Traffic Data Encoding Using Fixed References

• US 20170287328A1
• Filed: 03/29/2017
• Published: 10/05/2017
• Est. Priority Date: 03/29/2016
• Status: Abandoned Application

• Current Assignee: Sirius XM Radio Inc. (Liberty Media Corporation)
• Original Assignee: Sirius XM Radio Inc. (Liberty Media Corporation)
• Inventors: French, Leslie John
• Application Number:
  US15/473,113
• Publication Number:
  US 20170287328A1
• Time in Patent Office: Days
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/091 Traffic information broadcasting broadcasting communication H04H
• CPC Class Codes: G08G 1/092 Coding or decoding of the information
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/09675 where a selection from the received information takes place in the vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/096791 where the origin of the information is another vehicle

Abstract

A method is provided for encoding traffic incident and flow data using target map locations, such as OpenStreetMap (OSM) locations directly, rather than going through a conversion stage. In exemplary embodiments, the method can include selecting a set of fixed, identifiable locations along a roadbed, matching these to a target map, generating flow vectors in the target map'"'"'s referencing model, and deliver only target map location data to the external application. Non-point location data such as incidents can also be represented using the same scheme, using an offset along a previously defined path for the start and end points.

Claims

1. A computer-implemented method of encoding traffic data, the method comprising:

at a computing device having a data processor and computer memory;

matching a set of fixed locations along a roadbed to a target map;

generating flow vectors representing traffic data using the fixed locations of the target map; and

;

delivering the generated flow vectors to a receiver to enable the receiver to render the represented traffic data based on the generated flow vectors.

2. A computer-implemented method according to claim 1, further comprising receiving vehicle telematics data from a plurality of probes, and aggregating the received vehicle telematics data to generate current traffic data.

3. A computer-implemented method according to claim 2, wherein the traffic data is generated based at least in part on a traffic model and the current traffic data.

4. A computer-implemented method according to claim 1, wherein the traffic data is generated based at least in part on a traffic model.

5. A computer-implemented method according to claim 1, wherein the generating of flow vectors include translating coordinates of intermediate points between the fixed locations as vectors with respect to the fixed locations.

6. A computer-implemented method according to claim 1, wherein the target map is OpenStreetMap (OSM).

7. A computer-implemented method according to claim 6, wherein the fixed locations are represented using Nodes and Ways.

8. A computer-implemented method according to claim 1, wherein the set of locations are intersections.

9. A traffic encoding system comprising:

a processor;

a memory coupled to the processor; and

a program stored in the memory, the program including instructions for;

matching a set of fixed locations along a roadbed to a target map;

generating flow vectors representing traffic data using the fixed locations of the target map; and

;

delivering the generated flow vectors to a receiver to enable the receiver to render the represented traffic data based on the generated flow vectors.

10. A traffic encoding system according to claim 9, wherein the instructions further comprises receiving vehicle telematics data from a plurality of probes, and aggregating the received vehicle telematics data to generate current traffic data.

11. A traffic encoding system according to claim 10, wherein the traffic data is generated based at least in part on a traffic model and the current traffic data.

12. A traffic encoding system according to claim 11, wherein the traffic data is generated based at least in part on a traffic model.

13. A traffic encoding system according to claim 9, wherein the generating of flow vectors include translating coordinates of intermediate points between the fixed locations as vectors with respect to the fixed locations.

14. A traffic encoding system according to claim 9, wherein the target map is OpenStreetMap (OSM).

15. A traffic encoding system according to claim 14, wherein the fixed locations are represented using Nodes and Ways.

16. A traffic encoding system according to claim 9, wherein the fixed locations are intersections.

17. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions that, when executed by a data processor, causes the data processor to:

match a set of fixed locations along a roadbed to a target map;

generate flow vectors representing traffic data using the fixed locations of the target map; and

;

deliver the generated flow vectors to a receiver to enable the receiver to render the represented traffic data based on the generated flow vectors.

18. A non-transitory computer-readable storage medium according to claim 17, wherein the instructions further causes the data processor to receive vehicle telematics data from a plurality of probes, and aggregating the received vehicle telematics data to generate current traffic data.

19. A non-transitory computer-readable storage medium according to claim 17, wherein the traffic data is generated based at least in part on a traffic model and the current traffic data.

20. A non-transitory computer-readable storage medium according to claim 17, wherein the traffic data is generated based at least in part on a traffic model.

21. A non-transitory computer-readable storage medium according to claim 17, wherein the generating of flow vectors include translating coordinates of intermediate points between the fixed locations as vectors with respect to the fixed locations.

22. A non-transitory computer-readable storage medium according to claim 17, wherein the target map is OpenStreetMap (OSM).

23. A non-transitory computer-readable storage medium according to claim 22, wherein the fixed locations are represented using Nodes and Ways.

24. A non-transitory computer-readable storage medium according to claim 17, wherein the fixed locations are intersections.