Methods and Apparatus for Context Based Trip Planning

• US 20140172292A1
• Filed: 12/14/2012
• Published: 06/19/2014
• Est. Priority Date: 12/14/2012
• Status: Abandoned Application

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: McGee, Ryan Abraham, Filev, Dimitar Petrov, Kristinsson, Johannes Geir, Tseng, Fling, Phillips, Anthony Mark
• Application Number:
  US13/714,919
• Publication Number:
  US 20140172292A1
• Time in Patent Office: Days
• US Class Current: 701/418
• CPC Class Codes: G01C 21/3605 Destination input or retrieval
• CPC Class Codes: G01C 21/3608 using speech input, e.g. using speech recognition

Abstract

A system includes a processor configured to receive vehicle location and context information. The processor is also configured to execute a prediction algorithm to predict one or more next-destinations based on the location and context information compared to observed driver behavior stored in a database and deliver the one or more next-destinations to a vehicle computing system. The processor is further configured to receive next-destination input and utilizing the next-destination input as a new vehicle location and estimating new context information, repeat execution of the prediction algorithm, delivery of the predicted next-destinations, and receipt of the next-destination input, until input indicating completed journey assembly is received.

Claims

1. A system comprising:

a processor configured to;

receive vehicle location and context information;

execute a prediction algorithm to predict one or more next-destinations based on the location and context information compared to observed driver behavior stored in a database;

deliver the one or more next-destinations to a vehicle computing system;

receive a driver-selected next-destination input, selected from the delivered one or more next-destinations; and

utilize the next-destination input as a new vehicle location and estimate new context information, repeat execution of the prediction algorithm, delivery of the predicted next-destinations, and receipt of the next-destination input, until input indicating completed journey assembly is received.

2. The system of claim 1, wherein the context information includes driver identity.

3. The system of claim 1, wherein the context information includes a day of week.

4. The system of claim 1, wherein the context information includes a time of day.

5. The system of claim 1, wherein the estimated new context information includes a new time of day based at least in part on travel time to the new vehicle location from a previous vehicle location.

6. The system of claim 1, wherein the estimated new context information includes a new time of day based at least in part on projected time spent at the new vehicle location.

7. The system of claim 6, wherein the projected time spent at the new vehicle location is based at least in part on observed driver behavior stored in the database.

8. The system of claim 6, wherein the projected time spent at the new vehicle location is based at least in part on observed driver behavior stored in the database with relation to a business of a similar type as a business located at the new vehicle location.

9. The system of claim 6, wherein the projected time spent at the new vehicle location is based at least in part on observed driver behavior stored in the database for other drivers visiting a business of a similar type as a business located at the new vehicle location.

10. A computer-implemented method comprising:

receiving vehicle location and context information;

predicting multiple next-destinations, via a computer, based on the location and context information compared to observed driver behavior;

delivering the next-destinations to a vehicle;

receiving driver-selected next-destination input, selected from the delivered next-destination; and

utilizing the next-destination input as a new vehicle location and estimating new context information, repeating the steps of predicting, delivering, and receiving input, until input indicating completed journey assembly is received.

11. The method of claim 10, wherein the context information includes driver identity.

12. The method of claim 10, wherein the context information includes a day of week.

13. The method of claim 10, wherein the context information includes a time of day.

14. The method of claim 10, wherein the estimated new context information includes a new time of day based at least in part on travel time to the new vehicle location from a previous vehicle location.

15. The method of claim 10, wherein the estimated new context information includes a new time of day based at least in part on projected time spent at the new vehicle location.

16. The method of claim 15, wherein the projected time spent at the new vehicle location is based at least in part on observed driver behavior.

17. The method of claim 15, wherein the projected time spent at the new vehicle location is based at least in part on observed driver behavior stored in a database with relation to a business of a similar type as a business located at the new vehicle location.

18. The method of claim 15, wherein the projected time spent at the new vehicle location is based at least in part on observed driver behavior stored in a database for other drivers visiting a business of a similar type as a business located at the new vehicle location.

19. A non-transitory computer-readable storage medium storing instructions, which, when executed by a processor, cause the processor to perform a method comprising:

receiving vehicle location and context information;

predicting multiple next-destinations based on the location and context information compared to observed driver behavior;

delivering the next-destinations to a vehicle;

receiving driver-selected next-destination input, selected from the delivered next-destinations; and

utilizing the next-destination input as a new vehicle location and estimating new context information, repeating the steps of predicting, delivering, and receiving input, until input indicating completed journey assembly is received.

20. The computer readable storage medium of claim 19, wherein the context information includes driver identity information.