CN111527377B - Verification of digital maps - Google Patents
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- CN111527377B CN111527377B CN201780098047.8A CN201780098047A CN111527377B CN 111527377 B CN111527377 B CN 111527377B CN 201780098047 A CN201780098047 A CN 201780098047A CN 111527377 B CN111527377 B CN 111527377B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
- G01C21/3804—Creation or updating of map data
- G01C21/3807—Creation or updating of map data characterised by the type of data
- G01C21/3815—Road data
- G01C21/3819—Road shape data, e.g. outline of a route
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Abstract
Examples of the present disclosure describe methods and apparatus for verifying a portion of a road in a digital map. The method comprises the following steps: loading a part of roads in the digital map; identifying a road centerline or lane line of the portion of the road; selecting a set of samples on the road centerline or lane line; determining a spline curve based on the set of samples; calculating an average error between the spline curve and the set of samples; and verifying the portion of the link by comparing the average error to a threshold, wherein the portion of the link is correct if the average error is less than the threshold, and wherein the portion of the link is incorrect if the average error is equal to or greater than the threshold.
Description
Technical Field
The present disclosure relates generally to the field of Advanced Driving Assistance Systems (ADAS) or Highly Automated Driving (HAD), and more particularly to a method and apparatus for validating digital maps.
Background
For a long time, autopilot cars have been the subject of research efforts aimed at improving the safety and efficiency of car transportation. In recent years, increasingly complex sensors and automobiles make autopilot systems more realistic. High definition digital maps are commonly used in autopilot systems. It typically contains rich road element information such as road shape geometry, road type and turn direction, road links, etc. Such information is critical to vehicle navigation, positioning, and decision making. Thus, the accuracy of high definition digital maps is becoming increasingly important.
Currently, in order to test the correctness of high-definition digital maps, some people perform the test by manual inspection, while others perform the test by loading the high-definition digital map on a car and driving around areas on the high-definition digital map. The disadvantages of this test procedure on high definition digital maps are apparent. First, the testing process performed manually or by driving a car requires a lot of time and money. Second, if the high-definition digital map does have serious problems, driving based on the wrong high-definition digital map is also very dangerous.
Thus, it may be desirable to have an efficient, safe, and accurate testing process.
Disclosure of Invention
The present disclosure is directed to methods and apparatus for verifying a portion of a road in a digital map. Such methods and apparatus may enable efficient, secure, and accurate testing of digital maps and significantly reduce the cost of the testing.
According to a first exemplary embodiment of the present disclosure, there is provided a method for verifying a portion of a road in a digital map, the method comprising: loading a part of roads in the digital map; identifying a road centerline or lane line of the portion of the road; selecting a set of samples on the road centerline or lane line; determining a spline curve based on the set of samples; calculating an average error between the spline curve and the set of samples; and verifying the portion of the link by comparing the average error to a threshold, wherein the portion of the link is correct if the average error is less than the threshold, and wherein the portion of the link is incorrect if the average error is equal to or greater than the threshold.
According to a second exemplary embodiment of the present disclosure, there is provided an apparatus for verifying a portion of a road in a digital map, the apparatus comprising: a memory having stored therein computer executable instructions; and a processor coupled to the memory and configured to: loading a part of roads in the digital map; identifying a road centerline or lane line of the portion of the road; selecting a set of samples on the road centerline or lane line; determining a spline curve based on the set of samples; calculating an average error between the spline curve and the set of samples; and verifying the portion of the link by comparing the average error to a threshold, wherein the portion of the link is correct if the average error is less than the threshold, and wherein the portion of the link is incorrect if the average error is equal to or greater than the threshold.
According to a third exemplary embodiment of the present disclosure, there is provided an apparatus for verifying a portion of a road in a digital map, the apparatus comprising: a loading unit configured to load a part of roads in the digital map; an identification unit configured to identify a road center line or a lane line of the part of the road; a selection unit configured to select a set of samples on the road centerline or lane line; a determining unit configured to determine a spline curve based on the set of samples; a calculation unit configured to calculate an average error between the spline curve and the set of samples; and a verification unit configured to verify the part of the road by comparing the average error with a threshold value, wherein the part of the road is correct if the average error is smaller than the threshold value, and wherein the part of the road is incorrect if the average error is equal to or greater than the threshold value.
