in advance by other devices and stored. The electronic equipment can also directly acquire multi-frame point cloud data of the traffic sign line in the preset geographic area from other equipment.
And S304, constructing a grid map of a preset geographic area, and initializing the state value of each grid unit in the grid map.
The state value of the grid cell can be probability information that the traffic marking line passes through the grid cell, and the probability that the lane line passes through the grid cell can be reflected.
In the present embodiment, a grid map is represented by m, miRepresenting the ith grid cell in the grid map. m isiThere are two states: traffic sign line passes through grid cell mi(i.e., the data points with the traffic sign line fall within miCan use mi1), the traffic sign line does not pass through the grid cell mi(i.e., none of the data points of the traffic sign line fall within miCan use mi0 represents).
With p (m)i1) or p (m)i) Indicating traffic sign line passing grid cell miProbability of (1) in p (m)i0) or p (m)i) Indicating that the traffic sign line has not passed through the grid cell miThe probability of (c).
By xtRepresenting the pose of the vehicle at the time t, representing the point cloud data corresponding to one frame of image acquired by the vehicle at the time t by z, and representing the position of the vehicle at the time t by zk tDenotes ztThe k-th data point in (1), z is represented by ntThe total number of data points, k, is 1,2, …, n.
Then, updating the grid map can be modeled as solving the probability that all grid cells of the grid map have a traffic sign line to pass through (which can be expressed as p (m | x)0：t，z0：t) ) of the vehicle. Assuming that each grid cell is independent of each other, the following formula (1) is given:
Figure BDA0003067108780000091
wherein, p (m)i|x0：t，z0：t) Representing the passage of a traffic sign line through a grid cell m determined based on point cloud data and pose data at time 0-tiThe probability value of (2).
Based on equation (1), using bayesian rules and markov assumptions, the following equations (2) and (3) are given:
Figure BDA0003067108780000092
Figure BDA0003067108780000093
wherein, p (. about.m)i|x0t，z0：t) Indicating that the traffic sign line determined based on the point cloud data and the pose data at the time 0-t has not passed through the grid cell miThe probability value of (2).
Considering the stability of the probability value data operation, in order to improve the probability that the state value of the grid cell in the grid map can accurately and stably represent that the traffic sign line passes through the grid cell, the probability (represented by p) that the traffic sign line passes through the grid cell can be transformed by taking logarithms at two sides as follows, and the probability information that the traffic sign line passes through the grid cell is obtained:
Figure BDA0003067108780000101
and l represents probability information of the traffic sign line passing through the grid cell.
Dividing the above (2) by (3), and taking logarithm of both sides, the following formula (4) is obtained:
Figure BDA0003067108780000102
wherein, p (z)t|mi，xt) For observing model likelihood probabilities, p (z)t|～mi，xt)＝1-p(zt|mi，xt). If the pose x of the vehicle at the moment t is knowntAnd a grid unitmiIf a traffic sign line passes through the inside, an observed value (collected point cloud data) at the time t can be deduced.
Applying Bayesian rules, the following equations (5) and (6) are given:
Figure BDA0003067108780000103
Figure BDA0003067108780000104
substituting equations (5) and (6) into equation (4), the following equation (7) can be obtained:
l(mi|x0：t，z0：t)＝l(mi|x0：t-1，z0：t-1)+l(mi|zt，xt)-l(mi|xt) (7)
wherein, l (m)i|xt)＝l(mi) Denotes a grid cell miA priori initial few values. l (m)i|zt，xt) The value representing the inverse observation model is a constant value.
l(mi|x0：t，z0：t) Representing the passing of the traffic sign line through the grid cell m determined according to the multi-frame point cloud data of the time from 0 to t and the pose data of the vehicleiProbability information of (1). l (m)i|x0：t-1，z0：t-1) Representing the passing of the traffic sign line through the grid cell m determined according to the multi-frame point cloud data at the time of 0-t-1 and the pose data of the vehicleiProbability information of (1).
In this embodiment, the probability information that the traffic sign line passes through the grid cell is represented by the state value of the grid cell, and the initial state value of the grid cell is 0 (that is, the initial value of the probability information that the traffic sign line passes through the grid cell is 0, and the probability that the traffic sign line passes through the grid cell at this time is 0.5).
Based on the above equation (7), l (m)i|zt，xt) As an incremental value, for observation at time tData (a frame of point cloud data at the time t), if the data point of the traffic sign line falls into the grid cell miIn the method, the grid unit m after the point cloud data based on the time 0-t-1 is updated can be obtainediThe state value of (1) is increased by an increment value, and the updated grid unit m can be obtainediThe state value of (2).
