CN108088448A - The matching process and device of a kind of high-precision track group and traditional road - Google Patents
The matching process and device of a kind of high-precision track group and traditional road Download PDFInfo
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- CN108088448A CN108088448A CN201711163391.9A CN201711163391A CN108088448A CN 108088448 A CN108088448 A CN 108088448A CN 201711163391 A CN201711163391 A CN 201711163391A CN 108088448 A CN108088448 A CN 108088448A
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- track group
- traditional road
- road
- connecting line
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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
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- 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
- G01C21/30—Map- or contour-matching
- G01C21/32—Structuring or formatting of map data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Abstract
The present invention relates to a kind of high-precision track group and the matching process and device of traditional road, method comprises the following steps:Obtain the vector quantization data of a plurality of traditional road in the vector quantization data of a plurality of track group connecting line and conventional navigation map in high-precision map;The a plurality of track group connecting line is intersected into computing with a plurality of traditional road work successively, establishes the corresponding traditional road set intersected with it of track group connecting line described in each item;The traditional road set is filtered, obtains group connecting line matched traditional road in track described in each;According to track group connecting line and the matching relationship of traditional road, the matching relationship of high-precision track group and traditional road is established.Complicated mathematical computations dimension can be reduced to plane level by the present invention in the range of trueness error, using the relation of simple line segment and line segment, calculate the matching relationship of high-precision track group and traditional road.Algorithm is implemented simple and practicable, it is readily appreciated that.
Description
Technical field
The present invention relates to digital map navigation and technical field of data processing, and in particular to a kind of height in high-precision map
Precision track group and the matching process and device of the traditional road in traditional map.
Background technology
With the progressively application towards active safety and unpiloted next-generation high-precision navigation map, map datum from
The navigation on basis, guiding function progressively move towards the Premium Features of Body Control and active safety, the Route guiding work(of track rank
The advanced automatic Pilot of vehicle can be fully applicable to, active safety and unpiloted primary demand are met with this.
In high-precision map manufacturing process, the point (such as laser point cloud data) gathered from real road can be sweared
Quantification treatment finally constitutes the digital map data for sailing out of.Track rank data bulk after vector quantization is carried out is very huge
Greatly, it is unfavorable for quickly carrying out topological calculating, how efficiently obtains the problem of route guidance information of track rank is one important.
At this stage, solution has associated traditional data with track level data predominantly when making High-precision vehicle track data by hand
Come, using mature road computing technique, further calculate the guidance information of track rank.This method needs manual association
The map datum of two kinds of acquisition specifications, cannot meet the processing of mass data in producing efficiency and accuracy.
Related terms are explained:
1. high-precision track group
For completely describing to be located at a road section, the set in the track with identical travel direction.As shown in Figure 2.
2. High-precision vehicle road shape coordinate points
For completely describing the set put necessary to a track, each point must have X, Y-coordinate.X, Y-coordinate can
To be the X of the latitude and longitude coordinates under sphere centre coordinate system or the rectangular coordinate system under projected coordinate system, Y-coordinate.Such as Fig. 6
It is shown.
3. high-precision track node shape coordinate point
For completely describing a point of two or more high-precision track connection relation, this point must have
X, Y-coordinate.X, Y-coordinate can be the latitude and longitude coordinates under sphere centre coordinate system or the rectangular co-ordinate under projected coordinate system
The X of system, Y-coordinate.As shown in Figure 2.
4. high-precision track group connecting line shape coordinate point
For completely describing the set put necessary to the connection relation of two groups or more high-precision track group, each
Point must have X, Y-coordinate.X, Y-coordinate can be under the latitude and longitude coordinates under sphere centre coordinate system or projected coordinate system
Rectangular coordinate system X, Y-coordinate.As shown in Fig. 3,6.
5. the adjacent track group of high-precision
For completely describing the high-precision track group in the left side of one group of high-precision track group or right side.As shown in Figure 4.
