Granted Patent B2

US 12,423,733 · App. 18/497,673 · Granted Sep 23, 2025

Inventors: Ryan Michael Gross (Normal, IL); Joseph Robert Brannan (Bloomington, IL); Brian N. Harvey (Bloomington, IL)

Assignee: State Farm Mutual Automobile Insurance Company

G06Q30/0279G01C21/3446G01C21/3484G01C21/3492G01C21/3688G06N5/04G06N20/00G06Q30/0208H04W4/027H04W4/029

Abstract

Claims (59)

1. A user analytics computing device for processing vehicle-based telematics data, the user analytics computing device comprising at least one processor in communication with a memory device, the at least one processor configured to:

generate a driver profile of a driver based at least in part upon historical telematics data associated with a plurality of historical trips taken by the driver using a vehicle;

generate a contextualized driver profile by synthesizing the driver profile and contextual data associated with an environment in which the vehicle travelled during the plurality of historical trips;

based upon the contextualized driver profile, generate a user offering including an indication of driving behavior of the driver affecting the driver profile;

cause to be displayed, on a user computing device associated with the driver, the user offering including displaying the indication of driving behavior of the driver, a recommendation including at least one of (i) one or more alternate forms of transportation for the driver to incorporate when the driver takes trips or (ii) how to improve the driving behavior, and an incentive if the recommendation is implemented; and

after the user offering is displayed:

determine whether the recommendation has been implemented by analyzing current telematics data associated with current trips taken by the driver using the vehicle; and

in response to determining that the recommendation has been implemented, transmit, to the user computing device, a confirmation message indicating that the driver has earned the incentive.

2. The user analytics computing device of claim 1 , wherein the at least one processor is further configured to receive the historical telematics data from a vehicle computing device associated with the vehicle.

3. The user analytics computing device of claim 1 , wherein the at least one processor is further configured to access the contextual data from the memory device.

4. The user analytics computing device of claim 1 , wherein the contextualized driver profile includes (i) metrics associated with driving behavior of the driver within the environment and (ii) models associated with common routes driven by the driver using the vehicle.

5. The user analytics computing device of claim 1 , wherein the at least one processor is further configured to receive the current telematics data from a vehicle computing device associated with the vehicle.

6. The user analytics computing device of claim 1 , wherein the at least one processor is further configured to synthesize the driver profile and the contextual data by:

comparing an average speed of the vehicle during a portion of at least one route travelled by the driver during at least one of the plurality of historical trips and a posted speed limit along the at least one route;

determining that the vehicle exceeds the posted speed limit during the portion of the at least one route; and

updating the contextualized driver profile to include an indicator that the driver operates the vehicle above the posted speed limit at a location corresponding to the portion of the at least one route.

7. The user analytics computing device of claim 1 , wherein the at least one processor is further configured to synthesize the driver profile and the contextual data by:

identifying at least one route travelled by the driver during a subset of the plurality of historical trips as a common route;

model, using artificial intelligence, historical travel of the driver along the common route based upon (i) the driver profile, (ii) at least one of current, average, or predicted traffic data along the common route, and (iii) traffic light timing data of traffic lights disposed along the common route, wherein (ii) and (iii) are included in the contextual data; and

update the contextualized driver profile to include the modelled historical travel of the driver.

8. A computer-implemented method for processing vehicle-based telematics data, the method implemented by a user analytics computing device including at least one processor in communication with a memory device, the method comprising:

generating a driver profile of a driver based at least in part upon historical telematics data associated with a plurality of historical trips taken by the driver using a vehicle;

generating a contextualized driver profile by synthesizing the driver profile and contextual data associated with an environment in which the vehicle travelled during the plurality of historical trips;

based upon the contextualized driver profile, generating a user offering including an indication of driving behavior of the driver affecting the driver profile;

causing to be displayed, on a user computing device associated with the driver, the user offering including displaying the indication of driving behavior of the driver, a recommendation including at least one of (i) one or more alternate forms of transportation for the driver to incorporate when the driver takes trips or (ii) how to improve the driving behavior, and an incentive if the recommendation is implemented; and

after the user offering is displayed:

determining whether the recommendation has been implemented by analyzing current telematics data associated with current trips taken by the driver using the vehicle; and

in response to determining that the recommendation has been implemented, transmitting, to the user computing device, a confirmation message indicating that the driver has earned the incentive.