In this way, the initial state values of all the grid units in the grid map are set to be 0, the probability that the traffic sign line passes through the grid units is 0.5, and then all the frames of point cloud data are mapped into the grid map according to the multi-frame point cloud data of the traffic sign line. With the increase of the point cloud data frames mapped to the grid units, the state values of the grid units are increased, and after the mapping of all the point cloud data is completed, the possibility that a traffic sign line passes through each grid unit can be accurately determined, so that a traffic sign line map can be accurately generated.
It should be noted that, in another embodiment of this embodiment, before the point cloud data of the traffic sign line is acquired, a grid map of a preset geographic area may be constructed in advance, and a state value of each grid unit in the grid map is initialized. That is, step S304 may be performed before steps S301-S303.
After multi-frame point cloud data of the traffic sign line are acquired and a grid map is constructed and initialized, through the steps S305-S306, each frame of point cloud data is traversed, each frame of point cloud data is mapped to the grid map corresponding to the preset geographic area, and the state values of grid units corresponding to each frame of point cloud data are increased, so that the possibility that the traffic sign line passes through each grid unit can be accurately determined, and the traffic sign line map can be accurately generated.
Step S305, each frame of point cloud data comprises position information of a plurality of data points of the traffic sign line, and a grid unit corresponding to each data point is determined according to the position information of each data point in each frame of point cloud data.
In the step, according to the position information of each data point in each frame of point cloud data, a grid unit in which each data point falls is determined, and the grid unit in which the data point falls is used as a grid unit corresponding to the data point.
In this embodiment, the grid cell having the point cloud data refers to a grid cell in which at least one data point in the frame of point cloud data falls. A grid cell without point cloud data refers to a grid cell in which no data point in the frame of point cloud data falls.
In addition, for all data points and all grid cells, if a certain data point falls on the boundary of a certain grid cell, determining that the data point falls into the grid cell; alternatively, for all data points and all grid cells, if a data point falls on the boundary of a grid cell, it is determined that the data point does not fall into any grid cell. And uniformly processing all data points and all grid cells in the case of falling on the boundary.
Step S306, increasing the state value of the grid unit corresponding to each data point by a preset increment.
In this step, the state value of the grid cell having the corresponding data point is increased by a preset increment.
If one or more data points in one frame of point cloud data fall into a certain grid unit, the state value of the grid unit is increased by a preset increment. For a frame of point cloud data, if a data point in the frame of point cloud data falls into a grid unit, the state value of the grid unit is increased by a preset increment no matter whether the number of the data points falling into the grid unit is one or more.
If no data point in one frame of point cloud data falls into a certain grid cell, the state value of the grid cell is kept unchanged.
The preset increment may be a preset inverse observation model probability value, and may be set and adjusted according to the needs of the actual application scenario, which is not specifically limited herein.
And S307, generating a traffic sign line map of a preset geographic area according to the grid unit with the state value larger than the preset threshold value.
In the step, according to a preset threshold value, grid cells with state values larger than the preset threshold value are extracted from the grid map, and according to the grid cells with the state values larger than the preset threshold value, a traffic sign line map of a preset geographic area is generated.
The preset threshold may be set and adjusted according to the needs of the actual application scenario, and is not specifically limited herein.
In an alternative embodiment, this step can be implemented as follows:
and extracting the grid units with the state values larger than a preset threshold value according to the state values of all the grid units in the grid map, and taking the areas covered by the grid units with the state values larger than the preset threshold value as the areas covered by the traffic sign lines to obtain the traffic sign line map of the preset geographic area.
In another alternative embodiment, this step may be implemented as follows:
extracting the grid units with the state values larger than a preset threshold value according to the state values of all the grid units in the grid map; and taking the data points corresponding to the grid cells with the state values larger than the preset threshold value as track points of the traffic sign line, and generating a traffic sign line map of the preset geographic area according to the position information of the data points corresponding to the grid cells with the state values larger than the preset threshold value.
In this embodiment, probability information of the grid cells is updated through a series of addition operations, and thus constructed traffic sign line map data can be obtained, and the probability information can be represented as an 8-bit (bit) or 16-bit integer (int type) in a discretization manner in a computer, so that the operation of the computer is very convenient. The constructed traffic sign line map can effectively resist the influence of data noise and well maintain the consistency of the map (such as the straightness of a lane line, the smoothness of a bent part and the like). Exemplarily, an example of the traffic sign line map generated by the method provided by the present embodiment is shown in fig. 4, and the straightness of the lane line and the smoothness of the curved portion are both good.
