System and method for determining driving patterns using telematics data

1. A computer-implemented method for determining a driving pattern from raw telematics data originated from a client computing device in a vehicle, the method comprising:

removing, by one or more processors, a gravitational data component from telematics data in a first primary movement window of a vehicle trip leaving a vector defined by a longitudinal data component and a latitudinal data component in a longitudinal-latitudinal plane, wherein the first primary movement window is indicative of the client computing device being static with respect to movement of the vehicle;

combining, by the one or more processors, the longitudinal data component and the latitudinal data component to create an angular average;

generating, by the one or more processors, one or more yaw angle estimates from the primary movement window of the vehicle trip using the angular average; and

determining, by the one or more processors, a driving pattern using at least one of the yaw angle estimates.

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

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

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

5. The method of claim 1 further comprising:

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

determining, by the one or more processors, a driving pattern using at least one of: the pitch and roll angles; and

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 braking event, a left turn event or a right turn event.

6. The method of claim 1 further comprising:

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

determining, by 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.

7. A computer device for determining a driving pattern from raw telematics data originated from a client computing device in a vehicle, the computer 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:

remove a gravitational data component from telematics data in a first primary movement window of a vehicle trip leaving a vector defined by a longitudinal data component and a latitudinal data component in a longitudinal-latitudinal plane, wherein the first primary movement window is indicative of the client computing device being static with respect to movement of the vehicle;

combine the longitudinal data component and the latitudinal data component to create an angular average;

generate, using the angular average, one or more yaw angle estimates from the first primary movement window of the vehicle trip; and

determine a driving pattern based upon at least one of the yaw angle estimates.

8. The computer device of claim 7 , 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.

9. The computer device of claim 7 , 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 the vehicle, wherein the telematics data originates from the client computing device and includes a GPS speed data;

analyze the plurality of GPS data; and

determine that the plurality of GPS data is accurate.

10. The computer device of claim 7 , wherein the non-transitory computer executable instructions further cause the one or more processors to:

analyze the one or more yaw angle estimates; and

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

11. The computer device of claim 7 , wherein the non-transitory computer executable instructions further cause the one or more processors to:

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

determine a driving pattern using at least one of: the pitch and roll angles; and

determine that using at least the pitch and roll angles is indicative of at least one of: an acceleration of an acceleration event, a braking event, a left turn event or a right turn event.

12. A non-transitory computer readable storage medium having instructions stored thereon for determining a driving pattern from raw telematics data originated from a client computing device in a vehicle, the instructions when executed on one or more processors cause the one or more processors to:

remove a gravitational data component from the telematics data in a first primary movement window of a vehicle trip leaving a vector defined by a longitudinal data component and a latitudinal data component in a longitudinal-latitudinal plane, wherein the first primary movement window is indicative of the client computing device being static with respect to movement of the vehicle;

combine the longitudinal data component and the latitudinal data component to create an angular average of four times the directions of all vectors in the longitudinal-latitudinal plane such that all four acceleration effects of the plurality of telematics data are in one direction;

generate, using the angular average, one or more yaw angle estimates from the first primary movement window of the vehicle trip; and

determine a driving pattern based upon at least one of the yaw angle estimates.

13. The non-transitory computer readable storage medium of claim 12 , further comprising instructions stored thereon that 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.

14. The non-transitory computer readable storage medium of claim 12 , further comprising instructions stored thereon that cause the one or more processors to:

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

analyze the plurality of GPS data; and

determine that the plurality of GPS data is accurate.

15. The non-transitory computer readable storage medium of claim 12 , further comprising instructions stored thereon that cause the one or more processors to:

analyze the one or more yaw angle estimates; and

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

16. The non-transitory computer readable storage medium of claim 12 , further comprising instructions stored thereon that cause the one or more processors to:

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

determine a driving pattern using at least one of: the pitch and roll angles; and

determine that using at least the pitch and roll angles is indicative of at least one of: an acceleration of an acceleration event, a braking event, a left turn event or a right turn event.

17. The non-transitory computer readable storage medium of claim 12 , further comprising 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.