SYSTEM AND METHOD FOR DETERMINING DRIVING PATTERNS USING TELEMATICS DATA

• US 20150332518A1
• Filed: 05/15/2014
• Published: 11/19/2015
• Est. Priority Date: 05/15/2014
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Menon, Sunish Shreenarayan, Dosher, David James, Christensen, Scott Thomas
• Granted Patent: US 9,786,103 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/0825 using optical means
• CPC Class Codes: G07C 5/085 using electronic data carriers

Abstract

A computer implemented method for determining a yaw angle estimate or vehicle heading direction is presented. A data server may receive a plurality of telematics data originating from a client computing device and determine a first primary movement window from the telematics data. The data server may also determine a potential range of yaw angles from the plurality of telematics data from the first primary movement window and generate an equality that evaluates the potential range of yaw angles. The data server may further maximize the count of acceleration events of the telematics data from the first primary movement window to further generate one or more refined yaw angle estimates. The data server stores the one or more yaw angle estimates on a memory.

Claims

1. A computer implemented method for determining a driving pattern from raw telematics data, the method comprising:

receiving, via a computer network, a plurality of telematics data corresponding to a trip of a vehicle, wherein the plurality of telematics data originates from a client computing device and includes a gravitational data component, a longitudinal data component and a latitudinal data component;

identifying, by one or more processors, a first primary movement window of the vehicle trip;

identifying, by the one or more processors, one or more idling windows of the vehicle trip,

removing, by the one or more processors, the gravitational data component from the telematics data in the first primary movement window of the vehicle trip;

combining, by the one or more processors, the longitudinal data component and the latitudinal data component to create a function with all four effects of the plurality telematics data into one direction;

generating, by the one or more processors, a pitch and a roll angle from the first primary movement window of the vehicle trip;

generating, by the one or more processors, one or more yaw angle estimates from the first primary movement window of the vehicle trip using on the created function;

determining, by the one or more processors, a driving pattern using at least one of;

the pitch, roll and final yaw angle.

2. The method of claim 1 further comprising:

determining, by the one or more processors, a driving pattern using at least one of;

a constant speed time, an idling time, an acceleration event, a braking event, a turning event GPS data, gyroscope data and magnetometer data.

3. The method of claim 1 further comprising:

summarizing, by the one or more processors, the driving pattern from the first primary movement windows at one or more of;

a trip, a day, a month or a year level.

4. The method of claim 1 further comprising:

receiving, via the computer network, a plurality of GPS data corresponding to a trip of a vehicle, wherein the plurality of telematics data originates from a client computing device and includes a GPS speed data;

analyzing, by the one or more processors, the plurality of GPS data;

determining, by the one or more processors, that the plurality of GPS data is accurate; and

combining, by the one or more processors, the plurality of GPS data with the plurality of telematics data.

5. The method of claim 1 further comprising:

determining, by the one or more processors, a level of insurance risk based at least in part on the driving pattern and

estimating, by the one or more processors, an insurance premium using at least the driving pattern.

6. The method of claim 1 wherein determining the driving pattern further comprises:

determining, by the one or more processors, that using at least the pitch and roll angles is indicative of at least one of;

an acceleration data of an acceleration event, a breaking event, a left turn event or a right turn event.

7. The method of claim 1 further comprising:

analyzing, by the one or more processors, the one or more pitch and roll angle estimates; and

determining, at the one or more processors, a final yaw angle from the one or more yaw angle estimates that best aligns the acceleration data with the plurality of telematics data.

8. A computer device for determining a driving pattern from raw telematics data, the device comprising:

one or more processors; and

one or more memories coupled to the one or more processors;

the one or more memories including non-transitory computer executable instructions stored therein that, when executed by the one or more processors, cause the one or more processors to;

receive a plurality of telematics data corresponding to a trip of a vehicle, wherein the plurality of telematics data originates from a client computing device and the plurality of telematics data includes a gravitational data component, a longitudinal data component and a latitudinal data component;

identify a first primary movement of the vehicle trip;

identify one or more idling windows of the vehicle trip;

remove the gravitational constant from the telematics data in the first primary movement window of the vehicle trip;

combine the longitudinal data component and the latitudinal data component to create a function with all four effects of the plurality telematics data into one direction;

generate a pitch and a roll angle from the first primary movement window of the vehicle trip;

generate, based on the created function, one or more yaw angle estimates from the first primary movement window of the vehicle trip; and

determine a driving pattern using at least the pitch, roll and final yaw angle.

