Capacity based vehicle operation

• US 10,527,428 B1
• Filed: 07/19/2017
• Issued: 01/07/2020
• Est. Priority Date: 07/19/2017
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uatc, LLC (Uber Technologies, Inc.)
• Inventors: Mehta, Sisil
• Primary Examiner(s): Oh, Harry Y
• Application Number:
  US15/654,200
• Time in Patent Office: 902 Days
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• 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: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G06Q 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management

Abstract

Systems, methods, and vehicles for capacity based vehicle operation are provided. For example, a method can include receiving, by a computing system including one or more computing devices, object data based in part on one or more states of one or more objects. Based in part on the object data, the computing system can determine one or more features of the one or more objects. Based on a comparison of the one or more features of the one or more objects to a vehicle capacity criterion, the one or more objects that satisfy the vehicle capacity criterion can be determined. The vehicle capacity criterion can be based in part on a carrying capacity of an autonomous vehicle. In response to the one or more objects satisfying the vehicle capacity criterion, one or more control systems associated with operation of the autonomous vehicle can be activated by the computing system.

Claims

1. A computer-implemented method of operating an autonomous vehicle, the computer-implemented method comprising:

receiving, by a computing system comprising one or more computing devices, object data based in part on one or more states of one or more objects;

determining, by the computing system, based in part on the object data, one or more features of the one or more objects, wherein the one or more features comprise one or more identities of the one or more objects;

determining, by the computing system, based on a comparison of the one or more features of the one or more objects to one or more vehicle capacity criteria, whether the one or more objects satisfy the one or more vehicle capacity criteria, wherein the one or more vehicle capacity criteria are based in part on a carrying capacity of an autonomous vehicle;

responsive to the one or more objects satisfying the one or more vehicle capacity criteria, determining, by the computing system, a plurality of assigned locations to place the one or more objects inside the autonomous vehicle based in part on the one or more identities of the one or more objects and one or more object placement criteria; and

generating, by the computing system, based in part on the one or more assigned locations, one or more placement indications inside the autonomous vehicle, wherein the one or more placement indications comprise instructions for directing movement of the one or more objects to at least one of the plurality of assigned locations in the autonomous vehicle.

2. The computer-implemented method of claim 1, further comprising:

receiving, by the computing system, sensor output from one or more sensors or access output from a vehicle access system, wherein the object data is based in part on the sensor output or the access output.

3. The computer-implemented method of claim 2, wherein the one or more sensors are located on an exterior of the autonomous vehicle or an interior of the autonomous vehicle and comprise an optical sensor, an audio sensor, a tactile sensor, a temperature sensor, or an electromagnetic sensor.

4. The computer-implemented method of claim 1, wherein the one or more features or the one or more vehicle capacity criteria comprises a number of the one or more objects, one or more identities of the one or more objects, a weight or mass of the one or more objects, a distribution throughout the autonomous vehicle of the weight or mass of the one or more objects, a volume of the one or more objects, an electrostatic capacitance of the one or more objects, or a shape of the one or more objects.

5. The computer-implemented method of claim 1, further comprising:

receiving, by the computing system, capacity adjustment data comprising a route for the autonomous vehicle to travel, topographical conditions, road conditions, or weather conditions along the route; and

modifying, by the one or more computing devices, the one or more vehicle capacity criteria based on the capacity adjustment data.

6. The computer-implemented method of claim 1, wherein the activating the one or more control systems comprises activating a vehicle access system, a vehicle notification system, a vehicle communication system, or a vehicle propulsion system.

7. The computer-implemented method of claim 6, wherein the activating the vehicle access system comprises:

determining, by the computing system, that a spatial relationship between the one or more objects, an entrance to the autonomous vehicle, or a loading location external to the autonomous vehicle satisfies one or more access criteria; and

responsive to the spatial relationship satisfying the one or more access criteria, modifying, by the computing system, access to the autonomous vehicle, the modifying access to the autonomous vehicle comprising locking the entrance, unlocking the entrance, opening the entrance, closing the entrance, activating a passenger restraint system, or deactivating a passenger restraint system.

8. The computer-implemented method of claim 7, wherein the one or more access criteria are based in part on a threshold distance between the entrance and the loading location, a threshold distance between the entrance and the one or more objects, or an orientation of the entrance relative to the loading location.

9. The computer-implemented method of claim 6, wherein the activating the vehicle notification system comprises:

determining, by the computing system, based in part on the one or more features, one or more corresponding object locations of the one or more objects; and

generating, by the computing system, the one or more placement indications based in part on (i) the one or more object placement criteria, (ii) the one or more identities, and (iii) the one or more corresponding object locations of the one or more objects.

10. The computer-implemented method of claim 9, further comprising:

determining, by the computing system, based on the one or more identities and the one or more corresponding object locations, an order of ingress or egress for the one or more objects, wherein the one or more object placement criteria are based in part on the order of ingress or egress for the one or more objects.

