IP Library › Granted Patent US 12,240,468
Granted Patent B1
US 12,240,468 · App. 16/568,849 · Granted Mar 4, 2025

Driving analysis using vehicle-to-vehicle communication

Inventor: Mark V. Slusar (Chicago, IL)
Assignee: Allstate Insurance Company
B60W40/09B60W40/105G06Q40/08G08G1/0112G08G1/22G09B19/167B60W2554/80B60W2556/65G08G1/096791
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Quick Facts
Patent No.
US 12,240,468
App. No.
16/568,849
Granted
Mar 4, 2025
Kind
B1
Abstract

One or more driving analysis computing devices in a driving analysis system may be configured to analyze driving data, determine driving behaviors, and calculate driver scores based on driving data transmitted using vehicle-to-vehicle (V2V) communications. Driving data from multiple vehicles may be collected by vehicle sensors or other vehicle-based systems, transmitted using V2V communications, and then analyzed and compared to determine various driving behaviors by the drivers of the vehicles. Driver scores may be calculated or adjusted based on the determined driving behaviors of vehicle drivers, and also may be calculated or adjusted based on other the driver scores of nearby vehicles.

Claims (60)

1. A driving analysis computing device comprising:

a processor; and

a memory storing computer-executable instructions which, when executed by the processor, cause the driving analysis computing device to:

receive, at a first vehicle, vehicle driving data of a plurality of vehicles including a second vehicle from each vehicle using vehicle-to-vehicle communications while in commute when each vehicle is in a predefined proximity of the first vehicle while in commute and when at least one vehicle lane change has occurred with respect to one of the first vehicle or other vehicle of the plurality of vehicles, the at least one vehicle lane change having occurred within a near proximity of another vehicle of the plurality of vehicles;

determine a vehicle driving behavior of each vehicle of the plurality of vehicles while in commute and when the at least one vehicle lane change has occurred by analyzing at least the vehicle driving data, the vehicle driving behavior comprising a respective driver score for each vehicle, each driver score associated with a respective risk level below, at, or higher than a threshold risk level;

determine, while in commute during a commute portion and when the at least one vehicle lane change has occurred, a high threshold risk level frequency over a period of time within which the first vehicle drives in the predefined proximity of the plurality of vehicles having the respective risk level of the threshold risk level or higher, wherein the plurality of vehicles having the respective risk level of the threshold risk level or higher comprises at least one vehicle submitting upon the at least one vehicle lane change a first time vehicle-to-vehicle communication to the first vehicle and wherein the at least one vehicle is newly sharing the commute portion with the first vehicle, the respective risk level being defined by corresponding vehicle driving behavior and driver score of each of the drivers of each of the plurality of vehicles, including the driver of the second vehicle; and

reduce a driver score of the first vehicle associated with a driver of the first vehicle upon determining that the high threshold risk level frequency is greater than a predominantly high risk threshold frequency.

2. The driving analysis computing device of claim 1 , wherein the instructions, when executed, further cause the driving analysis computing device to:

determine the driver score for the second vehicle, or the driver of the second vehicle, based on the determined vehicle driving behavior of the second vehicle, the driver score being a measurement of driving abilities.

3. The driving analysis computing device of claim 1 , wherein the first vehicle further comprises a plurality of vehicle sensors, and

wherein the second vehicle driving data includes further information detected and received by at least one of the vehicle sensors, the information including at least one of:

a speed of the second vehicle;

a position of the second vehicle; or

a direction of travel of the second vehicle.

4. The driving analysis computing device of claim 1 , wherein the driver score is generated based on a plurality of vehicle behaviors of the second vehicle or the driver of the second vehicle.

5. The driving analysis computing device of claim 1 , wherein determining the vehicle driving behavior of the second vehicle comprises:

determining a first relative position of the second vehicle with respect to the first vehicle at a first time; and

determining a second relative position of the second vehicle with respect to the first vehicle at a second time after the first time.

6. The driving analysis computing device of claim 5 , wherein determining the vehicle driving behavior of the second vehicle comprises:

determining that the second vehicle drove within a specified proximity of a rear of the first vehicle for a specified amount of time based on the first and second relative positions and the first and second times, and

wherein the computer-executable instructions further cause the driving analysis computing device to determine a vehicle driving behavior of the first vehicle including determining that the first vehicle changed lanes in response to the vehicle driving behavior of the second vehicle.

7. The driving analysis computing device of claim 5 , wherein determining the vehicle driving behavior of the second vehicle comprises:

determining that the second vehicle cut off the first vehicle based on the first and second relative positions and the first and second times.

8. The driving analysis computing device of claim 1 , wherein the computer-executable instructions, when executed by the processor, further cause the driving analysis computing device to apply a positive impact on the first vehicle or the driver of the first vehicle by increasing the driver score of the first vehicle associated with the driver of the first vehicle upon determining that the high threshold risk level frequency is equal to or lower than the predominantly high risk threshold frequency.

9. A computer readable medium storing computer-executable instructions that, when executed by a processor, cause a driving analysis computing device to:

receive, at a first vehicle, vehicle driving data of a plurality of vehicles including a second vehicle from each vehicle using vehicle-to-vehicle communications while in commute when each vehicle is in a predefined proximity of the first vehicle while in commute and when at least one vehicle lane change has occurred with respect to one of the first vehicle or other vehicle of the plurality of vehicles, the at least one vehicle lane change having occurred within a near proximity of the other of another vehicle of the plurality of vehicles;

determine a vehicle driving behavior of the each vehicle while in commute and when the at least one vehicle lane change has occurred, based on an analysis of at least the—vehicle driving data of the plurality of vehicles, the vehicle driving behavior of each vehicle comprising a risk level;

determine, while in commute during a commute portion and when the at least one vehicle lane change has occurred, a high threshold risk level frequency over a period of time within which the first vehicle drives in the predefined proximity of the plurality of vehicles having the risk level of a threshold risk level or higher, wherein the plurality of vehicles having the respective risk level of the threshold risk level or higher comprises at least one vehicle submitting upon the at least one vehicle lane change a first time vehicle-to-vehicle communication to the first vehicle and wherein the at least one vehicle is newly sharing the commute portion with the first vehicle, the risk level being defined by corresponding vehicle driving behavior of each of the drivers of each of the plurality of vehicles; and

apply a negative impact on a vehicle driving behavior of the first vehicle or a driver of the first vehicle upon determining that the high threshold risk level frequency (ii) is greater than a predominantly high risk threshold frequency.

