Vehicle selection for on-demand transportation services

• US 10,762,447 B2
• Filed: 05/23/2017
• Issued: 09/01/2020
• Est. Priority Date: 05/23/2017
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uatc, LLC (Uber Technologies, Inc.)
• Inventors: Kislovskiy, Dima, Bradley, David McAllister
• Primary Examiner(s): Vetter, Daniel
• Application Number:
  US15/602,223
• Publication Number:
  US 20180341880A1
• Time in Patent Office: 1,197 Days
• CPC Class Codes: G06Q 10/02 Reservations, e.g. for tickets, services or events
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083

Abstract

An on-demand transportation management service can perform a selection process between a set of safety-driven autonomous vehicles (SDAVs), fully autonomous vehicles (FAVs), and human-driven vehicles (HDVs) to service transport requests based on a variety of selection parameters.

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;

for a given region, receive transport requests from requesting users in connection with an on-demand transportation service, each transport request indicating a pick-up location and a destination;

for each transport request, (i) determine a risk for an optimal route between the pick-up location and the destination, and (ii) based at least in part on the risk, perform a selection process between a set of safety-driven autonomous vehicles (SDAVs), fully autonomous vehicles (FAVs), and human-driven vehicles (HDVs) to service the transport request;

select a SDAV or a FAV as an optimal vehicle from the candidate set of vehicles to service the transport request; and

in response to selecting the SDAV from the candidate set of vehicles to service the transport request;

select a specified software version from a plurality of software versions stored on the SDAV for execution while servicing the transport request; and

transmit a set of transport instructions to the SDAV indicating the specified software version for execution while servicing the transport request; and

in response to selecting the FAV from the candidate set of vehicles to service the transport request;

select a verified software version stored on the FAV for execution while servicing the transport request based on the risk; and

transmit a set of transport instructions to the FAV indicating the verified software version for execution while servicing the transport request.

2. The on-demand transport system of claim 1, wherein the executed instructions further cause the on-demand transport system to further perform the selection process by determining a set of candidate vehicles within a certain proximity to the pick-up location, the set of candidate vehicles including at least one HDV, at least one SDAV, and at least one FAV.

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

for each vehicle in the set of candidate vehicles, determine an estimated time of arrival (ETA) to the pick-up location indicated in the transport request;

wherein the executed instructions further cause the on-demand transport system to perform the selection process based on an estimated time of arrival (ETA) of each of the set of candidate vehicles to the pick-up location.

4. The on-demand transport system of claim 3, wherein the executed instructions further cause the on-demand transport system to perform the selection process based on a desired time range for pick-up.

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

for each vehicle in the set of candidate vehicles, determine, based on historical data, an estimated revenue for the vehicle by servicing the transport request;

wherein the executed instructions cause the on-demand transport system to further perform the selection process based on the estimated revenue.

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

determine whether the optimal route is within an autonomy grid on which the SDAVs and FAVs operate in an autonomous mode.

7. The on-demand transport system of claim 6, wherein the autonomy grid comprises ground-truth mapped lanes, corresponding to localization maps stored in the SDAVs and FAVs, for the given region.

8. The on-demand transport system of claim 7, wherein the executed instructions further cause the on-demand transport system to:

exclude the FAVs from the selection process when the optimal route extends beyond the autonomy grid.

9. The on-demand transport system of claim 6, wherein the executed instructions further cause the on-demand transport system to:

based on one or more triggering conditions, remotely shut down or activate respective portions of the autonomy grid for autonomous operation.

10. The on-demand transport system of claim 9, wherein the one or more triggering conditions correspond to traffic conditions.

11. The on-demand transport system of claim 9, wherein the one or more triggering conditions correspond to weather conditions.

12. The on-demand transport system of claim 9, wherein the one or more triggering conditions correspond to at least one of a time of day, an event, or road conditions.

13. The on-demand transport system of claim 6, wherein the executed instructions further cause the on-demand transport system to:

collect vehicle fleet utilization data corresponding to an on-demand transportation service; and

establish a set of selection priorities for respective areas of the autonomy grid based on the vehicle fleet utilization data, each selection priority indicating whether a respective area of the autonomy grid is to favor HDVs, SDAVs, or FAVs for servicing transport requests;

wherein the executed instructions cause the on-demand transport system to further perform the selection process based on the set of selection priorities.

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

for a given region, receive transport requests from requesting users in connection with an on-demand transportation service, each transport request indicating a pick-up location and a destination;

for each transport request, (i) determine a risk for an optimal route between the pick-up location and the destination, and (ii) based at least in part on the risk, perform a selection process between a set of safety-driven autonomous vehicles (SDAVs), fully autonomous vehicles (FAVs), and human-driven vehicles (HDVs) to service the transport request;

select a SDAV or a FAV as an optimal vehicle from the candidate set of vehicles to service the transport request; and

in response to selecting the SDAV from the candidate set of vehicles to service the transport request;

select a specified software version from a plurality of software versions stored on the SDAV for execution while servicing the transport request; and

transmit a set of transport instructions to the SDAV indicating the specified software version for execution while servicing the transport request; and

in response to selecting the FAV from the candidate set of vehicles to service the transport request;

select a verified software version stored on the FAV for execution while servicing the transport request based on the risk; and

transmit a set of transport instructions to the FAV indicating the verified software version for execution while servicing the transport request.

15. The non-transitory computer readable medium of claim 14, wherein the executed instructions further cause the one or more processors to further perform the selection process by determining a set of candidate vehicles within a certain proximity to the pick-up location, the set of candidate vehicles including at least one HDV, at least one SDAV, and at least one FAV.

16. The non-transitory computer readable medium of claim 15, wherein the executed instructions further cause the one or more processors to:

for each vehicle in the set of candidate vehicles, determine an estimated time of arrival (ETA) to the pick-up location indicated in the transport request;

wherein the executed instructions further cause the on-demand transport system to perform the selection process based on an estimated time of arrival (ETA) of each of the set of candidate vehicles to the 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 perform the selection process based on a desired time range for pick-up.

18. A computer-implemented method of facilitating an on-demand transportation service, the method being performed by one or more processors and comprising:

for a given region, receiving transport requests from requesting users in connection with an on-demand transportation service, each transport request indicating a pick-up location and a destination;

for each transport request, (i) determining a risk for an optimal route between the pick-up location and the destination, and (ii) based at least in part on the risk, performing a selection process between a set of safety-driven autonomous vehicles (SDAVs), fully autonomous vehicles (FAVs), and human-driven vehicles (HDVs) to service the transport request;

selecting a SDAV or a FAV as an optimal vehicle from the candidate set of vehicles to service the transport request; and

in response to selecting the SDAV from the candidate set of vehicles to service the transport request;

selecting a specified software version from a plurality of software versions stored on the SDAV for execution while servicing the transport request; and

transmitting a set of transport instructions to the SDAV indicating the specified software version for execution while servicing the transport request; and

in response to selecting the FAV from the candidate set of vehicles to service the transport request;

selecting a verified software version stored on the FAV for execution while servicing the transport request based on the risk; and

transmitting a set of transport instructions to the FAV indicating the verified software version for execution while servicing the transport request.