11. One or more tangible, non-transitory computer-readable media storing computer-readable instructions that when executed by one or more processors cause the one or more processors to perform operations, the operations comprising:

receiving object data based in part on one or more states of one or more objects;

determining, based in part on the object data, one or more features of the one or more objects, wherein the one or more features comprise one or more identities of the one or more objects;

determining, based on a comparison of the one or more features of the one or more objects to one or more vehicle capacity criteria, whether the one or more objects satisfy the one or more vehicle capacity criteria, wherein the one or more vehicle capacity criteria are based in part on a carrying capacity of an autonomous vehicle;

responsive to the one or more objects satisfying the one or more vehicle capacity criteria, determining a plurality of assigned locations to place the one or more objects inside the autonomous vehicle based in part on the one or more identities of the one or more objects and one or more object placement criteria; and

generating, based in part on the one or more assigned locations, one or more placement indications inside the autonomous vehicle, wherein the one or more placement indications comprise instructions for directing movement of the one or more objects to at least one of the plurality of assigned locations in the autonomous vehicle.

12. The one or more tangible, non-transitory computer-readable media of claim 11, further comprising:

receiving sensor output from one or more sensors or access output from a vehicle access system, the object data based in part on the sensor output or the access output, wherein the one or more sensors are located on an exterior of the autonomous vehicle or an interior of the autonomous vehicle and comprise an optical sensor, an audio sensor, a tactile sensor, a temperature sensor, or an electromagnetic sensor.

13. The one or more tangible, non-transitory computer-readable media of claim 11, wherein the activating the one or more control systems comprises activating a vehicle access system, a vehicle notification system, a vehicle communication system, or a vehicle propulsion system.

14. The one or more tangible, non-transitory computer-readable media of claim 13, wherein the activating the vehicle access system comprises:

determining whether a spatial relationship between the one or more objects, an entrance to the autonomous vehicle, or a loading location external to the autonomous vehicle satisfies one or more access criteria, wherein the one or more access criteria is based in part on a threshold distance between the entrance and the loading location, a threshold distance between the entrance and the one or more objects, or an orientation of the entrance relative to the loading location; and

responsive to the spatial relationship satisfying the one or more access criteria, modifying access to the autonomous vehicle, the modifying access to the autonomous vehicle comprising locking the entrance, unlocking the entrance, opening the entrance, closing the entrance, activating a passenger restraint system, or deactivating a passenger restraint system.

15. The one or more tangible, non-transitory computer-readable media of claim 13, wherein the activating the vehicle notification system comprises:

determining, based in part on the one or more features, one or more corresponding object locations of the one or more objects; and

generating the one or more placement indications based in part on (i) the one or more object placement criteria, (ii) the one or more identities, and (iii) the one or more corresponding object locations of the one or more objects.

16. An autonomous vehicle comprising:

one or more processors;

one or more non-transitory computer-readable media storing instructions that when executed by the one or more processors cause the one or more processors to perform operations comprising;

receiving object data based in part on one or more states of one or more objects;

determining, based in part on the object data, one or more features of the one or more objects, wherein the one or more features comprise one or more identities of the one or more objects;

determining, based on a comparison of the one or more features of the one or more objects to one or more vehicle capacity criteria, whether the one or more objects satisfy the one or more vehicle capacity criteria, wherein the one or more vehicle capacity criteria are based in part on a carrying capacity of an autonomous vehicle;

responsive to the one or more objects satisfying the one or more vehicle capacity criteria, determining a plurality of assigned locations to place the one or more objects inside the autonomous vehicle based in part on the one or more identities of the one or more objects and one or more object placement criteria; and

generating, by the computing system, based in part on the one or more assigned locations, one or more placement indications inside the autonomous vehicle, wherein the one or more placement indications comprise instructions for directing movement of the one or more objects to at least one of the plurality of assigned locations in the autonomous vehicle.

17. The autonomous vehicle of claim 16, further comprising:

receiving sensor output from one or more sensors or access output from a vehicle access system, the object data based in part on the sensor output or the access output, wherein the one or more sensors are located on an exterior of the autonomous vehicle or an interior of the autonomous vehicle and comprise an optical sensor, an audio sensor, a tactile sensor, a temperature sensor, or an electromagnetic sensor.

18. The autonomous vehicle of claim 16, wherein the activating the one or more control systems comprises activating a vehicle access system, a vehicle notification system, a vehicle communication system, or a vehicle propulsion system.

19. The autonomous vehicle of claim 18, wherein the activating the vehicle access system comprises:

determining whether a spatial relationship between the one or more objects, an entrance to the autonomous vehicle, or a loading location external to the autonomous vehicle satisfies one or more access criteria, wherein the one or more access criteria is based in part on a threshold distance between the entrance and the loading location, a threshold distance between the entrance and the one or more objects, or an orientation of the entrance relative to the loading location; and

responsive to the spatial relationship satisfying the one or more access criteria, modifying access to the autonomous vehicle, the modifying access to the autonomous vehicle comprising locking the entrance, unlocking the entrance, opening the entrance, closing the entrance, activating a passenger restraint system, or deactivating a passenger restraint system.

20. The autonomous vehicle of claim 18, wherein the activating the vehicle notification system comprises:

determining, based in part on the one or more features, one or more corresponding object locations of the one or more objects; and

generating the one or more placement indications based in part on (i) the one or more object placement criteria, (ii) the one or more identities, and (iii) the one or more corresponding object locations of the one or more objects.