Path curve confidence factors

Patent metadata

Field	Value
Publication number	US-2016356609-A1
Application number	US-201615244480-A
Country	US
Kind code	A1
Filing date	Aug 23, 2016
Priority date	Feb 19, 2013
Publication date	Dec 8, 2016
Grant date	—

Abstract

In one embodiment, navigational features of a navigation device are activated or deactivated according to the accuracy of the geographic data. The navigation features may be predictive features related to upcoming portions of a path curve. The path curve is compared to measured data. For example, a first curve is accessed from a map database and a second curve is based on measured position data collected while traversing the path. The first curve and the second curve correspond to the same geographic area. A difference of an attribute between a section of the first curve and a section of the second curve is used to assign a confidence factor to the section of the first polycurve based on the difference. The attribute may be heading, position, curvature, or another aspect of the path curves.

First claim

We claim:

1 . A method comprising:
obtaining, from a map database, a first spline representing a path, wherein the first spline is formed with piecewise polynomial functions; generating a second spline based on measured position data collected from one or more sensors while traversing the path represented by the first spline; performing, with a processor, an alignment between a section of the first spline a section of the second spline, wherein the section of the first spline corresponds geographically to the section of the second spline; generating a confidence factor by comparing the section of the first spline to the section of the second spline; and influencing at least one advanced driving system when the confidence factor meets or exceeds a confidence threshold.

2 . The method of claim 1 , wherein a plurality of advanced driving assist systems are assigned individual confidence thresholds; and
wherein the plurality of advanced driving assist systems are individually enabled or disabled when the confidence factor meets or exceeds the corresponding confidence thresholds.

3 . The method of claim 1 , further comprising:
displaying the confidence threshold.

4 . The method of claim 1 , wherein a plurality of confidence factors are generated for a plurality of sections in succession.

5 . The method of claim 1 , wherein the measured position data is collected by at least one satellite based positioning sensor.

6 . The method of claim 1 , wherein the measured position data is collected by at least one inertial sensor.

7 . The method of claim 1 , further comprising:
determining a correlation value for a plurality of sections of the first spline by calculating the differences between a plurality of sections of the second spline and the plurality of sections of the first spline, wherein the first spline corresponds to link geometry in the map database; and comparing the correlation value to a correlation threshold.

8 . The method of claim 7 , further comprising:
excluding at least one of the plurality of sections of the first spline when the correlation value is less than the correlation threshold.

9 . The method of claim 7 , wherein the correlation value is based on shape.

10 . The method of claim 1 , wherein the first spline is defined by at least one control point and at least one knot.

11 . The method of claim 10 , wherein the at least one knot represents a point where the polynomial functions piece together; and
wherein the at least one control point represents a point on a line segment that defines a shape of the spline.

12 . The method of claim 1 , wherein the alignment between the section of the first spline and the section of the second spline is supplemented using heading data.

13 . The method of claim 1 , wherein the alignment between the section of the first spline and the section of the second spline is supplemented using shape data.

14 . An apparatus comprising:
at least one processor; and at least one memory including computer program code for one or more programs;
the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least:
obtaining a first spline representing a path from a map database;
generating a second spline based on measured position data collected while traversing the path;
generating a confidence factor by comparing a section of the first spline to a section of the second spline; and
controlling at least one advanced driving assist system based on a comparison of the confidence factor to a confidence threshold.

15 . The apparatus of claim 14 , wherein the first spline is defined by at least one control point defining a first polynomial and at least one knot joining the first polynomial with a second polynomial.

16 . The apparatus of claim 14 , the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least:
performing an alignment between the section of the first spline spanning the geographic distance and the section of the second spline corresponding the geographic distance, wherein the section of the first spline corresponds geographically to the section of the second spline.

17 . A non-transitory computer readable medium including instructions that when executed by a processor are operable to:
access a first spline representing a path in a map database, wherein the spline is formed with piecewise polynomial functions; generate a second spline based on measured data collected while traversing the path; align a section of the first spline spanning a geographic distance and a section of the second spline corresponding the geographic distance, wherein the section of the first spline corresponds geographically to the section of the second spline; assign a confidence factor by comparing the section of the first spline to the section of the second spline; and activate or deactivate at least one advanced driving assist system if the confidence factor meets or exceeds a confidence threshold.

18 . The non-transitory computer readable medium of claim 17 , wherein a plurality of advanced driving assist systems are assigned individual confidence thresholds; and
wherein the plurality of advanced driving assist systems are individually activated or deactivated when the confidence factor meets or exceeds the corresponding confidence thresholds.

19 . The non-transitory computer readable medium of claim 17 , the instructions when executed by the processor are operable to:
determining a correlation value for a plurality of sections of the first spline by calculating the differences between a plurality of sections of the second spline and the plurality of sections of the first spline, wherein the first spline corresponds to link geometry in the map database; comparing the correlation value to a correlation threshold; and excluding at least one of the plurality of sections of the first spline when the correlation value is less than the correlation threshold.

20 . The non-transitory computer readable medium of claim 17 , wherein the first spline is defined by at least one control point and at least one knot,
wherein the at least one knot represents a point where the polynomial functions piece together; and wherein the at least one control point represents a point on a line segment that defines a shape of the spline.

Assignees

• Here Global Bv

Inventors

• Dorum Ole Henry
• Lynch James D

Classifications

• G01C21/34

  Route searching; Route guidance · CPC title

• G01C21/32 Primary

  Structuring or formatting of map data · CPC title

• G01C21/3841

  Data obtained from two or more sources, e.g. probe vehicles · CPC title

• G01C21/3844 Primary

  Data obtained from position sensors only, e.g. from inertial navigation · CPC title

• G01C21/3819

  Road shape data, e.g. outline of a route · CPC title