6. road shape coordinate points
For completely describing the set put necessary to a road, each point must have X, Y-coordinate.X, Y-coordinate can
To be the X of the latitude and longitude coordinates under sphere centre coordinate system or the rectangular coordinate system under projected coordinate system, Y-coordinate.Such as Fig. 7
It is shown.
7. circuit node shape coordinate point
For completely describe two or two or more road connection relation a point, this point must have X, Y
Coordinate.X, Y-coordinate can be the latitude and longitude coordinates under sphere centre coordinate system or the rectangular coordinate system under projected coordinate system
X, Y-coordinate.As shown in Figure 5.
8. vector quantization data
By from the road of acquired original, track shape coordinate point, carrying out manually (or automatic) identification, extraction can keep
Road, the coordinate points of track shape have front and rear logical relation between each coordinate points.It is just achieved after the completion of road digitalization
Road, the vector quantization data in track.
The content of the invention
The present invention is directed to technical problem in the prior art, provides of a kind of high-precision track group and traditional road
Method of completing the square and device in acceptable accuracy requirement, space requirement, time range of needs, effectively calculate High-precision vehicle
The matching relationship of road group and traditional road.
The technical solution that the present invention solves above-mentioned technical problem is as follows:
One aspect of the present invention provides the matching process of a kind of high-precision track group and traditional road, it is characterised in that:Including
Following steps:
Step 1, obtain more in the vector quantization data of a plurality of track group connecting line and conventional navigation map in high-precision map
The vector quantization data of traditional road;
Step 2, a plurality of track group connecting line is intersected into computing with a plurality of traditional road work successively, establishes each item
The corresponding traditional road set intersected with it of the track group connecting line;
Step 3, the traditional road set is filtered, obtains group connecting line matched tradition in track described in each
Road;
Step 4, the track group connecting line and the matching relationship of traditional road obtained according to step 3, establishes high-precision track
Group and the matching relationship of traditional road.
Further, it is more in the vector quantization data of a plurality of track group connecting line and conventional navigation map in the high-precision map
The vector quantization data of traditional road include describing the coordinate point data of the track group connection wire shaped and for describing
The coordinate point data of the traditional road shape.
Further, the coordinate points data include sphere centre coordinate or projection coordinate.
Further, in the step 2, a plurality of track group connecting line is intersected with a plurality of traditional road work successively
Computing is established the corresponding traditional road set intersected with it of track group connecting line described in each item, is comprised the following steps:
Step 201, by road direction of advance, a track group connecting line C for not carrying out intersecting computing is taken successivelyp, obtain
Two extreme coordinates and line of the track group connecting line, obtain line segment
Step 202, a traditional road R for not carrying out intersecting computing is takenq, it is used to describe traditional road shape according to described
Coordinate points, obtain traditional road RqCoordinate point set:Rq={ P1,P2,...,Pn}q, and according to the coordinate point set,
It connects two adjacent coordinate points and forms line segment, obtain and traditional road RqCorresponding line segment aggregate:{L1,L2,...,Ln-1,
In,
Li={ Pi,Pi+1}i∈[1,n-1];
Step 203, line segment is judgedWhether with line segment aggregate { L1,L2,...,Ln-1Any one line segment intersection, if phase
Friendship then records CpIntersect at Rq;
Step 204, judge whether also exist not with line segmentThe traditional road of intersecting computing is carried out, if being jumped in the presence of if
Step 202, step 205 is otherwise performed;
Step 205, judge whether also there is the track group connecting line for not carrying out intersecting computing, if in the presence of jumping to step
Rapid 201, otherwise terminate intersecting computing, obtain the corresponding traditional road set intersected with it of each track group connecting line.
Further, in the step 3, the traditional road set is filtered, track group described in each is obtained and connects
The matched traditional road of wiring, comprises the following steps:
Step 301, for the corresponding traditional road set intersected with it of every track group connecting line, if element in set
Quantity is more than 1, then travels through the road attribute of all traditional roads in set, retains one and road category where the group connecting line of track
Property consistent traditional road, delete the other elements in set;
Step 302, repeat step 301, obtain all track group connecting lines and with its one-to-one traditional road
Road.
