METHOD AND APPARATUS FOR PREDICTING A DESTINATION USING A ROUTE SEARCH ALGORITHM

• US 20160097649A1
• Filed: 04/17/2014
• Published: 04/07/2016
• Est. Priority Date: 04/17/2013
• Status: Active Grant

• Current Assignee: TomTom Navigation B.V (TomTom NV)
• Original Assignee: TomTom Navigation B.V (TomTom NV)
• Inventors: Broadbent, Samuel Mark, Geelen, Pieter Andreas, Hareau, Stphane, Santiago Nunez, Jose F.
• Granted Patent: US 9,869,563 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/3453 Special cost functions, i.e. other than distance or default speed limit of road segments
• CPC Class Codes: G01C 21/3476 using point of interest [POI] information, e.g. a route passing visible POIs
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• 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 21/3667 Display of a road map G01C21/3614 takes precedence; guidance using 3D or perspective road maps G01C21/3635
• 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: G01C 21/3694 Output thereof on a road map
• CPC Class Codes: G01C 21/3697 Output of additional, non-guidance related information, e.g. low fuel level G01C21/3679 takes precedence
• CPC Class Codes: G08G 1/096827 where the route is computed onboard
• CPC Class Codes: G08G 1/096838 where the user preferences are taken into account or the user selects one route out of a plurality

Abstract

A method of predicting a destination of a user of a mobile device is described, together with a device for performing the same. The method comprises determining a location of the mobile device, and executing a route search algorithm with respect to a trip data-base. The trip database stores information indicative of a personal road network of a user of the mobile device, one or more road segments in the personal road network being associated with a respective destination location, and cost information associated with road segments in the personal network, the cost information being based, at least in part, on traversal information in the trip database.

Claims

1. A mobile device, comprising a processor communicably coupled to a trip database storing information indicative of a personal road network of a user of the mobile device, one or more road segments in the personal road network being associated with a respective destination location, wherein the processor is arranged to operably execute a prediction module to predict a destination based on a current location of the mobile device and the trip database, and wherein the prediction module is arranged to predict the destination by executing a route search algorithm with respect to the personal road network and cost information associated with road segments in the personal network, the cost information being based, at least in part, on traversal information in the trip database.

2. The mobile device of claim 1, wherein the traversal information is indicative of a number of times each road segment in the personal network has been traversed by the user.

3. The mobile device of claim 1, wherein the prediction module is arranged to select a road segment from the personal network based on the current location of the mobile device and to perform the route search using the road segment as a start location.

4. The mobile device of claim 3, wherein the road segment selected as the start location has a location corresponding to, or within a predetermined distance of, the current location.

5. The mobile device of claim 1, wherein the prediction module is arranged to predict the destination based on a current time and time information stored in the trip database indicative of a time of traversal of associated road segments in the personal network.

6. The mobile device of claim 5, wherein the prediction module is arranged to select a road segment from the personal network based on the current location of the mobile device and to perform the route search using the road segment as a start location when the current time corresponds to the time information.

7. The mobile device of claim 6, wherein the time information indicates one of a plurality of periods of time during which the road segment was traversed, and the current time corresponds to the time information when matching, or within a predetermined number of time periods of, the current time.

8. The mobile device of claim 1, wherein the processor is communicably coupled to a favourites database storing information indicative of one or more points of interest (POIs) selected by the user.

9. The mobile device of claim 8, wherein the one or more road segments in the personal network associated with a destination location are associated with POIs in the favourites database.

10. The mobile device of claim 1, wherein the personal network of the user comprises a plurality of road segments previously traversed by the user of the mobile device in one or more journeys.

11. The mobile device of claim 1, wherein the prediction module is arranged to provide the predicted destination to the user for selection as a destination of a current journey.

12. The mobile device of claim 1, comprising a display device, wherein the prediction module is arranged to provide a suggested destination interface comprising the predicted destination.

13. The mobile device of claim 1, wherein the prediction module is arranged to predict one or more further, less likely, destinations.

14. A method of predicting a destination of a user of a mobile device, comprising:

determining a location of the mobile device; and

executing a route search algorithm with respect to a trip database storing information indicative of a personal road network of a user of the mobile device, one or more road segments in the personal road network being associated with a respective destination location, and cost information associated with road segments in the personal network, the cost information being based, at least in part, on traversal information in the trip database.

15. The method of claim 14, wherein the predicted destination is a destination location associated with a road segment found by the route search algorithm.

16. The method of claim 14, comprising selecting a road segment from the personal network based on the location of the mobile device and performing the route search using the road segment as a start location.

18. The method of claim 14, comprising predict the destination based on a current time and time information stored in the trip database indicative of a time of traversal of associated road segments in the personal network.

21. The method of claim 14, wherein the one or more road segments in the personal network associated with a destination location are associated with user-selected points of interest (POIs) stored in a favourites database.

22. The method of claim 14, comprising providing the predicted destination to the user for selection as a destination of a current journey.

23. A non-transitory computer readable medium comprising computer software operable, when executed, to cause one or more processors to perform a method according to claim 14.

17. (canceled)

19-20. -20. (canceled)