According to a fourth exemplary embodiment of the present disclosure, a non-transitory machine-readable storage medium having instructions stored thereon that, when executed, cause a processor to implement a method for verifying a portion of a road in a digital map is provided.
According to a fifth exemplary embodiment of the present disclosure, a vehicle is provided that includes means for verifying a portion of a road in a digital map.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Additional aspects, features, and/or advantages of the examples will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.
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The foregoing and other aspects and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings, illustrating by way of example the principles of the disclosure. Note that the figures are not necessarily drawn to scale.
Fig. 1 (a) - (C) illustrate exemplary detailed examples of verification of a portion of roads in a digital map according to an exemplary embodiment of the present disclosure.
Fig. 2 illustrates a flowchart of an exemplary method for verifying a portion of a road in a digital map according to an exemplary embodiment of the present disclosure.
Fig. 3 illustrates a block diagram of an exemplary apparatus for verifying a portion of a road in a digital map, according to an exemplary embodiment of the present disclosure.
Fig. 4 illustrates a general hardware environment in which the present disclosure may be applied, according to an exemplary embodiment of the present disclosure.
Detailed Description
In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the described exemplary embodiments. It will be apparent, however, to one skilled in the art, that the described embodiments may be practiced without some or all of these specific details. In other exemplary embodiments, well known structures or processing steps have not been described in detail in order to avoid unnecessarily obscuring the concepts of the present disclosure.
The term "vehicle" as used in the specification refers to an automobile, an airplane, a helicopter, a ship, etc. The term "a or B" as used in the specification means "a and B" and "a or B", and does not mean that a and B are exclusive unless otherwise indicated.
As mentioned above, the accuracy of high definition digital maps is critical to vehicle navigation, positioning, and decision making. One way to determine whether a high definition digital map is correct is to determine whether a portion of the roads included in the high definition digital map have jitter. As used herein, the term "jitter" refers to the distortion or deviation of the road from the actual road shape geometry. For example, such jitter may be due to errors made when creating high definition digital maps, and should be avoided in order to provide accurate high definition digital maps.
Fig. 1 (a) - (C) illustrate exemplary detailed examples of verification of a portion of a road 110 in a digital map 100 according to an exemplary embodiment of the present disclosure.
Fig. 1 (a) depicts a portion of a roadway 110 that may have jitter in a section 115. In an example, the portion of the road 110 may be loaded from the digital map 100. The digital map 100 may be stored in an on-board autopilot system to facilitate autopilot. To test the correctness of the portion of the roadway 110, the centerline 120 of the portion of the roadway 110 may be identified. In an example, the centerline 120 of the portion of the road 110 may already be stored in the digital map 100 and may be loaded from the digital map 100 along with the portion of the road 110. Each point on the centerline 120 may have coordinates including an x-coordinate and a y-coordinate. Alternatively, the centerline 120 may not be stored in the digital map 110, but may be determined based on coordinates of the road edges. In an alternative, lane lines in the portion of the road may be identified instead of or in addition to the centerline 120. Such lane lines may already be stored in the digital map.
FIG. 1 (B) depicts a set of sampling points 130 having a centerline 120 1 、130 2 、……、130 N Is a part of the road 110. The set of sampling points 130 1 、130 2 、……、130 N Each of (a) has a coordinate (x i ,y i ) (i=1,..n), where N represents the number of sampling points on the centerline 120 and can be any positive integer. In one example, the set of sampling points 130 1 、130 2 、……、130 N May be uniformly selected among the road centerlines 120. For example, the distance between two adjacent sampling points may be 1m, and for all sampling points 130 1 、130 2 、……、130 N May be identical. In another example, the set of sampling points 130 1 、130 2 、……、130 N May not be uniformly selected among the road centerlines 120. For example, a first sampling point 130 1 And a second sampling point 130 2 The distance between the two may be equal to the second sampling point 130 2 And a third sampling point 130 3 The distances between them are different. In an alternative schemeInstead of or in addition to the sampling points selected on the road centerline 120, another set of sampling points may be selected on the lane lines in the portion of the road 110.
