State Farm Mutual Automobile Insurance Company

Todd Binion

Steven C Cielocha

Ronny S Bryant

Brian Mark Fields

Carol Marie Csanda

Stacey Gorsuch

Aaron Scott Chan

Torri Wollenschlager

Mohamed A Wazeer

Weixin Wu

Shawn C Bennett

Chien Che Huang

Stephen A Kohaus

Terry Quakenbush

Richard A Novak

Craig M Main

Shawn M Call

Jackie O Jordan, Ii

John Donovan

Daryoush Hakimi-Boushehri

John H Weekes

Elisabeth McDermeit

Jennifer Criswell

Gregory L Hayward

Scott T Christensen

Christopher Edward Gay

Joe Harr

Steve J Balbach

Jennifer Criswell Kellett

Andrea Lee Rhoades

Jeremy Myers

Mark E Clauss

Kelly S Minter

Heidi Brown-McCreery

Nicholas R Baker

Kyle Pott

Kerry Cote

Michael Harris, Jr

Joshua M Mast

Steven Joseph Balbach

Jeremy Carnahan

Michael Harris

Matt Megyese

Douglas L Dewey

Jeffrey Feid

Jeffrey Wyrick

Christina P Mullen

Steve Cielocha

Jessica Lynn Shull

Steven Schmidt

Wayne Louis Cecil

Ed Weidmann

John Anthony Argenziano

Catherine Sue Schwamberger

Courtney Clarke

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

Autonomous vehicle control assessment and selection

Methods and systems for automatically mitigating risks of water damage to a property caused by insurance-related events are provided. A smart home controller and/or insurance provider remote processor may analyze data received from a smart device disposed on, within, or proximate to a property associated with monitoring water flow, as well as data received from an insurance provider. If it is determined that an actual or potential risk of water leakage exists, the smart home controller or remote processor may automatically issue commands to the smart device to take actions that mitigate the risk of water damage. The smart home controller may transmit information about the actual or potential water leakage risks and any mitigative actions to an insurance provider. The insurance provider remote processor may interpret the transmitted data and perform insurance activities, such as providing a discount or premium, and/or adjusting an insurance policy associated with the property.

Systems and methods for automatically mitigating risk of water damage

Methods and systems for automatically mitigating risks of insurance-related events to a property are provided. According to certain aspects, a smart home controller or insurance provider remote processor may analyze data received from a plurality of smart devices disposed on, within, or proximate to a property, as well as data received from an insurance provider. If it is determined that an actual or potential risk of property damage exists, the smart home controller or insurance provider remote processor may automatically issue commands to one or more smart devices to take actions that mitigate the risk. The smart home controller may also transmit information about the actual or potential risks and any mitigative actions to an insurance provider. The insurance provider remote processor may interpret the transmitted data to perform insurance activities, such as providing a discount and/or adjusting an insurance premium or policy associated with the property.

Systems and methods for automatically mitigating risk of property damage

A computer-implemented method includes receiving a vehicle condition query via a computer network and retrieving condition data corresponding to a vehicle from a vehicle condition database. Further, the method includes determining a condition of the vehicle based on a collective analysis of the condition data, where the condition of the vehicle includes a market value of the vehicle and an overall quality level of the vehicle, and receiving a geographic location of a computing device. Still further, the method includes generating a vehicle condition report, where the vehicle condition report includes an interactive image of a first set of one or more visual condition descriptors indicative of the condition of the vehicle. Moreover, the method includes customizing the vehicle condition report according to the climate associated with the geographic location for the computing device, and communicating the vehicle condition report to the second computing device.

Systems and methods to assess the condition of a vehicle

Methods and systems for processing insurance policies associated with properties may be provided. A property may be populated with a plurality of smart devices or devices that are connected to a central controller, such as via wired or wireless communication, whereby the plurality of devices are covered by an insurance policy, such as a homeowners, renters, or personal articles insurance policy. The central controller may receive identifications for the devices, and may update an inventory list to include the plurality of devices. A total market value of the devices may be calculated, and the central controller may estimate any modification to the insurance policy based upon the total market value. The controller may facilitate the modification to the insurance policy with a customer and an insurance provider. The smart devices may be, or be associated with, appliances, electronics, computers, televisions, jewelry, vehicles, furniture, or other equipment or personal belongings.

