CN111527377A - Verification of digital maps - Google Patents
Verification of digital maps Download PDFInfo
- Publication number
- CN111527377A CN111527377A CN201780098047.8A CN201780098047A CN111527377A CN 111527377 A CN111527377 A CN 111527377A CN 201780098047 A CN201780098047 A CN 201780098047A CN 111527377 A CN111527377 A CN 111527377A
- Authority
- CN
- China
- Prior art keywords
- road
- samples
- spline curve
- threshold
- digital map
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Navigation (AREA)
- Traffic Control Systems (AREA)
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 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 High Automated Driving (HAD), and more particularly, to methods and apparatus for validating digital maps.
Background
Automotive driving has long been the subject of research efforts aimed at improving the safety and efficiency of automotive transportation. In recent years, increasingly complex sensors and automobiles have made autonomous driving systems more realistic. High definition digital maps are commonly used in autonomous driving systems. It typically contains rich road element information such as road shape geometry, road type and direction of turns, road connections, etc. Such information is critical to vehicle navigation, positioning, and decision making. Therefore, the correctness of high-definition digital maps becomes increasingly important.
Currently, in order to test the correctness of a high-definition digital map, some people perform tests by manual inspection, while others perform tests by loading the high-definition digital map on an automobile and driving around various areas on the high-definition digital map. The disadvantages of this testing procedure on high definition digital maps are evident. First, the testing process, either manual or by driving, takes a significant amount of time and money. Secondly, driving based on a wrong high-definition digital map is also very dangerous if the high-definition digital map does present serious problems.
Accordingly, it may be desirable to have an efficient, safe, and accurate testing process.
Disclosure of Invention
The present disclosure is directed to a method and apparatus for verifying a portion of a road in a digital map. Such methods and apparatus may enable efficient, safe, 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 including: loading a part of roads in the digital map; identifying a road centerline or lane line of the portion of 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 part of a road in a digital map, the apparatus including: 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 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 part of a road in a digital map, the apparatus including: a loading unit configured to load a part of roads in a digital map; an identification unit configured to identify a road center line or a lane line of the portion of road; a selection unit configured to select a set of samples on the road centerline or lane line; a determination 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 portion of the road by comparing the average error with a threshold, wherein the portion of the road is correct if the average error is less than the threshold, and wherein the portion of the road is incorrect if the average error is equal to or greater than the threshold.
According to a fourth exemplary embodiment of the present disclosure, a non-transitory machine-readable storage medium having instructions stored thereon is provided, which when executed cause a processor to implement a method for verifying a portion of a road in a digital map.
According to a fifth exemplary embodiment of the present disclosure, there is provided a vehicle including an apparatus 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.
Drawings
The foregoing and other aspects and advantages of the disclosure will become apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of the disclosure. Note that the drawings are not necessarily drawn to scale.
Fig. 1(a) - (C) illustrate an exemplary detailed example of verification of a portion of roads in a digital map according to an exemplary embodiment of the present disclosure.
Fig. 2 illustrates a flow diagram 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 example apparatus for verifying a portion of a road in a digital map, according to an example 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, and the like. 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 specified.
As mentioned above, the correctness of high-definition digital maps is critical for vehicle navigation, localization, 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 a road from the actual road shape geometry. For example, such jitter may be due to errors made in creating a high-definition digital map and should be avoided in order to provide an accurate high-definition digital map.
