IP Library Granted Patent US 11,194,328
Granted Patent B2
US 11,194,328 · App. 16/797,862 · Granted Dec 7, 2021

Operation-security system for an automated vehicle

Inventors: Serge Lambermont (Singapore, SG); Junsung Kim (Pittsburgh, PA); Junqing Wei (Bridgeville, PA); Gaurav Bhatia (Pittsburgh, PA)
Assignee: Motional AD LLC
G05D1/0077G01S13/865G01S13/867G01S13/931G05D1/0088G05D1/0248G05D1/0257G08G1/163G08G1/166G01S2013/9316G01S2013/9318G01S2013/9319G01S2013/93185G05D2201/0212G05D2201/0213
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Quick Facts
Patent No.
US 11,194,328
App. No.
16/797,862
Granted
Dec 7, 2021
Kind
B2
Abstract

An operation-security system for an automated vehicle includes an object-detector and a controller. The object-detector includes at least three sensors. Each sensor is one of a camera used to determine an image-location of an object proximate to a host-vehicle, a lidar-unit used to determine a lidar-location of the object proximate to the host-vehicle, and a radar-unit used to determine a radar-location of the object proximate to the host-vehicle. The controller is in communication with the at least three sensors. The controller is configured to determine a composite-location based on a comparison of locations indicated by the at least three sensors. Information from one sensor is ignored when a respective location indicated by the one sensor differs from the composite-location by greater than an error-threshold. If a remote sensor not on the host-vehicle is used, V2V or V2I communications may be used to communicate a location to the host-vehicle.

Claims (50)

1. An operation-security system for a vehicle, said system comprising:

an object-detector used to determine a first-location of an object proximate to a host-vehicle at a first-time, and a second-location of the object at a second-time characterized as a sampling-interval after the first-time; and

a controller in communication with the object-detector, said controller configured to:

determine a motion-vector of the host-vehicle, estimate an expected-location of the object at the second-time based on the motion-vector, the first-location, and the sampling-interval, wherein information from the object-detector at the second-time is ignored when the expected-location differs from the second-location by greater than an error-threshold; and

determine an object-vector based on a prior-difference between the first-location and a prior-location of the object proximate to the host-vehicle at a prior-time prior to the first-time, wherein the expected-location is also determined based on the object-vector.

2. The system of claim 1 , wherein the motion-vector is based on a yaw rate of the host-vehicle.

3. The system of claim 1 , wherein the object-detector comprises at least three sensors including:

a camera used to determine an imager-location of the object proximate to the host-vehicle;

a lidar-unit used to determine a lidar-location of the object proximate to the host-vehicle; and

a radar-unit used to determine a radar-location of the object proximate to the host-vehicle.

4. The system of claim 3 , wherein the first-location is based on at least one of an average range from the vehicle to the imager-location, the radar-location, and the lidar-location, an average azimuth angle from the vehicle to the imager-location, the radar-location, and the lidar-location, an average latitude of the imager-location, the radar-location, and the lidar-location, or an average longitude of the imager-location, the radar-location, and the lidar-location.

5. The system of claim 3 , wherein at least one of the at least three sensors comprises at least one remote sensor not mounted on or within the vehicle.

6. The system of claim 5 , comprising a transceiver configured to receive at least one of the imager-location, the radar-location, or the lidar-location from the at least one remote sensor.

7. The system of claim 1 , wherein said controller is further configured to:

monitor location information during operation of the host-vehicle, including looking for sudden, unusual, or unexpected changes in the motion-vector, the object-vector, and the expected-location over time; and

determine, using the monitored location information, that the system has been hacked.

8. The system of claim 7 , wherein said controller is further configured to:

in response to determining that the system has been hacked, take action to avoid erratic operation of the host-vehicle.

