Dynamic time series prediction of future traffic conditions

• US 7,813,870 B2
• Filed: 03/03/2006
• Issued: 10/12/2010
• Est. Priority Date: 03/03/2006
• Status: Expired due to Fees

• Current Assignee: Inrix Incorporated
• Original Assignee: Inrix Incorporated
• Inventors: Downs, Oliver B., Barker, Alec, Chapman, Craig H.
• Primary Examiner(s): Tran; Khoi
• Assistant Examiner(s): Figueroa; Jaime
• Application Number:
  US11/367,463
• Publication Number:
  US 20070208492A1
• Time in Patent Office: 1,684 Days
• Field of Search: 701/117, 701/119, 340/995.13
• US Class Current: 701/117
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/0968 Systems involving transmission of navigation instructions to the vehicle

Abstract

Techniques are described for generating predictions of future traffic conditions at multiple future times, such as by using probabilistic techniques to assess various input data while repeatedly producing future time series predictions for each of numerous road segments (e.g., in a real-time manner based on changing current conditions for a network of roads in a given geographic area). In some situations, one or more predictive Bayesian models and corresponding decision trees are automatically created for use in generating the future traffic condition predictions for each geographic area of interest, such as based on observed historical traffic conditions for those geographic areas. Predicted future traffic condition information may then be used in a variety of ways to assist in travel and for other purposes, such as to plan optimal routes through a network of roads based on predictions about traffic conditions for the roads at multiple future times.

Claims

1. A computer-readable storage medium whose contents include instructions that when executed configure a computing device to use predicted future traffic information for roads, by performing a method comprising:

receiving information indicating current traffic conditions at a first time of each of multiple road segments of one or more roads;

receiving information indicating other current conditions at the first time that affect traffic on the multiple road segments, the other current conditions including at least one of current weather conditions, current events that are scheduled to occur, and current schedules for school sessions;

using the information indicating the current traffic conditions at the first time and the other current conditions at the first time to, for each of multiple distinct future times after the first time, predict future traffic conditions for the one or more roads at that future time, the predicting of the future traffic conditions for the one or more roads for the multiple distinct future times being performed by the configured computing device and including generating multiple decision trees that represent the future traffic conditions for the one or more roads for the multiple distinct future times, each of the multiple future times being represented by at least one of the generated decision trees; and

providing information about the predicted future traffic conditions for at least one of the future times for use in facilitating travel on the one or more roads, the information about the predicted future traffic conditions for each of the at least one future times being obtained from the at least one generated decision tree that represents that future time.

2. The computer-readable storage medium of claim 1 wherein the predicting of the future traffic conditions for the one or more roads at the multiple future times further includes use of a predictive Bayesian network model for the one or more roads in order to predict a traffic congestion level at each of the multiple future times for each of at least one of the multiple road segments.

3. The computer-readable storage medium of claim 1 wherein the method further comprises identifying a route between a starting location and an ending location based at least in part on the predicted future traffic conditions, and wherein the providing of the information about the predicted future traffic conditions includes indicating the identified route to a user.

4. The computer-readable storage medium of claim 1 wherein the computer-readable medium is a memory of the computing device.

5. The computer-readable storage medium of claim 1 wherein the contents include one or more data structures for use in predicting future traffic information for roads, the one or more data structures representing a predictive Bayesian network model for the one or more roads and including multiple entries, some of the entries each corresponding to one of multiple road segments and one of multiple future times so as to store a predicted future traffic condition for that road segment at that future time, and other of the entries each corresponding to one of multiple current conditions that include current traffic conditions of each of the multiple road segments and one or more other current conditions so as to store input information for the predicting.

6. The computer-readable storage medium of claim 1 wherein the predicting of the future traffic conditions at the multiple future times is based on use of at least one predictive model that uses the indicated current traffic conditions and the indicated other current conditions as input.

7. The computer-readable storage medium of claim 6 wherein the at least one predictive model includes a Bayesian network.

8. The computer-readable storage medium of claim 1 wherein the multiple decision trees are generated to each represent a distinct combination of one of the road segments and one of the multiple future times.

9. The computer-readable storage medium of claim 6 wherein the at least one predictive model includes a probabilistic model.

10. The computer-readable storage medium of claim 1 wherein the generated multiple decision trees are further based at least in part on observed past traffic congestion levels on the road segments and on past traffic conditions and past other conditions that affected the past traffic congestion levels on the road segments.

11. The computer-readable storage medium of claim 1 wherein the method further comprises, after the predicting of the future traffic conditions for the one or more roads at the multiple future times, receiving updated current conditions information that is for a second time after the first time and that is distinct from the indicated current traffic conditions and the indicated other current conditions, automatically predicting new future traffic conditions for at least one of the one or more roads at each of at least some of the multiple future times based at least in part on the updated current conditions information for the second time, and using the predicted new future traffic conditions to facilitate travel on the one or more roads.