Fig. 1 (C) depicts a portion of a road 110 having a spline curve 140. Spline 140 may be based on sampling points 130 selected on centerline 120 1 、130 2 、……、130 N To determine. As is well known in the art of science, spline curve f (x) is a smooth curve obtained through a given set of control points and can be used to approximately describe the functional relationship between the coordinates of the given set of control points. In the present invention, the spline curve f (x) can pass through the sampling points 130 using a known method or known computer software (e.g., MATLAB, AUTOCAD, etc.) 1 、130 2 、……、130 N Obtained by means of coordinates of the coordinate system. In one example, the spline curve may be a B-spline curve. Alternatively, the spline curve may be a β spline curve.
After spline 140 is determined, spline 140 and sampling points 130 may be calculated 1 、130 2 、……、130 N Average error AE between. For example, the average error AE may be calculated according to the following equation:
wherein:
x i representing the ith sample point 130 i X-coordinate of (a);
y i representing the ith sample point 130 i Y-coordinate of (c);
f(x i ) Representing the y-coordinate of a point on spline 120, the x-coordinate of the point being equal to the i-th sampling point 130 i Is the same as the x coordinate of (a); and
n represents the number of sampling points on the centerline 120.
Alternatively, the average error AE may be calculated using any other known averaging method (e.g., a weighted averaging method).
The calculated average error AE may then be compared to a threshold value. In an example, the threshold may be in the range between 5cm and 40cm, preferably 20cm. The comparison result may be used to determine whether the portion of the link 110 is correct (e.g., whether the portion of the link 110 has jitter). If the comparison indicates that the calculated average error AE is less than the threshold, it may be determined that the portion of the link 110 is correct (e.g., the portion of the link 110 is free of jitter). On the other hand, if the comparison result indicates that the calculated average error AE is equal to or greater than the threshold value, it may be determined that the part of the road 110 is incorrect (e.g., the part of the road 110 has jitter). In the latter case, for example, a digital map including the portion of the road 110 may not be used and may need to be corrected or replaced.
Fig. 2 illustrates a flowchart of an exemplary method 200 for verifying a portion of a road in a digital map, according to an exemplary embodiment of the present disclosure. For example, the method 200 may be implemented within at least one processing circuit (e.g., the processor 404 of fig. 4), which may be located in an on-board computer system, a remote server, some other suitable device, or a combination of these devices. Of course, in various aspects within the scope of the present disclosure, process 200 may be implemented by any suitable device capable of supporting the relevant operations.
At block 210, a portion of a road may be loaded from a digital map. For example, the digital map may be stored in an in-vehicle system or a remote server. The portion of the road may be randomly selected from the digital map.
At block 220, a roadway centerline or lane line of the portion of roadway may be identified. In an example, the road centerline or lane line may already be stored in the digital map and thus may be directly loaded from the digital map with the portion of the road. As another example, the roadway centerline may be identified based on coordinates of roadway edges of the portion of roadway.
At block 230, a set of samples may be selected on a roadway centerline or lane line. In one example, the set of samples may be uniformly selected over the road centerline or lane line. For example, the interval between two adjacent samples is 1m. In another example, the set of samples may be selected non-uniformly over the roadway centerline or lane line.
At block 240, a spline curve may be determined based on the set of samples. For example, the spline curve may be a B-spline curve or a β -spline curve. In an example, the spline curve may be obtained from the set of sampled coordinates using computer software capable of generating the spline curve.
At block 250, an average error between the spline curve and the set of samples may be calculated. For example, equation (1) above may be used to calculate the average error.
At block 260, the average error obtained at block 250 may be compared to a threshold to determine if the portion of the road is correct. For example, the threshold may be any suitable value, preferably in the range between 5cm and 40cm, more preferably 20cm. In an example, if the average error is less than the threshold, it may be determined that the portion of the link is correct. However, if the average error is equal to or greater than the threshold value, it may be determined that the portion of the road is incorrect. In the latter case, the digital map may not be used and may need to be corrected or replaced.
