IP Library Granted Patent US 11,548,513
Granted Patent B2
US 11,548,513 · App. 16/611,343 · Granted Jan 10, 2023

Method and system for evaluating contextual risk profiles in a vehicle

Inventor: Adam John Boulton (Wirral, GB)
Assignee: BlackBerry Limited
B60W40/04B60W30/16B60W30/18163G05D1/0055G05D1/0088G07C5/08B60W2420/42B60W2554/00G05D2201/0213
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Quick Facts
Patent No.
US 11,548,513
App. No.
16/611,343
Granted
Jan 10, 2023
Kind
B2
Abstract

A method for evaluating contextual risk profiles at a computing device ( 110, 212, 312 ) in a vehicle ( 310 ), the method including obtaining information about a proximate vehicle ( 320, 330 ); utilizing the information to create a risk profile for the proximate vehicle ( 320, 330 ); and based on the risk profile, initiating an action at computing device ( 110, 212, 312 ).

Claims (44)

1. A method of a computing device in a first vehicle, the method comprising:

receiving, at the computing device in the first vehicle, image data acquired by a camera of the first vehicle, the image data comprising an image of a license plate of a second vehicle;

obtaining, by the computing device based on information of the license plate, information comprising a maintenance history of the second vehicle, the maintenance history comprising information regarding a worn or failed component of the second vehicle;

utilizing the maintenance history comprising the information regarding the worn or failed component of the second vehicle, creating, by the computing device, a risk profile for the second vehicle; and

based on the risk profile, initiating, by the computing device, an action comprising autonomously changing a position of the first vehicle relative to the second vehicle.

2. The method of claim 1 , comprising:

applying optical character recognition on the image of the license plate to obtain the information of the license plate; and

performing a database query based on the information of the license plate to obtain the maintenance history.

3. The method of claim 1 , comprising:

based on an image of the second vehicle acquired by the camera, determining, by the computing device, a vehicle make and model of the second vehicle; and

confirming that the information of the license plate matches the vehicle make and model.

4. The method of claim 1 , wherein the first vehicle is an autonomous vehicle, and wherein the action comprises increasing a following distance between the first vehicle and the second vehicle.

5. The method of claim 1 , wherein the first vehicle is an autonomous vehicle, and wherein the action comprises the first vehicle changing lanes.

6. The method of claim 1 , wherein the first vehicle is an autonomous vehicle, and wherein the action comprises allowing the second vehicle to pass.

7. The method of claim 1 , wherein the action further comprises alerting a driver if the risk profile exceeds a threshold risk.

8. The method of claim 1 , comprising:

determining, based on the maintenance history, that the second vehicle has the worn or failed component,

wherein the creating of the risk profile is based on the determining.

9. A computing device for a first vehicle, the computing device comprising:

a processor;

a communications subsystem; and

a non-transitory storage medium storing instructions executable on the processor to:

receive image data acquired by a camera of the first vehicle, the image data comprising an image of a license plate of a second vehicle;

obtain, based on information of the license plate, information comprising a maintenance history of the second vehicle, the maintenance history comprising information regarding a worn or failed component of the second vehicle;

utilizing the maintenance history comprising the information regarding the worn or failed component of the second vehicle, create a risk profile for the second vehicle; and

based on the risk profile, initiate an action at the first vehicle, the action comprising autonomously changing a position of the first vehicle relative to the second vehicle.

10. The computing device of claim 9 , wherein the non-transitory storage medium stores further instructions executable on the processor to:

apply optical character recognition on the image of the license plate to obtain an identification of the second vehicle;

and perform a database query based on the identification to obtain the maintenance history.

11. The computing device of claim 9 , wherein the non-transitory storage medium stores further instructions executable on the processor to:

based on an image of the second vehicle acquired by the camera, determine a vehicle make and model of the second vehicle;

and confirm that the information of the license plate matches the vehicle make and model.

12. The computing device of claim 9 , wherein the first vehicle is an autonomous vehicle, and wherein the action comprises increasing a following distance between the first vehicle and the second vehicle.

13. The computing device of claim 9 , wherein the first vehicle is an autonomous vehicle, and wherein the action comprises the first vehicle changing lanes.

14. The computing device of claim 9 , wherein the first vehicle is an autonomous vehicle, and wherein the action comprises allowing the second vehicle to pass.

15. The computing device of claim 9 , wherein the non-transitory storage medium stores further instructions executable on the processor to: determine, based on the maintenance history, that the second vehicle has the worn or failed component, wherein the creating of the risk profile is based on the determining.

16. The computing device of claim 9 , wherein the non-transitory storage medium stores further instructions executable on the processor to: obtain collision statistics of an intersection, wherein the creating of the risk profile is further based on the collision statistics.

17. A non-transitory computer readable medium storing instructions that upon execution cause a computing device in a first vehicle to:

receive image data acquired by a camera of the first vehicle, the image data comprising an image of a license plate of a second vehicle;

obtain, at the first vehicle based on information of the license plate, information comprising a maintenance history of the second vehicle, the maintenance history comprising information regarding a worn or failed component of the second vehicle;

utilizing the maintenance history comprising the information regarding the worn or failed component of the second vehicle, create, at the first vehicle, a risk profile for the second vehicle; and

based on the risk profile, initiate an action at the first vehicle, the action comprising autonomously changing a position of the first vehicle relative to the second vehicle.

18. The non-transitory computer readable medium of claim 17 , comprising further instructions that upon execution cause the computing device to: determine, based on the maintenance history, that the second vehicle has the worn or failed component, wherein the creating of the risk profile is based on the determining.

19. The non-transitory computer readable medium of claim 17 , comprising further instructions that cause the computing device to: obtain collision statistics of an intersection, wherein the creating of the risk profile is further based on the collision statistics.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 6, 2019
From: BOULTON, ADAM JOHN
To: BLACKBERRY UK LIMITED
Reel/Frame 050933/0308 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 6, 2019
From: BLACKBERRY UK LIMITED
To: BLACKBERRY LIMITED
Reel/Frame 050933/0357 →
Continuity (1)
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