System and method for predicting travel time for a travel route

• US 20070013551A1
• Filed: 08/15/2006
• Published: 01/18/2007
• Est. Priority Date: 03/05/2002
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Triangle Software LLC (Pelmorex, Inc.)
• Inventors: Gueziec, Andre
• Granted Patent: US 7,508,321 B2
• Time in Patent Office: Days
• US Class Current: 340/905
• CPC Class Codes: G01C 21/30 Map- or contour-matching
• CPC Class Codes: G01C 21/3407 specially adapted for specific applications
• 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 21/36 Input/output arrangements for on-board computers
• CPC Class Codes: G01C 21/3694 Output thereof on a road map
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G08G 1/0125 Traffic data processing
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/093 Data selection, e.g. prioritizing information, managing message queues, selecting the information to be output
• CPC Class Codes: G08G 1/0967 Systems involving transmission of highway information, e.g. weather, speed limits transmission of navigation instructions to the vehicle G08G1/0968
• 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 1/09675 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 1/096816 where the complete route is transmitted to the vehicle at once
• CPC Class Codes: G08G 1/096822 where the segments of the route are transmitted to the vehicle at different locations and times
• CPC Class Codes: G08G 1/096827 where the route is computed onboard
• CPC Class Codes: G08G 1/096866 where the complete route is shown to the driver
• CPC Class Codes: G08G 1/096888 where input information is obtained using learning systems, e.g. history databases
• CPC Class Codes: H04B 1/3822 specially adapted for use in vehicles H04B1/3827 takes precedence
• CPC Class Codes: H04W 4/025 : using location based information parameters
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services

Abstract

A system for predicting a travel time for a traffic route is disclosed. The traffic route comprises one or more road segments. A predicted travel time for each of those segments is calculated based, in part, on traffic speed data for each of the one or more road segments. A total travel time is then calculated for the route, the total travel time including a predicted travel time for each of the one or more road segments

Claims

1. A system for predicting a travel time for a traffic route, comprising:

a data source comprising data associated with a plurality of road segments, the plurality of road segments making up at least a portion of the traffic route;

a forecast engine configured to determine a predicted travel time for each of the plurality of road segments based on at least the data for each of the plurality of road segments; and

a publishing engine configured to publish a predicted travel time for the traffic route, the predicted travel time comprising a total travel time for each of the plurality of road segments making up the traffic route.

2. The system of claim 1, wherein the data is traffic speed data.

3. The system of claim 2, wherein the traffic speed data associated with each of the plurality of road segments is further associated with a particular time interval for each of the plurality of road segments.

4. The system of claim 3, wherein the forecast engine is further configured to determine a predicted travel time for each of the plurality of road segments based on at least the traffic speed data for each of the plurality of road segments in conjunction with a particular time interval.

5. The system of claim 3, further comprising a traveler data processor configured to associate traffic speed data with each of the plurality of road segments in conjunction with a particular time interval.

6. The system of claim 4, wherein the particular time interval comprises an expected time at which a traveler will reach each of the plurality of road segments.

7. The system of claim 2, wherein the traffic speed data is real-time traffic speed data.

8. The system of claim 7, wherein the real-time traffic speed data for each of the plurality of road segments is archived for future association with each of the plurality of road segments.

9. The system of claim 2, wherein the traffic speed data comprises information associated with a non-traffic event that influences traffic speed for at least one of the plurality of road segments making up the traffic route.

10. The system of claim 3, wherein the particular time interval for the traffic route is further associated with a particular time of day.

11. The system of claim 3, wherein the predicted travel time for the particular time interval is published as a graphical representation of predicted travel time versus departure time.

12. The system of claim 11, wherein the particular time interval is an entire duration of a trip utilizing the traffic route.

13. The system of claim 2, wherein the predicted travel time for at least one of the plurality of road segments comprises a default value derived from the predicted travel time of one or more road segments surrounding the at least one of the plurality of road segments.

14. The system of claim 11, wherein the publishing engine is further configured to publish a recommended departure time based on one or more travel patterns identified in the graphical representation.

15. The system of claim 14, wherein the recommended departure time is identified based on at least a point of maximum slope in the graphical representation.

16. The system of claim 5, wherein the traveler data processor is further configured to combine real-time traffic speed data for one of the plurality of road segments with historical speed data for the one of the plurality of road segments, the traveler data processor further configured to update the historical speed data for the one of the plurality of road segments, the one of the plurality of road segments being associated with a particular time interval, based on the combined traffic speed data.

24. The system of claim 10, wherein the particular time interval for the traffic route is associated with a particular day of the week.

25. The system of claim 10, wherein the particular time interval for the traffic route is associated with a series of days.

17. A method for predicting a travel time for a traffic route, comprising:

identifying one or more road segments making up the traffic route;

identifying a predicted travel time for each of the one or more road segments;

wherein the predicted travel time is based on at least data for each of the one or more road segments; and

calculating a total travel time for the traffic route, the total travel time comprising the predicted travel time for each of the one or more road segments.

18. The method of claim 17, wherein the data is traffic speed data.

19. The method of claim 18, wherein the predicted travel time for each of the one or more road segments is further associated with a particular time interval, the predicted travel time for each of the one or more road segments based on at least traffic speed data for each of the one or more road segments in conjunction with a particular time interval.

20. The method of claim 19, wherein the particular time interval comprises an expected time at which a traveler will reach each of the one or more road segments.

21. The method of claim 20, wherein the total travel time for the traffic route is published as a graphical representation of travel time versus departure time.

22. The method of claim 21, further comprising determining a recommended departure time based on one or more travel patterns identified in the published graphical representation, wherein the recommended departure time is identified based on a point of a maximum slope in the graphical representation.

23. A computer-readable medium having embodied thereon at least one program, the at least one program being executable by a processor to perform a method for predicting a travel time for a traffic route, the method comprising:

identifying one or more road segments making up the traffic route;

identifying a predicted travel time for each of the one or more road segments;

wherein the predicted travel time is based on at least traffic speed data for each of the one or more road segments; and

calculating a total travel time for the traffic route, the total travel time comprising the predicted travel time for each of the one or more road segments.