CN101922939B - Map matching method and device in navigation process - Google Patents
Map matching method and device in navigation process Download PDFInfo
- Publication number
- CN101922939B CN101922939B CN 200910086941 CN200910086941A CN101922939B CN 101922939 B CN101922939 B CN 101922939B CN 200910086941 CN200910086941 CN 200910086941 CN 200910086941 A CN200910086941 A CN 200910086941A CN 101922939 B CN101922939 B CN 101922939B
- Authority
- CN
- China
- Prior art keywords
- point
- road
- vehicle operating
- length
- curve
- 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.)
- Active
Links
Images
Abstract
The embodiment of the invention provides a map matching method and a device in a navigation process, solving the problem that the image position of a vehicle does not conform to the actual position on a map in a navigation system. The method is implemented as the following steps: obtaining vehicle running track points; determining a matching path based on the running track points and a road curvein the map; and matching the running track points to the matching path. Based on the embodiment of the invention, vehicle images can be matched to the proceeding road curve thereof accurately, thereby facilitating navigation, enhancing user satisfaction and improving product quality.
Description
Technical field
The present invention relates to a kind of airmanship, relate in particular to map-matching method and device in a kind of navigation procedure.
Background technology
In GPS (Global Position System, GPS), map match is one of gordian technique in the onboard navigation system.Described map match refers to, replaces the track of vehicle point with the intersection point point on the Road of map, in other words conj.or perhaps the tracing point of vehicle is remedied on the intersection point of its corresponding Road.Yet the location of existing GPS is directly to be placed on the relevant position of map with the image of the locating information that receives with vehicle.Like this, because the error of GPS receive data usually can cause the image of vehicle not on the relevant position of map, even jump phenomena occur.Fig. 1 illustrates the situation of prior art vehicle and road, and wherein, dotted line represents the automobile trajectory, and it is with the observation station of positioning error, and solid line a → b → c represents the trajectory of automobile actual motion.
In sum, existing airmanship has caused the picture position of vehicle in navigational system not conform to physical location on the map, thereby has had a strong impact on navigation effect.
Summary of the invention
Embodiments of the invention provide map-matching method and the device in a kind of navigation procedure, can solve the problem that the picture position of vehicle in navigational system and physical location on the map do not conform to.
Embodiments of the invention provide the map-matching method in a kind of navigation procedure, comprising:
Obtain the vehicle operating tracing point;
Determine the road of coupling according to described running orbit point and Roads in Maps curve;
Described running orbit point is matched on the road of described coupling.
Embodiments of the invention also provide the map matching means in a kind of navigation procedure, comprising:
Obtain the unit, be used for obtaining the vehicle operating tracing point;
Determining unit is used for according to the road of described running orbit point with the definite coupling of Roads in Maps curve;
Matching unit matches described running orbit point on the road of described coupling.
According to the embodiment of the invention, the image of vehicle is correctly matched on its road curve of advancing, thereby made things convenient for navigation, increased user's satisfaction, promoted the quality of product.
Description of drawings
Fig. 1 shows in the prior art situation of vehicle image and road in the guider;
Fig. 2 shows track of vehicle and six road curves to be matched;
Fig. 3 shows the method for map match in navigation procedure of the embodiment of the invention one;
Fig. 4 shows the schematic diagram of determining Distance conformability degree in the embodiment of the invention one;
Fig. 5 shows the schematic diagram of determining the curvature similarity in the embodiment of the invention one;
Fig. 6 shows the schematic diagram of determining the low pass similarity in the embodiment of the invention one by low-pass filter;
Fig. 7 shows the device of map match in navigation procedure of the embodiment of the invention two.
Embodiment
Understand and realization the present invention the existing embodiments of the invention of describing by reference to the accompanying drawings for the ease of persons skilled in the art.
Embodiment one
What the present invention adopted is the technology of the relevant matches of track of vehicle and map road line.Wherein track of vehicle also claims running orbit, and the road curve around the track of vehicle is called road curve to be matched.The process of coupling is exactly to seek the most similar road curve to be matched for track of vehicle.Fig. 2 shows track of vehicle and six road curve a to be matched, b, c, d, c, e, f.Track of vehicle is the curve that a plurality of points form, and these tracing points are the locating information points that directly obtain by GPS.
As shown in Figure 3, the present embodiment discloses the map-matching method in a kind of navigation procedure, comprises the steps:
In step 32, in order to determine the road of coupling, two physical quantitys of definable are described the degree of closeness of these two curves: Distance conformability degree and curvature similarity.Described Distance conformability degree refers to track of vehicle to the spacing distance value between the road curve, and this spacing distance is less just to illustrate that two curves are more similar.Described curvature similarity refer to the position angle of the track of vehicle tangent line road curve corresponding with this tangent line point of contact hang down point tangent line the position angle between difference, this differential seat angle is less just to illustrate that two curves are more similar.
Distance conformability degree can draw by the vertical line distance of each sampling point on the running orbit of vehicle to road curve to be matched, and the method that obtains Distance conformability degree is described below.
As shown in Figure 4, solid line represents road curve to be matched, and dotted line is the running orbit of vehicle, is respectively d0 from each tracing point to the length of perpendicular the road curve to be matched, d1, d2, d3, d4.Because GPS receives the variation of signal, so that drift or shake can occur track of vehicle point, be different thereby cause the length of these vertical lines.In this case, we define the average length D of vertical line as Distance conformability degree, and Distance conformability degree can be tried to achieve by formula (1):
D＝(d0+d1+d2+d3+d4)/5 (1)
If describe similarity between them with the vertical line average length value D between two curves, can pass through in formula (1) analysis chart 2 the track of vehicle curve respectively with the similarity of road curve a, b, c, d, e, f, obviously the vertical line average length Da of geometric locus and road a is greater than itself and other road curve b, c, d, e, the vertical line average length Db of f, Dc, Dd, De, Df.Therefore geometric locus is more similar to road curve b, and namely the Distance conformability degree of road curve b is maximum, like this, and the road curve that just road curve b is defined as mating.
In like manner, as shown in Figure 5, we are definable curvature similarity also, and namely the curvature similarity between two curves can be described with the position angle differential seat angle of every pair of sample point on two curves, described position angle refers to that clockwise direction is to the horizontal sextant angle of target direction line from the north pointer direction line of certain point.In Fig. 5, solid line represents road curve to be matched, and dotted line is the running orbit of vehicle, and two hang down between the point that difference is g0 between the position angle on the road curve to be matched corresponding with it of the position angle of per two adjacent track points, g1, g2, g3, g4.Wherein g0 is the difference between position angle and the position angle that fp0 to fp1 is connected of k0 to k1 line.Because GPS receives the variation of signal, so that drift or shake can occur track of vehicle point, thereby cause these position angles g0, g1, g2, g3, g4 is fluctuation status.In this case, we define the general bearing angular difference G of vertical line as the curvature similarity, and the curvature similarity can be tried to achieve by formula (2):
G＝(g0+g1+g2+g3+g4)/5 (2)
Track of vehicle curve in through type (2) analysis chart 2 respectively with the similarity of road curve a, b, c, d, e, f, obviously Gb is less than Ga, Gc, Ge, Gd, Gf.Therefore, geometric locus is similar in appearance to road curve b, like this, and the road curve that road curve b can be defined as mating.
In order to improve the accuracy of the road curve of determining coupling, Distance conformability degree and curvature similarity can be united use, namely adopt the associating similarity to determine the road curve of coupling, like this, can overcome better the complicacy of road network and the uncertainty of track of vehicle, determine that the method for associating similarity is as follows:
Score＝(1-a)*D
*+a*G
* [0＜＝a＜＝1] (3)
Wherein, coefficient a between [0,1], D
*Be the relative distance similarity, but through type: D
*=D/ tries to achieve apart from reference value, is a predetermined value apart from reference value, usually can be rule of thumb or the operating parameter setting of GPS, such as the distance error value of GPS; G
*Be the relative curvature likelihood, but through type: G
*=G/ curvature reference value is tried to achieve, with the distance reference value in like manner, the curvature reference value is a predetermined value, usually can be rule of thumb or the operating parameter setting of GPS, such as the error of curvature value of GPS.Score has reflected range difference D and the weight of differential seat angle G on the appraisal curve similarity.Coefficient a can draw by rule of thumb.The Score score value is less, and curve similarity is higher.
In utilization formula (3) analysis chart 2 the track of vehicle curve respectively with the similarity of road curve a, b, c, d, e, f, will obtain 6 score values such as (Score) a, (Score) b, (Score) c, (Score) d, (Score) e, (Score) f.Obviously (Score) b is minimum, so road b is the most similar to trajectory.Therefore, the road curve that road curve b is defined as mating.
In order to obtain better matching effect, also can adopt the methods such as low-pass filter, Kalman filter to calculate the value of vertical line and angular difference.As shown in Figure 6, the vertical range fractional value of k tracing point of y (k) expression vehicle, k tracing point of u (k) expression is to the vertical range of road curve.The below introduces the method for the coupling of using low-pass filter.
Calculate the low-pass filter of the vertical line distance between two curves:
y(k+1)＝a*y(k)+(1-a)*∑u(k-i)/(m+1) (4)
Wherein:
a＝0.5
m＝4
i＝[0，m]
∑ u (k-i)/(m+1) in the formula (4)=[u (k)+u (k-1)+u (k-2)+u (k-3)+u (k-4)]/5 are above-mentioned " two the vertical line average length value D between curve " just.
Y (k) in the formula (4) is calculated and is got by (k-1)～(k-5) sequence.
Suppose that the u (k) of any point is 0 before first point that GPS receives, like this,
Y (0)=0; When the tracing point of record be first, when also not having historical putting, the initialization value of fractional value is 0
y(1)＝a*y(0)+(1-a)*∑u(1-i)/(m+1)
y(2)＝a*y(1)+(1-a)*∑u(2-i)/(m+1)
y(3)＝a*y(2)+(1-a)*∑u(3-i)/(m+1)
We are these two values addition, that is: y (k)+∑ u (k-i)/(m+1) now
To obtain the length of perpendicular fractional value y (k+1) of (k+1) tracing point.This shows, formula (4) is to utilize the forward direction tracing point data of having calculated and some historical datas of surveying to remove to calculate the length of perpendicular fractional value y (k+1) of current tracing point (k+1).
In addition, in order to adjust these two kinds of data of y (k) and ∑ u (k-i)/(m+1) to the influence power of y (k+1) value, can design weighted value a.The value proportion that distributes these two data with (1-a) and a:
y(k+1)＝a*y(k)+(1-a)*∑u(k-i)/(m+1) (5)
By formula (5) as can be known, get different values by a, capable of regulating y (k) and ∑ weight.M has specified the scope of historical data.
For a new road, when tracing point has formed m+1, just can utilize these points to calculate the length of perpendicular fractional value of each later tracing point.Article one, the track of vehicle curve simultaneously to around all road curves do respectively the length of perpendicular fractional value, then the minimum road of the mark that obtains be the road that is matched to merit.
In like manner, also can utilize formula (4) to calculate differential seat angle (curvature similarity).At this moment, ∑ u (k-i)/(m+1) is the average angle difference of each tracing point of expression and road intersection point point; Y (k) is the angular difference numerical value of k point position; Y (k+1) is that (k+1) that calculate out puts the angular difference numerical value of position.
Equally, also can calculate the associating similarity, this season:
Dist_error=is relevant to the fractional value y (k+1) of length of perpendicular/apart from reference value
Heading_error=is relevant to the fractional value y (k+1) of differential seat angle/curvature reference value
Two fractional values are done Combined Treatment, finally can obtain the fractional value of the similarity degree of unique description trajectory and Road:
Score＝f*|Heading_error|+(1-f)*|Dist_error|
Article one, the track of vehicle line is done the Score computing to n bar Road on every side simultaneously, obtains n Score.Get that road of minimum value as the road curve of coupling.