9. The computer-implemented method of claim 8 further comprising receiving the historical telematics data from a vehicle computing device associated with the vehicle.

10. The computer-implemented method of claim 8 further comprising accessing the contextual data from the memory device.

11. The computer-implemented method of claim 8 , wherein the contextualized driver profile includes (i) metrics associated with driving behavior of the driver within the environment and (ii) models associated with common routes driven by the driver using the vehicle.

12. The computer-implemented method of claim 8 further comprising receiving the current telematics data from a vehicle computing device associated with the vehicle.

13. The computer-implemented method of claim 8 further comprising synthesizing the driver profile and the contextual data by:

comparing an average speed of the vehicle during a portion of at least one route travelled by the driver during at least one of the plurality of historical trips and a posted speed limit along the at least one route;

determining that the vehicle exceeds the posted speed limit during the portion of the at least one route; and

updating the contextualized driver profile to include an indicator that the driver operates the vehicle above the posted speed limit at a location corresponding to the portion of the at least one route.

14. The computer-implemented method of claim 8 further comprising synthesizing the driver profile and the contextual data by:

identifying at least one route travelled by the driver during a subset of the plurality of historical trips as a common route;

model, using artificial intelligence, historical travel of the driver along the common route based upon (i) the driver profile, (ii) at least one of current, average, or predicted traffic data along the common route, and (iii) traffic light timing data of traffic lights disposed along the common route, wherein (ii) and (iii) are included in the contextual data; and

update the contextualized driver profile to include the modelled historical travel of the driver.

15. At least one non-transitory computer-readable storage medium having computer-executable instructions embodied thereon, when executed by a user analytics computing device having at least one processor in communication with at least one memory device, the computer-executable instructions cause the at least one processor to:

generate a driver profile of a driver based at least in part upon historical telematics data associated with a plurality of historical trips taken by the driver using a vehicle;

generate a contextualized driver profile by synthesizing the driver profile and contextual data associated with an environment in which the vehicle travelled during the plurality of historical trips;

based upon the contextualized driver profile, generate a user offering including an indication of driving behavior of the driver affecting the driver profile;

cause to be displayed, on a user computing device associated with the driver, the user offering including displaying the indication of driving behavior of the driver, a recommendation including at least one of (i) one or more alternate forms of transportation for the driver to incorporate when the driver takes trips or (ii) how to improve the driving behavior, and an incentive if the recommendation is implemented; and

after the user offering is displayed:

determine whether the recommendation has been implemented by analyzing current telematics data associated with current trips taken by the driver using the vehicle; and

in response to determining that the recommendation has been implemented, transmit, to the user computing device, a confirmation message indicating that the driver has earned the incentive.

16. The computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to receive the historical telematics data from a vehicle computing device associated with the vehicle.

17. The computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to access the contextual data from the memory device.

18. The computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to receive the current telematics data from a vehicle computing device associated with the vehicle.

19. The computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to synthesize the driver profile and the contextual data by:

comparing an average speed of the vehicle during a portion of at least one route travelled by the driver during at least one of the plurality of historical trips and a posted speed limit along the at least one route;

determining that the vehicle exceeds the posted speed limit during the portion of the at least one route; and

updating the contextualized driver profile to include an indicator that the driver operates the vehicle above the posted speed limit at a location corresponding to the portion of the at least one route.

20. The computer-readable storage medium of claim 15 , wherein the computer-executable instructions further cause the at least one processor to synthesize the driver profile and the contextual data by:

identifying at least one route travelled by the driver during a subset of the plurality of historical trips as a common route;

model, using artificial intelligence, historical travel of the driver along the common route based upon (i) the driver profile, (ii) at least one of current, average, or predicted traffic data along the common route, and (iii) traffic light timing data of traffic lights disposed along the common route, wherein (ii) and (iii) are included in the contextual data; and

update the contextualized driver profile to include the modelled historical travel of the driver.

Assignments (1)

Continuity (3)

References Cited (56)