Fig. 3 illustrates a block diagram of an exemplary apparatus 300 for verifying a portion of a road in a digital map, according to an exemplary embodiment of the present disclosure. All of the functional blocks of apparatus 300 (including the various elements in apparatus 300, whether or not shown in the figures) may be implemented in hardware, software, or a combination of hardware and software to perform the principles of the present invention. Those skilled in the art will appreciate that the functional blocks depicted in fig. 3 may be combined or divided into sub-blocks to implement the principles of the present invention as described above. Thus, the description herein may support any possible combination or division or further definition of the functional blocks described herein.
As shown in fig. 3, an apparatus 300 for verifying a portion of a road in a digital map according to an exemplary embodiment of the present disclosure may include: a loading unit 310, an identification unit 320, a selection unit 330 and a determination unit 340. The loading unit 310 may be configured to load a portion of the roads in the digital map. The identification unit 320 may be configured to identify a road center line or a lane line of the part of the road. The selection unit 330 may be configured to select a set of samples on the road centerline or lane line. The determination unit 340 may be configured to determine a spline curve based on the set of samples.
Furthermore, the apparatus 300 for verifying a portion of a road in a digital map may further include a calculation unit 350 and a verification unit 360. The calculation unit 350 may be configured to calculate an average error between the spline curve and the set of samples. The verification unit 350 may be configured to verify the part of the road by comparing the average error with a threshold value.
Fig. 4 illustrates a general hardware environment 400 in which the present disclosure may be applied, according to an exemplary embodiment of the present disclosure.
With reference to fig. 4, a computing device 400 will now be described, the computing device 400 being an example of a hardware device applicable to aspects of the present disclosure. Computing device 400 may be any machine configured to perform processes and/or calculations and may be, but is not limited to, a workstation, a server, a desktop computer, a laptop computer, a tablet computer, a personal digital assistant, a smart phone, an in-vehicle computer, or any combination thereof. The above-mentioned apparatus 300 may be implemented, in whole or at least in part, by a computing device 400 or similar device or system.
When the computing device 400 is used as an in-vehicle device, the computing device 400 may also be connected to external devices, such as a GPS receiver, sensors for sensing different environmental data (such as acceleration sensors, wheel speed sensors, gyroscopes), and so forth. In this way, computing device 400 may, for example, receive location data and sensor data indicative of a driving situation of the vehicle. When the computing device 400 is used as an in-vehicle device, the computing device 400 may also be connected to other facilities (such as an engine system, a wiper, an antilock brake system, etc.) for controlling the running and operation of the vehicle.
In addition, the non-transitory storage device 410 may have map information and software elements so that the processor 404 may perform route guidance processing. In addition, the output device 406 may include a display for displaying a map, a position marker of the vehicle, and an image indicating a driving situation of the vehicle. The output device 406 may also include a speaker or interface with headphones for audio guidance.
Software elements may reside in the working memory 414 including, but not limited to, an operating system 416, one or more application programs 418, drivers, and/or other data and code. The instructions for performing the above-described methods and steps may be included in one or more applications 418, and the units of the apparatus 300 mentioned above may be implemented by the processor 404 reading and executing the instructions of the one or more applications 418. More specifically, the loading unit 310 of the apparatus 300 mentioned above may be implemented, for example, by the processor 404 when executing an application 418 having instructions for executing the block 210. In addition, the identification unit 320 of the apparatus 300 mentioned above may be implemented, for example, by the processor 404 when executing the application 418 having instructions for executing the block 220. Other elements of the apparatus 300 mentioned above may also be implemented, for example, by the processor 404 when executing an application 418 having instructions for performing one or more of the corresponding steps mentioned above. Executable code or source code of instructions of the software elements may be stored in a non-transitory computer readable storage medium (such as storage device 410 described above) and may be read into working memory 414, possibly by compilation and/or installation. Executable code or source code for the instructions of the software elements may also be downloaded from a remote location.
From the above embodiments, it will be apparent to those skilled in the art that the present disclosure may be implemented by software having necessary hardware, or by hardware, firmware, or the like. Based on such understanding, embodiments of the present disclosure may be implemented in part in software. The computer software may be stored in a readable storage medium such as a floppy disk, hard disk, optical disk, or flash memory of a computer. The computer software includes a series of instructions to cause a computer (e.g., a personal computer, a service station, or a network terminal) to perform a method according to respective embodiments of the present disclosure, or a portion thereof.