Fig. 1(a) - (C) illustrate an exemplary detailed example 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 road 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 in-vehicle autopilot system to facilitate autopilot. To test the correctness of the portion of roadway 110, a centerline 120 of the portion of 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 the coordinates of the road edges. In an alternative, lane lines in the portion of the roadway 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 block diagram having a set of sample points 130 on the centerline 1201、1302、……、130NA portion of the road 110. The set of sample points 1301、1302、……、130NEach of which has a coordinate (x)i，yi) (i-1.. N), where N represents the number of sampling points on the centerline 120 and may be any positive integer. In one example, the set of sample points 1301、1302、……、130NMay be selected evenly among the road center lines 120. For example, the distance between two adjacent sample points may be 1m, and for all sample points 1301、1302、……、130NMay be the same. In another example, the set of sample points 1301、1302、……、130NMay not be selected uniformly among the road center lines 120. For example, the first sampling point 1301And a second sampling point 1302May be spaced from the second sampling point 1302And a third sample point 1303The distance therebetween is different. In an alternative, instead of or in addition to the selected sample points on the road centerline 120, another set of sample 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. The spline 140 may be based on the sample points 130 selected on the centerline 1201、1302、……、130NTo be determined. As is well known in the field of mathematics, a spline curve f (x) is a smooth curve obtained by a given series of control points and can be used to approximately describe the functional relationship between the coordinates of the given series of control points. In the present invention, the spline curve f (x) may pass through the sample points 130 using known methods or known computer software (e.g., MATLAB, autosad, etc.)1、1302、……、130NIn one example, the spline curve may be a B-spline curve, alternatively, the spline curve may be an β spline curve.
After the spline curve 140 is determined, the spline curve 140 and the sample points 130 may be calculated1、1302、……、130NAverage error AE between. For example, the average error AE may be calculated according to the following equation:
wherein:
xirepresents the ith sample point 130iX coordinate of (a);
yirepresents the ith sample point 130iY-coordinate of (a);
f(xi) Represents the y coordinate of a point on the spline 120, the x coordinate of the point and the i-th sample point 130iThe x coordinates of (a) are the same; and
n represents the number of sample points on the centerline 120.
Alternatively, the average error AE may be calculated using any other known mean square method (e.g., a weighted average 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 20 cm. The comparison may be used to determine whether the portion of the road 110 is correct (e.g., whether the portion of the road 110 has jitter). If the comparison indicates that the calculated average error AE is less than the threshold, then the portion of the road 110 may be determined to be correct (e.g., the portion of the road 110 is not jittered). 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 portion of the road 110 is incorrect (e.g., the portion of the road 110 has jitter). In the latter case, for example, the digital map including the portion of road 110 may not be used and needs to be corrected or replaced.
Fig. 2 illustrates a flow diagram of an example method 200 for verifying a portion of a road in a digital map, according to an example 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 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 lane line or a center line of the portion of the 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 loaded directly from the digital map along with the portion of the road. As another example, a road centerline may be identified based on the coordinates of the road edges of the portion of the road.
At block 230, a set of samples may be selected on a road centerline or lane line. In an example, the set of samples may be selected uniformly on a road centerline or lane line. For example, the interval between two adjacent samples is 1 m. In another example, the set of samples may be selected non-uniformly on a road 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 whether the portion of the link is correct. For example, the threshold value may be any suitable value, preferably in the range between 5cm and 40cm, more preferably 20 cm. In one example, if the average error is less than the threshold, the portion of the road may be determined to be correct. However, if the average error is equal to or greater than the threshold, it may be determined that the portion of the road is incorrect. In the latter case, the digital map is not usable and needs to be corrected or replaced.
Fig. 3 illustrates a block diagram of an example apparatus 300 for validating a portion of roads in a digital map, according to an example embodiment of the present disclosure. All of the functional blocks of the apparatus 300 (including the various elements of the apparatus 300 whether shown in the figures or not) may be implemented in hardware, software, or a combination of hardware and software to carry out the principles of the 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 a road in a digital map. The identification unit 320 may be configured to identify a road center line or lane line of the portion of 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 roads 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 portion of the road by comparing the average error to a threshold.
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.
Referring to fig. 4, a computing device 400 will now be described, 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 processing and/or computing, 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 on-board 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, the computing device 400 may, for example, receive location data and sensor data indicative of a driving condition 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 for controlling the travel and operation of the vehicle (such as an engine system, wipers, a brake anti-lock system, etc.).
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 location marker of the vehicle, and an image indicating the driving condition of the vehicle. Output device 406 may also include a speaker or interface with headphones for audio guidance.
The bus 402 may include, but is not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an enhanced ISA (eisa) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus. Specifically, for an in-vehicle device, bus 402 may include a Controller Area Network (CAN) bus or other architecture designed for use in applications on an automobile.
