Warning for frequently traveled trips based on traffic

• US 10,371,526 B2
• Filed: 04/21/2017
• Issued: 08/06/2019
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: McGavran, Christine B., Moore, Bradford A., Bolsinga, Gregory D., Blumenberg, Christopher, Pylappan, Seejo K., van Os, Marcel
• Primary Examiner(s): Anwari, Maceeh
• Application Number:
  US15/494,163
• Publication Number:
  US 20170350703A1
• Time in Patent Office: 837 Days
• Field of Search: 701 29, 701465, 701 291- 299
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• 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 21/3617 using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• CPC Class Codes: G01C 21/362 received from an external device or application, e.g. PDA, mobile phone or calendar application
• 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: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models

Abstract

Some embodiments of the invention provide a novel prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for a user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following: (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user'"'"'s calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user. In some embodiments, the prediction engine only relies on user-specific data stored on the device on which this engine executes. Alternatively, in other embodiments, it relies only on user-specific data stored outside of the device by external devices/servers. In still other embodiments, the prediction engine relies on user-specific data stored both by the device and by other devices/servers.

Claims

1. A mobile device comprising:

a display;

a storage configured to store previous locations of the device and arrival times at the previous locations, including determining a confidence level for the at least one desired arrival time;

a processor; and

a non-transitory computer readable medium storing instructions that, when executed by the processor, cause the processor to;

formulate at least one predicted destination, at least one desired arrival time for the at least one predicted destination, and a predicted route to the at least one predicted destination based on the previous locations of the device and arrival times at the previous locations stored in the storage;

determine a current location of the device;

identify a traffic condition along the predicted route;

based on the identification, adaptively generate a normative traffic expression that indicates a traffic level as compared to a normal traffic level along the predicted route;

determine a time to depart in order to reach the at least one predicted destination at the at least one desired arrival time based on the current location of the device and the traffic condition; and

display at least one notification regarding the at least one predicted destination on the display, the at least one notification including a traffic alert prompt that includes the normative traffic expression and the time to depart in order to reach the at least one predicted destination at the at least one desired arrival time, the at least one notification presented in response to the confidence level exceeding a threshold value.

2. The mobile device of claim 1, wherein:

the previous locations comprise starting locations and ending locations; and

formulating the at least one predicted destination and at least one desired arrival time for the at least one predicted destination is further based on a time elapsed for travel between at least one starting location and at least one ending location based on the previous locations stored in the storage.

3. The mobile device of claim 1, wherein:

the instructions, when executed by the processor, further cause the processor to identify at least one route between the current location and the at least one predicted destination; and

the time to depart is further based on the at least one route.

4. The mobile device of claim 3, wherein:

the instructions, when executed by the processor, further cause the processor to identify at least one route condition for the at least one route; and

the time to depart is further based on the at least one route condition.

5. The mobile device of claim 4, wherein the at least one route condition comprises at least one traffic condition.

6. The mobile device of claim 4, wherein the storage is further configured to store the at least one route.

7. The mobile device of claim 4, wherein the at least one route is generated by a route generation engine using the current location and the at least one predicted destination as inputs.

8. The mobile device of claim 7, wherein the at least one traffic condition is identified by the route generation engine.

9. The mobile device of claim 7, wherein the instructions, when executed by the processor, further cause the processor to execute the route generation engine.

10. The mobile device of claim 7, wherein the instructions, when executed by the processor, further cause the processor to:

send the current location and the at least one predicted destination to a server comprising the route generation engine; and

receive, from the server, a result of executing the route generation engine comprising the at least one route.

11. The mobile device of claim 1, wherein the time to depart is a latest time to depart in order to reach the at least one predicted destination at the at least one desired arrival time.

12. A method comprising:

formulating, by a processor of a device, at least one predicted destination, at least one desired arrival time, and a predicted route to the at least one predicted destination for the at least one predicted destination based on previous locations of the device and arrival times at the previous locations stored in a storage of the device, including determining a confidence level for the at least one desired arrival time;

determining, by the processor, a current location of the device;

identifying, by the processor, a traffic condition along the predicted route;

based on the identification, adaptively generating a normative traffic expression that indicates a traffic level as compared to a normal traffic level along the predicted route;

determining, by the processor a time to depart in order to reach the at least one predicted destination at the at least one desired arrival time based on the current location of the device and the traffic condition; and

displaying, by the processor at least one notification regarding the at least one predicted destination on a display of the device, the at least one notification including a traffic alert prompt that includes the normative traffic expression and the time to depart in order to reach the at least one predicted destination at the at least one desired arrival time, the at least one notification presented in response to the confidence level exceeding a threshold value.

13. The method of claim 12, wherein:

the previous locations comprise starting locations and ending locations; and

formulating the at least one predicted destination and at least one desired arrival time for the at least one predicted destination is further based on a time elapsed for travel between at least one starting location and at least one ending location based on the previous locations stored in the storage.

14. The method of claim 12, further comprising:

identifying, by the processor, at least one route between the current location and the at least one predicted destination;

wherein the time to depart is further based on the at least one route.

15. The method of claim 14, further comprising:

identifying, by the processor, at least one route condition for the at least one route;

wherein the time to depart is further based on the at least one route condition.

16. The method of claim 15, wherein the at least one route condition comprises at least one traffic condition.

17. The method of claim 15, further comprising storing, in the storage, the at least one route.

18. The method of claim 15, wherein the at least one route is generated by a route generation engine using the current location and the at least one predicted destination as inputs.

19. The method of claim 18, wherein the at least one traffic condition is identified by the route generation engine.

20. The method of claim 18, further comprising executing, by the processor, the route generation engine.

21. The method of claim 18, further comprising:

sending, by the processor, the current location and the at least one predicted destination to a server comprising the route generation engine; and

receiving, by the processor from the server, a result of executing the route generation engine comprising the at least one route.

22. The method of claim 12, wherein the time to depart is a latest time to depart in order to reach the at least one predicted destination at the at least one desired arrival time.