IP Library Patent Application 18663871
Patent Application
App. No. 18/663,871

ACCIDENT RECONSTRUCTION IMPLEMENTING UNMANNED AERIAL VEHICLES (UAVS)

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Quick Facts
Patent No.
US None
App. No.
18/663,871
Abstract

Unmanned aerial vehicles (UAVs) may facilitate the generation of a virtual reconstruction model of a vehicle collision. UAVs may collect data (including images) related to the vehicle collision, such as with the insured's permission, which may be received by an external computing device associated with the insurer and utilized to perform a photogrammetric analysis of the images to determine vehicle impact points, the road layout at the scene of the collision, the state of the traffic light at the scene of the collision, the speeds and directions of vehicles, etc. This data may be used to generate a virtual reconstruction model of the vehicle collision. An insurer may use the virtual reconstruction model to perform various insurance-related tasks, such as allocating fault to drivers or autonomous vehicles involved in the vehicle collision, and adjustment of insurance pricing based upon the fault allocation.

Claims (64)

1 . A system for vehicle collision reconstruction using data from an unmanned aerial vehicle comprising:

an unmanned aerial vehicle (UAV);

a server in communication with the UAV via a network, the server including:

a processor; and

a non-transitory computer-readable memory storing instructions thereon that, when executed by the processor, cause the server to:

receive a request to inspect a vehicle involved in a vehicle collision, the request including a location of the vehicle;

instruct the UAV to travel to the location of the vehicle;

instruct the UAV to collect damage information associated with the vehicle using one or more sensors of the UAV; and

generate a virtual reconstruction model of the vehicle collision based upon the damage information collected by the UAV.

2 . The system of claim 1 , wherein the damage information includes vehicle collision images of (i) vehicles involved in a vehicular collision, and (ii) a scene of the vehicle collision.

3 . The system of claim 2 , wherein the instructions further cause the server to:

perform a photogrammetric analysis of the vehicle collision images; and

generate the virtual reconstruction model of the vehicle collision based upon the photogrammetric analysis of the vehicle collision images.

4 . The system of claim 3 , wherein to perform the photogrammetric analysis of the vehicle collision images, the instructions cause the server to:

identify one or more impact points of vehicles involved in the vehicle collision by analyzing the images of vehicles involved in the vehicular collision;

measure a structural crush distance for each of the one or more impact points for each of the vehicles; and

calculate a speed and direction of each of the vehicles involved in the vehicular collision or crash before, during, and after the vehicle collision based upon a location of each of the one or more impact points and the structural crush distance for each of the vehicles involved in the vehicle collision.

5 . The system of claim 4 , wherein to generate the virtual reconstruction model of the vehicle collision, the instructions cause the server to:

generate the virtual reconstruction model of the vehicle collision to indicate the calculated speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision.

6 . The system of claim 5 , wherein to perform the photogrammetric analysis of the vehicle collision images, the instructions cause the server to:

generate a scaled road layout corresponding to the scene of the vehicle collision by analyzing the images of the scene of the vehicle collision, and

generate the virtual reconstruction model of the vehicle collision to indicate the calculated speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision overlaid onto the scaled road layout.

7 . The system of claim 3 , wherein the instructions further cause the server to:

receive telematics data from one or more of the vehicles involved in the vehicular collision; and

verify the virtual reconstruction model with the telematics data.

8 . A computer-implemented method for vehicle collision reconstruction using data from an unmanned aerial vehicle, the method comprising:

receiving, by one or more processors, a request to inspect a vehicle involved in a vehicle collision, the request including a location of the vehicle;

instructing, by the one or more processors, an unmanned aerial vehicle (UAV) to travel to the location of the vehicle;

instructing, by the one or more processors, the UAV to collect damage information associated with the vehicle using one or more sensors of the UAV; and

generating, by the one or more processors, a virtual reconstruction model of the vehicle collision based upon the damage information collected by the UAV.

9 . The computer-implemented method of claim 8 , wherein the damage information includes vehicle collision images of (i) vehicles involved in a vehicular collision, and (ii) a scene of the vehicle collision.

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

performing, by the one or more processors, a photogrammetric analysis of the vehicle collision images; and

generating, by the one or more processors, the virtual reconstruction model of the vehicle collision based upon the photogrammetric analysis of the vehicle collision images.