Software elements may be located in 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. Instructions for performing the above-described methods and steps may be included in one or more applications 418, and the above-mentioned elements of apparatus 300 may be implemented by processor 404 reading and executing the instructions of one or more applications 418. More specifically, the above-mentioned loading unit 310 of the apparatus 300 may be implemented, for example, by the processor 404 when executing the application 418 with instructions for executing block 210. Additionally, the above-mentioned identification unit 320 of the apparatus 300 may be implemented, for example, by the processor 404 when executing the application 418 with instructions for performing block 220. The other units of the apparatus 300 mentioned above may also be implemented, for example, by the processor 404 when executing the application 418 with instructions for performing one or more of the respective steps mentioned above. Executable code or source code for the 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 is apparent to those skilled in the art that the present disclosure can be implemented by software having necessary hardware, or by hardware, firmware, and the like. Based on such understanding, embodiments of the present disclosure may be implemented partially 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 the 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 or a portion thereof according to a respective embodiment of the present disclosure.
Throughout the specification, reference has been made to "one example" or "an example" meaning that a particular described feature, structure or characteristic is included in at least one example. Thus, use of such phrases may refer to 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 can be practiced without one or more of the specific details, or with other methods, resources, materials, and so forth. In other instances, well-known structures, resources, or operations are not shown or described in detail to avoid obscuring aspects of the examples.
While examples and applications have been illustrated and described, it is to be understood that these examples are not limited to the precise configuration 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 road;
selecting a set of samples on the road centerline or the lane line;
determining a spline curve based on the set of samples;
calculating an average error AE between the spline curve and the set of samples; and
verifying the portion of the road 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 are selected uniformly on the road centerline or the lane line.
3. The method of any of claims 1-2, wherein the spline curve comprises a B-spline curve or a beta-spline curve.
4. The method according to any of claims 1-3, wherein the threshold value is in the range of 5cm to 40cm, and in particular 20 cm.
5. The method of any one of claims 1-4, wherein the AE is calculated using the following formula:
wherein:
xian x-coordinate representing an ith sample of the set of samples;
yia y-coordinate representing an ith sample of the set of samples;
f(xi) Representing a 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 a digital map;
an identification unit configured to identify a road center line or a lane line of the portion of road;
a selection unit configured to select a set of samples on the road centerline or lane line;
a determination 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 portion of the road 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.
7. The apparatus of claim 6, wherein the set of samples are selected uniformly on the road centerline or the lane line.
8. The apparatus of any of claims 6-7, wherein the spline curve comprises a B-spline curve or a beta-spline curve.
9. The device according to any of claims 6-8, wherein the threshold value is in the range of 5cm to 40cm, and in particular 20 cm.
10. The apparatus of any one of claims 6-9, wherein the AE is calculated using the following equation:
wherein:
xian x-coordinate representing an ith sample of the set of samples;
yia y-coordinate representing an ith sample of the set of samples;
f(xi) Representing a 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 road;
selecting a set of samples on the road centerline or the lane line;
determining a spline curve based on the set of samples;
calculating an average error AE between the spline curve and the set of samples; and
verifying the portion of the road 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 an apparatus according to any one of claims 6-11.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2017/118887 WO2019127074A1 (en) | 2017-12-27 | 2017-12-27 | Validation for a digital map |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111527377A true CN111527377A (en) | 2020-08-11 |
| CN111527377B CN111527377B (en) | 2023-06-13 |
Family
ID=67062787
