Patent Issued for System And Method For Determining Driving Patterns Using Telematics Data (USPTO 10,319,159) - Insurance News | InsuranceNewsNet

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June 25, 2019 Newswires
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Patent Issued for System And Method For Determining Driving Patterns Using Telematics Data (USPTO 10,319,159)

Insurance Daily News

2019 JUN 25 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Menon, Sunish Shreenarayan (Normal, IL); Dosher, David J. (Fitchburg, WI); Christensen, Scott Thomas (Bloomington, IL), filed on May 16, 2018, was published online on June 24, 2019.

The patent’s assignee for patent number 10,319,159 is State Farm Mutual Automobile Insurance Company (Bloomington, Illinois, United States).

News editors obtained the following quote from the background information supplied by the inventors: “The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.

“Many companies employ vehicle monitoring systems for a variety of purposes, including determination of insurance risk and/or premiums. These systems may monitor many vehicle attributes, such as location, speed, acceleration/deceleration, etc. The monitoring devices are integrated with the vehicle or plugged into the vehicle systems. Many of these monitoring systems require expert installation into the vehicle and further require the user to periodically withdraw the monitoring device to download the trip data.”

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors’ summary information for this patent: “This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

“In one embodiment, a computer implemented method for determining an orientation of a device and a driving pattern from telematics data may include 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. The method may further include identifying, by one or more processors, a first primary movement window of the vehicle trip and one or more idling windows of the vehicle trip. Primary movement refers to vehicle movement when the telematics device is static with respect to the vehicle. The method may also include determining constant speed times including idling times. The method may also include minimizing, by the one or more processors, an effect of gravity on the telematics data in the first primary movement window of the vehicle trip and generating, by the one or more processors, a pitch and a roll angle from the first primary movement window of the vehicle trip. The method may also include generating, by the one or more processors, one or more yaw angle estimates from the first primary movement window of the vehicle trip. The method may further include, by one or more processors, summarizing the driving pattern using at least idling times, constant speed times, acceleration events, breaking events, right turns, left turns and information from other sensor data like GPS, gyroscope, magnetometer and relate this to an insurance account to estimate driving risk and future insurance premium.”

The claims supplied by the inventors are:

“What is claimed is:

“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.”

For additional information on this patent, see: Menon, Sunish Shreenarayan; Dosher, David J.; Christensen, Scott Thomas. System And Method For Determining Driving Patterns Using Telematics Data. U.S. Patent Number 10,319,159, filed May 16, 2018, and published online on June 24, 2019. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=10,319,159.PN.&OS=PN/10,319,159RS=PN/10,319,159

(Our reports deliver fact-based news of research and discoveries from around the world.)

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