By adjusting the size of f, can solve angle and distance to the impact of Score, when increasing f, can be so that the angle points of the running orbit of vehicle has larger weight, thereby solve vehicle when intersection place sudden turn, the image of vehicle is correctly matched on the road curve.By practice as can be known, when the value condition of f is following situation, can solve preferably the impact that the vehicle sudden turn brings:
Also can the Score score value be optimized according to the situation of road curve:
I) Road to having been mated, the priority of its Score is the highest.
Score’＝0.25*(1+Score)
Ii) Road to being associated with quilt coupling road, the priority of its Score is inferior high.
Score’＝0.5*(1+Score)
Iii) all do not satisfy more than, then the priority of the Score of Road is on the low side.
Score’＝1+Score
Iv) to belonging to the Road of path planning, the priority of its Score is higher.
Score”＝0.5*Score’
V) to being subjected to the Road of the condition restriction such as forbidden, the priority of its Score is lower.
Score”＝1.5*Score’
Embodiment two
As shown in Figure 7, the present embodiment provides the map matching means in a kind of navigation procedure, comprising: obtain the unit, be used for obtaining the vehicle operating tracing point; Determining unit is used for according to the road of described running orbit point with the definite coupling of Roads in Maps curve; Matching unit matches described running orbit point on the road of described coupling.
Described determining unit can specifically comprise: the first computation subunit is used for calculating the Distance conformability degree between described running orbit and the Roads in Maps curve; First determines subelement, is used for the road that the road curve with the Distance conformability degree maximum is defined as mating.
Described determining unit can also specifically comprise: the second computation subunit is used for calculating the curvature similarity between described running orbit and the Roads in Maps curve; Second determines subelement, is used for the road that the road curve with curvature similarity maximum is defined as mating.
Described determining unit can also specifically comprise: the first computation subunit is used for calculating the Distance conformability degree between described running orbit and the Roads in Maps curve; The second computation subunit is used for calculating the curvature similarity between described running orbit and the Roads in Maps curve; The 3rd computation subunit is used for obtaining the associating similarity according to described Distance conformability degree and curvature similarity; The 3rd determines subelement, is used for uniting the road that the road curve of similarity maximum is defined as mating.
Described determining unit can also specifically comprise: the 4th computation subunit is used for calculating the low pass Distance conformability degree between described running orbit and the Roads in Maps curve; The 4th determines subelement, is used for the road that the road curve with low pass Distance conformability degree maximum is defined as mating.
Described determining unit can also specifically comprise: the 5th computation subunit is used for calculating the low pass curvature similarity between described running orbit and the Roads in Maps curve; The 5th determines subelement, is used for the road that the road curve with low pass curvature similarity maximum is defined as mating.
Described determining unit can also specifically comprise: the 4th computation subunit is used for the low pass Distance conformability degree between the described running orbit of calculating and the Roads in Maps curve; The 5th computation subunit is used for calculating the low pass curvature similarity between described running orbit and the Roads in Maps curve; The 6th computation subunit is used for obtaining low pass associating similarity according to described low pass Distance conformability degree and low pass curvature similarity; The 6th determines subelement, is used for low pass is united the road that the road curve of similarity maximum is defined as mating.
The principle of work of above-mentioned each unit can with reference to content among the embodiment one, not repeat them here.
According to the present embodiment, the image of vehicle is correctly matched on its road curve of advancing, increased user's satisfaction thereby made things convenient for to navigate, promoted the quality of product.
Although described the present invention by embodiment, those of ordinary skills know, without departing from the spirit and substance in the present invention, just can make the present invention that many distortion and variation are arranged, and scope of the present invention is limited to the appended claims.