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201780098047.8A Active CN111527377B (en) | 2017-12-27 | 2017-12-27 | Verification of digital maps |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN111527377B (en) |
| WO (1) | WO2019127074A1 (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11238607B2 (en) | 2020-03-31 | 2022-02-01 | Denso International America, Inc. | System and method for measuring the accuracy of an electronic map or a localization of a vehicle |
| 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 |
| CN112762947B (en) * | 2020-12-28 | 2024-04-05 | 上海汽车集团股份有限公司 | Map data calibration method and device and computer equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101017089A (en) * | 2006-02-07 | 2007-08-15 | 环达电脑(上海)有限公司 | System for fast renewing electronic map and method therefor |
| CN101290725A (en) * | 2007-04-17 | 2008-10-22 | 株式会社日立制作所 | Digital road map generation system and map generation method |
| US20140244153A1 (en) * | 2013-02-28 | 2014-08-28 | Navteq B.V. | Method and apparatus for processing location-based imaging and trace data |
| KR20170114408A (en) * | 2016-04-04 | 2017-10-16 | 경희대학교 산학협력단 | System and method for probiding roadway type information using road characteristic information |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103954275B (en) * | 2014-04-01 | 2017-02-08 | 西安交通大学 | Lane line detection and GIS map information development-based vision navigation method |
| DE102016203723A1 (en) * | 2016-03-08 | 2017-09-14 | Robert Bosch Gmbh | Method and system for determining the pose of a vehicle |
| CN106525057A (en) * | 2016-10-26 | 2017-03-22 | 陈曦 | Generation system for high-precision road map |
-
2017
- 2017-12-27 WO PCT/CN2017/118887 patent/WO2019127074A1/en active Application Filing
- 2017-12-27 CN CN201780098047.8A patent/CN111527377B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101017089A (en) * | 2006-02-07 | 2007-08-15 | 环达电脑(上海)有限公司 | System for fast renewing electronic map and method therefor |
| CN101290725A (en) * | 2007-04-17 | 2008-10-22 | 株式会社日立制作所 | Digital road map generation system and map generation method |
| US20140244153A1 (en) * | 2013-02-28 | 2014-08-28 | Navteq B.V. | Method and apparatus for processing location-based imaging and trace data |
| KR20170114408A (en) * | 2016-04-04 | 2017-10-16 | 경희대학교 산학협력단 | System and method for probiding roadway type information using road characteristic information |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111527377B (en) | 2023-06-13 |
| WO2019127074A1 (en) | 2019-07-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108922173B (en) | Vehicle deviation detection method and device | |
| CN107328410B (en) | Method for locating an autonomous vehicle and vehicle computer | |
| CN111819419B (en) | Distortion correction for digital map of vehicle | |
| CN106842269A (en) | Localization method and system | |
| US9619945B2 (en) | Recommending an alternative route to a service location to service a vehicle issue that was detected by a change in status in a sensor of the automobile's diagnostic system | |
| CN111527377B (en) | Verification of digital maps | |
| WO2016086792A1 (en) | Driving behavior analysis method and device | |
| CN108413972A (en) | Method for verifying the electronic map for being used for vehicle | |
| CN110288154A (en) | Speed predicting method, device, equipment and medium | |
| US20170030717A1 (en) | Estimating apparatus, travel direction estimating method, and non-transitory computer readable storage medium | |
| CN111856521A (en) | Data processing method and device, electronic equipment and storage medium | |
| EP3109592A1 (en) | Method and apparatus for determining road stacking based upon error statistics | |
| EP3425339A1 (en) | Position estimating device, position estimating method and program | |
| US9733092B2 (en) | Vehicle position detection device and program | |
| KR20200046868A (en) | Apparatus for notice parking lot of vehicle, system having the same and method thereof | |
| CN115372020A (en) | Automatic driving vehicle test method, device, electronic equipment and medium | |
| CN109631925B (en) | Main and auxiliary road determining method and device, storage medium and electronic equipment | |
| CN111596288B (en) | Method and device for measuring speed, vehicle-mounted terminal and vehicle-mounted speed measuring system | |
| CN111326006B (en) | Reminding method, reminding system, storage medium and vehicle-mounted terminal for lane navigation | |
| CN106485917B (en) | A kind of method and apparatus for adjudicating vehicle to change lane | |
| WO2014129501A1 (en) | Passage detection system, passage detection method, passage detection device, program, and recording medium | |
| JP6347207B2 (en) | Navigation device, navigation method, and navigation program | |
| CN111354207A (en) | Display method, display system, storage medium and vehicle-mounted terminal for front road condition | |
| US20220035050A1 (en) | Server, non-transitory computer readable medium, communication apparatus, and vehicle | |
| JP6054808B2 (en) | Parallel road judgment device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |