Patent Issued for Systems and methods for generating improved vehicle usage analytics based upon vehicle sensor and telematics data (USPTO 12002305): State Farm Mutual Automobile Insurance Company

2024 JUN 25 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Brannan, Joseph Robert (Bloomington, IL, US), Gross, Ryan Michael (Normal, IL, US), Harvey, Brian N. (Bloomington, IL, US), filed on February 3, 2020, was published online on June 4, 2024.

The assignee for this patent, patent number 12002305, is State Farm Mutual Automobile Insurance Company (Bloomington, Illinois, United States).

Reporters obtained the following quote from the background information supplied by the inventors: “Connected vehicles are vehicles equipped with communications abilities (e.g., vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and/or vehicle-to-network (V2N) communication). Such vehicles are increasingly common. Connected vehicles are often equipped with a variety of sensors that are potential sources of data (e.g., telematics data) regarding drivers of the connected vehicle and trips taken by the connected vehicle and/or an environment around the connected vehicle.

“Individuals use mobile devices (e.g., mobile telephones) for a variety of purposes and often carry mobile devices while traveling. Such usage may be an additional source of data. For example, mobile devices may be equipped to generate data (e.g., telematics data) using instruments built into the mobile device, such as an accelerometer or global positioning system (GPS) device. This data obtained from connected cars and/or mobile devices may be useful for a variety of applications.

“However, there are currently limitations in the ability of computing devices to utilize such data in automated processes. For example, known computing devices do not use sensor data obtained from connected vehicles, for example, to identify a driver or number of passengers of the vehicle, which may be useful in applications such as usage-based insurance, where an insurance premium is based upon an individual driver’s actual driving behavior. Accordingly, in order to implement these applications, these different forms of information may need to be reconciled by human beings, which may result in lack of timeliness, inaccuracies, inconvenience, or other drawbacks.”

In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “The present embodiments may relate to, inter alia, systems and methods for generating improved vehicle usage analytics based upon vehicle sensor data and/or telematics data. In exemplary embodiments, the systems and methods may be performed by a vehicle analytics (VA) computing device. The VA computing device may collect and analyze telematics data (e.g., acceleration, position, velocity, orientation, etc.) and/or sensor data (e.g., data obtained from sensors onboard a vehicle) from a connected vehicle and/or mobile device associated with an individual in order to assess an individual’s transportation behavior, and/or provide individualized insurance coverage options or incentives based upon the individual’s transportation behavior. For example, the VA computing device may be capable of identifying a driver for an individual trip of a vehicle (e.g., a connected vehicle) and may assess the driving behavior of the identified driver for insurance purposes (e.g., calculating an insurance premium) using telematics data corresponding to the individual trip.

“The systems and methods may also include building a trip database including information associated with a plurality of trips taken using a connected car and telematics data associated with each of the plurality of trips, and analyzing the trip data to determine transportation behavior of one or more identified drivers of the connected car. For example, the number of passengers present in the connected car for each trip may be determined.

“The systems and methods may also include generating, using machine learning techniques, a driver profile model for an individual driver that characterizes the individual driver’s driving behavior based upon, for example, telematics data. The driver profile may be used, for example, to identify the individual driver as a driver for a particular trip (e.g., of a connected car), calculate a premium for a usage-based insurance (UBI) policy associated with the individual driver, and/or generate recommendations to improve the individual driver’s driving behavior (e.g., to drive more safely).

“In one aspect, a vehicle analytics (VA) computing device may be provided. The VA computing device may include a processor (and/or associated transceiver) in communication with a memory device and a telematics device, and the processor (and/or associated transceiver) may be configured to: (1) receive, from the telematics device, telematics data corresponding to a vehicle; (2) identify a plurality of trips of the vehicle based upon the telematics data; (3) store the telematics data corresponding to each trip of the plurality of trips in a database in association with a trip identifier corresponding to the trip; (4) identify, for each trip of the plurality of trips, a driver of the vehicle based upon the telematics data; (5) store, in association with each trip identifier, a user identifier corresponding to the identified driver for the trip identifier; (6) parse, for each user identifier, the database to aggregate telematics data associated with the user identifier; and/or (7) calculate, for each user identifier, an insurance premium for an insurance policy (such as a UBI policy) associated with the user identifier based upon the aggregated telematics data corresponding to the user identifier. The VA computing device may include additional, less, or alternate functionality, including that discussed elsewhere herein.

