Suggestive mapping

• US 9,163,952 B2
• Filed: 04/15/2011
• Issued: 10/20/2015
• Est. Priority Date: 04/15/2011
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Viola, Paul A., Jiang, Zhaowei, Krumm, John C., Dyor, Matthew Graham, Horvitz, Eric J., Cheng, Lili
• Primary Examiner(s): Kiswanto, Nicholas
• Application Number:
  US13/088,040
• Publication Number:
  US 20120265433A1
• Time in Patent Office: 1,649 Days
• Field of Search: 701/410, 701/411, 701/414, 701/415, 701/420, 701/424
• US Class Current: 1/1
• 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, the location information including at least one of location information included in a calendar appointment of a user device of the one or more user devices, location information of a contact of a user device of the one or more user devices, or location information of a social network website;

storing the location information;

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

predicting a plurality of destinations 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;

ranking the plurality of destinations based at least in part on an inferred likelihood of desirability of each destination of the plurality of destinations, the inferred likelihood of desirability being computed based at least in part on the stored location information and the determined travel vector, wherein the plurality of destinations include at least a first ranked destination and a second ranked destination;

preparing a plurality of maps, each map of the plurality depicting a route to the respective predicted destination;

displaying at least a first map of the route to the first ranked destination;

providing a user with an option to request a different predicted destination; and

if a user request for the different predicted destination is received, then displaying at least a second map of the route to the second ranked 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 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, wherein the prepared maps are displayed by an output device of the user device.

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, each of the first map of the route to the first ranked destination and the second map of the route to the second ranked destination to the user device.

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

8. The method of claim 7, wherein the contextual information of the 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 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 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 the request for the different predicted destination from the user, and 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 of the computing device.

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

storing location information for a client device of a user over time, the location information including at least one of location information included in a calendar appointment of the client device, location information of a contact of the user of the client device, or location information of a social network website;

determining a travel vector of the client device;

predicting a plurality of destinations of the client device based at least in part on the stored location information and the determined travel vector;

ranking the plurality of destinations based at least in part on an inferred likelihood of desirability of each destination of the plurality of destinations, the inferred likelihood of desirability being computed based at least in part on the stored location information and the determined travel vector, wherein the plurality of destinations include at least a first ranked destination and a second ranked destination;

preparing a plurality of maps, each map of the plurality depicting a next travel instruction to the respective predicted destination;

displaying at least a first map including the travel instruction to the first ranked destination;

providing a user with an option to request a different predicted destination; and

if a user request for the different predicted destination is received, then displaying at least a second map of the route to the second ranked destination.

16. The one or more computer-readable storage media of claim 15, wherein the stored location information for the client device of a user over time comprises historical location information of the client device, historical location information included in an electronic communication sent from or received by the client device, historical location information included in a calendar appointment of the client device, and/or historical location information of a contact of the user of the client device, and wherein selecting a 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 the travel instruction to the respective predicted destination comprises a map depicting at least a next travel instruction to the respective predicted destination at a first velocity of the client device, a map depicting more than one next travel instructions to the respective 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 respective predicted destination, or ii) from a current location of the client device to the respective 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 location information module, stored in the memory and executable on the one or more processors, to maintain location information of a client device, the location information including at least one of location information included in a calendar appointment of the client device, location information of a contact of a user of the client device, or location information of a social network website;

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 plurality of destinations of the client device based at least in part on the maintained historical location information and the determined travel vector of the client device, then rank the plurality of destinations based at least in part on an inferred likelihood of desirability of each destination of the plurality of destinations, the inferred likelihood of desirability being computed based at least in part on the location information and the determined travel vector, wherein the plurality of destinations include at least a first ranked destination and a second ranked destination;

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

a map display module, stored in the memory and executable on the one or more processors, to display at least a first map including the travel instruction to the first ranked destination, provide a user with an option to request a different predicted destination, and if a user request for the different predicted destination is received, then display at least a second map including the travel instruction to the second ranked destination.

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.