IP Library › Granted Patent US 12,290,751
Granted Patent B2
US 12,290,751 · App. 17/404,158 · Granted May 6, 2025

Systems and methods for generating virtual maps in virtual games

Inventors: Kenneth Jason Sanchez (San Francisco, CA); Micah Wind Russo (Oakland, CA)
Assignee: QUANATA, LLC
A63F13/65A63F13/5378A63F2300/69
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Quick Facts
Patent No.
US 12,290,751
App. No.
17/404,158
Granted
May 6, 2025
Kind
B2
Abstract

Method and system for generating virtual maps. For example, the method includes determining first real-world driving characteristics based upon first real-world telematics data of a first real-world user, determining first real-world geolocation characteristics based upon first real-world geolocation data of the first real-world user, generating a first virtual map based upon the first real-world driving characteristics and the first real-world geolocation characteristics, presenting the first virtual map in a virtual game, determining second real-world driving characteristics based upon second real-world telematics data of a second real-world user, determining second real-world geolocation characteristics based upon second real-world geolocation data of the second real-world user, generating a second virtual map based upon the second real-world driving characteristics and the second real-world geolocation characteristics, and presenting the second virtual map in the virtual game.

Claims (102)

1. A computer-implemented method for generating one or more virtual maps in one or more virtual games, the computer-implemented method comprising:

receiving, by a computing device, (i) first real-world telematics data from one or more sensors of a first electronic device connected to a first vehicle and (ii) first real-world geolocation data associated with one or more prior first real-world vehicle trips made by a first real-world user;

determining, by the computing device and using a trained deep-learning model, one or more first real-world driving characteristics based at least in part upon first recognizable patterns of the first real-world telematics data;

determining, by the computing device, one or more first real-world geolocation characteristics based at least in part upon the first real-world geolocation data;

generating, by the computing device, a first virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more first real-world geolocation characteristics, the first virtual map being generated for a first virtual character associated with the first real-world user;

presenting, by the computing device through a user interface of the first electronic device, at least the first virtual map in a virtual game;

receiving, by the computing device, (i) second real-world telematics data from one or more sensors of a second electronic device connected to a second vehicle, and (ii) second real-world geolocation data associated with one or more prior second real-world vehicle trips made by a second real-world user;

determining, by the computing device and using the trained deep-learning model, one or more second real-world driving characteristics based at least in part upon second recognizable patterns of the second real-world telematics data;

determining, by the computing device, one or more second real-world geolocation characteristics based at least in part upon the second real-world geolocation data;

generating, by the computing device, a second virtual map based at least in part upon the one or more second real-world driving characteristics and the one or more second real-world geolocation characteristics, the second virtual map being generated for a second virtual character associated with the second real-world user; and

presenting, by the computing device through a user interface of the second electronic device, at least the second virtual map in the virtual game;

wherein:

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics, the one or more second real-world driving characteristics, the one or more first real-world geolocation characteristics, and the one or more second real-world geolocation characteristics; and

the first virtual map and the second virtual map are presented at a same time in a same virtual game played by the first real user or the second real user.

2. The computer-implemented method of claim 1 , wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are different;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are the same; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being different and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being the same.

3. The computer-implemented method of claim 1 , wherein;

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are the same;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are different; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being the same and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being different.

4. The computer-implemented method of claim 1 , wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are different;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are different; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being different and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being different.

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

receiving, by the computing device, first real-world environmental data associated with the one or more prior first real-world vehicle trips made by the first real-world user;

generating, by the computing device, one or more first virtual environmental conditions for the first virtual character based at least in part upon the first real-world environmental data; and

applying, by the computing device, the one or more first virtual environmental conditions to the first virtual map for the first virtual character to experience in the virtual game.

6. The computer-implemented method of claim 5 , further comprising:

receiving, by the computing device, second real-world environmental data associated with the one or more prior second real-world vehicle trips made by the second real-world user;

generating, by the computing device, one or more second virtual environmental conditions for the second virtual character based at least in part upon the second real-world environmental data; and

applying, by the computing device, the one or more second virtual environmental conditions to the second virtual map for the second virtual character to experience in the virtual game.

7. The computer-implemented method of claim 1 , wherein the generating, by the computing device, the first virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more first real-world geolocation characteristics includes:

generating a first network of virtual roads in the first virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more first real-world geolocation characteristics.

8. The computer-implemented method of claim 7 , wherein the generating, by the computing device, the second virtual map based at least in part upon the one or more second real-world driving characteristics and the one or more second real-world geolocation characteristics includes:

generating a second network of virtual roads in the second virtual map based at least in part upon the one or more second real-world driving characteristics and the one or more second real-world geolocation characteristics.

9. The computer-implemented method of claim 8 , wherein the first network of virtual roads in the first virtual map and the second network of virtual roads in the second virtual map are different.