Further, in the step 4, the track group connecting line and the matching relationship of traditional road that are obtained according to step 3 are built
The matching relationship of vertical high-precision track group and traditional road, including:
The head end track group connecting line of each high-precision track group and tail end track group in high-precision map is obtained successively to connect
Wiring, according to head end track group connecting line and the corresponding traditional road of tail end track group connecting line, establish high-precision track group with
The matching relationship of traditional road.
The beneficial effects of the invention are as follows:In the range of trueness error, complicated mathematical computations dimension can be reduced to flat
Face grade using the relation of simple line segment and line segment, calculates the matching relationship of high-precision track group and traditional road.Algorithm is real
It applies simple and practicable, it is readily appreciated that.
Another aspect of the present invention provides the coalignment of a kind of high-precision track group and traditional road, including:
Data acquisition module, for obtaining the vector quantization data and conventional pilot of a plurality of track group connecting line in high-precision map
The vector quantization data of a plurality of traditional road in boat map;
Gather generation module, for successively mutually shipping a plurality of track group connecting line with a plurality of traditional road
It calculates, establishes the corresponding traditional road set intersected with it of track group connecting line described in each item;
Matching relationship filtering module for being filtered to the traditional road set, obtains track group described in each
The matched traditional road of connecting line;
Matching relationship generation module for the matching relationship according to track group connecting line and traditional road, establishes high-precision
The matching relationship of track group and traditional road.
Further, it is more in the vector quantization data of a plurality of track group connecting line and conventional navigation map in the high-precision map
The vector quantization data of traditional road include describing the coordinate point data of the track group connection wire shaped and for describing
The coordinate point data of the traditional road shape.
Further, the coordinate points data include sphere centre coordinate or projection coordinate.
The beneficial effects of the invention are as follows:In the range of trueness error, complicated mathematical computations dimension can be reduced to flat
Face grade using the relation of simple line segment and line segment, calculates the matching relationship of high-precision track group and traditional road.Algorithm is real
It applies simple and practicable, it is readily appreciated that.
Description of the drawings
The process flow of the matching process of a kind of Fig. 1 high-precision track groups provided in an embodiment of the present invention and traditional road
Figure;
Fig. 2 high-precisions track group, track shape, the definition graph of track node;
The definition graph of Fig. 3 high-precisions track group connecting line;
The definition graph of the adjacent track group of Fig. 4 high-precisions;
The definition graph of Fig. 5 roads circuit node;
The definition graph of the phasor coordinate point set in Fig. 6 tracks group connecting line and track;
The definition graph of the phasor coordinate point set of Fig. 7 roads;
The definition graph of the method for the representative line segment of Fig. 8 construction track group connecting lines;
The definition graph of the method for Fig. 9 construction road line segment aggregates;
Figure 10 filters the definition graph for not meeting match information;
Figure 11 establishes the definition graph of high-precision track group and the match information of road;
Figure 12 establishes the definition graph of adjacent track group and the match information of road;
The coalignment structure diagram of a kind of Figure 13 high-precision track groups provided in an embodiment of the present invention and traditional road.
Specific embodiment
The principle of the present invention and feature are described below in conjunction with example, the given examples are served only to explain the present invention, and
It is non-to be used to limit the scope of the present invention.
As shown in Figure 1, on the one hand the embodiment of the present invention provides the matching process of a kind of high-precision track group and traditional road,
Its specific embodiment, comprises the following steps:
1. high-precision track group connecting line data are read in:Read in the vector after the group connecting line digitized processing of high-precision track
Change data.
After reading in data, therefore, to assure that vector quantization data are ordered into.Context and real generation i.e. between coordinate points
Boundary is consistent.The collection of note high-precision track group connecting line vector quantization coordinate points is combined into { P1,P2,P3...Pn, as shown in Figure 6;
Traditional road data are read in:Read in road digitalization treated vector quantization data.
After reading in data, therefore, to assure that vector quantization data are ordered into.Context and real generation i.e. between coordinate points
Boundary is consistent.The collection of note traditional road vector quantization coordinate points is combined into { P1',P2',P3'...Pn', as shown in Figure 7;
2. high-precision track group connecting line intersects computing with traditional road.