9. A computer-implemented method, comprising:

determining, using an object-detector, a first-location of an object proximate to a host-vehicle at a first-time, and a second-location of the object at a second-time characterized as a sampling-interval after the first-time; and

determining, using a controller, a motion-vector of the host-vehicle;

estimating, using the controller, an expected-location of the object at the second-time based on the motion-vector, the first-location, and the sampling-interval, wherein information from the object-detector at the second-time is ignored when the expected-location differs from the second-location by greater than an error-threshold; and

determining, using the controller, an object-vector based on a prior-difference between the first-location and a prior-location of the object proximate to the host-vehicle at a prior-time prior to the first-time, wherein the expected-location is also determined based on the object-vector.

10. The method of claim 9 , wherein the motion-vector is based on a yaw rate of the host-vehicle.

11. The method of claim 9 , wherein the object-detector comprises at least three sensors including:

a camera used to determine an imager-location of the object proximate to the host-vehicle;

a lidar-unit used to determine a lidar-location of the object proximate to the host-vehicle; and

a radar-unit used to determine a radar-location of the object proximate to the host-vehicle.

12. The method of claim 11 , wherein the first-location is based on at least one of an average range from the vehicle to the imager-location, the radar-location, and the lidar-location, an average azimuth angle from the vehicle to the imager-location, the radar-location, and the lidar-location, an average latitude of the imager-location, the radar-location, and the lidar-location, or an average longitude of the imager-location, the radar-location, and the lidar-location.

13. The method of claim 11 , wherein at least one of the at least three sensors comprises at least one remote sensor not mounted on or within the vehicle.

14. The method of claim 9 , comprising:

monitoring location information during operation of the host-vehicle, including looking for sudden, unusual, or unexpected changes in the motion-vector, the object-vector, and the expected-location over time; and

determining, using the monitored location information, that a system of the host-vehicle has been hacked.

15. The method of claim 14 , comprising:

in response to determining that the system of the host-vehicle has been hacked, taking action to avoid erratic operation of the host-vehicle.

16. At least one non-transitory computer-readable medium storing instructions which, when executed by at least one processor, cause the at least one processor to perform operations comprising:

determining, using an object-detector, a first-location of an object proximate to a host-vehicle at a first-time, and a second-location of the object at a second-time characterized as a sampling-interval after the first-time; and

determining, using a controller, a motion-vector of the host-vehicle;

estimating, using the controller, an expected-location of the object at the second-time based on the motion-vector, the first-location, and the sampling-interval, wherein information from the object-detector at the second-time is ignored when the expected-location differs from the second-location by greater than an error-threshold; and

determining, using the controller, an object-vector based on a prior-difference between the first-location and a prior-location of the object proximate to the host-vehicle at a prior-time prior to the first-time, wherein the expected-location is also determined based on the object-vector.

17. The at least one non-transitory computer-readable medium of claim 16 , wherein the object-detector comprises at least three sensors including:

a camera used to determine an imager-location of the object proximate to the host-vehicle;

a lidar-unit used to determine a lidar-location of the object proximate to the host-vehicle; and

a radar-unit used to determine a radar-location of the object proximate to the host-vehicle.

18. The at least one non-transitory computer-readable medium of claim 17 , wherein at least one of the at least three sensors comprises at least one remote sensor not mounted on or within the vehicle.

19. The at least one non-transitory computer-readable medium of claim 16 storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:

monitoring location information during operation of the host-vehicle, including looking for sudden, unusual, or unexpected changes in the motion-vector, the object-vector, and the expected-location over time; and

determining, using the monitored location information, that a system of the host-vehicle has been hacked.

20. The at least one non-transitory computer-readable medium of claim 16 storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:

in response to determining that the system of the host-vehicle has been hacked, taking action to avoid erratic operation of the host-vehicle.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 23, 2020
From: APTIV TECHNOLOGIES LIMITED
To: MOTIONAL AD LLC
Reel/Frame 053863/0399 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 3, 2020
From: DELPHI TECHNOLOGIES, INC.
To: APTIV TECHNOLOGIES LIMITED
Reel/Frame 052305/0377 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 3, 2020
From: LAMBERMONT, SERGE; KIM, JUNSUNG; WEI, JUNQING; BHATIA, GAURAV
To: DELPHI TECHNOLOGIES, INC.
Reel/Frame 052313/0702 →