Claims (7)
1. the map-matching method in the navigation procedure is characterized in that, comprising:
Obtain the vehicle operating tracing point;
With the vertical line average length value substitution low-pass filter computing formula between the length of perpendicular fractional value of the forward direction tracing point that calculated and two curves, calculate the length of perpendicular fractional value between described vehicle operating tracing point and the Roads in Maps curve; Vertical line average length between described two curves is the mean value that the historical track on the vehicle operating geometric locus is put the length of perpendicular of road curve to be matched;
The road that the road curve of length of perpendicular fractional value minimum is defined as mating;
Described vehicle operating tracing point is matched on the road of described coupling;
Described low-pass filter computing formula is:
Wherein, i=[0, m], a=[0,1] and, m is historical track point number;
Y (k+1) is the length of perpendicular fractional value between current vehicle operating tracing point and the Roads in Maps curve;
Y (k) is the length of perpendicular fractional value of forward direction tracing point;
U (k-i) is the length of perpendicular that the historical track on the vehicle operating geometric locus is put road curve to be matched;
2. the map-matching method in the navigation procedure is characterized in that, comprising:
Obtain the vehicle operating tracing point;
With the angular difference numerical value of the forward direction tracing point that calculated and the historical track point on the vehicle operating geometric locus average angle difference substitution low-pass filter computing formula with road intersection point point to be matched, calculate the angular difference numerical value between described vehicle operating tracing point and the Roads in Maps curve;
The road that the road curve of angular difference numerical value minimum is defined as mating;
Described vehicle operating tracing point is matched on the road of described coupling;
Described low-pass filter computing formula is:
Wherein, i=[0, m], a=[0,1] and, m is historical track point number;
Y (k+1) is the angular difference numerical value between current vehicle operating tracing point and the Roads in Maps curve;
Y (k) is the angular difference numerical value of forward direction tracing point;
U (k-i) is the position angle of the historical track point on the vehicle operating geometric locus and azimuthal angular difference value of road intersection point point to be matched; Described position angle refers to that clockwise direction is to the horizontal sextant angle of target direction line from the north pointer direction line of historical track point or intersection point point;
3. the map-matching method in the navigation procedure is characterized in that, comprising:
Obtain the vehicle operating tracing point;
With the vertical line average length value substitution low-pass filter computing formula between the length of perpendicular fractional value of the forward direction tracing point that calculated and two curves, calculate the length of perpendicular fractional value between described vehicle operating tracing point and the Roads in Maps curve; Vertical line average length between described two curves is the mean value that the historical track on the vehicle operating geometric locus is put the length of perpendicular of road curve to be matched;
With the angular difference numerical value of the forward direction tracing point that calculated and the historical track point on the vehicle operating geometric locus average angle difference substitution low-pass filter computing formula with road intersection point point to be matched, calculate the angular difference numerical value between described vehicle operating tracing point and the Roads in Maps curve;
With described length of perpendicular fractional value and described angular difference numerical value substitution associating calculating formula of similarity, obtain low pass associating similarity;
Low pass is united the road that the road curve of similarity minimum is defined as mating;
Described vehicle operating tracing point is matched on the road of described coupling;
Described low-pass filter computing formula is:
Wherein, i=[0, m], a=[0,1] and, m is historical track point number;
Y (k+1) is length of perpendicular fractional value or the angular difference numerical value between current vehicle operating tracing point and the Roads in Maps curve;
Y (k) is length of perpendicular fractional value or the angular difference numerical value of forward direction tracing point;
U (k-i) is that historical track point on the vehicle operating geometric locus is to length of perpendicular or the position angle of the historical track point on the vehicle operating geometric locus and azimuthal angular difference value of road intersection point point to be matched of road curve to be matched; Described position angle refers to that clockwise direction is to the horizontal sextant angle of target direction line from the north pointer direction line of historical track point or intersection point point;
4. method as claimed in claim 3 is characterized in that, described low pass associating calculating formula of similarity is:
When angular difference numerical value during less than or equal to 45 °, f=[0.2,0.5];
When angular difference numerical value during greater than 45 °, f=0.5.
