Coordinating on-demand transportation with autonomous vehicles

• US 10,290,074 B2
• Filed: 05/25/2017
• Issued: 05/14/2019
• Est. Priority Date: 05/25/2017
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uber Technologies, Inc.
• Inventors: Sweeney, Matthew, Levandowski, Anthony
• Primary Examiner(s): Trivedi, Atul
• Application Number:
  US15/605,060
• Publication Number:
  US 20180342035A1
• Time in Patent Office: 719 Days
• Field of Search: 701 23
• 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 21/3617 using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• 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: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G08G 1/202 Dispatching vehicles on the basis of a location, e.g. taxi dispatching

Abstract

An on-demand transport facilitation system can receive transport requests from requesting users throughout a given region, and select autonomous vehicles (AVs) and human driver to service the transport requests. The AV can operating on a mapped and labeled autonomy grid within the given region. For a given transport request, the transport system can determine an optimal pick-up location along the autonomy grid based on the current location of the requesting user and a current location of a selected AV, and transmit data indicating walking directions from the current location of the requesting user to the optimal pick-up location. The transport system may then coordinate the rendezvous by monitoring progress made by the requesting user and AV to the optimal pick-up location, and controlling the pace of the AV.

Claims

1. An on-demand transport system comprising:

one or more processors; and

one or more memory resources storing instructions that, when executed by the one or more processors, cause the on-demand transport system to;

receive a transport request from a rider device of a requesting user;

based on a current location of the requesting user, select an autonomous vehicle (AV) to service the transport request, the selected AV operating on an autonomy grid within a given region;

determine an optimal pick-up location along the autonomy grid based on the current location of the requesting user and a current location of the selected AV;

transmit, to the rider device, data indicating walking directions from the current location of the requesting user to the optimal pick-up location;

monitor progress made by the requesting user to the optimal pick-up location; and

transmit, to the selected AV, modulation commands instructing the selected AV to modulate progression to the optimal pick-up location based on the progress made by the requesting user to the optimal pick-up location.

2. The on-demand transport system of claim 1, wherein the executed instructions further cause the on-demand transport system to:

update the optimal pick-up location to a new pick-up location along the autonomy grid based on at least one of the progress made by the requesting user to the optimal pick-up location or progress made by the selected AV to the optimal pick-up location.

3. The on-demand transport system of claim 1, wherein the executed instructions cause the on-demand transport system to determine the optimal pick-up location by performing an optimization between the current location of the requesting user and the current location of the selected AV.

4. The on-demand transport system of claim 3, wherein the transport request indicates a drop-off location for the requesting user, and wherein the executed instructions cause the on-demand transport system to further perform the optimization based on the drop-off location.

5. The on-demand transport system of claim 1, wherein the executed instructions cause the on-demand transport system to select the AV by (i) identifying a set of candidate vehicles within a predetermined proximity of the current location of the requesting user, (ii) determining an estimated time of arrival (ETA) for each of the set of candidate vehicles to the current location of the requesting user, and (iii) determining at least one of a time savings or a cost savings for the requesting user by rendezvousing with the selected AV at the optimal pick-up location as compared with the ETAs of the set of candidate vehicles.

6. The on-demand transport system of claim 1, wherein the data indicating the walking directions further indicates the current location of the selected AV in real time.

7. The on-demand transport system of claim 1, wherein the on-demand transport system connects with the rider device of the requesting user via a designated rider application executing on the rider device.

8. The on-demand transport system of claim 7, wherein the transport request comprises a carpool request selected by the requesting user on the designated rider application.

9. The on-demand transport system of claim 7, wherein the transport request comprises an AV request selected by the requesting user on the designated rider application.

