CN101324440A - Map-matching method based on forecast ideology - Google Patents
Map-matching method based on forecast ideology Download PDFInfo
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Abstract
The invention provides a map matching method based on a prediction idea, which comprises following steps: (1) analyzing the topological and geometric characteristics of a road where a vehicle runs currently; (2) deducing the geometric form of the road where the vehicle runs currently; (3) constructing a prediction model by using the geometric form, and the history positioning points, road planning result, and the positioning system of a GPS and DR system as the input condition; (4) predicting the matched point or trajectory by adopting a prediction method based on the existing matched trajectory when no road planning result is available, or predicting the matched point or the trajectory by adopting a prediction method based on the road planning result when a road planning result is available; and (5) combining the predicted matched point or the trajectory with candidate road information to obtain an optimal matched road, and updating the position of a vehicle mark in real time. The map matching method can effectively improve the matching effect of navigation equipment on a special and complex road and ensure the performance of the navigation equipment.
Description
Technical field
The invention belongs to the guider algorithm, particularly relate to a kind of map-matching method.
Background technology
Auto navigation be unable to do without map of navigation electronic, and map-matching method is to connect the locating information that obtained by GPS receiver or other sensors and the bridge of map of navigation electronic.Map-matching method is by certain algorithm, according to locating information and electronic map data, on map of navigation electronic, determine the current road that travels of vehicle, and on map, show the position of vehicle real-time and accurately, simultaneously, the accurate match result is also as the initial conditions of navigator route guidance.Therefore, a cover matching accuracy rate height, map-matching method efficient, that real-time is good are the important leverages of outstanding car navigation device.
Map-matching method is a lot, mainly comprises direct projection algorithm, relevance algorithms, probability statistics algorithm, based on the algorithm of fuzzy logic theory, based on algorithm of D-S evidence theory etc.All there is a common shortcoming in these algorithms, promptly when the complicated road, because complicacy, the similarity of road, such as roadway characteristics such as Y-shaped crossing, parallel roads, usually cause matching error or do not match, and have influenced the performance of navigator.
Summary of the invention
Technical matters to be solved by this invention is: a kind of map-matching method based on prediction thought is provided, and this method can effectively improve the matching accuracy rate of car navigation device at complicated road, improves the overall performance of navigational system.
The technical solution used in the present invention is: a kind of map-matching method based on prediction thought, and its step comprises:
1) the road topology feature and the geometric properties of the current driving of analysis vehicle;
2) infer the geometric shape of the road of vehicle current driving according to step 1) gained road topology feature and geometric properties;
3) with step 2) geometric shape of gained road, and the locating information of historical anchor point, route programming result, GPS and dead reckoning (DR) system is as the initial conditions of prediction, and set up forecast model;
4) according to the initial conditions and the forecast model of step 3), when not having route programming result, adopt Forecasting Methodology, carry out the prediction of match point or track based on existing matching track; When route programming result, adopt Forecasting Methodology based on route programming result, carry out the prediction of match point or track;
5) step 4) is predicted the match point that obtains or track and candidate roads information merge, determined the Optimum Matching road, and real-time update car target position.
Advantage of the present invention: for various complicated roads, as cross junction, traffic circle, overhead viaduct, Y-shaped crossing, parallel road etc., map-matching algorithm based on prediction thought all can be in real time, mate exactly, make car navigation device performance boost a class.
Description of drawings
Fig. 1 embodiment of the invention synoptic diagram 1.
Fig. 2 embodiment of the invention synoptic diagram 2.
Fig. 3 road form is inferred synoptic diagram.
Fig. 4 matching result prediction process flow diagram.
Embodiment
Implementation method of the present invention may further comprise the steps:
1) topological characteristic and the geometric properties of the road of analysis vehicle current driving;
2) infer the geometric shape of the road of vehicle current driving according to the topological characteristic and the geometric properties of step 1) gained road;
3) with step 2) geometric shape of gained road, and the locating information of historical anchor point, route programming result, GPS and DR system is as the initial conditions of prediction, and set up forecast model;
4) according to the initial conditions and the forecast model of step 3), when not having route programming result, adopt Forecasting Methodology, carry out the prediction of match point or track based on historical anchor point; When route programming result, adopt Forecasting Methodology based on route programming result, carry out the prediction of match point or track;
5) step 4) is predicted the match point that obtains or track and candidate roads merge, determined the optimum matching road, and real-time update car target position.