2.1) high-precision track group connecting line C is obtained1First shape coordinate point P1With the last one shape coordinate point
Pn, remember by point P1With point PnThe line segment of composition is L, as shown in Figure 8.
2.2) traditional road R is obtainedaShape coordinate point, it is assumed that the collection of road vectors coordinate points is combined into { P1',P2',
P3'...Pn', line segment then is formed with adjacent two coordinate points, obtains line segment L1{P1',P2', line segment L2{P2',P3' ... line segment
Ln-1{Pn-1',Pn', as shown in Figure 9.
2.3) ask line segment L whether with line segment aggregate { L1,L2,L3...Ln-1Any one section of intersecting, record C1Intersect at Ra。
2.4) step 2.2, step 2.3 are repeated, finds all traditional road line segments intersected with line segment L.Record C1It is intersecting
In road set { Ra,Rb,Rc...}。
2.5) repeat the above steps, calculate all high-precision track group connecting lines and traditional road intersects information.Note
Record C1Intersect at road set { Ra,Rb,Rc...}、C2Intersect at road set { Rd,Re...}、…、CnIntersect at road set
{Rx,Ry...}。
3. establish high-precision track group connecting line and traditional road overlapping relation.
3.1) information that obtaining step 2 records, such as:C1Intersect at road set { Ra,Rb,Rc...}.If collective number
Have overhead section above road more than 1, where illustrating high-precision track group connecting line or lower section have tunnel road etc. other
Some cases, it is necessary to according to track group connect line attribute and road attribute filter incongruent section (such as:Road number, road
Road grade, link name, track quantity, road type etc.), it only leaves a road and is connected lines matching with the high-precision track group.
Such as:Record C1Intersect at road Ra, as shown in Figure 10.
3.2) step 3.1 is repeated, calculates the matching relationship of all high-precision track group connecting lines and traditional road.Such as:
Record C1Intersect at road Ra、C2Intersect at road Rd、…、CnIntersect at road Ry。
4. establish high-precision track group and traditional road matching relationship.
4.1) the head end connecting line A of high-precision track group A is obtained1And tail end connecting line A2B1, it is obtained according to step 3
Set of records ends finds track group connecting line A respectively1、A2B1Intersecting road as shown in figure 11, is recorded as road set { R1,
R1}.Establish high-precision track group A and road R1Matching relationship.Road set is also likely to be a plurality of different road, is such as schemed
Shown in 11, track group B and road R1、R2、R3Establish matching relationship.
4.2) step 4.1 is repeated, travels through all high-precision track groups, calculates all high-precision tracks group and road
Matching relationship.
4.3) if there is there is high-precision track group that cannot match with any road, attempt to find its adjoining track group
The matched road of institute.Such case is present in offline unseparated situation on traditional road, and as shown in figure 12, track group B can be just
It cannot can often be believed with road R matchings, track group A with any path adaptation by the matching of the adjoining track group B of track group A
Breath establishes the matching relationship of track group A and road R.
On the other hand the embodiment of the present invention provides the coalignment of a kind of high-precision track group and traditional road, such as Figure 13 institutes
Show, including:
Data acquisition module, for obtaining the vector quantization data of a plurality of track group connecting line and a plurality of biography in high-precision map
The vector quantization data of system road;
Gather generation module, for successively mutually shipping a plurality of track group connecting line with a plurality of traditional road
It calculates, establishes the corresponding traditional road set intersected with it of track group connecting line described in each item;
Matching relationship filtering module for being filtered to the traditional road set, obtains track group described in each
The matched traditional road of connecting line;
Matching relationship generation module for the matching relationship according to track group connecting line and traditional road, establishes high-precision
The matching relationship of track group and traditional road.
A plurality of tradition in the vector quantization data of a plurality of track group connecting line and conventional navigation map in the high-precision map
The vector quantization data of road include describing the coordinate point data of the track group connection wire shaped and for describing the biography
The coordinate point data of system road shape.