9. The computer device of claim 8, wherein the non-transitory computer executable instructions further cause the one or more processors to:

summarize, the driving pattern from the first primary movement windows at one or more of;

a trip, a day, a month and a year level and relating that with an insurance account to determine driving risk.

10. The computer device of claim 8, wherein the non-transitory computer executable instructions further cause the one or more processors to:

receive a plurality of GPS data corresponding to a trip of a vehicle, wherein the plurality of telematics data originates from a client computing device and includes a GPS speed data;

analyze the plurality of GPS data;

determine that the plurality of GPS data is accurate; and

combine the plurality of GPS data with the plurality of telematics data.

11. The computer device of claim 8, wherein the non-transitory computer executable instructions further cause the one or more processors to:

determine a level of insurance risk based at least in part on the driving pattern and

estimate an insurance premium using at least the driving pattern.

12. The computer device of claim 8, wherein the non-transitory computer executable instructions further cause the one or more processors to:

analyze the one or more pitch and roll angle estimates; and

determine a final yaw angle from the one or more yaw angle estimates that best aligns the acceleration data with the plurality of telematics data.

13. The computer device of claim 8, wherein the non-transitory computer executable instructions further cause the one or more processors to:

determine that using at least the pitch and roll angles is indicative of at least one of;

an acceleration of an acceleration event, a breaking event, a left turn event or a right turn event.

14. A computer readable storage medium comprising non-transitory computer readable instructions stored thereon for determining a driving pattern from raw telematics data, the instructions when executed on one or more processors cause the one or more processors to:

receive a plurality of telematics data corresponding to a trip of a vehicle, wherein the plurality of telematics data originates from a client computing device and the plurality of telematics data includes a gravitational data component, a longitudinal data component and a latitudinal data component;

identify a first primary movement window of the vehicle trip;

identify one or more idling windows of the vehicle trip;

remove the gravitational data component from the telematics data in the first primary movement window of the vehicle trip;

combining, by the one or more processors, the longitudinal data component and the latitudinal data component to create a function with all four effects of the plurality telematics data into one direction;

generate a pitch and a roll angle from the first primary movement window of the vehicle trip;

generate, based on the created function, one or more yaw angle estimates from the first primary movement window of the vehicle trip; and

determine a driving pattern using at least the pitch, roll and final yaw angle.

15. The computer device of claim 14, wherein the non-transitory computer executable instructions further cause the one or more processors to:

summarize, the driving pattern from the first primary movement windows at one or more of;

a trip, a day, a month and a year level.

16. The computer device of claim 14, wherein the non-transitory computer executable instructions further cause the one or more processors to:

receive a plurality of GPS data corresponding to a trip of a vehicle, wherein the plurality of telematics data originates from a client computing device and includes a GPS speed data;

analyze the plurality of GPS data;

determine that the plurality of GPS data is accurate; and

combine the plurality of GPS data with the plurality of telematics data.

17. The computer readable storage medium of claim 14, comprising further instructions stored thereon that cause the one or more processors to:

determine a level of insurance risk based at least in part on the driving pattern and

estimating an insurance premium using at least the driving pattern.

18. The computer readable storage medium of claim 14, comprising further instructions stored thereon that cause the one or more processors to:

analyze the one or more pitch and roll angle estimates; and

determine a final yaw angle from the one or more yaw angle estimates that best aligns the acceleration data with the plurality of telematics data.

19. The computer readable storage medium of claim 14, comprising further instructions stored thereon that cause the one or more processors to:

determine that using at least the pitch and roll angles is indicative of at least one of;

an acceleration of an acceleration event, a breaking event, a left turn event or a right turn event.

20. The computer readable storage medium of claim 14, comprising further instructions stored thereon that cause the one or more processors to:

determine a driving pattern using at least one of;

a constant speed time, an idling time, an acceleration event, a braking event, a turning event GPS data, gyroscope data and magnetometer data.