IP Library › Granted Patent US 12,092,468
Granted Patent B2
US 12,092,468 · App. 18/139,836 · Granted Sep 17, 2024

Methods and systems for response vehicle deployment

Inventors: Bryan R. Nussbaum (Bloomington, IL); Rebecca A. Little (Mesa, AZ); Kevin L. Mitchell (Tempe, AZ); Nathan C. Summers (Mesa, AZ); An Ho (Phoenix, AZ)
Assignee: State Farm Mutual Automobile Insurance Company
G01C21/3461G01C21/3638G06N20/00G06T17/05G08G1/202
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Quick Facts
Patent No.
US 12,092,468
App. No.
18/139,836
Granted
Sep 17, 2024
Kind
B2
Abstract

Computer implemented methods and systems for deploying response vehicles based on a virtual environment. A server may obtain a virtual model of an overall region wherein the virtual model was generated based upon a plurality of images captured by a remote imaging vehicle. The server may then provide the virtual model to a user electronic device for rendering in a virtual environment. The server may then determine a target location within the overall region at which the response vehicle should be deployed and generate a route for the response vehicle to follow. The route may be based on damage indicated by the virtual model of the overall region. The server may then provide the route to the user electronic device and/or the response vehicle.

Claims (101)

1. A computer-implemented method comprising:

receiving image data captured by an imaging vehicle, the image data representing a ground surface of a physical region;

determining a target location on the ground surface of the physical region;

determining, based at least in part on the image data, one or more damage locations on the ground surface of the physical region;

determining a ground-based route from a location associated with a response vehicle on the ground surface of the physical region, to the target location, wherein determining the ground-based route is based at least in part on the one or more damage locations;

generating a virtual representation of the physical region, based at least in part on the image data, including a graphical overlay depicting the ground-based route; and

providing the virtual representation to a rendering device associated with the response vehicle.

2. The computer-implemented method of claim 1 , wherein receiving the image data comprises:

determining an image capture characteristic of the imaging vehicle, based at least in part on the physical region and one or more capabilities of the imaging vehicle; and

transmitting, to the imaging vehicle, a control command identifying the image capture characteristic.

3. The computer-implemented method of claim 2 , wherein the imaging vehicle is an aerial imaging drone, and wherein the image capture characteristic comprises at least one of an image resolution, an image angle, an altitude from which the image data is captured, or a travel path of the aerial imaging drone.

4. The computer-implemented method of claim 1 , wherein determining the target location comprises:

identifying, based at least in part on the image data, a physical location proximate to a first damage location.

5. The computer-implemented method of claim 1 , wherein determining the ground-based route comprises:

determining, based at least in part on the image data, that a physical roadway in the physical region is non-traversable;

determining a first route from the location associated with the response vehicle to the target location, wherein the first route includes the non-traversable physical roadway;

determining a second route from the location associated with the response vehicle to the target location, wherein the second route does not include the non-traversable physical roadway; and

selecting the second route to be indicated in the graphical overlay.

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

determining an off-road capability of the response vehicle; and

determining, based at least in part on the off-road capability of the response vehicle, that an off-road portion of the ground-based route is traversable by the response vehicle.

7. The computer-implemented method of claim 1 , wherein determining the one or more damage locations comprises:

extracting metadata from the image data, the metadata including at least timestamp data and location data associated with the image data;

determining a first subset of the image data captured prior to damage occurring at the one or more damage locations within the physical region, based at least in part on the timestamp data;

generating a first model of the physical region, based at least in part on the first subset of the image data;

determining a second subset of the image data captured subsequent to damage occurring at the one or more damage locations within the physical region, based at least in part on the timestamp data; and

generating a second model of the physical region, based at least in part on the second subset of the image data.

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

executing a machine learning model, based at least in part on the image data, to determine the target location;

determining the response vehicle based on a distance from a current location of the response vehicle to the target location; and

transmitting a signal identifying the target location to the response vehicle.

9. A system comprising:

a means for receiving image data captured by an imaging vehicle, the image data representing a ground surface of a physical region;

a means for determining a target location on the ground surface of the physical region;

a means for determining, based at least in part on the image data, one or more damage locations on the ground surface of the physical region;

a means for determining a ground-based route from a location associated with a response vehicle on the ground surface of the physical region, to the target location, wherein determining the ground-based route is based at least in part on the one or more damage locations;

a means for generating a virtual representation of the physical region, based at least in part on the image data, including a graphical overlay depicting the ground-based route; and

a means for providing the virtual representation to a rendering device associated with the response vehicle.

10. The system of claim 9 , wherein the means for receiving the image data comprises:

a means for determining an image capture characteristic of the imaging vehicle, based at least in part on the physical region and one or more capabilities of the imaging vehicle; and

a means for transmitting, to the imaging vehicle, a control command identifying the image capture characteristic.

11. The system of claim 9 , wherein the means for determining the target location comprises:

a means for identifying, based at least in part on the image data, a physical location proximate to a first damage location.

12. The system of claim 9 , further comprising:

a means for determining an off-road capability of the response vehicle; and

a means for determining, based at least in part on the off-road capability of the response vehicle, that an off-road portion of the ground-based route is traversable by the response vehicle.

