Selecting vehicle type for providing transport

• US 9,940,651 B2
• Filed: 12/02/2016
• Issued: 04/10/2018
• Est. Priority Date: 05/13/2015
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uber Technologies, Inc.
• Inventors: Ross, William, Bares, John, LaRose, David, Sweeney, Matthew
• Primary Examiner(s): Kan, Yuri
• Application Number:
  US15/367,521
• Publication Number:
  US 20170083957A1
• Time in Patent Office: 494 Days
• CPC Class Codes: G01C 21/3438 Rendez-vous, i.e. searching a destination where several users can meet, and the routes to this destination for these users; Ride sharing, i.e. searching a route such that at least two users can share a vehicle for at least part of the route
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• 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: G05D 1/0027 involving a plurality of vehicles, e.g. fleet or convoy travelling fleet control of land vehicles from a control room G05D1/0297; traffic control systems for road vehicles G08G1/00; for marine craft G08G3/00; for aircraft G08G5/00
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/0217 in accordance with energy consumption, time reduction or distance reduction criteria
• CPC Class Codes: G05D 1/0234 using optical markers or beacons optical beacons per se G01S1/70
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G08G 1/20 Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching
• CPC Class Codes: H05K 999/99 dummy group

Abstract

A transport arrangement system operates to receive a transport request from a user, and to make a selection of a vehicle type for the user based at least in part on a set of criteria associated with the transport request or user information. For example, the determination of whether an autonomous vehicle is to be provided can be based at least in part on the destination specified with the transport request.

Claims

1. A system for arranging transport, the system comprising:

a memory that stores a set of instructions;

one or more processors which use the set of instructions to;

receive a transport request from a user; and

determine, based at least in part on information specified with the transport request, whether to fulfill the transport request using an autonomous vehicle.

2. The system of claim 1, wherein the information specified with the transport request includes a pickup location.

3. The system of claim 1, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on a preference of the user.

4. The system of claim 3, wherein the preference of the user includes a setting, in a customer profile stored with the system, to prefer autonomous vehicles or human-driven vehicles.

5. The system of claim 3, wherein the one or more processors determine the preference of the user from recent types of vehicles which provided transport services for the user, such as a number of times the user received or specifically requested autonomous vehicles or human-driven vehicles.

6. The system of claim 3, wherein the one or more processors determine the preference of the user from rating information the user provided for past transport services.

7. The system of claim 1, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on one or more special requests made by the user with the transport request.

8. The system of claim 1, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on an estimated cost of fulfilling the transport request with the autonomous vehicle.

9. The system of claim 8, wherein the estimated cost incorporates probabilistic determinations as to whether the autonomous vehicle may encounter a delay or deviation in a route while fulfilling the transport request.

10. The system of claim 8, wherein the estimated cost of fulfilling the transport request using the autonomous vehicle includes a monetary cost to the user, a cost basis for a transport provider, and/or a lost opportunity cost for the user and the transport provider.

11. The system of claim 8, wherein the one or more processors compare the estimated cost of fulfilling the transport request using the autonomous vehicle with a cost of fulfilling the transport request using a human-driven vehicle.

12. The system of claim 11, wherein the estimated cost of fulfilling the transport request using the autonomous vehicle and the cost of fulfilling the transport request using a human-driven vehicle are based on a current supply and demand for autonomous vehicles and human-driven vehicles in a geographic region of the user.

13. The system of claim 1, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on (i) determining one or more routes for the autonomous vehicle to a destination, and (ii) comparing the one or more routes to an optimal route that can be provided by a human-driven vehicle.

14. The system of claim 13, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a lowest estimated time of arrival for the autonomous vehicle with a lowest estimated time of arrival for the human-driven vehicle.

15. The system of claim 13, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a distance traveled to the destination for the autonomous vehicle with a distance traveled to the destination for the human-driven vehicle.

16. The system of claim 13, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a road type for a selected route of the autonomous vehicle with a road type for a selected route of the human-driven vehicle.

17. The system of claim 1, wherein the one or more processors use the set of instructions to:

determine one of a pickup location or alternative destination for the transport request in order to (i) determine a route that accommodates an ability of the autonomous vehicle, (ii) reduce an estimated time of arrival in using the autonomous vehicle for the transport request, and/or (iii) reduce a distance traveled in using the autonomous vehicle for the transport request.

18. The system of claim 1, wherein the one or more processors use the set of instructions to:

transmit a message to the user, the message including a selection of a vehicle type to fulfill the transport request;

receive, from the user, an alternative selection for a different vehicle type;

and

fulfill the transport request using the different vehicle type specified in the alternative selection.

19. A method for arranging transport, the method being implemented by one or more processors and comprising:

receiving a transport request from a user; and

determining, based at least in part on information specified with the transport request, whether to fulfill the transport request using an autonomous vehicle.

20. The method of claim 19, wherein the information specified with the transport request includes a pickup location.

21. The method of claim 19, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on a preference of the user.

22. The method of claim 21, wherein the preference of the user includes a setting in a customer profile to prefer autonomous vehicles or human-driven vehicles.

23. The method of claim 21, wherein the one or more processors determine the preference of the user from recent types of vehicles which provided transport services for the user, such as a number of times the user received or specifically requested autonomous vehicles or human-driven vehicles.

24. The method of claim 21, wherein the one or more processors determine the preference of the user from rating information the user provided for past transport services.

25. The method of claim 19, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on one or more special requests made by the user with the transport request.

26. The method of claim 19, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on an estimated cost of fulfilling the transport request with the autonomous vehicle.

