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1. WO2011053389 - PROCÉDÉS ET APPAREILS POUR DÉTERMINER UN ÉLÉMENT GÉOMÉTRIQUE D'UN ÉLÉMENT NAVIGABLE

Note: Texte fondé sur des processus automatiques de reconnaissance optique de caractères. Seule la version PDF a une valeur juridique

[ EN ]

What is claimed is:

1. A method of determining a geometric feature of at least one navigable feature, the method comprising:

first determining a baseline based on sequential location measurements along the at least one navigable feature (S320);

first sorting and clustering the sequential location measurements into a plurality of location measurement groups that are along the baseline (S340); second determining a normal distribution for each of the plurality of location measurement groups based on the sequential location measurements (S340); and

third determining the geometric feature based on the normal

distributions (S380).

2. The method of claim 1 , wherein

the first sorting and clustering (S340) includes,

determining a center of at least one of the plurality of location measurement groups (S350), and

the third determining (S380) includes,

determining the geometric feature based further on the determined center.

3. The method of claim 2, wherein the second determining (S340) includes, determining normal distributions of distances between the center of the least one of the plurality of location measurement groups and the sequential location measurements in the at least one of the plurality of location

measurement groups (S352).

4. The method of any one of claims 1 to 3, further comprising:

second sorting and clustering the sequential location measurements based on the second determining.

5. The method of claim 4, wherein the second sorting and clustering includes, excluding sequential location measurements based on the second determining (S358) .

6. The method of any of claims 1 to 3, wherein the third determining (S380) includes,

determining the geographic feature based on weighted averages applied to corresponding sequential location measurements.

7. The method of claim 6, wherein each weighted average is based on a perpendicular distance between the corresponding sequential location measurement and the baseline.

8. The method of any of claims 1 to 7, further comprising:

third sorting and clustering sequential location measurements along a second baseline into a second plurality of location measurement groups, wherein

the determined geometric feature is the second baseline.

9. The method of claim 8, further comprising:

fourth determining a normal distribution for each of the second plurality of location measurement groups; and

fifth determining a second geometric feature based on the normal distributions generated from the fourth determining.

10. The method of any of claims 1 -9, wherein the first determining (S320) includes,

generating a new map based on the sequential location measurements along the at least one navigable feature.

1 1. The method as claimed in any of claims 1 to 10, wherein the navigable feature includes at least one of a same road, a same path, a same highway and a same transportation segment.

12. The method of any of claims 1 to 1 1 , wherein the geometric feature is a street centreline.

13. The method as claimed in any of claims 1 to 12, wherein the sequential location measurements are collected by a navigation device (200).

14. The method of claim 13, wherein the navigation device (200) is any one of a personal navigation device, a mobile phone, a personal digital assistant and an in vehicle device.

15. A computer readable medium including program segments for, when executed on a processor of a server (202), causing the server (202) to implement the method of any of claims 1 to 14.

16. Computer software comprising one or more software modules operable, when executed in an execution environment, to cause a processor (204) to: determine a baseline (410) based on sequential location measurements along at least one navigable feature;

sort and cluster the sequential location measurements into a plurality of location measurement groups that are along the baseline;

determine a normal distribution for each of the plurality of location measurement groups based on the sequential location measurements; and

determine a geometric feature (460) of the at least one navigable feature based on the normal distributions.

17. The computer software of claim 16, wherein the processor (204) further: determines a center of at least one of the plurality of location

measurement groups, and

determines the geometric feature (460) based further on the determined centers.

18. The computer software of claim 17, wherein the processor (204) further: determines normal distributions of distances between the center of the least one of the plurality of location measurement groups and the location measurements in the at least one of the plurality of location measurement groups.

19. The computer software of any one of claims 16 to 18, wherein the processor (204) further:

sorts and clusters the sequential location measurements based on the normal distributions.

20. The computer software of claim 19, wherein the processor (204) further: excludes sequential location measurements based on the normal distributions.

21. The computer software of any of claims 16 to 18, wherein the processor (204) further:

determines the geographic feature (460) based on weighted averages applied to corresponding sequential location measurements.

22. The computer software of claim 21 , wherein each weighted average is based on a perpendicular distance between the corresponding sequential location measurement and the baseline.

23. The computer software of any of claims 16 to 22, wherein the processor (204) further:

sorts and clusters sequential location measurements along a second baseline (460), wherein

the determined geometric feature (460) is the second baseline

(460).

24. The computer software of claim 23, wherein the processor further:

determines a normal distribution for each of the second plurality of location measurement groups; and

determines a second geometric feature (710) based on the normal distributions of the second plurality of location measurement groups.

25. The computer software of any of claims 16-24, wherein the processor (204) further:

generates a new map based on the sequential location measurements along the at least one navigable feature.

26. The computer software as claimed in any of claims 16 to 25, wherein the navigable feature includes at least one of a same road, a same path, a same highway and a same transportation segment.

27. The computer software of any of claims 16 to 26, wherein the geometric feature (460) is a street centreline.

28. The computer software as claimed in any of claims 16 to 27, wherein the probe sensor data is collected by a navigation device (200).

29. The computer software of claim 28, wherein the navigation device (200) is any one of a personal navigation device, a mobile phone, a personal digital assistant and an in vehicle device.

30. A server (202) comprising:

an input device configured to receive sequential location measurements; and

a processor (204) configured to,

determine a baseline (410) based on the sequential location measurements along at least one navigable feature,

sort and cluster the sequential location measurements into a plurality of location measurement groups that are along the baseline (410), determine a normal distribution for each of the plurality of location measurement groups based on the sequential location measurements, and

determine a geometric feature (460) of the at least one navigable feature based on the normal distributions.