13. The system of claim 9 , further comprising:

a means for executing a machine learning model, based at least in part on the image data, to determine the target location;

a means for determining the response vehicle based on a distance from a current location of the response vehicle to the target location; and

a means for transmitting a signal identifying the target location to the response vehicle.

14. A computer system comprising:

one or more processors; and

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

receiving image data captured by an imaging vehicle, the image data representing a ground surface of a physical region;

determining a target location on the ground surface of the physical region;

determining, based at least in part on the image data, one or more damage locations on the ground surface of the physical region;

determining a ground-based route from a location associated with a response vehicle on the ground surface of the physical region, to the target location, wherein determining the ground-based route is based at least in part on the one or more damage locations;

generating a virtual representation of the physical region, based at least in part on the image data, including a graphical overlay depicting the ground-based route to the target location; and

providing the virtual representation to a rendering device associated with the response vehicle.

15. The computer system of claim 14 , wherein receiving the image data comprises:

determining an image capture characteristic of the imaging vehicle, based at least in part on the physical region and one or more capabilities of the imaging vehicle; and

transmitting, to the imaging vehicle, a control command identifying the image capture characteristic.

16. The computer system of claim 15 , wherein the imaging vehicle is an aerial imaging drone, and wherein the image capture characteristic comprises at least one of an image resolution, an image angle, an altitude from which the image data is captured, or a travel path of the aerial imaging drone.

17. The computer system of claim 14 , wherein determining the target location comprises:

identifying, based at least in part on the image data, a physical location proximate to a first damage location.

18. The computer system of claim 14 , wherein determining the ground-based route comprises:

determining, based at least in part on the image data, that a physical roadway in the physical region is non-traversable;

determining a first route from the location associated with the response vehicle to the target location, wherein the first route includes the non-traversable physical roadway;

determining a second route from the location associated with the response vehicle to the target location, wherein the second route does not include the non-traversable physical roadway; and

selecting the second route to be indicated in the graphical overlay.

19. The computer system of claim 14 , the operations further comprising:

determining an off-road capability of the response vehicle; and

determining, based at least in part on the off-road capability of the response vehicle, that an off-road portion of the ground-based route is traversable by the response vehicle.

20. The computer system of claim 14 , wherein determining the one or more damage locations comprises:

extracting metadata from the image data, the metadata including at least timestamp data and location data associated with the image data;

determining a first subset of the image data captured prior to damage occurring at the one or more damage locations within the physical region, based at least in part on the timestamp data;

generating a first model of the physical region, based at least in part on the first subset of the image data;

determining a second subset of the image data captured subsequent to damage occurring at the one or more damage locations within the physical region, based at least in part on the timestamp data; and

generating a second model of the physical region, based at least in part on the second subset of the image data.

21. The computer system of claim 14 , the operations further comprising:

executing a machine learning model, based at least in part on the image data, to determine the target location;

determining the response vehicle based on a distance from a current location of the response vehicle to the target location; and

transmitting a signal identifying the target location to the response vehicle.

22. One or more non transitory computer readable media storing instructions executable by a processor, wherein the instructions, when executed, cause the processor to perform operations comprising:

receiving image data captured by an imaging vehicle, the image data representing a ground surface of a physical region;

determining a target location on the ground surface of the physical region;

determining, based at least in part on the image data, one or more damage locations on the ground surface of the physical region;

determining a ground-based route from a location associated with a response vehicle on the ground surface of the physical region, to the target location, wherein determining the ground-based route is based at least in part on the one or more damage locations;

generating a virtual representation of the physical region, based at least in part on the image data, including a graphical overlay depicting the ground-based route; and

providing the virtual representation to a rendering device associated with the response vehicle.

23. The one or more non transitory computer readable media of claim 22 , wherein receiving the image data comprises:

determining an image capture characteristic of the imaging vehicle, based at least in part on the physical region and one or more capabilities of the imaging vehicle; and

transmitting, to the imaging vehicle, a control command identifying the image capture characteristic.

24. The one or more non transitory computer readable media of claim 22 , wherein determining the ground-based route comprises:

determining, based at least in part on the image data, that a physical roadway in the physical region is non-traversable;

determining a first route from the location associated with the response vehicle to the target location, wherein the first route includes the non-traversable physical roadway;

determining a second route from the location associated with the response vehicle to the target location, wherein the second route does not include the non-traversable physical roadway; and

selecting the second route to be indicated in the graphical overlay.

25. The one or more non transitory computer readable media of claim 22 , the operations further comprising:

determining an off-road capability of the response vehicle; and

determining, based at least in part on the off-road capability of the response vehicle, that an off-road portion of the ground-based route is traversable by the response vehicle.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 26, 2023
From: NUSSBAUM, BRYAN R.; LITTLE, REBECCA A.; MITCHELL, KEVIN L.; SUMMERS, NATHAN C.; HO, AN
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 063472/0379 →
Continuity (3)
Continuation 16915557 · Jun 29, 2020
Continuation 15946920 · Apr 6, 2018
Related Publication 20230258463A1 · Aug 17, 2023