Throughout this specification, reference has been made to "one example" or "an example" that means that a particular described feature, structure, or characteristic is included in at least one example. Thus, the use of such phrases may involve more than one example. Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more examples.
One skilled in the relevant art will recognize, however, that the examples may be practiced without one or more of the specific details, or with other methods, resources, materials, etc. In other instances, well-known structures, resources, or operations have not been shown or described in detail to avoid obscuring aspects of these examples.
While examples and applications have been illustrated and described, it should be understood that these examples are not limited to the precise configurations and resources described above. Various modifications, changes, and variations apparent to those skilled in the art may be made in the arrangement, operation, and details of the methods and systems disclosed herein without departing from the scope of the claimed examples.
Claims (13)
1. A method for verifying a portion of a road in a digital map, comprising:
loading a part of roads in the digital map;
identifying a road centerline or lane line of the portion of the road;
selecting a set of samples on the roadway centerline or the lane line;
determining a spline based on the set of samples;
calculating an average error AE between the spline curve and the set of samples; and
the portion of the road is verified by comparing the AE to a threshold, wherein the portion of the road is correct if the AE is less than the threshold, and wherein the portion of the road is incorrect if the AE is equal to or greater than the threshold.
2. The method of claim 1, wherein the set of samples is uniformly selected over the roadway centerline or the lane line.
3. The method of claim 1, wherein the spline curve comprises a B-spline curve or a β -spline curve.
4. The method according to claim 1, wherein the threshold value is in the range of 5cm to 40cm, and in particular 20cm.
5. The method of claim 1, wherein the AE is calculated using the formula:
wherein:
x i an x-coordinate representing an ith sample in the set of samples;
y i a y-coordinate representing an ith sample in the set of samples;
f(x i ) Representing the y-coordinate of a point on the spline curve, the x-coordinate of the point being the same as the x-coordinate of the ith sample in the set of samples; and
n represents the number of samples in the set of samples.
6. An apparatus for verifying a portion of a road in a digital map, comprising:
a loading unit configured to load a part of roads in the digital map;
an identification unit configured to identify a road center line or a lane line of the part of the road;
a selection unit configured to select a set of samples on the road centerline or lane line;
a determining unit configured to determine a spline curve based on the set of samples;
a calculation unit configured to calculate an average error AE between the spline curve and the set of samples; and
a verification unit configured to verify the part of the road by comparing the AE with a threshold value, wherein the part of the road is correct if the AE is smaller than the threshold value, and wherein the part of the road is incorrect if the AE is equal to or greater than the threshold value.
7. The apparatus of claim 6, wherein the set of samples is uniformly selected over the roadway centerline or the lane line.
8. The apparatus of claim 6, wherein the spline curve comprises a B-spline curve or a β -spline curve.
9. The apparatus according to claim 6, wherein the threshold value is in the range of 5cm to 40cm, and in particular 20cm.
10. The apparatus of claim 6, wherein the AE is calculated using the formula:
wherein:
x i an x-coordinate representing an ith sample in the set of samples;
y i a y-coordinate representing an ith sample in the set of samples;
f(x i ) Representing the y-coordinate of a point on the spline curve, the x-coordinate of the point being the same as the x-coordinate of the ith sample in the set of samples; and
n represents the number of samples in the set of samples.
11. An apparatus for verifying a portion of a road in a digital map, comprising:
a memory having computer-executable instructions stored therein; and
a processor coupled to the memory and configured to:
loading a part of roads in the digital map;
identifying a road centerline or lane line of the portion of the road;
selecting a set of samples on the roadway centerline or the lane line;
determining a spline based on the set of samples;
calculating an average error AE between the spline curve and the set of samples; and
the portion of the road is verified by comparing the AE to a threshold, wherein the portion of the road is correct if the AE is less than the threshold, and wherein the portion of the road is incorrect if the AE is equal to or greater than the threshold.
12. A non-transitory machine-readable storage medium having instructions stored thereon that, when executed, cause a processor to implement the method of any of claims 1-5.
13. A vehicle comprising the apparatus of any one of claims 6-11.
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CN112418035A (en) * | 2020-11-12 | 2021-02-26 | 武汉光庭信息技术股份有限公司 | Automatic evaluation method and system for medium-precision map data |
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