SUGGESTIVE MAPPING

• US 20120265433A1
• Filed: 04/15/2011
• Published: 10/18/2012
• Est. Priority Date: 04/15/2011
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Viola, Paul A., Jiang, Zhaowei, Krumm, John C., Dyor, Matthew Graham, Horvitz, Eric J., Cheng, Lili
• Granted Patent: US 9,163,952 B2
• Time in Patent Office: Days
• US Class Current: 701/410
• 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

Abstract

A suggestive mapping device may predict, suggest, and/or provide potential destinations to a user. Additionally, the device may store historical location data of the user, determine a travel vector of the user, and predict the destination of the user based at least in part on the historical location data and/or the travel vector. Further, the device may provide hands-free maps to destinations when the user does not know the address at least by receiving contextual data of the user and/or contextual data of the user'"'"'s contacts. Such hands-free, suggestive mapping devices may facilitate more effective navigation.

Claims

1. A method comprising:

under control of one or more computing devices configured with executable instructions,

receiving location information for one or more user devices over time;

storing the location information;

determining a current travel vector of a user device of the one or more user devices;

predicting a destination of the user device, wherein the predicting is based at least in part on the stored location information and/or the determined current travel vector;

preparing for display a map depicting an entire route to the predicted destination.

2. The method of claim 1, wherein the stored location information for the one or more user devices over time comprises historical location information of a user device of the one or more user devices, historical location information included in an electronic communication sent from or received by a user device of the one or more user devices, historical location information included in a calendar appointment of a user device of the one or more user devices, and/or historical location information of a contact of a user device of the one or more user devices.

3. The method of claim 1, wherein the computing device is a user device of the one or more user devices, and wherein determining a travel vector of the user device comprises detecting, by the user device, a current location, a current direction, and a current velocity of the user device and calculating the travel vector based at least in part on the current location, the current direction, and the current velocity.

4. The method of claim 3, further comprising displaying, by an output device of the user device, the prepared map.

5. The method of claim 1, wherein the computing device is a remote computing device, and wherein determining a travel vector of the user device comprises receiving, from the user device, a current location, a current direction, and a current velocity of the user device and calculating the travel vector based at least in part on the current location, the current direction, and the current velocity.

6. The method of claim 5, further comprising sending, by an output device of the remote computing device, the prepared map to the user device.

7. The method of claim 1, wherein predicting a destination is further based at least in part on contextual information of a user device.

8. The method of claim 7, wherein context information of a user device comprises current location information of a user device of the one or more user devices, a current calendar appointment of a user device of the one or more user devices, a current electronic communication of a user device of the one or more user devices, current location information of a contact of a user device of the one or more user devices, and/or current calendar appointments of a contact of a user device of the one or more user devices.

9. The method of claim 1, wherein the map depicting the entire route for the user device to the predicted destination comprises a route from a predicted starting point to the predicted destination or from a current location of the user device to the predicted destination.

10. The method of claim 1, further comprising preparing for display, by the one or more processors of the computing device, one or more maps depicting one or more travel instructions to the predicted destination.

11. The method of claim 10, wherein the computing device is a remote computing device, and further comprising sending, by an output device of the remote computing device, at least one of the one or more prepared maps to a user device of the one or more user devices based at least in part on the travel vector of the user device.

12. The method of claim 10, wherein the computing device is a user device of the one or more user devices, and further comprising displaying, by an output device of the user device, at least one of the one or more prepared maps based at least in part on the travel vector of the user device.

13. The method of claim 10, wherein the one or more maps are ranked based at least in part on an inferred likelihood of desirability of a user of the user device.

14. The method of claim 1, further comprising receiving, by an input device of the computing device, an indication of a request for a different predicted destination, wherein the indication is based at least in part on a physical gesture detected by a swipe or pattern of movement detected by an accelerometer, such as the computing device being shaken.

15. One or more computer-readable media storing computer-executable instructions that, when executed by a processor, perform acts comprising:

storing historical location information for a client device of a user over time;

determining a travel vector of the client device;

predicting a destination of the client device, comprising selecting a most probable destination based at least in part on the stored historical location information and/or the determined travel vector;

preparing a map depicting a travel instruction to the predicted destination.

16. The one or more computer-readable storage media of claim 15, wherein the stored historical location information for a client device of a user over time comprises location information of the client device, location information included in an electronic communication sent from or received by the client device, location information included in a calendar appointment of the client device, and/or location information of a contact of the user of the client device, and wherein selecting the most probable destination is further based on contextual information comprising a current location of the client device, a current calendar appointment of the client device, a current electronic communication of the client device, a current location of a contact of the user of the client device, a current calendar appointment of a contact of the user of the client device, and/or current traffic information.

17. The one or more computer-readable storage media of claim 15, wherein the map depicting a travel instruction to the predicted destination comprises a map depicting at least a next travel instruction to the predicted destination at a first velocity of the client device, a map depicting more than one next travel instructions to the predicted destination at a second velocity of the client device, or a map depicting each travel instruction i) from a predicted starting point to the predicted destination, or ii) from a current location of the client device to the predicted destination at a third velocity of the client device, wherein the first velocity is less than the second velocity and the second velocity is less than the third velocity.

18. A system comprising:

memory;

one or more processors communicatively coupled to the memory;

a historical location information module, stored in the memory and executable on the one or more processors, to maintain historical location information of a client device;

a travel vector determination module, stored in the memory and executable on the one or more processors, to determine a travel vector of the client device based on a current location, a current travel direction, and a current velocity of the client device; and

a destination prediction module, stored in the memory and executable on the one or more processors, to predict a destination of the client device based at least in part on the maintained historical location information and/or the determined travel vector of the client device.

19. The system of claim 18, further comprising:

a contextual input module, stored in the memory and executable on the one or more processors, to receive contextual information of the client device and/or a contact of a user of the client device, wherein the contextual information comprises current location information of the client device or a contact of the user of the client device, current appointment information of the client device or a contact of the user of the client device, current communication information of the client device or a contact of the user of the client device, and/or real-time information associated with travel to the predicted destination, wherein the destination prediction module further predicts the destination of the client device based at least in part on the contextual information of the client device.

20. The system of claim 18, further comprising:

a map generation module, stored in the memory and executable on the one or more processors, to generate a map depicting at least a next travel instruction to the predicted destination; and

a map display module, stored in the memory and executable on the one or more processors, to display the generated map based at least in part on the travel vector of the client device.