In this embodiment, based on the grid map corresponding to the preset geographic area, the initial state values of all grid cells in the grid map are all set to 0, which indicates that the probability that the traffic sign line passes through the grid cells is 0.5. Furthermore, according to multi-frame point cloud data of the traffic sign line in the preset geographic area, each frame of point cloud data is mapped into the grid map by traversing each frame of point cloud data, the state value of the grid unit with the point cloud data is increased, and the state value of the grid unit without the point cloud data is kept unchanged. After traversing all the point cloud data, the more times the point cloud data are mapped to the grid cells, the larger the state value of the grid cells is, the higher the possibility that the traffic sign line passes through the grid cells is, and the traffic sign line map of the preset geographic area is generated according to the grid cells of which the state values are larger than the preset threshold value. The traffic sign line map can be generated through a series of addition operations, so that the calculation amount is greatly reduced, and the map generation efficiency is improved. Meanwhile, the whole map is generated at one time, the mistaken identification and splicing processes caused by curve fitting and splicing are avoided, the method is suitable for scenes constructed by various different maps, and the map accuracy and consistency are improved.
Fig. 5 is a schematic diagram of an apparatus for generating a traffic sign line map according to a third embodiment of the present disclosure. The device for generating the traffic sign line map provided by the embodiment of the disclosure can execute the processing flow provided by the method for generating the traffic sign line map. As shown in fig. 5, the apparatus 50 for generating a traffic sign line map includes: a point cloud data acquisition module 501, a data point mapping module 502, a grid map updating module 503 and a traffic sign line map generation module 504.
Specifically, the point cloud data obtaining module 501 is configured to obtain multi-frame point cloud data of a traffic sign line in a preset geographic area.
The data point mapping module 502 is configured to map each frame of point cloud data to a grid map corresponding to a preset geographic area, where the grid map includes a plurality of grid units.
And a grid map updating module 503, configured to add a state value of a grid unit corresponding to each frame of point cloud data.
And a traffic sign line map generating module 504, configured to generate a traffic sign line map of a preset geographic area according to the grid unit of which the state value is greater than the preset threshold value.
The device provided in the embodiment of the present disclosure may be specifically configured to execute the method embodiment provided in the first embodiment, and specific functions are not described herein again.
In the embodiment, based on the grid map corresponding to the preset geographic area and the multi-frame point cloud data of the traffic sign line in the preset geographic area, each frame of point cloud data is mapped into the grid map by traversing each frame of point cloud data, and the state value of the grid unit with the point cloud data is increased, while the state value of the grid unit without the point cloud data is kept unchanged. After traversing all the point cloud data, the more times the point cloud data is mapped to the grid cell, the larger the state value of the grid cell is, and the higher the possibility that the traffic sign line passes through the grid cell is. And generating a traffic sign line map of a preset geographic area according to the grid unit with the state value larger than the preset threshold value, and generating the traffic sign line map through a series of addition operations, so that the calculation amount is greatly reduced, and the map generation efficiency is improved. Meanwhile, the whole map is generated at one time, the mistaken identification and splicing processes caused by curve fitting and splicing are avoided, the method is suitable for scenes constructed by various different maps, and the map accuracy and consistency are improved.
Fig. 6 is a schematic diagram of an apparatus for generating a traffic sign line map according to a fourth embodiment of the present disclosure. The device for generating the traffic sign line map provided by the embodiment of the disclosure can execute the processing flow provided by the method for generating the traffic sign line map. As shown in fig. 6, the apparatus 60 for generating a traffic sign line map includes: a point cloud data acquisition module 601, a data point mapping module 502, a grid map updating module 603 and a traffic sign line map generation module 604.
Specifically, the point cloud data obtaining module 601 is configured to obtain multi-frame point cloud data of a traffic sign line in a preset geographic area.
The data point mapping module 602 is configured to map each frame of point cloud data to a grid map corresponding to a preset geographic area, where the grid map includes a plurality of grid units.
And a grid map updating module 603, configured to add a state value of a grid unit corresponding to each frame of point cloud data.
The traffic sign line map generating module 604 is configured to generate a traffic sign line map of a preset geographic area according to the grid unit of which the state value is greater than the preset threshold value.
Optionally, the state value of the grid cell is probability information that the traffic sign line passes through the grid cell, and the initial value of the state value of the grid cell is 0.
Optionally, each frame of point cloud data includes location information for a plurality of data points of the traffic sign line. The fig. 6 data point mapping module 602 is further configured to determine a grid unit corresponding to each data point according to the position information of each data point in each frame of point cloud data.
The grid map updating module 603 is further configured to increase the state value of the grid cell corresponding to each data point by a preset increment.