27. The method of claim 26, wherein the estimated cost incorporates probabilistic determinations as to whether the autonomous vehicle may encounter a delay or deviation in a route while fulfilling the transport request.

28. The method of claim 26, wherein the estimated cost of fulfilling the transport request using the autonomous vehicle includes a monetary cost to the user, a cost basis for a transport provider, and/or a lost opportunity cost for the user and the transport provider.

29. The method of claim 26, wherein the one or more processors compare the estimated cost of fulfilling the transport request using the autonomous vehicle with a cost of fulfilling the transport request using a human-driven vehicle.

30. The method of claim 29, wherein the estimated cost of fulfilling the transport request using the autonomous vehicle and the cost of fulfilling the transport request using a human-driven vehicle are based on a current supply and demand for autonomous vehicles and human-driven vehicles in a geographic region of the user.

31. The method of claim 19, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on (i) determining one or more routes for the autonomous vehicle to a destination, and (ii) comparing the one or more routes to an optimal route that can be provided by a human-driven vehicle.

32. The method of claim 31, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a lowest estimated time of arrival for the autonomous vehicle with a lowest estimated time of arrival for the human-driven vehicle.

33. The method of claim 31, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a distance traveled to the destination for the autonomous vehicle with a distance traveled to the destination for the human-driven vehicle.

34. The method of claim 31, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a road type for a selected route of the autonomous vehicle with a road type for a selected route of the human-driven vehicle.

35. The method of claim 19, further comprising:

determining one of a pickup location or alternative destination for the transport request in order to (i) determine a route that accommodates an ability of the autonomous vehicle, (ii) reduce an estimated time of arrival in using the autonomous vehicle for the transport request, and/or (iii) reduce a distance traveled in using the autonomous vehicle for the transport request.

36. The method of claim 19, further comprising:

transmitting a message to the user, the message including a selection of a vehicle type to fulfill the transport request;

receiving, from the user, an alternate selection for a different vehicle type; and

fulfilling the transport request using the different vehicle type specified in the alternate selection.

37. A non-transitory computer-readable medium that stores instructions, which when executed by one or more processors, cause the one or more processors to perform operations comprising:

receiving a transport request from a user; and

determining, based at least in part on information specified with the transport request, whether to fulfill the transport request using an autonomous vehicle.

38. The non-transitory computer-readable medium of claim 37, wherein the information specified with the transport request includes a pickup location.

39. The non-transitory computer-readable medium of claim 37, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on a preference of the user.

40. The non-transitory computer-readable medium of claim 39, wherein the preference of the user includes a setting in a customer profile to prefer autonomous vehicles or human-driven vehicles.

41. The non-transitory computer-readable medium of claim 39, wherein the one or more processors determine the preference of the user from recent types of vehicles which provided transport services for the user, such as a number of times the user received or specifically requested autonomous vehicles or human-driven vehicles.

42. The non-transitory computer-readable medium of claim 39, wherein the one or more processors determine the preference of the user from rating information the user provided for past transport services.

43. The non-transitory computer-readable medium of claim 37, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on one or more special requests made by the user with the transport request.

44. The non-transitory computer-readable medium of claim 37, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on an estimated cost of fulfilling the transport request with the autonomous vehicle.

45. The non-transitory computer-readable medium of claim 44, wherein the estimated cost incorporates probabilistic determinations as to whether the autonomous vehicle may encounter a delay or deviation in a route while fulfilling the transport request.

46. The non-transitory computer-readable medium of claim 44, wherein the estimated cost of fulfilling the transport request using the autonomous vehicle includes a monetary cost to the user, a cost basis for a transport provider, and/or a lost opportunity cost for the user and the transport provider.

47. The non-transitory computer-readable medium of claim 44, wherein the one or more processors compare the estimated cost of fulfilling the transport request using the autonomous vehicle with a cost of fulfilling the transport request using a human-driven vehicle.

48. The non-transitory computer-readable medium of claim 47, wherein the estimated cost of fulfilling the transport request using the autonomous vehicle and the cost of fulfilling the transport request using a human-driven vehicle are based on a current supply and demand for autonomous vehicles and human-driven vehicles in a geographic region of the user.

49. The non-transitory computer-readable medium of claim 37, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on (i) determining one or more routes for the autonomous vehicle to a destination, and (ii) comparing the one or more routes to an optimal route that can be provided by a human-driven vehicle.

50. The non-transitory computer-readable medium of claim 49, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a lowest estimated time of arrival for the autonomous vehicle with a lowest estimated time of arrival for the human-driven vehicle.

51. The non-transitory computer-readable medium of claim 49, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a distance traveled to the destination for the autonomous vehicle with a distance traveled to the destination for the human-driven vehicle.

52. The non-transitory computer-readable medium of claim 49, wherein the one or more processors determine whether to fulfill the transport request using the autonomous vehicle based at least in part on comparing a road type for a selected route of the autonomous vehicle with a road type for a selected route of the human-driven vehicle.

53. The non-transitory computer-readable medium of claim 37, wherein the one or more processors use the instructions to:

determine one of a pickup location or alternative destination for the transport request in order to (i) determine a route that accommodates an ability of the autonomous vehicle, (ii) reduce an estimated time of arrival in using the autonomous vehicle for the transport request, and/or (iii) reduce a distance traveled in using the autonomous vehicle for the transport request.

54. The non-transitory computer-readable medium of claim 37, wherein the one or more processors use the instructions to:

transmit a message to the user, the message including a selection of a vehicle type to fulfill the transport request;

receive, from the user, an alternative selection for a different vehicle type; and

fulfill the transport request using the different vehicle type specified in the alternative selection.