Methods and systems for creating digital street network database

• US 9,377,313 B2
• Filed: 05/21/2010
• Issued: 06/28/2016
• Est. Priority Date: 06/16/2009
• Status: Active Grant

• Current Assignee: Tomtom Global Content B.V (TomTom NV)
• Original Assignee: Tomtom North America Incorporated (TomTom NV)
• Inventors: Wilson, Christopher Kenneth Hoover
• Primary Examiner(s): To, Tuan C.
• Assistant Examiner(s): MOTT, GENNA M
• Application Number:
  US13/378,717
• Publication Number:
  US 20120095682A1
• Time in Patent Office: 2,230 Days
• Field of Search: 703/2, 340/988, 340/995.14, 340/995.2, 702/5, 702/150, 701/117, 701/400, 701/408, 701/409, 701/411, 701/450, 701/461, 701/468, 701/469, 701/495, 701/517, 701/532, 707/E17.018
• US Class Current: 1/1
• 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, said features comprising geometry of the transportation network and attributes associated therewith, the method comprising:

acquiring, from one or more location sensors, a plurality of probe trace data for an area of interest, said probe trace data comprising a series of sequential location measurements acquired by said one or more location sensors;

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

determining, by the processor, features of the digital representation of the transportation network based on the plurality of maneuvers;

updating, by the processor, the digital representation of the transportation network by storing the determined features, wherein geometry of the transportation network in the updated digital representation is stored as a series of the plurality of maneuvers; and

providing, by the processor, the updated digital representation for use by one or more of a navigation device and an advanced driver assistance system (ADAS).

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

3. The method of claim 1, wherein the geometry of the digital representation of the transportation network is stored as a polyline representation of the plurality of maneuvers.

4. The method of claim 3, 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.

5. The method of claim 1, wherein the geometry of the digital representation of the transportation network is stored as a mathematical curve representation of the plurality of maneuvers.

6. The method of claim 5, 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.

7. 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.

8. 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; and

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

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

9. The method of claim 8, wherein the clustered segments of the transportation network are stored as the features of the digital representation of the transportation network.

10. The method of claim 8, wherein the decision points are points at which clusters of the probe trace data converge or diverge.

11. The method of claim 8, 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.

12. 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

fitting a mathematical curve to combined probe trace data between each pair of adjacent choke points,

wherein the fitted and combined probe trace data are stored as the features of the digital representation of the transportation network.

13. A system for determining features of a digital representation of a transportation network, said features comprising geometry of the transportation network and attributes associated therewith, the system comprising:

a receiver for receiving a plurality of probe trace data for an area of interest, said probe trace data comprising a series of sequential location measurements acquired by one or more location sensors; 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;

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

updating the digital representation of the transportation network by storing the determined features, wherein geometry of the transportation network in the updated digital representation is stored as a series of the plurality of maneuvers; and

providing the updated digital representation for use by one or more of a navigation device and an advanced driver assistance system (ADAS).

14. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor of a computer system, cause the processor to perform a method comprising:

acquiring, from one or more location sensors, a plurality of probe trace data for an area of interest, said probe trace data comprising a series of sequential location measurements acquired by said one or more location sensors;

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

determining, by the processor, features of the digital representation of the transportation network based on the plurality of maneuvers;

wherein said features comprise geometry of the transportation network and attributes associated therewith; and

updating, by the processor, the digital representation of the transportation network by storing the determined features, wherein geometry of the transportation network in the updated digital representation is stored as a series of the plurality of maneuvers; and

providing, by the processor, the updated digital representation for use by one or more of a navigation device and an advanced driver assistance system (ADAS).