CN101922939A - Map matching method and device in navigation process - Google Patents
Map matching method and device in navigation process Download PDFInfo
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- CN101922939A CN101922939A CN 200910086941 CN200910086941A CN101922939A CN 101922939 A CN101922939 A CN 101922939A CN 200910086941 CN200910086941 CN 200910086941 CN 200910086941 A CN200910086941 A CN 200910086941A CN 101922939 A CN101922939 A CN 101922939A
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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 curve in 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 is meant, replaces the track of vehicle point with the intersection point point on the road route of map, in other words conj.or perhaps the tracing point of vehicle is remedied on the intersection point of its pairing road route.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 GPS receives the error of data, the image that usually can cause vehicle even jump phenomena occurs not on the relevant position of map.Fig. 1 illustrates the situation of prior art vehicle and road, and wherein, dotted line is represented the automobile trajectory, and it has 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 road curve in described running orbit point and the map;
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 to obtain the vehicle operating tracing point;
Determining unit is used for according to the road of described running orbit point with the definite coupling of map road 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 synoptic diagram of determining in the embodiment of the invention one apart from similarity;
Fig. 5 shows the synoptic diagram of determining the curvature similarity in the embodiment of the invention one;
Fig. 6 shows the synoptic 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 in conjunction with 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 route.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 are formed, and these tracing points are the locating information points that directly obtain by GPS.
As shown in Figure 3, 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: apart from similarity and curvature similarity.Describedly be meant track of vehicle to the spacing distance value between the road curve apart from similarity, this spacing distance is more little just to illustrate that two curves are similar more.Described curvature similarity be meant the position angle of track of vehicle tangent line and this tangent line point of contact road corresponding curve hang down point tangent line the position angle between difference, this differential seat angle is more little just to illustrate that two curves are similar more.
Can draw by the vertical line distance of each sampling point on the running orbit of vehicle apart from similarity, the method for acquisition apart from similarity is described below to road curve to be matched.
As shown in Figure 4, solid line is represented 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 the variation of GPS received signal makes the track of vehicle point that drift or shake can take place, and is different thereby cause the length of these vertical lines.In this case, we define the average length D of vertical line as the distance similarity, can be tried to achieve by formula (1) apart from similarity:
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, promptly road curve b apart from the similarity maximum, like this, the road curve that road curve b is defined as mating just.
In like manner, as shown in Figure 5, we are definable curvature similarity also, and promptly 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 is meant the north pointer direction line from certain point, and clockwise direction is to the horizontal sextant angle of target direction line.In Fig. 5, solid line is represented 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 the variation of GPS received signal makes the track of vehicle point that drift or shake can take place, thereby causes 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, can will unite use apart from similarity and curvature similarity, promptly adopt the associating similarity to determine the road curve of coupling, like this, can overcome the complicacy of road network and the uncertainty of track of vehicle better, 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, 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, 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 more little, and the curve similarity is high more.
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 the better matching effect, also can adopt 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.Introduce the method for the coupling of utilization low-pass filter below.
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 that formula (4) is to utilize 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 the influence power of these two kinds of data of y (k) and ∑ u (k-i)/(m+1), can design weighted value a to y (k+1) value.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, can adjust y (k) and ∑ weight by a.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 the length of perpendicular fractional value respectively, 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 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 fractional value y (the k+1)/curvature reference value of differential seat angle
Two fractional values are done Combined Treatment, finally can obtain the fractional value of the similarity degree of unique description trajectory and road route:
Score＝f*|Heading_error|+(1-f)*|Dist_error|
Article one, the track of vehicle line is done the Score computing to n bar road route on every side simultaneously, obtains n Score.Get the road curve of that road of minimum value as coupling.
By adjusting the size of f, can solve the influence of angle and distance, when increasing f, can make the angle points of running orbit of vehicle that bigger weight is arranged Score, thereby when solving vehicle and turning suddenly, the image of vehicle is correctly matched on the road curve at the intersection place.By practice as can be known, when the value condition of f is following situation, can solve the influence that vehicle is turned and brought suddenly preferably:
Also can the Score score value be optimized according to the situation of road curve:
I) the road route to having been mated, the priority of its Score is the highest.
Score’＝0.25*(1+Score)
Ii) to mating the road route that road is associated with quilt, the priority of its Score is inferior high.
Score’＝0.5*(1+Score)
All do not satisfy iii), then the priority of the Score of road route is on the low side.
Score’＝1+Score
Iv) to belonging to the road route of path planning, the priority of its Score is higher.
Score”＝0.5*Score’
V) to being subjected to the road route of condition restriction such as forbidden, the priority of its Score is lower.
Score”＝1.5*Score’
Embodiment two
As shown in Figure 7, present embodiment provides the map matching means in a kind of navigation procedure, comprising: obtain the unit, be used to obtain the vehicle operating tracing point; Determining unit is used for according to the road of described running orbit point with the definite coupling of map road curve; Matching unit matches described running orbit point on the road of described coupling.
Described determining unit can specifically comprise: first computation subunit, be used for calculating between described running orbit and the map road curve apart from similarity; First determines subelement, is used for the road that the road curve with distance similarity maximum is defined as mating.