As shown in Figure 3, above-mentioned steps 2) specifically comprise again:
21) information according to the map, input form point and node data.
22) according to step 1) gained form point and node data, and the vehicle current location information, judge whether vehicle arrives next node, if "Yes" enters step 23), if "No" enters step 24).
23), judge the geometric shape of the road link to each other with node, for example cross junction, traffic circle, overhead viaduct, Y-shaped road etc. according to roadway characteristic.
24), judge the feature of the road between current location and the node, for example straight line or curve according to form point information.
As shown in Figure 4, above-mentioned steps 4) specifically comprise again:
41) beginning matching result prediction;
42) judge whether to carry out path planning, if "Yes" enters step 43), if "No" enters step 45);
43), predict according to route programming result;
44) according to step 43) the gained result, infer according to current vehicle speed, course information again, enter step 47 then);
45) according to historical anchor point, predict;
46) according to step 45) the gained result, use curve-fitting method further to predict, and proofread and correct;
47) obtain the matching result predicted, i.e. match point or track.
Embodiment 1:
As shown in Figure 1, solid line is a road, and dotted line is a positioning track, and Diamond spot is an anchor point, and the triangle form point is a match point, and circular point is future position.At an intersection, A, B, C and D are the match point of prediction, and the P point is the anchor point that is used for mating, and road 1, road 2, road 3 etc. are the candidate matches highway section.Vehicle actual travel route is according to match point track solid line, and current anchor point is P.
1. analyze the road and the geometric shape of vehicle current driving:
1) topological characteristic and the geometric properties of analysis vehicle current driving road.
2), import the coordinate of each match point (triangle form point) and anchor point (Diamond spot) again according to step 1) gained cartographic information.
3) according to step 2) gained form point and node data, and the vehicle current location information, to judge, vehicle has arrived next node (crossing).
4) according to form point information, judge the geometric shape that links to each other with current location between the road, in this example the junction of three roads.
2. predict and coupling:
5) with the geometric shape of step 4) gained road, and the locating information of historical anchor point, GPS and DR system is as the initial conditions of prediction, and sets up forecast model.
6) beginning matching result prediction.
7) judge whether to carry out path planning.Owing to do not have route programming result, enter step 8).
8), and predict by historical anchor point (Diamond spot) according to step 5) gained forecast model.
9) according to step 8) gained result, further predict by the matched curve of historical anchor point again, and proofread and correct according to current vehicle speed, course information.Get four alternative future position A, B, C and D at last.
10), calculate to such an extent that P point and B are nearest, so road 2 is Optimum Matching roads according to the coordinate of the alternative future position of step 9) gained.The matching result that obtains predicting, promptly the route of walking is a route 2, realistic route.
Embodiment 2:
As shown in Figure 2, P1～P6 is an anchor point, and N1～N6 is the node or the form point of road, and automobile actual travel route is N1 → N2 → N4 → N5.In the actual travel process, if adopt conventional map-matching method, P1, P2, P3, P4 can correctly match on the N1_N2 of highway section, and for the anchor point P5 that enters the Y-shaped crossing, matching error then can occur, and P5 has been matched highway section N2_N3.The matching process that employing the present invention relates to can make P5 match highway section N2_N4, promptly obtains correct coupling, guarantees the performance of navigator.
According to the concrete embodiment of the present invention, whether carry out path planning according to equipment and divide two processes forecasting process.
1. analyze the geometric shape of the road of vehicle current driving:
1) topological characteristic and the geometric properties of analysis vehicle current driving road.
2), import the coordinate of anchor point (black circle) again according to step 1) gained cartographic information.
3) according to step 2) gained form point and node data, and vehicle current location information is judged, vehicle is the no show N2 next node N4 of ordering still.
4) according to form point information, judge the geometric shape of the current road that travels of vehicle, in this example Y type curve mouth.
2. predict and coupling, be divided into two kinds of situations of a, b:
A., route programming result is arranged
A5) with the geometric shape of step 4) gained road, the locating information of GPS and DR system is as the initial conditions of prediction, and sets up forecast model.
A6) beginning matching result prediction.
A7) highway section N2_N4_N5 is a route programming result, and promptly system enters step a8 for the travel route that the user sets).