10. The computer readable medium of claim 9 , wherein the instructions, when executed, further cause the driving analysis computing device to:

determine a driver score for the second vehicle, or the driver of the second vehicle, based on the determined vehicle driving behavior of the second vehicle, the driver score being a measurement of driving abilities.

11. The computer readable medium of claim 9 , wherein the first vehicle further comprises a plurality of vehicle sensors, and

wherein the second vehicle driving data further includes, as received by at least one of the vehicle sensors, at least one of:

a speed of the second vehicle;

a position of the second vehicle; or

a direction of travel of the second vehicle.

12. The computer readable medium of claim 9 , wherein the second vehicle driving data transmitted from the second vehicle comprises a driver score associated with the second vehicle or the driver of the second vehicle, the driver score being generated based on a plurality of vehicle behaviors of the second vehicle or the driver of the second vehicle.

13. The computer readable medium of claim 9 , wherein determining the second vehicle driving behavior of the second vehicle comprises:

determining a first relative position of the second vehicle with respect to the first vehicle at a first time; and

determining a second relative position of the second vehicle with respect to the first vehicle at a second time after the first time.

14. The computer readable medium of claim 13 , wherein determining the vehicle driving behavior of the second vehicle comprises:

determining that the second vehicle tailgated the first vehicle based on the first and second relative positions and the first and second times, and

wherein the computer-executable instructions further cause the driving analysis computing device to determine a vehicle driving behavior of the first vehicle including determining that the first vehicle changed lanes in response to the vehicle driving behavior of the second vehicle.

15. The computer readable medium of claim 13 , wherein determining the vehicle driving behavior of the second vehicle comprises:

determining that the second vehicle cut off the first vehicle based on the first and second relative positions and the first and second times.

16. The computer readable medium of claim 9 , wherein the computer-executable instructions, when executed by the processor, further cause the driving analysis computing device to apply a positive impact on the vehicle driving behavior of the first vehicle or the driver of the first vehicle upon determining that the high threshold risk level frequency is equal to or lower than the predominantly high risk threshold frequency.

17. A method comprising:

receiving, by an analysis module of a first vehicle, vehicle driving data of a plurality of vehicles including a second vehicle from each vehicle using vehicle-to-vehicle communications while in commute when each vehicle is in a predefined proximity of the first vehicle while in commute and when at least one vehicle lane change has occurred with respect to one of the first vehicle or other vehicle of the plurality of vehicles, the at least one vehicle lane change having occurred within a near proximity of another vehicle of the plurality of vehicles;

determining, by the analysis module, a vehicle driving behavior of each vehicle while in commute and when the at least one vehicle lane change has occurred by analyzing at least the vehicle driving data of the plurality of vehicles, the vehicle driver behavior of each vehicle comprising a risk level;

determining, by the analysis module, while in commute during a commute portion and when the at least one vehicle lane change has occurred, a frequency over a period of time within which the first vehicle drives in the predefined proximity of the plurality of vehicles having the risk level of a threshold risk level or higher, wherein the plurality of vehicles having the respective risk level of the threshold risk level or higher comprises at least one vehicle submitting upon the at least one vehicle lane change a first time vehicle-to-vehicle communication to the first vehicle and wherein the at least one vehicle is newly sharing the commute portion with the first vehicle, the risk level being defined by corresponding vehicle driving behavior of each driver of each of the plurality of vehicles; and

applying a negative impact on a vehicle driving behavior of the first vehicle or a driver of the first vehicle upon determining that the high threshold risk level frequency is greater than a predominantly high risk threshold frequency.

18. The method of claim 17 , wherein determining the vehicle driving behavior of the second vehicle comprises:

determining a first relative position of the second vehicle with respect to the first vehicle at a first time; and

determining a second relative position of the second vehicle with respect to the first vehicle at a second time after the first time.

19. The method of claim 18 , wherein determining the vehicle driving behavior of the second vehicle comprises:

determining that the second vehicle tailgated the first vehicle based on the first and second relative positions and the first and second times, and

wherein the method further comprising determining a vehicle driving behavior of the first vehicle including determining that the first vehicle changed lanes in response to the vehicle driving behavior of the second vehicle.

20. The method of claim 17 , further comprising:

applying a positive impact on the vehicle driving behavior of the first vehicle or the driver of the first vehicle upon determining that the frequency over the period of time with which the first vehicle, or the driver of the first vehicle, drives in the predefined proximity of the plurality of vehicles having the threshold risk level or higher is equal to or lower than the threshold frequency; and

adjusting an insurance premium associated with the first vehicle or driver of the first vehicle to increase based on applying the positive impact and to decrease based on applying the negative impact.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 12, 2019
From: SLUSAR, MARK V.
To: ALLSTATE INSURANCE COMPANY
Reel/Frame 050359/0436 →
Continuity (3)
Continuation 15459851 · Mar 15, 2017
Continuation 14832197 · Aug 21, 2015
Continuation 13904682 · May 29, 2013
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