Method for constructing and revising road maps in a database for a vehicle

• US 9,279,689 B2
• Filed: 01/04/2011
• Issued: 03/08/2016
• Est. Priority Date: 09/06/2007
• Status: Active Grant

• Current Assignee: GM Global Technology Operations LLC (General Motors Company)
• Original Assignee: GM Global Technology Operations LLC (General Motors Company)
• Inventors: Van Buer, Darrel J.
• Primary Examiner(s): Nguyen, John Q
• Assistant Examiner(s): King, Rodney P
• Application Number:
  US12/984,347
• Publication Number:
  US 20110099171A1
• Time in Patent Office: 1,890 Days
• Field of Search: 701/201, 701/202, 701207-210, 701/217, 701/412, 701/418, 701/430, 701/450, 701/532, 701/533
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3815 Road data
• CPC Class Codes: G01C 21/3837 Data obtained from a single source
• CPC Class Codes: G01C 21/3844 Data obtained from position sensors only, e.g. from inertial navigation

Abstract

A method for constructing and revising road maps in a vehicle map database using vehicle location signals to provide traffic flow information for recognized vehicle patterns from past vehicle travel. The method includes identifying vehicle travel segments as a series of exemplar points from the location signals. Exemplar points in each travel segment are eliminated to define the travel segment by a beginning exemplar point and an ending exemplar point. A potential ending exemplar point may be redefined if an average location of the exemplar points from a line connecting the beginning point and the potential ending point is outside of a threshold distance. The travel segments are stored in a database, where each stored travel segment includes a travel time. The method compares new vehicle travel segments to the stored vehicle travel segments to identify a match, and then revise the vehicle travel time for the stored travel segments.

Claims

1. A method for constructing and revising road maps in a database for a vehicle, said method comprising:

identifying vehicle travel segments of the vehicle as a series of exemplar points using signals from a system that provides vehicle position wherein condensed versions of trip logs create the vehicle travel segments;

processing the condensed versions of trip logs to provide map construction and map database refinement between data collection and correlation;

eliminating intermediate exemplar points in each travel segment to define the travel segment by a beginning exemplar point and an ending exemplar point of the travel segment;

storing the travel segments in the database;

identifying a travel time associated with each stored travel segment;

comparing new vehicle travel segments to the stored vehicle travel segments to identify matches between the new travel segments and the stored travel segments, wherein comparing the new vehicle travel segments to the stored vehicle travel segments includes comparing travel segments that only partially overlap;

revising the travel time of a stored travel segment if a new travel segment does match a stored travel segment; and

self-organizing the database such that a statistical profile that captures the road conditions experienced by the vehicle are developed, wherein private roads, recently constructed roads and changes to roads are automatically recorded.

2. The method according to claim 1 wherein comparing new vehicle travel segments to the stored vehicle travel segments includes comparing and matching new travel segments to stored travel segments where a new travel segment is shorter than a stored travel segment and has different end points, or the stored travel segment is shorter than a new travel segment and has different end points.

3. The method according to claim 1 wherein comparing new vehicle travel segments to the stored vehicle travel segments includes projecting points on the new travel segment to the stored travel segment using a line perpendicular to the stored travel segment.

4. The method according to claim 3 wherein comparing new travel segments to the stored travel segments includes projecting points on the new travel segment to the stored travel segment that are within a predetermined distance of the stored travel segment.

5. The method according to claim 3 wherein comparing new vehicle travel segments to the stored vehicle travel segments includes projecting a point from the new vehicle travel segment to the stored travel segment that identifies a curve or bend in the travel segment.

6. The method according to claim 1 further comprising identifying locations in the stored vehicle travel segments that define travel speeds where the flow of traffic changes using historical data of the travel segments that includes time, speed and location, and separating the stored travel segments into sub-segments at the locations that define travel speeds where the flow of traffic changes.

7. The method according to claim 6 wherein the location where the flow of traffic changes identifies a traffic signal location.

8. The method according to claim 6 wherein identifying locations where the flow of traffic changes include using the exemplar points in the travel segment to identify how fast the vehicle is traveling.

9. The method according to claim 1 wherein the system that provides the vehicle location signals is a GPS system.

10. The method according to claim 1 wherein the beginning exemplar point is a location where the vehicle is turned on or determined from a vehicle stay at a fixed point for a predetermined period of time.

11. A method for constructing and revising road maps in a database for a vehicle, said method comprising:

determining a set of travel segments representing exemplar points of travel along a particular vehicle route;

identifying a series of travel points wherein each travel point represents a position of the vehicle;

determining a beginning point of travel and an ending point of travel, wherein the beginning point of travel is a first exemplar point;

calculating a maximum deviation relative to a line segment between the first exemplar point and the ending point;

determining whether the ending point is a next exemplar point based on the maximum deviation;

storing the travel segments in the database;

comparing new vehicle travel segments to the stored vehicle travel segments to identify matches between the new travel segments and the stored travel segments, wherein comparing the new vehicle travel segments to the stored vehicle travel segments includes comparing travel segments that only partially overlap;

revising statistical data associated with the stored vehicle travel segment if a new travel segment is found to match a stored travel segment; and

wherein the statistical data is organized such that a statistical profile that captures the road conditions experienced by the vehicle are developed by identifying locations in the stored travel segments that define travel speeds where the flow of traffic changes using historical data of the travel segments that includes time, speed and location, and separating the stored travel segments into sub-segments to create a statistical profile that is customized for the sub-segments.

12. The method according to claim 11 further including calculating a second line segment representing an average distance between each travel points relative to the line segment between the first exemplar point and the ending point.

13. The method according to claim 12 further including eliminating the ending point as the next exemplar point if the second line segment exceeds the maximum deviation.

14. The method according to claim 12 further including selecting a new ending point if the second line segment exceeds the maximum deviation.

15. The method according to claim 12 further including establishing the ending point as the next exemplar point and eliminating intermediate travel point therebetween if the second line segment does not exceed the maximum deviation.

16. A method for constructing and revising road maps in a database for a vehicle, said method comprising:

identifying vehicle travel segments of the vehicle as a series of exemplar points from a system that provides vehicle position;

eliminating intermediate exemplar points in each travel segment to define the travel segment by a beginning exemplar point and an ending exemplar point of the travel segment;

storing the travel segments in the database;

identifying a travel time associated with each stored travel segment;

separating the travel segments into sub-segments based on locations in the travel segments where speed often changes using historical data of the travel segments that includes time, speed and location; and

creating and dynamically revising the road maps to increase the accuracy of the view of locations and stretches of road that have distinct speed profiles to produce a realistic traffic assessment capable of discriminating between typical and unusual traffic.

17. The method according to claim 16 wherein the location where the speed often changes identifies a traffic signal location.

18. The method according to claim 16 wherein separating the travel segments includes using the exemplar points in the travel segment to identify how fast the vehicle is traveling.

19. The method according to claim 16 further comprising self-organizing the database such that a statistical profile that captures the road conditions experienced by the vehicle are developed, wherein private roads, recently constructed roads and changes to roads are automatically recorded.