Systems and methods for managing insurance associated with devices populated within a property

Methods and systems for predictively generating an insurance claim in response to detecting an imminent insurance-related event are provided. According to certain aspects, a smart home controller or insurance provider remote processor may store a first set of data received from smart devices disposed on, or proximate to, a property. This data may be analyzed to detect that an insurance-related event is imminent and calculate a likelihood that a property owner will file an insurance claim in response to damage caused by the imminent insurance-related event. If there is a sufficient likelihood that an insurance claim will be filed, the smart home controller or remote processor may store a second set of data received from the smart devices. Subsequently, according to certain aspects, the second set of data may be analyzed to prepopulate an automatically generated insurance claim with information detailing damage to the property caused by the insurance-related event.

Systems and methods for predictively generating an insurance claim

Methods and systems for assigning damage to a property to causes of loss are provided. A smart home controller and/or an insurance provider remote processor (or server) may generate a time sequence of events for damage associated with an insure-related event. The time-sequence of events may be analyzed to identify causes of loss associated with damage to the property. The smart home controller or insurance provider remote processor may further analyze the time-sequence of event to determine a portion of the overall damage associated with each cause of loss. Subsequently, according to certain aspects, the smart home controller or insurance provider remote processor may automatically generate a prepopulated insurance claim for damage associated with the insurance-related event, and/or transmit the automatically prepared insurance claim to an insured for their review, approval, and/or modification, such as via wireless communication to a mobile device associated with the insured.

Systems and methods for assigning damage caused by an insurance-related event

Systems and methods are provided for automating property assessment using probable roof loss confidence scores. More particularly, the systems and methods may generate a base-line probable roof loss confidence score based upon buildings, roof, weather, hail, and climate data. The systems and methods may predict a specific event and a set of characteristics of the specific event. The systems and methods may predict a level of roof damage and a cost of roof damage based upon the predicted level of roof damage. The systems and methods may adjust a risk-related factor, and may further adjust policy parameters based upon the risk-related factor. A probable roof loss confidence score may be generated, as well as property insurance claims data or property insurance loss mitigation data based upon probable roof loss confidence score data.

Systems and methods for automating property assessment using probable roof loss confidence scores

Systems and methods for analyzing image data to identify cabinet products are disclosed. A computer-implemented method may include receiving, from an electronic device via a network connection, at least one digital image depicting a cabinet. The method also may include analyzing, by one or more processors, the at least one digital image to determine a first set of characteristics of the cabinet. Additionally, the method may include accessing, by the one or more processors from memory, a second set of characteristics corresponding to a plurality of cabinet products and comparing the first set of characteristics to the second set of characteristics to identify a cabinet product of the plurality of cabinet products that matches the cabinet. Further, the method may include transmitting, to the electronic device via the network connection, an indication of the cabinet product.

System and method for identifying cabinetry

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for generating or updating usage-based insurance policies for autonomous or semi-autonomous vehicles may be provided. A request to generate an insurance quote may be received via wireless communication, and with the customer's permission, risk levels associated with intended usage by the customer of an autonomous or semi-autonomous vehicle may be determined. An insurance policy may be adjusted based upon the risk levels and the intended vehicle usage. The insurance policy may then be presented on the customer's mobile device for review and approval. In some aspects, the vehicle may be rented, and the intended vehicle usage is measured in distance or duration of vehicle operation. Insurance discounts may be provided to risk averse vehicle owners based upon low risk levels.

Autonomous vehicle insurance based upon usage

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features arm provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Autonomous vehicle accident and emergency response

Computer-implemented methods, servers, and tangible, non-transitory computer-readable media storing instructions for creating one or more new insurance policy quotes for a customer associated with a customer vehicle may be may be described. The computer-implemented methods, servers, and instructions may include receiving a coverage type for the customer vehicle, causing usage data corresponding to the coverage type to be tracked, receiving the usage data, generating the new insurance policy quotes corresponding to the coverage type based upon at least the usage data, and causing the new insurance policy quotes to be displayed.

Dynamic auto insurance policy quote creation based on tracked user data

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may be disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.

A system for determining drone operation rules configured to (i) receive a plurality of telematics data from a plurality of missions; (ii) analyze the plurality of telematics data to determine one or more mission trends; and (iii) determine one or more rules based upon the one or more mission trends.

Systems and methods for analyzing unmanned aerial missions

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Bloomington, IL, United States of America

Todd Binion