Optionally, as shown in fig. 6, the point cloud data obtaining module 601 includes:
the data acquisition submodule 6011 is configured to acquire an image in a preset geographic area acquired by a vehicle, and acquire pose data when the vehicle acquires the image;
the first mapping submodule 6012 is configured to determine mapping points of pixel points of a traffic sign line in the image in the vehicle body coordinate system;
the second mapping submodule 6013 is configured to project the mapping points to the world coordinate system according to the pose data, obtain coordinates of corresponding projection points, and generate a frame of point cloud data according to the coordinates of the projection points.
Optionally, the first mapping sub-module is further configured to:
determining pixel points of traffic sign lines in the image; and mapping the pixel points into mapping points under the vehicle body coordinate system according to the camera model corresponding to the image to obtain the coordinates of the mapping points.
Optionally, as shown in fig. 6, the traffic sign line map generating module 604 includes:
the first generation submodule 6041 is configured to use an area covered by the grid cell whose state value is greater than the preset threshold as an area covered by a traffic sign line, so as to obtain a traffic sign line map of a preset geographic area.
Optionally, as shown in fig. 6, the traffic sign line map generating module 604 includes:
a second generation submodule 6042 configured to:
and taking the data points corresponding to the grid cells with the state values larger than the preset threshold value as track points of the traffic sign line, and generating a traffic sign line map of the preset geographic area according to the position information of the data points corresponding to the grid cells with the state values larger than the preset threshold value.
Optionally, as shown in fig. 6, the apparatus 60 for generating a traffic sign line map further includes:
a grid map construction module 605 to:
and constructing a grid map corresponding to a preset geographic area, and initializing the state value of each grid unit.
The device provided in the embodiment of the present disclosure may be specifically configured to execute the method embodiment provided in the second embodiment, and specific functions are not described herein again.
In this embodiment, based on the grid map corresponding to the preset geographic area, the initial state values of all grid cells in the grid map are all set to 0, which indicates that the probability that the traffic sign line passes through the grid cells is 0.5. Furthermore, according to multi-frame point cloud data of the traffic sign line in the preset geographic area, each frame of point cloud data is mapped into the grid map by traversing each frame of point cloud data, the state value of the grid unit with the point cloud data is increased, and the state value of the grid unit without the point cloud data is kept unchanged. After traversing all the point cloud data, the more times the point cloud data are mapped to the grid cells, the larger the state value of the grid cells is, the higher the possibility that the traffic sign line passes through the grid cells is, and the traffic sign line map of the preset geographic area is generated according to the grid cells of which the state values are larger than the preset threshold value. The traffic sign line map can be generated through a series of addition operations, so that the calculation amount is greatly reduced, and the map generation efficiency is improved. Meanwhile, the whole map is generated at one time, the mistaken identification and splicing processes caused by curve fitting and splicing are avoided, the method is suitable for scenes constructed by various different maps, and the map accuracy and consistency are improved.
The present disclosure also provides an electronic device and a readable storage medium according to an embodiment of the present disclosure.
According to an embodiment of the present disclosure, the present disclosure also provides a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to perform the solution provided by any of the embodiments described above.
FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital 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. 7, the electronic device 700 includes a computing unit 701, which may perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Computing unit 701 may be a variety of general purpose and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The computing unit 701 performs the various methods and processes described above, such as method XXX. For example, in some embodiments, method XXX may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of a computer program may be loaded onto and/or installed onto device 700 via ROM 702 and/or communications unit 709. When the computer program is loaded into RAM 703 and executed by computing unit 701, one or more steps of method XXX described above may be performed. Alternatively, in other embodiments, computing unit 701 may be configured to perform method XXX by any other suitable means (e.g., by way 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 can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.
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 application 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 in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims (19)

1. A method of generating a traffic sign line map, comprising:
acquiring multi-frame point cloud data of a traffic sign line in a preset geographic area;
mapping each frame of point cloud data to a grid map corresponding to the preset geographic area, wherein the grid map comprises a plurality of grid units;
increasing the state value of the grid unit corresponding to each frame of point cloud data;
and generating a traffic sign line map of the preset geographic area according to the grid unit with the state value larger than the preset threshold value.
2. The method of claim 1, wherein the state value of the grid cell is information on a probability that a traffic sign line passes through the grid cell, and the initial value of the state value of the grid cell is 0.
3. The method of claim 1 or 2, wherein each frame of the point cloud data comprises position information of a plurality of data points of a traffic sign line;
the mapping of each frame of point cloud data to the grid map corresponding to the preset geographic area comprises: determining a grid unit corresponding to each data point according to the position information of each data point in each frame of point cloud data;
the increasing of the state value of the grid unit corresponding to each frame of the point cloud data comprises: and increasing the state value of the grid unit corresponding to each data point by a preset increment.
