Detecting objects within a vehicle in connection with a service

• US 9,963,926 B2
• Filed: 06/21/2017
• Issued: 05/08/2018
• Est. Priority Date: 05/11/2015
• Status: Active Grant

• Current Assignee: Uber Technologies, Inc.
• Original Assignee: Uber Technologies, Inc.
• Inventors: Bradley, David McAllister, Valois, Jean-Sebastien
• Primary Examiner(s): Antonucci, Anne M
• Application Number:
  US15/629,372
• Publication Number:
  US 20170284148A1
• Time in Patent Office: 321 Days
• CPC Class Codes: B60N 2/002 Seats provided with an occupancy detection means mounted therein or thereon detection means responsive to presence or absence of children B60N2/266
• CPC Class Codes: B60R 11/04 Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
• CPC Class Codes: E05F 15/70 with automatic actuation
• CPC Class Codes: E05Y 2400/44 Sensors therefore E05Y2400/322, E05Y2400/33, E05Y2400/55, E05Y2400/56, E05Y2400/852 take precedence
• CPC Class Codes: E05Y 2400/45 Control modes
• CPC Class Codes: E05Y 2900/548 Trunk lids
• 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 1/0212 with means for defining a desired trajectory involving a plurality of land vehicles G05D1/0287
• CPC Class Codes: G05D 1/0276 using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/083 Shipping
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G08B 21/24 Reminder alarms, e.g. anti-loss alarms

Abstract

A system for monitoring a vehicle used in providing a service is disclosed. The system detects when the service is complete, and upon detecting that the service is complete, the system determines, from one or more sensors of the vehicle, that an object which should have been removed from the vehicle after completion of the transport service, remains in the vehicle. The system then automatically initiates performance of a remedial action.

Claims

1. A method for monitoring an autonomous vehicle that is operating to provide a transport service, the method being implemented by one or more processors and comprising:

receiving, from a remote system, instructions for the autonomous vehicle to provide a first transport service from a start location to a destination;

receiving first image information of an interior of the autonomous vehicle from one or more cameras positioned within the autonomous vehicle, wherein the first image information is captured by the one or more cameras in response to the autonomous vehicle being within a first predetermined distance of the start location of the first transport service;

receiving second image information of the interior of the autonomous vehicle from the one or more cameras positioned within the autonomous vehicle, wherein the second image information is captured by the one or more cameras in response to the autonomous vehicle being within a second predetermined distance of the destination of the first transport service;

comparing the first image information and the second image information; and

in response to detecting a discrepancy between the first image information and the second image information, automatically initiating performance of a remedial action.

2. The method of claim 1, wherein the discrepancy identifies damage to the autonomous vehicle, including a stain, spill, rip, or scratch.

3. The method of claim 1, wherein the discrepancy identifies an object in the second image information which was not present in the first image information.

4. The method of claim 3, further comprising performing an image recognition process on the first image information and the second image information to recognize the object based on visual characteristics.

5. The method of claim 3, wherein automatically initiating performance of the remedial action includes transmitting a notification that the object is still present in the autonomous vehicle to a computing system that arranged the first transport service.

6. The method of claim 3, further comprising:

scheduling an additional transport service to deliver the object to a specified location in response to receiving a request from a user of the first transport service to deliver the object to the specified location.

7. The method of claim 3, wherein automatically initiating performance of the remedial action includes causing the autonomous vehicle to remain stationary at a specified location until the object is detected as being removed from the autonomous vehicle.

8. The method of claim 1, wherein automatically initiating performance of the remedial action includes communicating, over one or more networks, a message to a computing device associated with a user of the first transport service, the message notifying the user of the discrepancy between the first image information and the second image information.

9. The method of claim 8, wherein the message includes an image of the discrepancy or results of the comparison between the first image information and the second image information.

10. An autonomous vehicle comprising:

one or more sensors generating sensor data; and

a control system to execute instructions that cause the autonomous vehicle to;

operate to provide a first transport service;

receive, from a remote system, instructions for the autonomous vehicle to provide a first transport service from a start location to a destination;

receive first image information of an interior of the autonomous vehicle from one or more cameras positioned within the autonomous vehicle, wherein the first image information is captured by the one or more cameras in response to the autonomous vehicle being within a first predetermined distance of the start location of the first transport service;

receive second image information of the interior of the autonomous vehicle from the one or more cameras positioned within the autonomous vehicle, wherein the second image information is captured by the one or more cameras in response to the autonomous vehicle being within a second predetermined distance of the destination of the first transport service;

compare the first image information and the second image information; and

in response to detecting a discrepancy between the first image information and the second image information, automatically initiate performance of a remedial action.

11. The autonomous vehicle of claim 10, wherein the discrepancy identifies damage to the autonomous vehicle, including a stain, spill, rip, or scratch.

12. The autonomous vehicle of claim 10, wherein the discrepancy identifies an object in the second image information which was not present in the first image information.

13. The autonomous vehicle of claim 12, further comprising performing an image recognition process on the first image information and the second image information to recognize the object based on visual characteristics.

14. The autonomous vehicle of claim 12, wherein automatically initiating performance of the remedial action includes transmitting a notification that the object is still present in the autonomous vehicle to a computing system that arranged the first transport service.

15. The autonomous vehicle of claim 12, further comprising:

scheduling an additional transport service to deliver the object to a specified location in response to receiving a request from a user of the first transport service to deliver the object to the specified location.

16. The autonomous vehicle of claim 12, wherein automatically initiating performance of the remedial action includes causing the autonomous vehicle to remain stationary at a specified location until the object is detected as being removed from the autonomous vehicle.

17. The autonomous vehicle of claim 10, wherein automatically initiating performance of the remedial action includes communicating, over one or more networks, a message to a computing device associated with a user of the first transport service, the message notifying the user of the discrepancy between the first image information and the second image information.

18. The autonomous vehicle of claim 17, wherein the message includes an image of the discrepancy or results of the comparison between the first image information and the second image information.

19. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of an on-board computing system of an autonomous vehicle, causes the on-board computing system to:

operate to provide a first transport service;

receive, from a remote system, instructions for the autonomous vehicle to provide a first transport service from a start location to a destination;

receive first image information of an interior of the autonomous vehicle from one or more cameras positioned within the autonomous vehicle, wherein the first image information is captured by the one or more cameras in response to the autonomous vehicle being within a first predetermined distance of the start location of the first transport service;

receive second image information of the interior of the autonomous vehicle from the one or more cameras positioned within the autonomous vehicle, wherein the second image information is captured by the one or more cameras in response to the autonomous vehicle being within a second predetermined distance of the destination of the first transport service;

compare the first image information and the second image information; and

in response to detecting a discrepancy between the first image information and the second image information, automatically initiate performance of a remedial action.

20. The non-transitory computer-readable medium of claim 19, wherein the discrepancy identifies an object in the second image information which was not present in the first image information.