12. The computer-readable storage medium of claim 11 wherein the provided information about the predicted future traffic conditions are provided to one or more recipients for use in facilitating travel of the one or more recipients on the one or more roads, and wherein the using of the predicted new future traffic conditions to facilitate travel on the one or more roads includes providing updated information to at least one of the recipients.

13. The computer-readable storage medium of claim 1 wherein the indicated current traffic conditions of each of the multiple road segments include at least one of a measured average speed on the road segment, a measured traffic volume on the multiple road segment, and one or more times at which the road segment has been congested.

14. The computer-readable storage medium of claim 13 wherein the indicated other current conditions include the current weather conditions, the current events that are scheduled to occur, and the current schedules for school sessions.

15. The computer-readable storage medium of claim 14 wherein the indicated other current conditions further include one or more indications of a level of congestion for the multiple road segments, current expectations for future weather, current traffic accidents on the road segments, current construction activities on the road segments, a current time of day, and a current day of week.

16. The computer-readable storage medium of claim 13 wherein the indicated current traffic conditions of each of the multiple road segments further include indications of prior traffic conditions for the road segments.

17. The computer-readable storage medium of claim 1 wherein the received information indicating the current traffic conditions is obtained at least in part from a network of multiple traffic sensors such that each of at least some of the road segments each correspond to one or more of the multiple traffic sensors.

18. The computer-readable storage medium of claim 1 wherein the received information indicating the current traffic conditions is obtained at least in part from multiple vehicles traveling the one or more roads, each vehicle able to repeatedly determine vehicle travel data that includes at least one of location of the vehicle, speed of the vehicle, and travel direction of the vehicle, and to provide the determined vehicle travel data.

19. The computer-readable storage medium of claim 1 wherein the received information indicating the current traffic conditions is obtained at least in part from multiple users traveling the one or more roads, each user having a mobile device operative to provide geo-location data including at least one of location of the device and speed of the device.

20. The computer-readable storage medium of claim 1 wherein the indicated other current conditions include the current weather conditions, and wherein the received information indicating the other current conditions include at least one of an air temperature, a wind speed, a wind direction, an amount of precipitation measured over a period of time, and a level of sky cover.

21. The computer-readable storage medium of claim 1 wherein the indicated other current conditions include the current scheduled events, and wherein the received information indicating the other current conditions includes for each of the current scheduled events at least one associated time and at least one associated location.

22. The computer-readable storage medium of claim 1 wherein the indicated other current conditions include the current school session schedules, and wherein the received information indicating the other current conditions includes for each current school session schedule at least one associated time and at least one associated location of one or more schools.

23. The computer-readable storage medium of claim 1 wherein the providing of the information about the predicted future traffic conditions for use in facilitating travel on the one or more roads includes presenting the information to a user.

24. The computer-readable storage medium of claim 1 wherein the providing of the information about the predicted future traffic conditions for use in facilitating travel on the one or more roads includes providing the information to a third party service that uses the provided information to facilitate travel on the roads.

25. The computer-readable storage medium of claim 1 wherein the one or more roads include multiple roads, and wherein the providing of the information about the predicted future traffic conditions for use in facilitating travel on the multiple roads includes:

identifying multiple route options between a starting location and a destination location over the multiple roads, each of the route options including at least one of the road segments;

selecting at least one of the multiple route options as being preferred based at least in part on the predicted future traffic conditions; and

providing one or more indications of the selected route options.

26. The computer-readable storage medium of claim 1 wherein the providing of the information about the predicted future traffic conditions for use in facilitating travel on the one or more roads includes generating comparative information regarding the predicted future traffic conditions and other traffic conditions for the one or more roads, and providing one or more indications of the generated comparative information.

27. The computer-readable storage medium of claim 26 wherein the other traffic conditions for the one or more roads are determined normal traffic conditions for the one or more roads.

28. The computer-readable storage medium of claim 27 wherein the other traffic conditions for the one or more roads are determined using types of information designated by a user, and wherein the one or more indications of the generated comparative information are provided to the user.

29. The computer-readable storage medium of claim 27 wherein the other traffic conditions for the one or more roads are historical traffic conditions for the one or more roads for a designated prior time.

30. The computer-readable storage medium of claim 26 wherein the other traffic conditions for the one or more roads are historical average traffic conditions for the one or more roads.

31. The computer-readable storage medium of claim 1 wherein the method further comprises, for each of one or more of the multiple future times, automatically forecasting a future level of traffic congestion for each of one or more of the road segments at that future time based at least in part on the indicated other current conditions and not based on the indicated current traffic conditions, and providing one or more indications of at least some of the forecasted future levels of traffic congestion.

32. The computer-readable storage medium of claim 1 wherein the predicted future traffic conditions each include at least one associated vehicle speed.

33. The computer-readable storage medium of claim 1 wherein the one or more roads include multiple roads that are part of an interconnected network in a single geographic area.