System and method for determining a prediction of average speed for a segment of roadway

• US 7,702,452 B2
• Filed: 09/12/2008
• Issued: 04/20/2010
• Est. Priority Date: 07/25/2003
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Triangle Software LLC (Pelmorex, Inc.)
• Inventors: Kantarjiev, Christopher, Hubbard, Jonathan, Tash, Jonathan
• Primary Examiner(s): Beaulieu, Yonel
• Application Number:
  US12/283,748
• Publication Number:
  US 20090118996A1
• Time in Patent Office: 585 Days
• Field of Search: 701200-204, 701117-119, 701/25
• US Class Current: 701/119
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/3453 Special cost functions, i.e. other than distance or default speed limit of road segments
• CPC Class Codes: G01C 21/3492 employing speed data or traffic data, e.g. real-time or historical traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G01C 21/3667 Display of a road map G01C21/3614 takes precedence; guidance using 3D or perspective road maps G01C21/3635
• CPC Class Codes: G01C 21/3679 Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities G01C21/3611 takes precedence
• CPC Class Codes: G01C 21/3691 Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions arrangements for giving variable traffic instructions G08G1/09
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0145 for active traffic flow control

Abstract

The present invention provides a system and method for determining the necessary departure time to allow for an on-time or desired arrival time at a particular location over a particular route based on the evaluation of historic, present, and predicted road conditions.

Claims

1. A system for determining a prediction of average speed comprising:

a data aggregation server configured to manage a plurality of data sets;

a road speed prediction engine executable by a processor to generate a traffic pattern for a particular segment of roadway at a given time of day and a particular day of the week based on the plurality of data sets, and generate a prediction of average speed; and

memory configured to store the prediction of average speed.

2. The system of claim 1, wherein the plurality of data sets includes delayed batch traffic data.

3. The system of claim 1, wherein the plurality of data sets includes real time traffic data.

4. The system of claim 1, wherein the prediction of average speed includes a long-term prediction of average speed.

5. The system of claim 1, wherein the prediction of average speed includes a short-term prediction of average speed.

6. The system of claim 1, further comprising a routing engine configured to determine a departure time and route to arrive at a destination at a given time while traveling a known number of miles at the prediction of average speed.

7. The system of claim 2, wherein the delayed batch traffic data includes historically observed road speeds.

8. The system of claim 2, wherein the delayed batch traffic data includes weather information.

9. The system of claim 2, wherein the delayed batch traffic data includes an incident report.

10. The system of claim 2, wherein the delayed batch traffic data includes a traffic sensor loop report.

11. The system of claim 2, wherein the delayed batch traffic data speed includes a highway patrol report.

12. The system of claim 2, wherein the delayed batch traffic data includes verified data matched to road segments.

13. The system of claim 2, wherein the delayed batch traffic data includes a satellite data report.

14. The system of claim 2, wherein the delayed batch traffic data includes a report from a driver in traffic with a cellular phone.

15. The system of claim 7, wherein the historically observed road speed includes road construction data for a particular segment of roadway at a given time of day and day of week.

16. The system of claim 7, wherein the historically observed road speed includes accident data for a particular segment of roadway at a given time of day and day of week.

17. The system of claim 3, wherein the real time traffic data includes a traffic sensor report.

18. The system of claim 3, wherein the real time traffic data includes a traffic helicopter report.

19. The system of claim 3, wherein the real time traffic data includes a highway patrol report.

20. The system of claim 3, wherein the real time traffic data includes a live-news feeds report.

21. The system of claim 3, wherein the real time traffic data includes a satellite data report.

22. The system of claim 3, wherein the real time traffic data includes a report from a driver in traffic with a cellular phone.

23. A method for determining a prediction of average speed comprising:

aggregating a plurality of data sets;

generating a traffic pattern for a particular segment of roadway at a given time of day and a particular day of the week based on the plurality of data sets;

predicting an average speed for the particular segment of roadway at the given time of day and the particular day of the week; and

storing the prediction of average speed.

24. The method of claim 23, wherein the average speed is a long-term prediction of average speed.

25. The method of claim 23, wherein the average speed is a short-term prediction of average speed.

26. The method of claim 23, wherein the traffic pattern includes road construction data for the particular segment of roadway at the given time of day and the particular day of the week.

27. The method of claim 23, wherein the traffic pattern includes real-time accident data for the particular segment of roadway at the given time of day and the particular day of the week.

28. The method of claim 23, further comprising delivering the traffic pattern in response to a specific request from the road speed prediction engine.

29. The method of claim 23, further comprising delivering the traffic pattern in response to a routinely scheduled transfer of data.

30. The method of claim 23, further comprising determining a departure time and route to arrive at a destination at a given time while traveling a known number of miles at the prediction of average speed.

31. A computer-readable storage medium having embodied thereon a program, the program being executable by a computer processor to perform a method for determining a prediction of average speed for a particular segment of roadway, the method comprising:

aggregating a plurality of data sets;

generating a traffic pattern for a particular segment of roadway at a given time of day and a particular day of the week based on the plurality of data sets;

predicting an average speed for the particular segment of roadway at the given time of day and the particular day of the week; and

storing the prediction of average speed.