Determining a route to destination based on partially completed route

• US 7,831,384 B2
• Filed: 12/30/2005
• Issued: 11/09/2010
• Est. Priority Date: 10/29/2004
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: AOL Inc. (Apollo Global Management, Inc.)
• Inventors: Bill, David S.
• Primary Examiner(s): Black; Thomas G
• Assistant Examiner(s): LOUIE, WAE LENNY
• Application Number:
  US11/321,648
• Publication Number:
  US 20060173841A1
• Time in Patent Office: 1,775 Days
• Field of Search: 701/117, 701/200, 701/201, 701/208, 701/209, 701/210, 701/211, 707/6, 340/995.22, 340/995.14, 340/995.19, 340/995.18
• US Class Current: 701/209
• CPC Class Codes: G01C 21/3407 specially adapted for specific applications
• 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

Abstract

Techniques are provided for predicting a destination for a ground-based vehicle. Travel patterns are accessed and a series of locations of a ground-based vehicle are received. At least some of the received locations are related to at least one accessed travel pattern, and a destination of the ground-based vehicle is predicted based on relating the received locations with the travel patterns. An existence of an event may be predicted using the predicted destinations of a ground-based vehicle.

Claims

1. A computer-implemented method for predicting a destination for a ground-based vehicle, the method comprising:

accessing, using a processor, travel patterns via a delivery network, the accessed travel patterns being associated with a particular user;

receiving, using the processor, a series of locations of the particular user in a ground-based vehicle;

relating, using the processor, at least some of the received locations to at least one accessed travel pattern;

predicting, using the processor, a destination of the particular user in the ground-based vehicle based on relating the received locations to the travel patterns; and

generating a route based on the predicted destination.

2. The method of claim 1 further comprising displaying an indication of the predicted destination or a user confirmation for the indication of the predicted destination.

3. The method of claim 1 further comprising notifying a user of information related to the predicted destination.

4. The method of claim 3 wherein notifying the user includes notifying a user that an event is predicted at the destination.

5. The method of claim 4 further comprising interrogating a user for more information related to the event so as to distinguish between multiple events occurring within a proximity threshold.

6. The method of claim 3 wherein notifying the user includes notifying the user about a point of interest along the route to the destination.

7. The method of claim 6 wherein the point of interest includes an ATM, a gas station, a restaurant, or a shopping venue related to the destination.

8. The method of claim 1 further comprising notifying a user of information related to a route to the predicted destination.

9. The method of claim 1 further comprising determining a route to the predicted destination and providing driving directions to the destination.

10. The method of claim 1 wherein the travel patterns include historical route information.

11. The method of claim 1 wherein the travel pattern comprises real-time route information indicative of other vehicles in transit as the travel patterns are accessed.

12. The method of claim 11 wherein the prior routes traveled are routes traveled by the ground-based vehicle.

13. The method of claim 1 wherein the travel patterns comprise prior routes traveled by a portable device currently associated with the ground-based vehicle.

14. The method of claim 1 wherein the travel patterns comprise routes traveled during a particular time of day.

15. The method of claim 1 wherein the travel patterns comprise routes traveled during a particular day of week.

16. The method of claim 1 wherein the travel patterns comprise a frequency of traveling a route.

17. The method of claim 1 wherein the travel patterns comprise a travel pattern of a person associated with the vehicle.

18. The method of claim 1 further comprising accessing information about a network of roads.

19. The method of claim 18 wherein the information about the network of roads comprises a routing graph representing a network of roads and including two or more nodes and one or more links, each link representing a road and each node representing an intersection that includes at least one road.

20. The method of claim 1 wherein a location in the series is determined from a global positioning system associated with the ground-based vehicle.

21. The method of claim 20 wherein a location in the series is received from a global positioning system that is external to the vehicle.

22. The method of claim 21 wherein a location in the series is received from a global positioning receiver that is internal to the vehicle.

23. The method of claim 1 wherein a location in the series is determined from a mobile device associated with the ground-based vehicle.

24. The method of claim 23 wherein the mobile device comprises a mobile telephone.

25. The method of claim 1 wherein a location in the series is determined by triangulating a position of the ground-based vehicle.

26. The method of claim 1 wherein receiving the series of locations includes receiving a single location and a direction of travel.

27. The method of claim 1 wherein receiving a series of locations includes receiving a single location and time of day.

28. The method of claim 1 further comprising:

detecting an interest by others in a venue; and

using the interest by others in the venue to predict the destination.

