Methods of providing insurance savings based upon telematics and driving behavior identification

Patent metadata

Field	Value
Publication number	US-11565654-B2
Application number	US-202017081623-A
Country	US
Kind code	B2
Filing date	Oct 27, 2020
Priority date	Jul 21, 2014
Publication date	Jan 31, 2023
Grant date	Jan 31, 2023

Abstract

A system and method may collect telematics and/or other data, and apply the data to insurance-based applications. From the data, an insurance provider may determine accurate vehicle usage information, including information regarding who is using a vehicle and under what conditions. An insurance provider may likewise determine risk levels or a risk profile for an insured driver (or other drivers), which may be used to adjust automobile or other insurance policies. The insurance provider may also use the data collected to adjust behavior based insurance using incentives, recommendations, or other means. For customers that opt-in to the data collection program offered, the present embodiments present the opportunity to demonstrate a low or moderate risk lifestyle and the chance for insurance-related savings based upon that low or moderate risk.

First claim

What is claimed is:

1. A computer-implemented method for using telematics data, comprising:
collecting, at one or more processors, telematics data associated with driving behavior of an insured driver and biometric data associated with the insured driver from one or more sensors, the telematics data comprising sensor data indicative of visual information and at least one hard braking event;
verifying, by the one or more processors based on the visual information, an accuracy of the at least one hard braking event and whether an unexpected action of another vehicle or a pedestrian is a cause of the at least one hard braking event;
determining, by the one or more processors, one or more driving risk scores associated with the insured driver based upon the collected telematics data and the verified cause and accuracy of the at least one hard braking event, wherein each driving risk score indicates a level of risk of a vehicle accident;
generating, by the one or more processors, a risk aversion score associated with the insured driver based upon the one or more driving risk scores, wherein the risk aversion score indicates risk preferences of the insured driver;
determining, by the one or more processors, one or more of physical, mental, or emotional conditions of the insured driver based upon the biometric data and the risk aversion score; and
in response to determining, by the one or more processors, that the one or more of the physical, mental, or emotional conditions indicate a high risk of the vehicle accident for the insured driver,
transmitting, by the one or more processors, a warning notification to a mobile device of the insured driver or an onboard computer of the insured vehicle in real-time, and
limiting, by one or more processors associated with the mobile device or the onboard computer, functionality of the mobile device or at least one component of the insured vehicle for the insured driver.

2. The computer-implemented method of claim 1 , wherein determining the one or more driving risk scores includes:
analyzing the collected telematics data to determine one or more of the following usage characteristics: (i) driving characteristics associated with the driving behavior of the insured driver, or (ii) driving environments associated with the driving behavior of the insured driver, and
determining the one or more driving risk scores based upon the determined usage characteristics.

3. The computer-implemented method of claim 2 , wherein
the driving characteristics include one or more of the following: vehicle speed, vehicle braking, vehicle acceleration, vehicle turning, vehicle position in a lane, vehicle distance from other vehicles, use of safety equipment, or insured driver alertness; and
the driving environments include one or more of the following: geographic location, time of day, type of road, weather conditions, traffic conditions, construction conditions, or route traveled.

4. The computer-implemented method of claim 2 , wherein the driving environment includes a daily commute of the insured driver to and from a workplace.

5. The computer-implemented method of claim 1 , further comprising adjusting an insurance policy associated with the insured driver by adjusting a risk level associated with the insured driver for the insurance policy based upon the determined risk aversion score.

6. The computer-implemented method of claim 5 , wherein the insurance policy is one or more of the following: an automobile insurance policy, a health insurance policy, a disability insurance policy, an accident insurance policy, or an excess liability insurance policy.

7. The computer-implemented method of claim 5 , wherein the adjustment to the insurance policy includes one or more of the following: a premium, a rate, a reward, a deductible, or a limit.

8. The computer-implemented method of claim 5 , further comprising:
transmitting, via a communication network, information regarding the adjustment to the insurance policy to one or more insurance customers associated with the insurance policy for review; and
receiving, at the one or more processors, a confirmation of the adjustment to the insurance policy from at least one of the one or more insurance customers.

9. The computer-implemented method of claim 1 , wherein determining the one or more driving risk scores includes:
determining the identity of one or more drivers of one or more insured vehicles, including the insured vehicle;
determining usage characteristics of the one or more drivers associated with the one or more insured vehicles, including one or more of the following: (i) an amount that each of the one or more drivers uses each of the one or more insured vehicles, (ii) driving behavior characteristics of each of the one or more drivers with respect to each of the one or more insured vehicles, or (iii) the vehicle environments in which each of the one or more drivers operates the one or more insured vehicles; and
determining the one or more driving risk scores based upon the determined usage characteristics.

10. The computer-implemented method of claim 1 , wherein determining the one or more driving risk scores is based, at least in part, upon one or more of the following: a location the insured vehicle is parked or an amount of time the insured vehicle is garaged.

11. The computer-implemented method of claim 1 , wherein determining the one or more driving risk score is based, at least in part, upon analysis of vehicle maintenance records.

12. The computer-implemented method of claim 1 , wherein the one or more sensors are disposed within or communicatively connected to one or more of the following: the mobile device or the on-board computer.

13. The computer-implemented method of claim 1 , wherein the telematics data further includes data generated by one or more of the following: (i) a vehicle other than the insured vehicle associated with the insured driver; (ii) the insured vehicle, based upon vehicle-to-vehicle communication with one or more other vehicles; (iii) an infrastructure component; or (iv) road side equipment.

14. A computer system for using telematics data, comprising:
one or more processors;
one or more communication modules adapted to communicate data; and
a program 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:
collect telematics data associated with driving behavior of an insured driver and biometric data associated with the insured driver from one or more sensors via the one or more communication modules, the telematics data comprising sensor data indicative of visual information and at least one hard braking event;
verify based on the visual information an accuracy of the at least one hard braking event and whether an unexpected action of another vehicle or a pedestrian is a cause of the at least one hard braking event;
determine one or more driving risk scores associated with the insured driver based upon the collected telematics data and the verified cause and accuracy of the at least one hard braking event, wherein each driving risk score indicates a level of risk of a vehicle accident;
generate a risk aversion score associated with the insured driver based upon the one or more driving risk scores, wherein the risk aversion score indicates risk preferences of the insured driver;
determine one or more of physical, mental, or emotional conditions of the insured driver based upon the biometric data and the risk aversion score; and
in response to the one or more of the physical, mental, or emotional conditions indicatin

Assignees

• State Farm Mutual Automobile Insurance Co

Inventors

• Potter Thomas Michael
• Clauss Mark E
• Carter Dustin Ryan
• Graff Douglas Albert
• Baumann Megan Michal
• Bonnom Atlanta
• Cope Craig
• Lawyer Jennifer Luella
• Simpson Curtis
• Baumann Nathan W

Classifications

• B60R25/04 Primary

  operating on the propulsion system, e.g. engine or drive motor · CPC title

• G08B25/00

  Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems · CPC title

• B60R25/102 Primary

  a signal being sent to a remote location, e.g. a radio signal being transmitted to a police station, a security company or the owner · CPC title

• B60W2030/082

  Vehicle operation after collision · CPC title

• B60W40/08

  related to drivers or passengers · CPC title