The coordinate points data include sphere centre coordinate or projection coordinate.
Complicated mathematical computations dimension can be reduced to plane level by the present invention in the range of trueness error, using simple
Line segment and line segment relation, calculate the matching relationship of high-precision track group and traditional road.Algorithm implements simple and practicable, appearance
It is readily understood.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all the present invention spirit and
Within principle, any modifications, equivalent replacements and improvements are made should all be included in the protection scope of the present invention.
Claims (10)
1. the matching process of a kind of high-precision track group and traditional road, it is characterised in that:Comprise the following steps:
Step 1, a plurality of biography in the vector quantization data of a plurality of track group connecting line and conventional navigation map is obtained in high-precision map
The vector quantization data of system road;
Step 2, a plurality of track group connecting line is intersected into computing with a plurality of traditional road work successively, established described in each item
The corresponding traditional road set intersected with it of track group connecting line;
Step 3, the traditional road set is filtered, obtains the matched traditional road of track group connecting line described in each
Road;
Step 4, the track group connecting line and the matching relationship of traditional road obtained according to step 3, establish high-precision track group with
The matching relationship of traditional road.
2. the matching process of a kind of high-precision track group and traditional road according to claim 1, it is characterised in that:The height
In precision map in the vector quantization data of a plurality of track group connecting line and conventional navigation map a plurality of traditional road vector quantization number
According to the seat including the coordinate point data for being used to describe the track group connection wire shaped and for describing the traditional road shape
Punctuate data.
3. the matching process of a kind of high-precision track group and traditional road according to claim 2, it is characterised in that:The seat
Punctuate data include sphere centre coordinate or projection coordinate.
4. the matching process of a kind of high-precision track group and traditional road according to Claims 2 or 3, it is characterised in that:Institute
It states in step 2, a plurality of track group connecting line is intersected into computing with a plurality of traditional road work successively, is established described in each item
The corresponding traditional road set intersected with it of track group connecting line, comprises the following steps:
Step 201, by road direction of advance, a track group connecting line C for not carrying out intersecting computing is taken successivelyp, obtain the track
Two extreme coordinates and line of group connecting line, obtain line segment
Step 202, a traditional road R for not carrying out intersecting computing is takenq, according to the seat for being used to describe traditional road shape
Punctuate obtains traditional road RqCoordinate point set:Rq={ P1,P2,...,Pn}q, and according to the coordinate point set, connection
Two adjacent coordinate points form line segment, obtain and traditional road RqCorresponding line segment aggregate:{L1,L2,...,Ln-1, wherein,
Li={ Pi,Pi+1} i∈[1,n-1];
Step 203, line segment is judgedWhether with line segment aggregate { L1,L2,...,Ln-1Any one line segment intersection, if intersecting
Record CpIntersect at Rq;
Step 204, judge whether also exist not with line segmentThe traditional road of intersecting computing is carried out, if jumping to step in the presence of if
202, otherwise perform step 205;
Step 205, judge whether also there is the track group connecting line for not carrying out intersecting computing, if in the presence of jumping to step
201, otherwise terminate intersecting computing, obtain the corresponding traditional road set intersected with it of each track group connecting line.
5. the matching process of a kind of high-precision track group and traditional road according to claim 4, it is characterised in that:The step
In rapid 3, the traditional road set is filtered, obtains the matched traditional road of track group connecting line described in each
Road comprises the following steps:
Step 301, for the corresponding traditional road set intersected with it of every track group connecting line, if number of elements in set
More than 1, then the road attribute of all traditional roads in set is traveled through, retain one and road attribute one where the group connecting line of track
The traditional road of cause deletes the other elements in set;
Step 302, repeat step 301, obtain all track group connecting lines and with its one-to-one traditional road.
6. the matching process of a kind of high-precision track group and traditional road according to claim 5, it is characterised in that:The road
Road attribute includes the one or more in road number, category of roads, link name, track quantity, road type.