4. The method according to any one of claims 1-3, wherein each frame of point cloud data of a traffic sign line within a preset geographical area is acquired by:
acquiring an image in the preset geographic area acquired by a vehicle, and acquiring pose data when the vehicle acquires the image;
determining the mapping points of the pixel points of the traffic sign lines in the image under the vehicle body coordinate system;
projecting the mapping points to a world coordinate system according to the pose data to obtain the coordinates of the corresponding projection points;
and generating a frame of point cloud data according to the coordinates of the projection points.
5. The method of claim 4, wherein the determining mapped points of pixel points of traffic sign lines in the image in a vehicle body coordinate system comprises:
determining pixel points of traffic sign lines in the image;
and mapping the pixel points into mapping points under a vehicle body coordinate system according to a camera model corresponding to the image to obtain coordinates of the mapping points.
6. The method according to any one of claims 1-5, wherein the generating a traffic sign line map for the preset geographic area according to the grid cells having state values greater than a preset threshold comprises:
and taking the area covered by the grid unit with the state value larger than the preset threshold value as the area covered by the traffic sign line to obtain the traffic sign line map of the preset geographic area.
7. The method according to any one of claims 1-5, wherein the generating a traffic sign line map according to the grid cells having the state values greater than a preset threshold value comprises:
using data points in the point cloud data corresponding to the grid unit with the state value larger than the preset threshold value as track points of the traffic sign line;
and generating a traffic sign line map of the preset geographic area according to the position information of the track points.
8. The method of any of claims 1-7, further comprising:
and constructing a grid map corresponding to the preset geographic area, and initializing the state value of each grid unit.
9. An apparatus for generating a traffic sign line map, comprising:
the point cloud data acquisition module is used for acquiring multi-frame point cloud data of a traffic sign line in a preset geographic area;
the data point mapping module is used for mapping each frame of point cloud data to a grid map corresponding to the preset geographic area, and the grid map comprises a plurality of grid units;
the grid map updating module is used for increasing the state value of a grid unit corresponding to each frame of point cloud data;
and the traffic sign line map generating module is used for generating a traffic sign line map of the preset geographic area according to the grid unit of which the state value is greater than the preset threshold value.
10. The apparatus of claim 9, wherein the state value of the grid cell is information on a probability that a traffic sign line passes through the grid cell, and the initial value of the state value of the grid cell is 0.
11. The apparatus of claim 9 or 10, wherein each frame of the point cloud data comprises location information for a plurality of data points of a traffic sign line;
the data point mapping module is further to:
determining a grid unit corresponding to each data point according to the position information of each data point in each frame of point cloud data;
the grid map update module is further to:
and increasing the state value of the grid unit corresponding to each data point by a preset increment.
12. The apparatus of any of claims 9-11, wherein the point cloud data acquisition module comprises:
the data acquisition submodule is used for acquiring images in the preset geographic area acquired by the vehicle and acquiring pose data when the vehicle acquires the images;
the first mapping submodule is used for determining mapping points of pixel points of the traffic sign lines in the image under a vehicle body coordinate system;
and the second mapping submodule is used for projecting the mapping points to a world coordinate system according to the pose data to obtain the coordinates of the corresponding projection points, and generating a frame of point cloud data according to the coordinates of the projection points.
13. The apparatus of claim 12, wherein the first mapping sub-module is further to:
determining pixel points of traffic sign lines in the image;
and mapping the pixel points into mapping points under a vehicle body coordinate system according to a camera model corresponding to the image to obtain coordinates of the mapping points.
14. The apparatus of any of claims 9-13, wherein the traffic sign line map generation module comprises:
and the first generation submodule is used for taking the area covered by the grid unit with the state value larger than the preset threshold value as the area covered by the traffic sign line to obtain the traffic sign line map of the preset geographic area.
15. The apparatus of any of claims 9-13, wherein the traffic sign line map generation module comprises:
a second generation submodule for:
using data points in the point cloud data corresponding to the grid unit with the state value larger than the preset threshold value as track points of the traffic sign line;
and generating a traffic sign line map of the preset geographic area according to the position information of the track points.
16. The apparatus of any of claims 9-15, further comprising:
a grid map construction module to:
and constructing a grid map corresponding to the preset geographic area, and initializing the state value of each grid unit.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.
19. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-8.
CN202110528222.0A 2021-05-14 2021-05-14 Method, apparatus and storage medium for generating traffic sign line map Pending CN113298910A (en)

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