Method for predicting a travel time for a traffic route

• US 8,537,033 B2
• Filed: 07/30/2012
• Issued: 09/17/2013
• Est. Priority Date: 03/05/2002
• Status: Expired due to Term

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Triangle Software LLC (Pelmorex, Inc.)
• Inventors: Gueziec, Andre
• Primary Examiner(s): Nguyen, Tai T
• Application Number:
  US13/561,327
• Publication Number:
  US 20120290204A1
• Time in Patent Office: 414 Days
• Field of Search: 340/905, 340/906, 340/907, 340/988, 340/994, 340/995.24, 340/995.27, 701/410, 701/423, 701/438, 701/461, 701/468
• 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 method for predicting a travel time for a traffic route, the method comprising:

associating real-time traffic speed data with historical speed data to generate combined traffic speed data for a plurality of road segments during a particular time interval;

determining a predicted travel time for a plurality of road segments based on a plurality of travel patterns, wherein the plurality of travel patterns include at least;

the combined traffic speed data for the plurality of road segments during a particular time interval, and

non-traffic event data that influences traffic speed for at least one of the road segments;

publishing a predicted travel time for the traffic route, wherein the predicted travel time includes a total travel time for each of the plurality of road segments making up the traffic route;

publishing a recommended departure time based on the plurality of travel patterns and predicted travel time; and

automatically updating the publication of the predicted travel time in response to changes in the plurality of travel patterns.

2. The method of claim 1, wherein the publication of predicted travel time includes a graphic representation of the road segments.

3. The method of claim 2, wherein the graphic representation of the road segments is three-dimensional.

4. The method of claim 1, wherein the recommended departure time is identified based on at least a point of maximum slope in the graphical representation.

5. The method of claim 1, wherein the time interval is associated with a particular day of the week.

6. The method of claim 5, wherein the time interval is further associated with a particular time of the day.

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

a data source comprising real-time speed data;

a traveler data processor that combines the real-time speed data with historical speed data to generate combined traffic speed data for a plurality of road segments during a particular time interval;

a forecast engine stored in memory and executable to determine a predicted travel time for a plurality of road segments based on a plurality of travel patterns, wherein the plurality of travel patterns include at least;

the combined traffic speed data for the plurality of road segments during a particular time interval, and

non-traffic event data that influences traffic speed for at least one of the road segments; and

a publishing engine stored in memory and executable to;

publish a predicted travel time for the traffic route, wherein the predicted travel time includes a total travel time for each of the plurality of road segments making up the traffic route,

publish a recommended departure time based on the plurality of travel patterns and predicted travel time, and

automatically update the publication of the predicted travel time in response to changes in the plurality of travel patterns.

8. The system of claim 7, wherein the publication of predicted travel time includes a graphic representation of the road segments.

9. The system of claim 8, wherein the graphic representation of the road segments is three-dimensional.

10. The system of claim 7, wherein the recommended departure time is identified based on at least a point of maximum slope in the graphical representation.

11. The system of claim 7, wherein the time interval is associated with a particular day of the week.

12. The system of claim 11, wherein the time interval is further associated with a particular time of the day.

13. A non-transitory computer-readable storage 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:

associating real-time traffic speed data with historical speed data to generate combined traffic speed data for a plurality of road segments during a particular time interval;

determining a predicted travel time for a plurality of road segments based on a plurality of travel patterns, wherein the plurality of travel patterns include at least;

the combined traffic speed data for the plurality of road segments during a particular time interval, and

non-traffic event data that influences traffic speed for at least one of the road segments;

publishing a predicted travel time for the traffic route, wherein the predicted travel time includes a total travel time for each of the plurality of road segments making up the traffic route;

publishing a recommended departure time based on the plurality of travel patterns and predicted travel time; and

automatically updating the publication of the predicted travel time in response to changes in the plurality of travel patterns.

14. The non-transitory computer-readable storage medium of claim 13, wherein the publication of predicted travel time includes a graphic representation of the road segments.

15. The non-transitory computer-readable storage medium of claim 14, wherein the graphic representation of the road segments is three-dimensional.

16. The non-transitory computer-readable storage medium of claim 13, wherein the recommended departure time is identified based on at least a point of maximum slope in the graphical representation.

17. The non-transitory computer-readable storage medium of claim 13, wherein the time interval is associated with a particular day of the week.

18. The non-transitory computer-readable storage medium of claim 17, wherein the time interval is further associated with a particular time of the day.