A8) according to route programming result, in conjunction with data such as form point, nodes, the position angle of utilization planning road respective stretch, the speed of a motor vehicle of automobile, combined cycle etc. can calculate the coordinate (602,136) of the corresponding prediction match point of P5.
A9) coordinate of P5 is (592,133).Calculate step a8) coordinate of gained future position and the spacing of P5 coordinate be 5.4 meters, can calculate simultaneously P5 is 4.6 meters to the distance of path planning N2_N4, with 5.4 meters close, and P5 is 8.5 meters to the distance of highway section N2_N3, and further infers according to current vehicle speed, course information.
A10) according to step a9) the gained data, can judge, automobile is to travel according to path planning, promptly highway section N2_N4 is the Optimum Matching result that P5 is ordered, and has avoided matching error.
B. there is not route programming result
B5) with the geometric shape of step 4) gained road, and the locating information of historical anchor point, GPS and DR system is as the initial conditions of prediction, and sets up forecast model.
B6) beginning matching result prediction.
B7) there is not the path planning point, so according to historical anchor point (P1～P4), predict enters step b8).
B8) according to step b5) the gained forecast model, and predict by historical anchor point.
B9) according to b8) the gained result, adopt polynomial fitting method again, select P1, P2,4 historical anchor points such as P3, P4, the curve's equation that match obtains is: y=601.6558-1.3840321x+0.001010101x
2According to this curvilinear equation, utilize GPS/DR integrated positioning output result, promptly information such as the speed of P1～P4, position can calculate its corresponding prediction match point coordinate and be (604,136) on the curve of match.
B10) according to step b9) gained future position coordinate, can calculate future position is 3.6 meters to the distance of corresponding anchor point P5; Future position is 6.7 meters to the distance of highway section N2_N3; Future position is 2.7 meters to the distance of highway section N2_N4, with 3.6 meters approaching.Simultaneously, according to step b9) the gained matched curve, can calculate the deflection of the line of future position and previous anchor point P4.According to distance and deflection difference, and the weight of direction initialization is the twice of distance, and the distance weighting factor is 10, the direction weight factor is 20, can calculate the weights of two candidate road section, promptly the weights of highway section N2_N3 are 27.5, and the weights of highway section N2_N4 are 29.2.
B11) according to step b10) the various data of gained, can judge that the matching result of P5 is highway section N2_N4, avoided matching error.
Claims (3)
- One kind based on the prediction thought map-matching method, it is characterized in that its step comprises:1) the road topology feature and the geometric properties of the current driving of analysis vehicle;2) infer the geometric shape of the road of vehicle current driving according to step 1) gained road topology feature and geometric properties;3) with step 2) geometric shape of gained road, and the locating information of historical anchor point, route programming result, GPS and dead reckoning (DR) system is as the initial conditions of prediction, and set up forecast model;4) according to the initial conditions and the forecast model of step 3), when not having route programming result, adopt, carry out the prediction of match point or track based on the fixed Forecasting Methodology in history location; When route programming result, adopt Forecasting Methodology based on route programming result, carry out the prediction of match point or track;5) step 4) is predicted the match point that obtains or track and candidate roads information merge, determined the Optimum Matching road, and real-time update car target position.
- 2. the map-matching method based on prediction thought as claimed in claim 1 is characterized in that its step 2), specifically comprise:21) information according to the map, input form point and node data;22) according to the form point and the node data of step 1), and the vehicle current location information, judge whether vehicle arrives next node, if "Yes" enters step 23), if "No" enters step 24);23), judge the geometric shape of the road that links to each other with node according to roadway characteristic;24), judge the feature of the road between current location and the node according to form point information.
- 3. the map-matching method based on prediction thought as claimed in claim 1 is characterized in that its step 4), specifically comprises:41) beginning matching result prediction;42) judge whether to carry out path planning, if "Yes" enters step 43), if "No" enters step 45);43), predict according to route programming result;44) according to step 43) the gained result, predict according to current vehicle speed, course information again, enter step 47 then);45) according to historical anchor point, predict;46) according to step 45) the gained result, use curve-fitting method further to predict, and proofread and correct;47) obtain the matching result predicted, i.e. match point or track.
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| CN101986102A (en) * | 2010-10-14 | 2011-03-16 | 天津大学 | Method for matching electronic map in urban geographic information system |
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