IP Library Granted Patent US 10,940,870
Granted Patent B1
US 10,940,870 · App. 16/203,250 · Granted Mar 9, 2021

Systems and methods for visualizing predicted driving risk

Inventors: Theobolt N. Leung (San Francisco, CA); Micah Wind Russo (Oakland, CA)
Assignee: BlueOwl, LLC
B60W50/14B60W30/095B60W40/09G06N5/046B60W2050/0035B60W2050/146
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Quick Facts
Patent No.
US 10,940,870
App. No.
16/203,250
Granted
Mar 9, 2021
Kind
B1
Abstract

Systems and methods of visualizing predicted driving risk are provided herein. Vehicle sensor data associated with a vehicle operator may be analyzed. Based on the analysis of the vehicle sensor data, one or more vehicle operation risks associated with the vehicle operator may be predicted. Each vehicle operation risk may be associated with a portion of a vehicle associated with the vehicle operator. Additionally, each vehicle operation risk may be assigned a priority level, e.g., based on predicted likelihood of occurrence, predicted danger to the vehicle operator, predicted damage to the vehicle, etc. A display overview of the vehicle may be presented to the vehicle operator. In the display overview of the vehicle portions of the vehicle associated with each of the predicted vehicle operation risks may be highlighted. The portions may be highlighted differently (using different colors, heavier/lighter shading, etc.) based on the priority level of their associated risks.

Claims (55)

1. A computer-implemented method of visualizing predicted driving risk, the method comprising:

analyzing, by a processor, vehicle sensor data associated with a vehicle operator;

predicting, by the processor, based upon the vehicle sensor data, one or more vehicle operation risks associated with the vehicle operator, wherein each risk of the one or more vehicle operation risks is associated with a risk of damage to a particular portion of a vehicle associated with the vehicle operator;

presenting, by the processor, to the vehicle operator, a first display overview of the vehicle, wherein the first display overview of the vehicle includes a first graphical representation of the vehicle; and

highlighting, by the processor, in the first graphical representation of the vehicle, vehicle parts on the vehicle corresponding to the particular portion of the vehicle associated with each risk of the one or more vehicle operation risks.

2. The computer-implemented method of claim 1 , wherein the vehicle sensor data associated with the vehicle operator include one or more of: speed data, acceleration data, braking data, cornering data, object range distance data, turn signal data, seatbelt use data, location data, phone use data, weather data, and/or road type data.

3. The computer-implemented method of claim 1 , wherein each risk of the one or more vehicle operation risks is assigned a priority level based upon one or more of: (i) predicted likelihood of occurrence; (ii) predicted danger to the vehicle operator; and/or (iii) predicted damage to the vehicle.

4. The computer-implemented method of claim 3 , wherein highlighting the particular portion of the vehicle associated with each risk of the one or more vehicle operation risks further comprises:

highlighting each portion of the vehicle differently based upon the priority level of each risk of the one or more vehicle operation risks.

5. The computer-implemented method of claim 4 , wherein highlighting each portion of the vehicle differently based upon the priority level of each risk of the one or more vehicle operation risks further comprises:

highlighting portions of the vehicle associated with higher priority risks in a first color; and

highlighting portions of the vehicle associated with lower priority risks in a second color.

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

identifying, by the processor, one or more steps for reducing the one or more vehicle operation risks; and

presenting, by the processor, to the vehicle operator, a vehicle operation guidance based upon the one or more steps for reducing the one or more vehicle operation risks.

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

presenting, by the processor, to the vehicle operator, a second display overview of the vehicle, wherein the second display overview of the vehicle includes a second graphical representation of the vehicle; and

highlighting, by the processor, in the second graphical representation of the vehicle, the vehicle parts on the vehicle corresponding to portions of the vehicle associated with the one or more vehicle operation risks to be reduced based upon the vehicle operation guidance.

8. A computer system for visualizing predicted driving risk, the computer system comprising:

one or more processors; and

one or more memories storing instructions that, when executed by the one or more processors, cause the computer system to:

analyze vehicle sensor data associated with a vehicle operator;

predict, based upon the vehicle sensor data, one or more vehicle operation risks associated with the vehicle operator, wherein each risk of the one or more vehicle operation risks is associated with a risk of damage to a particular portion of a vehicle associated with the vehicle operator;

present, to the vehicle operator, a first display overview of the vehicle, wherein the first display overview of the vehicle includes a first graphical representation of the vehicle; and

highlight, in the first graphical representation of the vehicle, vehicle parts on the vehicle corresponding to the particular portion of the vehicle associated with each risk of the one or more vehicle operation risks.