5. the map matching means in the navigation procedure is characterized in that, comprising:
Obtain the unit, be used for obtaining the vehicle operating tracing point;
The 4th computation subunit, be used for the length of perpendicular fractional value of the forward direction tracing point that will calculate and the vertical line average length value substitution low-pass filter computing formula between two curves, calculate the length of perpendicular fractional value between described vehicle operating tracing point and the Roads in Maps curve; Vertical line average length between described two curves is the mean value that the historical track on the vehicle operating geometric locus is put the length of perpendicular of road curve to be matched;
The 4th determines subelement, is used for the road that the road curve with length of perpendicular fractional value minimum is defined as mating;
Matching unit is for the road that described running orbit point is matched described coupling;
Described low-pass filter computing formula is:
Wherein, i=[0, m], a=[0,1] and, m is historical track point number;
Y (k+1) is the length of perpendicular fractional value between current vehicle operating tracing point and the Roads in Maps curve;
Y (k) is the length of perpendicular fractional value of forward direction tracing point;
U (k-i) is the length of perpendicular that the historical track on the vehicle operating geometric locus is put road curve to be matched;
6. the map matching means in the navigation procedure is characterized in that, comprising:
Obtain the unit, be used for obtaining the vehicle operating tracing point;
The 5th computation subunit, be used for the average angle difference substitution low-pass filter computing formula of historical track point and road intersection point point to be matched on the angular difference numerical value of the forward direction tracing point that will calculate and the vehicle operating geometric locus, calculate the angular difference numerical value between described vehicle operating tracing point and the Roads in Maps curve;
The 5th determines subelement, is used for the road that the road curve with angular difference numerical value minimum is defined as mating;
Matching unit is for the road that described running orbit point is matched described coupling;
Described low-pass filter computing formula is:
Wherein, i=[0, m], a=[0,1] and, m is historical track point number;
Y (k+1) is the angular difference numerical value between current vehicle operating tracing point and the Roads in Maps curve;
Y (k) is the angular difference numerical value of forward direction tracing point;
U (k-i) is the position angle of the historical track point on the vehicle operating geometric locus and azimuthal angular difference value of road intersection point point to be matched; Described position angle refers to that clockwise direction is to the horizontal sextant angle of target direction line from the north pointer direction line of historical track point or intersection point point;
7. the map matching means in the navigation procedure is characterized in that, comprising:
Obtain the unit, be used for obtaining the vehicle operating tracing point;
The 4th computation subunit, be used for the length of perpendicular fractional value of the forward direction tracing point that will calculate and the vertical line average length value substitution low-pass filter computing formula between two curves, calculate the length of perpendicular fractional value between described vehicle operating tracing point and the Roads in Maps curve; Vertical line average length between described two curves is the mean value that the historical track on the vehicle operating geometric locus is put the length of perpendicular of road curve to be matched;
The 5th computation subunit, be used for the average angle difference substitution low-pass filter computing formula of historical track point and road intersection point point to be matched on the angular difference numerical value of the forward direction tracing point that will calculate and the vehicle operating geometric locus, calculate the angular difference numerical value between described vehicle operating tracing point and the Roads in Maps curve;
The 6th computation subunit is used for described length of perpendicular fractional value and described angular difference numerical value substitution associating calculating formula of similarity are obtained low pass associating similarity;
The 6th determines subelement, is used for low pass is united the road that the road curve of similarity minimum is defined as mating;