10. The on-demand transport system of claim 1, wherein the executed instructions further cause the on-demand transport system to:

transmit a notification to the rider device providing a status update while the requesting user progresses towards the optimal pick-up location, the status update indicating one of (i) a projected wait time for the requesting user when the requesting user arrives at the optimal pick-up location, (ii) an on-target status indicating an adequate convergence rate upon the optimal pick-up location by the requesting user and the selected AV, or (iii) an indication that the requesting user is projected to miss the selected AV at the optimal pick-up location.

11. The on-demand transport system of claim 1, wherein the executed instructions further cause the on-demand transport system to:

when the requesting user misses the selected AV, failover to an alternate AV operating on the autonomy grid; and

transmit an update to the rider device of the requesting user indicating an ETA for the alternate AV.

12. The on-demand transport system of claim 1, wherein the executed instructions cause the on-demand transport system to select the AV as one of multiple vehicles to service the transport request to transport the requesting user to a desired drop-off location.

13. The on-demand transport system of claim 12, wherein the executed instructions further cause the on-demand transport system to:

determine a rendezvous point along the autonomy grid at which the selected AV is to rendezvous with a human-driven vehicle to transport the requesting user from the rendezvous point to the desired drop-off location.

14. The on-demand transport system of claim 13, wherein the executed instructions further cause the on-demand transport system to:

select the human-driven vehicle to rendezvous with the selected AV from a set of candidate vehicles within a given proximity to the rendezvous point;

transmit a transport invitation to a driver of the human-driven vehicle to pick-up the requesting user at the rendezvous point; and

receive data indicating that the driver has accepted the transport invitation.

15. The on-demand transport system of claim 14, wherein the executed instructions further cause the on-demand transport system to:

coordinate timing of the rendezvous between the selected AV and the human-driven vehicle by (i) determining respective ETAs for the human-driven vehicle and the selected AV to the rendezvous point, and (ii) transmitting live mapping data to a driver device of the driver indicating progress of the selected AV to the rendezvous point.

16. A non-transitory computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:

receive a transport request from a rider device of a requesting user;

based on a current location of the requesting user, select an autonomous vehicle (AV) to service the transport request, the selected AV operating on an autonomy grid within a given region;

determine an optimal pick-up location along the autonomy grid based on the current location of the requesting user and a current location of the selected AV;

transmit, to the rider device, data indicating walking directions from the current location of the requesting user to the optimal pick-up location;

monitor progress made by the requesting user to the optimal pick-up location; and

transmit, to the selected AV, modulation commands instructing the selected AV to modulate progression to the optimal pick-up location based on the progress made by the requesting user to the optimal pick-up location.

17. The non-transitory computer readable medium of claim 16, wherein the executed instructions further cause the one or more processors to:

update the optimal pick-up location to a new pick-up location along the autonomy grid based on at least one of the progress made by the requesting user to the optimal pick-up location or progress made by the selected AV to the optimal pick-up location.

18. The non-transitory computer readable medium of claim 16, wherein the executed instructions further cause the one or more processors to determine the optimal pick-up location by performing an optimization between the current location of the requesting user and the current location of the selected AV.

19. A computer-implemented method of coordinating on-demand transportation, the method being performed by one or more processors and comprising:

receiving a transport request from a rider device of a requesting user;

based on a current location of the requesting user, selecting an autonomous vehicle (AV) to service the transport request, the selected AV operating on an autonomy grid within a given region;

determining an optimal pick-up location along the autonomy grid based on the current location of the requesting user and a current location of the selected AV;

transmitting, to the rider device, data indicating walking directions from the current location of the requesting user to the optimal pick-up location;

monitoring progress made by the requesting user to the optimal pick-up location; and

transmitting, to the selected AV, modulation commands instructing the selected AV to modulate progression to the optimal pick-up location based on the progress made by the requesting user to the optimal pick-up location.

20. The method of claim 19, further comprising:

updating the optimal pick-up location to a new pick-up location along the autonomy grid based on at least one of the progress made by the requesting user to the optimal pick-up location or progress made by the selected AV to the optimal pick-up location.