Traffic Aggregation and Reporting in Real-Time

• US 20150348406A1
• Filed: 05/29/2014
• Published: 12/03/2015
• Est. Priority Date: 05/29/2014
• Status: Active Grant

• Current Assignee: HERE Global B.V. (HERE Holding Corporation)
• Original Assignee: HERE Global B.V. (HERE Holding Corporation)
• Inventors: Fowe, James Adeyemi
• Granted Patent: US 9,934,683 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station

Abstract

Systems, apparatuses, and methods are provided for aggregating and reporting real-time traffic conditions. Real-time traffic data for a network is collected. A request from a customer is received for a percentage of the real-time traffic data in the network, the percentage being greater than 0% and less than 100%. The real-time traffic data in the network is aggregated. The aggregated real-time traffic data is reported to the customer.

Claims

1. A method comprising:

collecting real-time traffic data for a network;

receiving a request from a customer for a percentage of the real-time traffic data in the network, the percentage being greater than 0% and less than 100%;

aggregating, using a processor, the real-time traffic data in the network; and

reporting the aggregated real-time traffic data to the customer.

2. The method of claim 1, wherein the aggregating comprises prioritizing the real-time traffic data for a plurality of road segments based on a naï

ve algorithm.

3. The method of claim 2, wherein the naï

ve algorithm determines a cost function for each road segment of the plurality of road segments by multiplying a traffic density by a difference of a real-time average speed and a historic average speed, and wherein the prioritizing is based on the cost functions for the plurality of road segments.

4. The method of claim 2, wherein the naï

ve algorithm determines a cost function for each road segment of the plurality of road segments by multiplying a traffic density by a historic average speed by a difference of a real-time average speed and the historic average speed, and wherein the prioritizing is based on the cost functions for the plurality of road segments.

5. The method of claim 1, wherein the aggregating comprises prioritizing the real-time traffic data for a plurality of connected road segments based on a minimum spanning tree algorithm.

6. The method of claim 5, wherein the minimum spanning tree algorithm determines a cost function for each road segment of the plurality of connected road segments, wherein:

7. The method of claim 5, wherein the minimum spanning tree algorithm determines a cost function for each road segment of the plurality of connected road segments, wherein:

8. The method of claim 7, wherein w1>

w2.

9. The method of claim 7, wherein w2>

w1.

10. The method of claim 1, wherein the reporting comprises encoding the aggregated real-time traffic data in a TPEG-ML file.

11. The method of claim 1, wherein the percentage of real-time traffic data is less than 10%.

12. A method comprising:

collecting real-time traffic data for a network;

receiving a request from a customer for a percentage of the real-time traffic data in the network, the percentage being greater than 0% and less than 100%;

aggregating, using a processor, the real-time traffic data in the network by prioritizing the real-time traffic data for a plurality of road segments based on a minimum spanning tree algorithm; and

reporting the aggregated real-time traffic data to the customer in a TPEG-ML file,

wherein the minimum spanning tree algorithm determines a cost function for each road segment of the plurality of road segments, wherein;

13. 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 perform;

collect real-time traffic data for a network;

receive a request from a customer for a percentage of the real-time traffic data in the network, the percentage being greater than 0% and less than 100%;

aggregate, using a processor, the real-time traffic data in the network; and

report the aggregated real-time traffic data to the customer.

14. The apparatus of claim 13, wherein the aggregating comprises prioritizing the real-time traffic data for a plurality of road segments based on a naï

ve algorithm,

wherein the naï

ve algorithm determines a cost function for each road segment of the plurality of road segments by multiplying a traffic density by a difference of a real-time average speed and a historic average speed, and wherein the prioritizing is based on the cost functions for the plurality of road segments.

15. The apparatus of claim 13, wherein the aggregating comprises prioritizing the real-time traffic data for a plurality of road segments based on a naï

ve algorithm,

wherein the naï

ve algorithm determines a cost function for each road segment of the plurality of road segments by multiplying a traffic density by a historic average speed by a difference of a real-time average speed and the historic average speed, and wherein the prioritizing is based on the cost functions for the plurality of road segments.

16. The apparatus of claim 13, wherein the aggregating comprises prioritizing the real-time traffic data for a plurality of connected road segments based on a minimum spanning tree algorithm,

wherein the minimum spanning tree algorithm determines a cost function for each road segment of the plurality of connected road segments, wherein:

17. The apparatus of claim 13, wherein the aggregating comprises prioritizing the real-time traffic data for a plurality of connected road segments based on a minimum spanning tree algorithm,

wherein the minimum spanning tree algorithm determines a cost function for each road segment of the plurality of connected road segments, wherein:

18. The apparatus of claim 17, wherein w1>

w2.

19. The apparatus of claim 17, wherein w2>

w1.

20. The apparatus of claim 13, wherein the reporting comprises encoding the aggregated real-time traffic data in a TPEG-ML file.

21. The apparatus of claim 13, wherein the percentage of real-time traffic data is less than 10%.