“In another aspect, a computer-implemented method may be provided. The computer-implemented method may be performed by a vehicle analytics (VA) computing device including a processor (and/or associated transceiver) in communication with a memory device and a telematics device. The computer-implemented method may include: (1) receiving, by the VA computing device, from the telematics device, telematics data corresponding to a vehicle; (2) identifying, by the VA computing device, a plurality of trips of the vehicle based upon the telematics data; (3) storing, by the VA computing device, the telematics data corresponding to each trip of the plurality of trips in a database in association with a trip identifier corresponding to the trip; (4) identifying, by the VA computing device, for each trip of the plurality of trips, a driver of the vehicle based upon the telematics data; (5) storing, by the VA computing device, in association with each trip identifier, a user identifier corresponding to the identified driver for the trip identifier; (6) parsing, by the VA computing device, for each user identifier, the database to aggregate telematics data associated with the user identifier; and/or (7) calculating, by the VA computing device, for each user identifier, an insurance premium for an insurance policy (such as a UBI policy) associated with the user identifier based upon the aggregated telematics data corresponding to the user identifier. The computer-implemented method may include additional, less, or alternate actions, including those discussed elsewhere herein.”

The claims supplied by the inventors are:

“1. A vehicle analytics (VA) computing device comprising a processor in communication with a memory device and a vehicle, the processor configured to: receive, from telematics sensors associated with the vehicle, historical telematics data corresponding to the vehicle, the historical telematics data including historical sensor data collected from the vehicle; generate, using the historical telematics data, a driver profile model for a user of the vehicle; receive, from the telematics sensors, additional telematics data associated with a plurality of trips driven by the user using the vehicle; train, using machine learning techniques and the additional telematics data, the driver profile model to identify patterns in driving behaviors of the user, the driving behaviors including a driving style of the user, routes driven by the user, and driving preferences of the user; store, in a database, the trained driver profile model; receive, from the telematics sensors, current telematics data associated with a trip taken by the vehicle; identify the user as a driver of the vehicle during the trip by comparing the current telematics data to the trained driver profile model; in response to identifying the user as the driver of the vehicle, output, from the trained driver profile model, (i) a driver profile of the user and (ii) driving recommendations for the user based upon the identified patterns for the user, the driving recommendations including recommendations for the user to improve driving behaviors associated with vehicle operation; cause the driving recommendations to be displayed on a user device of the user; transmit a prompt to the user device to confirm that the user is the driver of the vehicle; receive, from the user device, a confirmation indicating that the user is the driver; reinforce the trained driver profile model for the user based upon the confirmation, the confirmation causing the VA computing device to add weight to the identified patterns when identifying the user as the driver; and determine, based upon subsequent telematics data received from the telematics sensors, that the user followed the driving recommendations transmitted to the user device.

“2. The VA computing device of claim 1, wherein the processor is configured to determine a number of passengers based upon the historical sensor data received from the vehicle.

“3. The VA computing device of claim 1, wherein the telematics sensors include at least one of one or more cameras, seat sensors, active suspension systems sensors, or door sensors.

“4. The VA computing device of claim 1, wherein the processor is further configured to: identify, for each trip of the plurality of trips, a vehicle driver of the vehicle based upon the historical telematics data; store, in association with each trip identifier, a user identifier corresponding to the identified vehicle driver for that trip identifier; parse, for each user identifier, the database to aggregate historical telematics data associated with that user identifier; and generate, for each user identifier, a usage-based insurance (UBI) policy associated with that user identifier based upon the aggregated historical telematics data corresponding to that user identifier, wherein each UBI policy includes a corresponding insurance premium.

“5. The VA computing device of claim 4, wherein to identify the vehicle driver of the vehicle, the processor is configured to: receive, from the vehicle, current sensor data; compare the received current sensor data to the historical sensor data stored in the database in association with a candidate user identifier; and identify the candidate user identifier as the vehicle driver of the vehicle.

“6. The VA computing device of claim 5, wherein the processor is configured to: generate, based upon the aggregated historical telematics data associated with the candidate user identifier, a prediction of an attribute that corresponds to the historical telematics data; verify the prediction based upon an indicator input from a vehicle user to determine that the aggregated historical telematics data actually corresponds to the attribute; and build, based upon the determination, a driver profile model for the vehicle user by storing the attribute in association with the aggregated historical telematics data and the candidate user identifier in the database.