Matching unit is for the road that described running orbit point is matched described coupling;
Described low-pass filter computing formula is:
Wherein, i=[0, m], a=[0,1] and, m is historical track point number;
Y (k+1) is length of perpendicular fractional value or the angular difference numerical value between current vehicle operating tracing point and the Roads in Maps curve;
Y (k) is length of perpendicular fractional value or the angular difference numerical value of forward direction tracing point;
U (k-i) is the angular difference value that the historical track point on the vehicle operating geometric locus is put road intersection point point to be matched to length of perpendicular or the historical track on the vehicle operating geometric locus of road curve to be matched;
Described position angle refers to that clockwise direction is to the horizontal sextant angle of target direction line from the north pointer direction line of historical track point or intersection point point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200910086941 CN101922939B (en) | 2009-06-11 | 2009-06-11 | Map matching method and device in navigation process |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200910086941 CN101922939B (en) | 2009-06-11 | 2009-06-11 | Map matching method and device in navigation process |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101922939A CN101922939A (en) | 2010-12-22 |
| CN101922939B true CN101922939B (en) | 2013-09-18 |
Family
ID=43338006
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 200910086941 Active CN101922939B (en) | 2009-06-11 | 2009-06-11 | Map matching method and device in navigation process |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101922939B (en) |
Families Citing this family (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103256937B (en) * | 2012-02-17 | 2016-05-18 | 北京四维图新科技股份有限公司 | The method of route matching and device |
| CN102944244B (en) * | 2012-10-10 | 2015-05-20 | 北京世纪高通科技有限公司 | Method and device for acquisition of path planning engine parameter weight |
| CN104019821B (en) * | 2013-02-28 | 2018-02-09 | 腾讯科技（深圳）有限公司 | The matching process and device of a kind of electronic map |
| CN104718462B (en) * | 2013-05-20 | 2018-02-13 | 英特尔公司 | For mixing the technology of virtual and entity floor maps |
| CN104215256B (en) * | 2013-06-05 | 2018-03-23 | 深圳市赛格导航科技股份有限公司 | The method that route or travel by vehicle is shown on map |
| CN103499828B (en) * | 2013-10-22 | 2015-07-29 | 北京世纪高通科技有限公司 | The method of Floating Car track map match and device |
| CN103914600B (en) * | 2014-04-23 | 2017-07-18 | 北京市市政工程设计研究总院有限公司 | A kind of road alignment method for evaluating similarity and device based on perspective view principle |
| CN104596530B (en) * | 2014-05-27 | 2017-10-31 | 腾讯科技（深圳）有限公司 | A kind of vehicle positioning method and device |
| CN104200042B (en) * | 2014-09-17 | 2017-09-01 | 王伟 | A kind of location data trace tracking method |
| CN104484999B (en) * | 2014-12-31 | 2017-08-22 | 百度在线网络技术（北京）有限公司 | The method and device of dynamic information is determined based on user trajectory |
| CN106469505B (en) * | 2015-08-20 | 2021-05-18 | 方正国际软件(北京)有限公司 | Floating car track deviation rectifying method and device |
| CN105841708A (en) * | 2016-03-16 | 2016-08-10 | 佛山科学技术学院 | Vehicle navigation and positioning track matching method based on path tracing |
| CN106500705A (en) * | 2016-10-20 | 2017-03-15 | 上海智驾电子科技有限公司 | Alignment system and localization method based on lane detection |
| CN106840175B (en) * | 2016-12-06 | 2020-01-10 | 北京中交兴路信息科技有限公司 | Method and device for matching vehicle running track with road network |
| CN108571973B (en) * | 2017-03-08 | 2021-03-05 | 阿里巴巴（中国）有限公司 | Road matching method and device |
| CN109001773A (en) * | 2017-06-06 | 2018-12-14 | Comlab（北京）通信系统设备有限公司 | A kind of localization method and its device |
| CN107331180A (en) * | 2017-08-10 | 2017-11-07 | 佛山市三水区彦海通信工程有限公司 | A kind of automobile speed limit information cuing method |
| CN108583624B (en) * | 2018-04-12 | 2020-11-24 | 中车青岛四方机车车辆股份有限公司 | Train running state visualization method and device |
| CN111380542B (en) * | 2018-12-28 | 2023-03-17 | 沈阳美行科技股份有限公司 | Vehicle positioning and navigation method and device and related system |
| CN109827582A (en) * | 2019-03-29 | 2019-05-31 | 深圳市鹏途交通科技有限公司 | A kind of method and system of quick determining road network disease relative position |
| CN110068338A (en) * | 2019-04-30 | 2019-07-30 | 杭州视氪科技有限公司 | A kind of route memory system and method |
| CN110426050B (en) * | 2019-08-07 | 2021-08-03 | 北京百度网讯科技有限公司 | Map matching correction method, device, equipment and storage medium |