29. The method of claim 28 wherein detecting the interest by others in the venue includes receiving a route request by the others.

30. The method of claim 28 wherein detecting the interest by others in the venue includes receiving location and direction information for users travelling via a different route.

31. The method of claim 28 wherein detecting the interest by others in the venue includes receiving an indication that the others are travelling via a same route.

32. The method of claim 28 wherein detecting the interest by others in the venue includes determining users with a similar profile have referenced event information published on a communications network.

33. The method of claim 32 further determining that the users with the similar profile are travelling to the venue.

34. A method of predicting existence of an event, the method comprising:

receiving, using a processor, a request to generate a route to a destination via a delivery network for a particular user;

accessing, using the processor, a time constraint associated with the request;

relating, using the processor, the route for the particular user to other routes based on the time constraint and the destination;

determining, based on relating the route to other routes, that multiple users are traveling to the destination; and

based on determining that the multiple users are traveling to the destination, predicting the existence of an event at the destination using the processor.

35. The method of claim 34 wherein the route comprises a route derived from an in-vehicle navigation system.

36. The method of claim 34 wherein the destination comprises a location predicted based on a partially completed route traveled by a ground-based vehicle.

37. The method of claim 34 wherein the route comprises a route determined in response to a mapping query.

38. The method of claim 34 further comprising notifying a user of the event.

39. The method of claim 38 wherein notifying the user comprises interrogating the user for more information related to the event so as to distinguish between multiple events occurring within a proximity threshold.

40. The method of claim 38 wherein notifying the user comprises providing information related to anticipated traffic conditions associated with the event.

41. The method of claim 40 wherein providing information related to the anticipated traffic conditions associated with the event comprises providing a suggested alternative route to the location of the event.

42. The method of claim 38 wherein notifying the user comprises providing information related to anticipated parking conditions for the event.

43. The method of claim 38 wherein notifying the user comprises providing event information that is received from a source other than a mapping system used to detect the event.

44. The method of claim 34 wherein accessing a time constraint associated with the request includes accessing a time constraint associated with submission of the event.

45. The method of claim 34 wherein accessing a time constraint associated with the request includes accessing a time constraint associated with a travel time specified by the request.

46. A computer-implemented method for predicting a destination for a ground-based vehicle, the method comprising:

accessing, using a processor, travel patterns via a delivery network, the accessed travel patterns being associated with a particular user;

receiving, using the processor, a series of locations of the particular user in a ground-based vehicle;

determining, using the processor, a degree of travel for the ground-based vehicle, the degree of travel indicative of an extent to which a destination is identified as being local to a user;

relating, using the processor, at least some of the received locations to at least one accessed travel pattern;

predicting, using the processor, the destination of the particular user based on relating the received locations to the travel patterns; and

identifying, using the processor, a route to the destination that is supported by the degree of travel.

47. The method of claim 46 wherein determining the degree of travel includes determining that the user is travelling beyond a local environment.

48. The method of claim 47 wherein identifying the destination includes determining that the destination represents a point of interest for a user travelling beyond the local environment.

49. The method of claim 47 wherein identifying the destination includes determining that other users are travelling beyond their local environment are travelling to the destination.

50. The method of claim 46 determining the degree of travel includes determining that the user is travelling in a local environment.

51. The method of claim 50 wherein identifying the destination includes determining that the destination represents a point of interest for a user travelling in the local environment.

52. The method of claim 50 wherein determining the degree of travel includes determining that the user is travelling beyond a local environment.

54. The method of claim 52 wherein identifying the event includes determining that one of the results represents a point of interest for a user travelling beyond the local environment.

55. The method of claim 52 wherein identifying the event includes determining that other users are travelling beyond their local environment are travelling to the destination.

56. The method of claim 52 determining the degree of travel includes determining that the user is travelling in a local environment.

57. The method of claim 56 wherein identifying the event includes determining that one of the results represents a point of interest for a user travelling in the local environment.

53. A computer-implemented method for predicting an event for a ground-based vehicle, the method comprising:

accessing, using a processor, travel patterns via a delivery network, the accessed travel patterns being associated with a particular user;

receiving, using the processor, a series of locations of the particular user in a ground-based vehicle;

determining, using the processor, a degree of travel for the ground-based vehicle, the degree of travel indicative of an extent to which a destination is identified as being local to a user;

relating, using the processor, at least some of the received locations to at least one accessed travel pattern;

predicting results based on relating the received locations to the travel patterns;

generating a route based on the predicted result; and

identifying at least one event on the route from one of the results that is supported by the degree of travel.