11 . The computer-implemented method of claim 10 , wherein performing the photogrammetric analysis of the vehicle collision images includes

identifying, by the one or more processors, one or more impact points of vehicles involved in the vehicle collision by analyzing the images of vehicles involved in the vehicular collision;

measuring, by the one or more processors, a structural crush distance for each of the one or more impact points for each of the vehicles; and

calculating, by the one or more processors, a speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision based upon a location of each of the one or more impact points and the structural crush distance for each of the vehicles involved in the vehicle collision.

12 . The computer-implemented method of claim 11 , wherein generating the virtual reconstruction model of the vehicle collision includes:

generating, by the one or more processors, the virtual reconstruction model of the vehicle collision to indicate the calculated speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision.

13 . The computer-implemented method of claim 12 , wherein performing the photogrammetric analysis of the vehicle collision images includes:

generating, by the one or more processors, a scaled road layout corresponding to the scene of the vehicle collision by analyzing the images of the scene of the vehicle collision, and

generating, by the one or more processors, the virtual reconstruction model of the vehicle collision to indicate the calculated speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision overlaid onto the scaled road layout.

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

receiving, by the one or more processors, telematics data from one or more of the vehicles involved in the vehicular collision; and

verifying, by the one or more processors, the virtual reconstruction model with the telematics data.

15 . A non-transitory computer readable media for vehicle collision reconstruction using data from an unmanned aerial vehicle, the non-transitory computer readable media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to:

receive a request to inspect a vehicle involved in a vehicle collision, the request including a location of the vehicle;

instruct an unmanned aerial vehicle (UAV) to travel to the location of the vehicle;

instruct the UAV to collect damage information associated with the vehicle using one or more sensors of the UAV; and

generate a virtual reconstruction model of the vehicle collision based upon the damage information collected by the UAV.

16 . The non-transitory computer readable media of claim 15 , wherein the damage information includes vehicle collision images of (i) vehicles involved in a vehicular collision, and (ii) a scene of the vehicle collision.

17 . The non-transitory computer readable media of claim 16 , wherein the instructions further cause the one or more processors to:

perform a photogrammetric analysis of the vehicle collision images; and

generate the virtual reconstruction model of the vehicle collision based upon the photogrammetric analysis of the vehicle collision images.

18 . The non-transitory computer readable media of claim 17 , wherein to perform the photogrammetric analysis of the vehicle collision images, the instructions cause the one or more processors to:

identify one or more impact points of vehicles involved in the vehicle collision by analyzing the images of vehicles involved in the vehicular collision;

measure a structural crush distance for each of the one or more impact points for each of the vehicles; and

calculate a speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision based upon a location of each of the one or more impact points and the structural crush distance for each of the vehicles involved in the vehicle collision.

19 . The non-transitory computer readable media of claim 18 , wherein to generate the virtual reconstruction model of the vehicle collision, the instructions cause the one or more processors to:

generate the virtual reconstruction model of the vehicle collision to indicate the calculated speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision.

20 . The non-transitory computer readable media of claim 19 , wherein to perform the photogrammetric analysis of the vehicle collision images, the instructions cause the one or more processors to:

generate a scaled road layout corresponding to the scene of the vehicle collision by analyzing the images of the scene of the vehicle collision, and

generate the virtual reconstruction model of the vehicle collision to indicate the calculated speed and direction of each of the vehicles involved in the vehicular collision before, during, and after the vehicle collision overlaid onto the scaled road layout.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 18, 2025
From: STATE FARM MUTUAL AUTOMOBILE INSURANCE CO.
To: NEARMAP US, INC.
Reel/Frame 070548/0732 →
CORRECTIVE ASSIGNMENT TO CORRECT THE APPLICATION NUMBER 17979729 PREVIOUSLY RECORDED ON REEL 67476 FRAME 596. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Dec 13, 2024
From: TOFTE, NATHAN L.; RYAN, TIMOTHY W.; BAUMANN, NATHAN W.; JACOB, MICHAEL SHAWN; LILLIE, JOSHUA DAVID; HARVEY, BRIAN N; LYONS, ROXANE; GRANT, ROSEMARIE GEIER
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 069633/0540 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 21, 2024
From: TOFTE, NATHAN L.; RYAN, TIMOTHY W.; BAUMANN, NATHAN W.; JACOB, MICHAEL SHAWN; LILLIE, JOSHUA DAVID; HARVEY, BRIAN N; LYONS, ROXANE; GRANT, ROSEMARIE GEIER
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 067476/0596 →