7. according to a kind of high-precision track group of claim 5 or 6 and the matching process of traditional road, it is characterised in that:Institute
State in step 4, the track group connecting line and the matching relationship of traditional road obtained according to step 3, establish high-precision track group with
The matching relationship of traditional road, including:
The head end track group connecting line of each high-precision track group and tail end track group connecting line in high-precision map are obtained successively,
According to head end track group connecting line and the corresponding traditional road of tail end track group connecting line, high-precision track group and traditional road are established
The matching relationship on road.
8. the coalignment of a kind of high-precision track group and traditional road, it is characterised in that:Including
Data acquisition module, for obtaining in high-precision map the vector quantization data of a plurality of track group connecting line and conventional navigation
The vector quantization data of a plurality of traditional road in figure;
Gather generation module, for a plurality of track group connecting line to be intersected computing with a plurality of traditional road work successively,
Establish the corresponding traditional road set intersected with it of track group connecting line described in each item;
Matching relationship filtering module for being filtered to the traditional road set, obtains group connection in track described in each
The traditional road of lines matching;
Matching relationship generation module for the matching relationship according to track group connecting line and traditional road, establishes high-precision track
Group and the matching relationship of traditional road.
9. the coalignment of a kind of high-precision track group and traditional road according to claim 7, it is characterised in that:The height
In precision map in the vector quantization data of a plurality of track group connecting line and conventional navigation map a plurality of traditional road vector quantization number
According to the seat including the coordinate point data for being used to describe the track group connection wire shaped and for describing the traditional road shape
Punctuate data.
10. the matching process of a kind of high-precision track group and traditional road according to claim 8, it is characterised in that:It is described
Coordinate points data include sphere centre coordinate or projection coordinate.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH11272165A (en) * | 1998-03-19 | 1999-10-08 | Buyodo Seisanbu:Kk | Method for eliminating discontinuity of plural map sheets and plural continued map sheets |
US5991427A (en) * | 1996-07-31 | 1999-11-23 | Aisin Seiki Kabushiki Kaisha | Method and apparatus for detecting a lane on a road |
CN102102992A (en) * | 2009-12-22 | 2011-06-22 | 山东省计算中心 | Multistage network division-based preliminary screening method for matched roads and map matching system |
CN105043403A (en) * | 2015-08-13 | 2015-11-11 | 武汉光庭信息技术有限公司 | High precision map path planning system and method |
CN106203278A (en) * | 2016-06-28 | 2016-12-07 | 中国人民解放军信息工程大学 | A kind of extract the method and device of two-track road on map |
CN106886604A (en) * | 2017-03-03 | 2017-06-23 | 东南大学 | A kind of intersection road net model suitable for track level navigator fix |
-
2017
- 2017-11-21 CN CN201711163391.9A patent/CN108088448B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5991427A (en) * | 1996-07-31 | 1999-11-23 | Aisin Seiki Kabushiki Kaisha | Method and apparatus for detecting a lane on a road |
JPH11272165A (en) * | 1998-03-19 | 1999-10-08 | Buyodo Seisanbu:Kk | Method for eliminating discontinuity of plural map sheets and plural continued map sheets |
CN102102992A (en) * | 2009-12-22 | 2011-06-22 | 山东省计算中心 | Multistage network division-based preliminary screening method for matched roads and map matching system |
CN105043403A (en) * | 2015-08-13 | 2015-11-11 | 武汉光庭信息技术有限公司 | High precision map path planning system and method |
CN106203278A (en) * | 2016-06-28 | 2016-12-07 | 中国人民解放军信息工程大学 | A kind of extract the method and device of two-track road on map |
CN106886604A (en) * | 2017-03-03 | 2017-06-23 | 东南大学 | A kind of intersection road net model suitable for track level navigator fix |
Cited By (36)
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Denomination of invention: A matching method and device between high-precision Lane Group and traditional road Effective date of registration: 20210909 Granted publication date: 20200421 Pledgee: Wuhan Jiangxia sub branch of Bank of Communications Co., Ltd Pledgor: WUHHAN KOTEL BIG DATE Corp. Registration number: Y2021980009115 |