System and methods for determining owner's preferences based on vehicle owner's telematics data

• US 10,703,379 B1
• Filed: 02/04/2019
• Issued: 07/07/2020
• Est. Priority Date: 02/04/2019
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Harvey, Brian N., Brannan, Joseph Robert, Wilson, J. Lynn, Riley, Sr., Matthew Eric, Gross, Ryan
• Primary Examiner(s): Fan, Hongmin
• Application Number:
  US16/266,936
• Time in Patent Office: 519 Days
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: G06Q 30/0645 Rental transactions; Leasing transactions
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C

Abstract

Embodiments described herein receive telematics data collected over a period of time, wherein the telematics data is indicative of operation of a vehicle by an owner of the vehicle during the period of time; analyze the telematics data to identify driving behavior(s) of the owner during the period of time; predict one or more user preference values of a vehicle-sharing platform profile of the owner based on the identified one or more driving behaviors, wherein the one or more user preference values define one or more criteria for vehicle renters with whom the first vehicle can be shared; apply the one or more criteria to a potential vehicle renter; and cause an indication of the first vehicle of the owner to be displayed via a mobile device of the potential renter only if the potential vehicle renter satisfies the one or more criteria.

Claims

1. A computer-implemented method of predicting a user preference carried out by a vehicle-sharing platform, the method comprising:

receiving, by one or more processors, telematics data collected over a first period of time, wherein the telematics data is indicative of operation of a first vehicle by an owner of the first vehicle during the first period of time;

analyzing, by the one or more processors, the telematics data to identify one or more driving behaviors of the owner during the first period of time;

predicting, by the one or more processors, one or more user preference values of a vehicle-sharing platform profile of the owner based on the identified one or more driving behaviors, wherein the one or more user preference values define one or more criteria for vehicle renters with whom the first vehicle can be shared;

applying, by the one or more processors, the one or more criteria to a potential vehicle renter; and

causing, by the one or more processors, an indication of the first vehicle of the owner to be displayed via a mobile device of the potential renter only if the potential vehicle renter satisfies the one or more criteria.

2. The computer-implemented method of claim 1, wherein applying the one or more criteria to the potential vehicle renter includes:

receiving, by the one or more processors, renter telematics data collected over a second period of time, wherein the renter telematics data is indicative of operation of a second vehicle by the potential vehicle renter during the second period of time; and

determining, by the one or more processors, whether the potential vehicle renter satisfies the one or more criteria by comparing the renter telematics data, or data derived therefrom, with the one or more user preference values.

3. The computer-implemented method of claim 2, wherein the second vehicle is a rental vehicle shared by another vehicle owner.

4. The computer-implemented method of claim 2, wherein the second vehicle is a vehicle owned by the potential renter.

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

causing, by the one or more processors, the one or more user preference values to be displayed via a mobile device of the owner.

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

modifying, by the one or more processors, the one or more user preference values based on an input received via the mobile device of the owner.

7. The computer-implemented method of claim 1, wherein the at least one of the one or more user preference values is associated with one or more of:

acceleration, speed, lateral force, or time period.

8. A computer system implementing a vehicle-sharing platform for predicting a user preference, the computer system comprising:

one or more processors; and

memory coupled to the one or more processors and storing executable instructions that when executed by the one or more processors cause the computer system to;

receive telematics data collected over a first period of time, wherein the telematics data is indicative of operation of a first vehicle by an owner of the first vehicle during the first period of time;

analyze the telematics data to identify one or more driving behaviors of the owner during the first period of time;

predict one or more user preference values of a vehicle-sharing platform profile of the owner based on the identified one or more driving behaviors, wherein the one or more user preference values define one or more criteria for vehicle renters with whom the first vehicle can be shared;

apply the one or more criteria to a potential vehicle renter; and

cause an indication of the first vehicle of the owner to be displayed via a mobile device of the potential renter only if the potential vehicle renter satisfies the one or more criteria.

9. The computer system of claim 8, wherein the executable instructions cause the computing system to apply the one or more criteria to the potential vehicle renter by:

receiving renter telematics data collected over a second period of time, wherein the renter telematics data is indicative of operation of a second vehicle by the potential vehicle renter during the second period of time; and

determining whether the potential vehicle renter satisfies the one or more criteria by comparing the renter telematics data, or data derived therefrom, with the one or more user preference values.

10. The computer system platform of claim 9, wherein the second vehicle is a rental vehicle shared by another vehicle owner.

11. The computer system of claim 9, wherein the second vehicle is a vehicle owned by the potential renter.

12. The computer system of claim 8, wherein the executable instructions further cause the computer system to:

display the one or more user preference values via a mobile device of the owner.

13. The computer system of claim 12, wherein the executable instructions that when executed by the one or more processors further cause the computer system to:

modify the one or more user preference values based on an input received via the mobile device of the owner.

14. The computer system of claim 8, wherein the at least one of the one or more user preference values is associated with one or more of:

acceleration, speed, lateral force, or time period.

15. A non-transitory, tangible computer-readable medium storing machine readable instructions for predicting a user preference that, when executed by one or more processors of a vehicle-sharing platform, cause the one or more processors to:

receive telematics data collected over a first period of time, wherein the telematics data is indicative of operation of a first vehicle by an owner of the first vehicle during the first period of time;

analyze the telematics data to identify one or more driving behaviors of the owner during the first period of time;

predict one or more user preference values of a vehicle-sharing platform profile of the owner based on the identified one or more driving behaviors, wherein the one or more user preference values define one or more criteria for vehicle renters with whom the first vehicle can be shared;

apply the one or more criteria to a potential vehicle renter; and

cause an indication of the first vehicle of the owner to be displayed via a mobile device of the potential renter only if the potential vehicle renter satisfies the one or more criteria.

16. The non-transitory, tangible computer-readable medium of claim 15, wherein the machine readable instructions cause the one or more processors to apply the one or more criteria to the potential vehicle renter by:

receiving renter telematics data collected over a second period of time, wherein the renter telematics data is indicative of operation of a second vehicle by the potential vehicle renter during the second period of time; and

determining whether the potential vehicle renter satisfies the one or more criteria by comparing the renter telematics data, or data derived therefrom, with the one or more user preference values.

17. The non-transitory, tangible computer-readable medium of claim 16, wherein the second vehicle is a rental vehicle shared by another vehicle owner.

18. The non-transitory, tangible computer-readable medium of claim 15, wherein the machine readable instructions further cause the one or more processors to:

display the one or more user preference values via a mobile device of the owner.

19. The non-transitory, tangible computer-readable medium of claim 18, wherein the machine readable instructions further cause the one or more processors to:

modify the one or more user preference values based on an input received via the mobile device of the owner.

20. The non-transitory, tangible computer-readable medium of claim 15, wherein the at least one of the one or more user preference values is associated with one or more of:

acceleration, speed, lateral force, or time period.