| CN111624636B (en) * | 2020-05-25 | 2023-06-20 | 腾讯科技（深圳）有限公司 | Data processing method, device, electronic equipment and computer readable medium |
| CN111932887B (en) * | 2020-08-17 | 2022-04-26 | 武汉四维图新科技有限公司 | Method and equipment for generating lane-level track data |
| CN113126132B (en) * | 2021-04-09 | 2022-11-25 | 内蒙古科电数据服务有限公司 | Method and system for calibrating and analyzing track in mobile inspection |
| CN113514072B (en) * | 2021-09-14 | 2021-12-14 | 自然资源部第三地理信息制图院 | Road matching method oriented to navigation data and large-scale drawing data |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1959429A (en) * | 2006-10-16 | 2007-05-09 | 同济大学 | Method and system for matching distributed maps |
| CN101324440A (en) * | 2008-07-29 | 2008-12-17 | 光庭导航数据（武汉）有限公司 | Map-matching method based on forecast ideology |
-
2009
- 2009-06-11 CN CN 200910086941 patent/CN101922939B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1959429A (en) * | 2006-10-16 | 2007-05-09 | 同济大学 | Method and system for matching distributed maps |
| CN101324440A (en) * | 2008-07-29 | 2008-12-17 | 光庭导航数据（武汉）有限公司 | Map-matching method based on forecast ideology |
Non-Patent Citations (2)
| Title |
|---|
| JP特开2001-272239A 2001.10.05 |
| 柏钢等.一种改进的地图匹配算法在车辆导航中的应用.《中国惯性技术学报》.1999,第7卷(第1期),第17-18，35页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101922939A (en) | 2010-12-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101922939B (en) | Map matching method and device in navigation process | |
| CN102538781B (en) | Machine vision and inertial navigation fusion-based mobile robot motion attitude estimation method | |
| CN105371840B (en) | A kind of inertia/visual odometry/laser radar Combinated navigation method | |
| JP4897542B2 (en) | Self-positioning device, self-positioning method, and self-positioning program | |
| JP6026295B2 (en) | Curve shape modeling apparatus, method, and in-vehicle navigation apparatus | |
| CN106595656B (en) | A kind of identification of highway alignment feature and calculation method of parameters based on vehicle-mounted POS | |
| CN108873038A (en) | Autonomous parking localization method and positioning system | |
| CN109186597B (en) | Positioning method of indoor wheeled robot based on double MEMS-IMU | |
| TW201205040A (en) | Probe data processing | |
| CN105698822B (en) | Initial Alignment Method between autonomous type inertial navigation based on reversed Attitude Tracking is advanced | |
| CN103528584B (en) | Based on the polar region inertial navigation of horizontal geographic coordinate system | |
| WO2016070723A1 (en) | Dead-reckoning navigation and positioning method and system for obtaining longitude and latitude of vehicle by speedometer | |
| CN102331259A (en) | Trace information generating apparatus and method and computer-readable recording medium | |
| CN109945860A (en) | A kind of INS and DR inertial navigation method and system based on satellite tight integration | |
| CN103674021A (en) | Integrated navigation system and method based on SINS (Strapdown Inertial Navigation System) and star sensor | |
| CN104390646A (en) | Position matching method for underwater vehicle terrain aided inertial navigation system | |
| CN102466802B (en) | Dead reckoning is used to follow the trail of the method at vehicle location and vehicle heading angle and realize the follow-up mechanism of the method | |
| US10724871B2 (en) | Camera-based heading-hold navigation | |
| CN107110979A (en) | Attitude angle computing device, attitude angle computational methods and attitude angle calculation procedure | |
| US20140058563A1 (en) | Method and system for the directed control of robotic assets | |
| CN107797125A (en) | A kind of method for reducing deep-sea detecting type AUV navigation positioning errors | |
| CN104776847B (en) | A kind of method that gyroscopic drift is estimated suitable for underwater navigation system single-point | |
| US9766081B2 (en) | System and method for roundabouts from probe data using vector fields | |
| CN110058288A (en) | Unmanned plane INS/GNSS integrated navigation system course error modification method and system | |
| EP3060943B1 (en) | Improved system for post processing gnss/ins measurement data and camera image data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20200515 Address after: 310052 room 508, floor 5, building 4, No. 699, Wangshang Road, Changhe street, Binjiang District, Hangzhou City, Zhejiang Province Patentee after: Alibaba (China) Co.,Ltd. Address before: 100080 Beijing city Haidian District No. 3 Suzhou Street Daheng Technology Building South 18 Patentee before: AUTONAVI INFORMATION TECHNOLOGY Co.,Ltd. |
|
| TR01 | Transfer of patent right |