9. The computer system of claim 8 , wherein the vehicle sensor data associated with the vehicle operator include one or more of: speed data, acceleration data, braking data, cornering data, object range distance data, turn signal data, seatbelt use data, location data, phone use data, weather data, and/or road type data.

10. The computer system of claim 8 , wherein each risk of the one or more vehicle operation risks is assigned a priority level based upon one or more of: (i) predicted likelihood of occurrence; (ii) predicted danger to the vehicle operator; and/or (iii) predicted damage to the vehicle.

11. The computer system of claim 10 , wherein the instructions that cause the computer system to highlight the particular portion of the vehicle associated with each risk of the one or more vehicle operation risks further cause the computer system to:

highlight each portion of the vehicle differently based upon the priority level of each risk of the one or more vehicle operation risks.

12. The computer system of claim 11 , wherein the instructions that cause the computer system to highlight each portion of the vehicle differently based upon the priority level of each risk of the one or more vehicle operation risks further cause the computer system to:

highlight portions of the vehicle associated with higher priority risks in a first color; and

highlight portions of the vehicle associated with lower priority risks in a second color.

13. The computer system of claim 8 , wherein the instructions, when executed by the one or more processors, further cause the computer system to:

identify one or more steps for reducing the one or more vehicle operation risks; and

present, to the vehicle operator, a vehicle operation guidance based upon the one or more steps for reducing the one or more vehicle operation risks.

14. The computer system of claim 13 , wherein the instructions, when executed by the one or more processors, further cause the computer system to:

present, to the vehicle operator, a second display overview of the vehicle, wherein the second display overview of the vehicle includes a second graphical presentation of the vehicle; and

highlight, in the second graphical presentation of the vehicle, the vehicle parts on the vehicle corresponding to portions of the vehicle associated with the one or more vehicle operation risks to be reduced based upon the vehicle operation guidance.

15. A non-transitory computer-readable storage medium having stored thereon a set of instructions for visualizing predicted driving risk, executable by a processor, the set of instructions comprising instructions for:

analyzing vehicle sensor data associated with a vehicle operator;

predicting, based on the vehicle sensor data, one or more vehicle operation risks associated with the vehicle operator, wherein each risk of the one or more vehicle operation risks is associated with a risk of damage to a particular portion of a vehicle associated with the vehicle operator;

presenting, to the vehicle operator, a first display overview of the vehicle, wherein the first display overview of the vehicle includes a first graphical representation of the vehicle; and

highlighting, in the first graphical representation of the vehicle, vehicle parts on the vehicle corresponding to the particular portion of the vehicle associated with each risk of the one or more vehicle operation risks.

16. The non-transitory computer-readable storage medium of claim 15 , wherein each risk of the one or more vehicle operation risks is assigned a priority level based upon one or more of: (i) predicted likelihood of occurrence; (ii) predicted danger to the vehicle operator; and/or (iii) predicted damage to the vehicle.

17. The non-transitory computer-readable storage medium of claim 16 , wherein the instructions for highlighting the particular portion of the vehicle associated with each risk of the one or more vehicle operation risks further comprise instructions for:

highlighting each portion of the vehicle differently based upon the priority level of each risk of the one or more vehicle operation risks.

18. The non-transitory computer-readable storage medium of claim 17 , wherein the instructions for highlighting each portion of the vehicle differently based upon the priority level of each risk of the one or more vehicle operation risks further comprise instructions for:

highlighting portions of the vehicle associated with higher priority risks in a first color; and

highlighting portions of the vehicle associated with lower priority risks in a second color.

19. The non-transitory computer-readable storage medium of claim 15 , further comprising instructions for:

identifying one or steps for reducing the one or more vehicle operation risks; and

presenting, to the vehicle operator, a vehicle operation guidance based upon the one or more steps for reducing the one or more vehicle operation risks.

20. The non-transitory computer-readable storage medium of claim 19 , further comprising instructions for:

presenting, to the vehicle operator, a second display overview of the vehicle, wherein the second display overview of the vehicle includes a second graphical presentation of the vehicle; and

highlighting, in the second graphical representation of the vehicle, the vehicle parts on the vehicle corresponding to portions of the vehicle associated with the one or more vehicle operation risks to be reduced based upon the vehicle operation guidance.

Assignments (2)
CHANGE OF NAME Recorded May 29, 2024
From: BLUEOWL, LLC
To: QUANATA, LLC
Reel/Frame 067558/0600 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 24, 2019
From: LEUNG, THEOBOLT N.; RUSSO, MICAH WIND
To: BLUEOWL, LLC
Reel/Frame 048124/0074 →
Cited By (1)
US 12,214,795