“7. The VA computing device of claim 1, wherein the historical sensor data includes at least one of seat position settings, radio settings, camera data, or key fob data.

“8. The VA computing device of claim 1, wherein the processor is further configured to: cause an application running on the user device to display the driving recommendations to the user.

“9. The VA computing device of claim 1, wherein the processor is further configured to: receive funds from the user; transmit the funds to a financial institution to be deposited into a hybrid savings account; and transfer, from an insurance provider to the hybrid savings account, a reward when the user follows the driving recommendations.

“10. The VA computing device of claim 1, wherein the processor is further configured to: store the historical telematics data corresponding to each trip of the plurality of trips in the database in association with a trip identifier corresponding to the trip; and store the identified patterns in the database in association with the trip identifier corresponding to each of the plurality of trips.

“11. A computer-implemented method performed by a vehicle analytics (VA) computing device including a processor in communication with a memory device and a vehicle, the computer-implemented method comprising: receiving, by the VA computing device, from telematics sensors associated with the vehicle, historical telematics data corresponding to the vehicle, the historical telematics data including historical sensor data collected from the vehicle; generating, by the VA computing device using the historical telematics data, a driver profile model for a user of the vehicle; receiving, by the VA computing device from the telematics sensors, additional telematics data associated with a plurality of trips driven by the user using the vehicle; training, by the VA computing device using machine learning techniques and the additional telematics data, the driver profile model to identify, by the VA computing device, patterns in driving behaviors of the user, the driving behaviors including a driving style of the user, routes driven by the user, and driving preferences of the user; storing, by the VA computing device, in a database, the trained driver profile model; receiving, by the VA computing device from the telematics sensors, current telematics data associated with a trip taken by the vehicle; identifying, by the VA computing device, the user as a driver of the vehicle during the trip by comparing the current telematics data to the trained driver profile model; in response to identifying the user as the driver of the vehicle, outputting, by the VA computing device from the trained driver profile model, (i) a driver profile of the user and (ii) driving recommendations for the user based upon the identified patterns for the user, the driving recommendations including recommendations for the user to improve driving behaviors associated with vehicle operation; causing, by the VA computing device, the driving recommendations to be displayed on a user device of the user; transmitting, by the VA computing device, a prompt to the user device to confirm that the user is the driver of the vehicle; receiving, by the VA computing device from the user device, a confirmation indicating that the user is the driver; reinforcing, by the VA computing device, the trained driver profile model for the user based upon the confirmation, the confirmation causing the VA computing device to add weight to the identified patterns when identifying the user as the driver; and determining, by the VA computing device based upon subsequent telematics data received from the telematics sensors, that the user followed the driving recommendations transmitted to the user device.

“12. The computer-implemented method of claim 11, wherein the method further comprises determining, by the VA computing device, a number of passengers based upon the historical sensor data received from the vehicle.

“13. The computer-implemented method of claim 11, wherein the telematics sensors include at least one of one or more cameras, seat sensors, active suspension systems sensors, or door sensors.

“14. The computer-implemented method of claim 11, wherein the method further comprises: identifying, for each trip of the plurality of trips, a vehicle driver of the vehicle based upon the historical telematics data; storing, in association with each trip identifier, a user identifier corresponding to the identified vehicle driver for that trip identifier; parsing, for each user identifier, the database to aggregate historical telematics data associated with that user identifier; and generating, for each user identifier, a usage-based insurance (UBI) policy associated with that user identifier based upon the aggregated historical telematics data corresponding to that user identifier, wherein each UBI policy includes a corresponding insurance premium.

“15. The computer-implemented method of claim 14, wherein identifying the vehicle driver of the vehicle comprises: receiving, by the VA computing device, from the vehicle, current sensor data; comparing, by the VA computing device, the received current sensor data to the historical sensor data stored in the database in association with a candidate user identifier; and identifying, by the VA computing device, the candidate user identifier as the vehicle driver of the vehicle.”

There are additional claims. Please visit full patent to read further.

For more information, see this patent: Brannan, Joseph Robert. Systems and methods for generating improved vehicle usage analytics based upon vehicle sensor and telematics data. U.S. Patent Number 12002305, filed February 3, 2020, and published online on June 4, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(12002305)&db=USPAT&type=ids

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