Described determining unit can also specifically comprise: second computation subunit is used for calculating the curvature similarity between described running orbit and the map road 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: first computation subunit, be used for calculating between described running orbit and the map road curve apart from similarity; Second computation subunit is used for calculating the curvature similarity between described running orbit and the map road curve; The 3rd computation subunit is used for obtaining the associating similarity according to described apart from similarity and curvature similarity; The 3rd determines subelement, be used for will associating similarity maximum the road curve road that is defined as mating.
Described determining unit can also specifically comprise: the 4th computation subunit is used for calculating low pass between described running orbit and the map road curve apart from similarity; The 4th determines subelement, is used for the road that low pass is defined as mating apart from the road curve of similarity maximum.
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 map road 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 and calculates low pass between described running orbit and the map road curve apart from similarity; The 5th computation subunit is used for calculating the low pass curvature similarity between described running orbit and the map road curve; The 6th computation subunit is used for obtaining low pass associating similarity according to described low pass apart from similarity 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 not repeat them here with reference to content among the embodiment one.
According to 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.
Though 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 (14)
1. the map-matching method in the navigation procedure is characterized in that, comprising:
Obtain the vehicle operating tracing point;
Determine the road of coupling according to road curve in described running orbit point and the map;
Described running orbit point is matched on the road of described coupling.
2. method according to claim 1 is characterized in that, described road according to the definite coupling of road curve in described running orbit point and the map specifically comprises:
Calculate in described running orbit and the map between the road curve apart from similarity;
The road that will be defined as mating apart from the road curve of similarity maximum.
3. method according to claim 1 is characterized in that, described road according to the definite coupling of road curve in described running orbit point and the map specifically comprises:
Calculate the curvature similarity between the road curve in described running orbit and the map;
The road that the road curve of curvature similarity maximum is defined as mating.
4. method according to claim 1 is characterized in that, described road according to the definite coupling of road curve in described running orbit point and the map specifically comprises:
Calculate in described running orbit and the map between the road curve apart from similarity;
Calculate the curvature similarity between the road curve in described running orbit and the map;
Obtain the associating similarity according to described apart from similarity and curvature similarity;
The road that the road curve of associating similarity maximum is defined as mating.
5. method according to claim 1 is characterized in that, described road according to the definite coupling of road curve in described running orbit point and the map specifically comprises:
Calculate in described running orbit and the map low pass between the road curve apart from similarity;
The road that low pass is defined as mating apart from the road curve of similarity maximum.
6. method according to claim 1 is characterized in that, described road according to the definite coupling of road curve in described running orbit point and the map specifically comprises:
Calculate the low pass curvature similarity between the road curve in described running orbit and the map;
The road that the road curve of low pass curvature similarity maximum is defined as mating.
7. method according to claim 1 is characterized in that, described road according to the definite coupling of road curve in described running orbit point and the map specifically comprises:
Calculate in described running orbit and the map low pass between the road curve apart from similarity;
Calculate the low pass curvature similarity between the road curve in described running orbit and the map;
Obtain low pass associating similarity according to described low pass apart from similarity and low pass curvature similarity;
Low pass is united the road that the road curve of similarity maximum is defined as mating.
8. the map matching means in the navigation procedure is characterized in that, comprising:
Obtain the unit, be used to obtain the vehicle operating tracing point;
Determining unit is used for according to the road of described running orbit point with the definite coupling of map road curve;
Matching unit matches described running orbit point on the road of described coupling.
9. device according to claim 8 is characterized in that, described determining unit specifically comprises:
First computation subunit, be used for calculating between described running orbit and the map road curve apart from similarity;
First determines subelement, is used for the road that the road curve with distance similarity maximum is defined as mating.
10. device according to claim 8 is characterized in that, described determining unit specifically comprises:
Second computation subunit is used for calculating the curvature similarity between described running orbit and the map road curve;
Second determines subelement, is used for the road that the road curve with curvature similarity maximum is defined as mating.
11. device according to claim 8 is characterized in that, described determining unit specifically comprises:
First computation subunit, be used for calculating between described running orbit and the map road curve apart from similarity;
Second computation subunit is used for calculating the curvature similarity between described running orbit and the map road curve;
The 3rd computation subunit is used for obtaining the associating similarity according to described apart from similarity and curvature similarity;
The 3rd determines subelement, be used for will associating similarity maximum the road curve road that is defined as mating.
12. device according to claim 8 is characterized in that, described determining unit specifically comprises:
The 4th computation subunit is used for calculating low pass between described running orbit and the map road curve apart from similarity;
The 4th determines subelement, is used for the road that low pass is defined as mating apart from the road curve of similarity maximum.
13. device according to claim 8 is characterized in that, described determining unit specifically comprises:
The 5th computation subunit is used for calculating the low pass curvature similarity between described running orbit and the map road curve;
The 5th determines subelement, is used for the road that the road curve with low pass curvature similarity maximum is defined as mating.
14. device according to claim 8 is characterized in that, described determining unit specifically comprises:
The 4th computation subunit is used for the and calculates low pass between described running orbit and the map road curve apart from similarity;
The 5th computation subunit is used for calculating the low pass curvature similarity between described running orbit and the map road curve;
The 6th computation subunit is used for obtaining low pass associating similarity according to described low pass apart from similarity 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.
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