10. A computing device for generating one or more virtual maps in one or more virtual games, the computing device comprising:

one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to:

receive (i) first real-world telematics data from one or more sensors of a first electronic device connected to a first vehicle and (ii) first real-world geolocation data associated with one or more prior first real-world vehicle trips made by a first real-world user;

determine, using a trained deep-learning model, one or more first real-world driving characteristics based at least in part upon first recognizable patterns of the first real-world telematics data;

determine one or more first real-world geolocation characteristics based at least in part upon the first real-world geolocation data;

generate a first virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more first real-world geolocation characteristics, the first virtual map being generated for a first virtual character associated with the first real-world user;

present, through a user interface of the first electronic device, at least the first virtual map in a virtual game;

receive (i) second real-world telematics data from one or more sensors of a second electronic device connected to a second vehicle, and (ii) second real-world geolocation data associated with one or more prior second real-world vehicle trips made by a second real-world user;

determine, using the trained deep-learning model, one or more second real-world driving characteristics based at least in part upon second recognizable patterns of the second real-world telematics data;

determine one or more second real-world geolocation characteristics based at least in part upon the second real-world geolocation data;

generate a second virtual map based at least in part upon the one or more second real-world driving characteristics and the one or more second real-world geolocation characteristics, the second virtual map being generated for a second virtual character associated with the second real-world user; and

present, through a user interface of the second electronic device, at least the second virtual map in the virtual game;

wherein:

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics, the one or more second real-world driving characteristics, the one or more first real-world geolocation characteristics, and the one or more second real-world geolocation characteristics; and

the first virtual map and the second virtual map are presented at a same time in a same virtual game played by the first real user or the second real user.

11. The computing device of claim 10 , wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are different;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are same; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being different and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being the same.

12. The computing device of claim 10 wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are the same;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are different; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being the same and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being different.

13. The computing device of claim 10 , wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are different;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are different; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being different and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being different.

14. The computing device of claim 10 , wherein, the instructions, when executed by the one or more processors, further cause the one or more processors to:

receive first real-world environmental data associated with the one or more prior first real-world vehicle trips made by the first real-world user;

generate one or more first virtual environmental conditions for the first virtual character based at least in part upon the first real-world environmental data; and

apply the one or more first virtual environmental conditions to the first virtual map for the first virtual character to experience in the virtual game.

15. The computing device of claim 14 , wherein, the instructions, when executed by the one or more processors, further cause the one or more processors to:

receive second real-world environmental data associated with the one or more prior second real-world vehicle trips made by the second real-world user;

generate one or more second virtual environmental conditions for the second virtual character based at least in part upon the second real-world environmental data; and

apply the one or more second virtual environmental conditions to the second virtual map for the second virtual character to experience in the virtual game.

16. The computing device of claim 15 , wherein the one or more first virtual environmental conditions and the one or more second virtual environmental conditions are different.

17. A non-transitory computer-readable medium storing instructions for generating one or more virtual maps in one or more virtual games, wherein the instructions, when executed by one or more processors of a computing device, cause the computing device to:

receive (i) first real-world telematics data from one or more sensors of a first electronic device connected to a first vehicle and (ii) first real-world geolocation data associated with one or more prior first real-world vehicle trips made by a first real-world user;

determine, using a trained deep-learning model, one or more first real-world driving characteristics based at least in part upon first recognizable patterns of the first real-world telematics data;

determine one or more first real-world geolocation characteristics based at least in part upon the first real-world geolocation data;

generate a first virtual map based at least in part upon the one or more first real-world driving characteristics and the one or more first real-world geolocation characteristics, the first virtual map being generated for a first virtual character associated with the first real-world user;

present, through a user interface of the first electronic device, at least the first virtual map in a virtual game;

receive (i) second real-world telematics data from one or more sensors of a second electronic device connected to a second vehicle, and (ii) second real-world geolocation data associated with one or more prior second real-world vehicle trips made by a second real-world user;

determine, using the trained deep-learning model, one or more second real-world driving characteristics based at least in part upon second recognizable patterns of the second real-world telematics data;

determine one or more second real-world geolocation characteristics based at least in part upon the second real-world geolocation data;

generate a second virtual map based at least in part upon the one or more second real-world driving characteristics and the one or more second real-world geolocation characteristics, the second virtual map being generated for a second virtual character associated with the second real-world user; and

present, through a user interface of the second electronic device, at least the second virtual map in the virtual game;

wherein:

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics, the one or more second real-world driving characteristics, the one or more first real-world geolocation characteristics, and the one or more second real-world geolocation characteristics; and

the first virtual map and the second virtual map are presented at a same time in a same virtual game played by the first real user or the second real user.

18. The non-transitory computer-readable medium of claim 17 , wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are different;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are the same; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being different and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being the same.

19. The non-transitory computer-readable medium of claim 17 , wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are the same;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are different; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being the same and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being different.

20. The non-transitory computer-readable medium of claim 17 , wherein:

the one or more first real-world driving characteristics and the one or more second real-world driving characteristics are different;

the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics are different; and

the first virtual map and the second virtual map are generated to be different in response to the one or more first real-world driving characteristics and the one or more second real-world driving characteristics being different and the one or more first real-world geolocation characteristics and the one or more second real-world geolocation characteristics being different.

Assignments (3)
CHANGE OF NAME Recorded Dec 20, 2024
From: BLUEOWL, LLC
To: QUANATA, LLC
Reel/Frame 069754/0484 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 7, 2024
From: RUSSO, MICAH WIND
To: BLUEOWL, LLC
Reel/Frame 068209/0896 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 14, 2024
From: SANCHEZ, KENNETH JASON
To: BLUEOWL, LLC
Reel/Frame 067411/0926 →
Continuity (1)
Related Publication 20230057816A1 · Feb 23, 2023
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