Methods and Systems for Creating Digital Street Network Database

• US 20120095682A1
• Filed: 05/21/2010
• Published: 04/19/2012
• Est. Priority Date: 06/16/2009
• Status: Active Grant

• Current Assignee: Tomtom Global Content B.V (TomTom NV)
• Original Assignee: Tomtom Global Content B.V (TomTom NV)
• Inventors: Wilson, Christopher Kenneth Hoover
• Granted Patent: US 9,377,313 B2
• Time in Patent Office: Days
• US Class Current: 701/532
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 30/0953 the prediction being responsive to vehicle dynamic parameters
• CPC Class Codes: B60W 40/10 related to vehicle motion
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01C 21/3819 Road shape data, e.g. outline of a route
• CPC Class Codes: G01C 21/3841 Data obtained from two or more sources, e.g. probe vehicles
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: Y02T 10/84 Data processing systems or methods, management, administration

Abstract

In a method for creating a digital representation of a transportation network location measurement data is acquired, and a plurality of maneuvers between choke points are generated from the location measurement data. The digital representation of the transportation network is then created and stored based on the plurality of maneuvers.

Claims

1. A method for determining features of a digital representation of a transportation network, the method comprising:

acquiring a plurality of probe trace data for an area of interest;

determining a plurality of choke points in relation to the probe trace data, each of said choke points comprising a non-decision point falling between adjacent decision points in said probe trace data;

generating a plurality of maneuvers from said probe trace data, each of said maneuvers comprising a mean path of a plurality of probe trace data that traverse the same path between adjacent choke points; and

determining and storing features of the digital representation of the transportation network based on the plurality of maneuvers.

2. The method of claim 1, wherein each of the decision points is a point at which the cluster of probe trace data following the same path diverges to one of several paths, or a point at which the cluster of probe trace data converges to a single path.

4. The method of claim 1, wherein the features of the digital representation of the transportation network are stored as a polyline representation of the plurality of maneuvers.

5. The method of claim 4, wherein the transportation network is a vehicle network in which a maneuver represents a single lane of street segments, the street segments including a plurality of lanes.

6. The method of claim 1, wherein the features of the digital representation of the transportation network are stored as a mathematical curve representation of the plurality of maneuvers.

7. The method of claim 6, wherein the transportation network is a vehicle network in which a maneuver represents a single lane of street segments, the street segments including a plurality of lanes.

9. The method of claim 1, wherein the choke points are associated with characteristics of the probe trace data, the characteristics including relative accuracy of the probe trace data and at least one of direction of movement, speed, and type of location probe from which the probe trace data are taken.

10. The method of claim 1, further comprising:

clustering the probe trace data for location probes following a same path;

determining decision points in the transportation network by comparing the clusters of probe trace data;

creating choke points based on the clusters of probe trace data and the determined decision points; and

wherein

the plurality of maneuvers are generated by examining clustered segments of the transportation network between adjacent ones of the created choke points.

11. The method of claim 10, wherein the clustered segments of the transportation network are stored as the features of the digital representation of the transportation network.

12. The method of claim 10, wherein the decision points are points at which the clusters of the location measurement data converge or diverge.

13. The method of claim 10, wherein the examining of the plurality of clustered segments of the transportation network comprises:

combining the clustered segments to determine a mean path between adjacent ones of the created choke points.

14. The method of claim 1, further comprising:

clustering the location measurement data for location probes following a same path;

determining decision points in the transportation network by comparing the clusters of location measurement data;

creating choke points based on the clusters of location measurement data and the determined decision points;

fitting a mathematical curve to combined location measurement data between each pair of adjacent choke points; and

wherein

the fitted and combined location measurement data are stored as the features of the digital representation of the transportation network.

15. An Advance Driver Assistance System (ADAS) comprising:

the features of the digital representation of the transportation network created according to the method of claim 1.

27. A computer program product, comprising a computer readable medium having a computer readable program code embodied therein, said computer readable program code containing instructions that when executed by a processor of a computer system implement the method of claim 1.

3. (canceled)

8. (canceled)

16. A system for determining features of a digital representation of a transportation network, the system comprising:

a receiver for receiving a plurality of probe trace data for an area of interest; and

a processor configured to;

determine a plurality of choke points in relation to said probe trace data, each of said choke points comprising a non-decision point falling between adjacent decision points in said probe trace data;

generate a plurality of maneuvers from said probe trace data, each of said maneuvers comprising a mean path of a plurality of probe trace data that traverses the same path between adjacent choke points; and

determining and storing the features of the digital representation of the transportation network based on said plurality of maneuvers.

17-26. -26. (canceled)