State Farm Mutual Automobile Insurance Company

Roxane Lyons

Steven C Cielocha

William J Leise

Kristopher Keith Gaudin

Leo Nelson Chan

John Adrian Nepomuceno

Edward P Matesevac

Jeremy Myers

Jennifer Criswell Kellett

Rajiv C Shah

Matthew S Megyese

Jennifer L Crawford

Brian N Harvey

Nathan Lee Tofte

Michael Shawn Jacob

Rosemarie Geier Grant

Nathan Wilhelm Baumann

Joshua David Lillie

Timothy W Ryan

John H Jenkins

Amber L Wyatt

Gregory Dwayne Carter

Aaron Brucker

Andrew Crouthamel

Systems and methods are described for using data collected by unmanned aerial vehicles (UAVs) to generate insurance claim estimates that an insured individual may quickly review, approve, or modify. When an insurance-related event occurs, such as a vehicle collision, crash, or disaster, one or more UAVs are dispatched to the scene of the event to collect various data, including data related to vehicle or real property (insured asset) damage. With the insured's permission or consent, the data collected by the UAVs may then be analyzed to generate an estimated insurance claim for the insured. The estimated insurance claim may be sent to the insured individual, such as to their mobile device via wireless communication or data transmission, for subsequent review and approval. As a result, insurance claim handling and/or the online customer experience may be enhanced.

Unmanned aerial vehicle (UAV) data collection and claim pre-generation for insured approval

Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

System for determining road slipperiness in bad weather conditions

Various techniques are described utilizing one or more unmanned aerial vehicles (UAVs, or 'drones') for various disaster and/or catastrophe-related purposes. UAVs may collect data in an attempt to predict the occurrence and/or extent of a catastrophe and/or to mitigate the impact of a catastrophe before and, if not at that time, once it has occurred. The UAVs may perform various tasks such that the damage to property caused by a catastrophe (or potential catastrophe) may be eliminated or mitigated. A UAV may receive a flight path based on an energy consumption related condition and operate based on the flight path. Operating based on the flight path includes docking the UAV with a power supply device for charging a power source of the UAV.

Disaster damage analysis and loss mitigation implementing unmanned aerial vehicles (UAVs)

Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding a property, and collect data related to property. A location for an inspection of a property to be conducted by a UAV may be received, and one or more images depicting a view of the location may be displayed via a user interface. Additionally, a geofence boundary may be determined based on an area corresponding to a property boundary, where the geofence boundary represents a geospatial boundary in which to limit flight of the UAV. Furthermore, a navigation route may be determined which corresponds to the geofence boundary for inspection of the property by the UAV, the navigation route having waypoints, each waypoint indicating a location for the UAV to obtain drone data. The UAV may be directed around the property using the determined navigation route.

Insurance underwriting and re-underwriting implementing unmanned aerial vehicles (UAVs)

Unmanned aerial vehicles (UAVs) may facilitate the generation of a virtual reconstruction model of a vehicle collision. UAVs may collect data (including images) related to the vehicle collision, such as with the insured's permission, which may be received by an external computing device associated with the insurer and utilized to perform a photogrammetric analysis of the images to determine vehicle impact points, the road layout at the scene of the collision, the state of the traffic light at the scene of the collision, the speeds and directions of vehicles, etc. This data may be used to generate a virtual reconstruction model of the vehicle collision. An insurer may use the virtual reconstruction model to perform various insurance-related tasks, such as allocating fault to drivers or autonomous vehicles involved in the vehicle collision, and adjustment of insurance pricing based upon the fault allocation.

Accident reconstruction implementing unmanned aerial vehicles (UAVs)

Systems and methods relate to, inter alia, calculating a collision risk index for an area based upon historical traffic data. The systems and methods may further generate a notification to automatically engage or disengage an autonomous, or semi-autonomous, vehicle control feature in a vehicle based upon the collision risk index for the area. The systems and methods may further transmit the notification to a device of the vehicle to facilitate automatically engaging or disengaging an autonomous, or semi-autonomous, vehicle control feature in the vehicle as the vehicle approaches the area. As a result, vehicle collisions may be reduced, and vehicle safety enhanced.

Collision risk-based engagement and disengagement of autonomous control of a vehicle

A computer-implemented method for assessing damage to a plurality of properties is provided. After an occurrence of an event that is a potential cause of insured losses, image data depicting an aerial view of the properties may be received from an aerial platform. The image data may be processed to determine a subsequent condition of each property after occurrence of the event. Further, a damage severity level may be determined for each property, and used to display a map depicting different regions having properties with different respective damage severity levels.

Providing data associated with insured losses

Systems and methods are disclosed for educating vehicle drivers. Auto insurance claim data may be analyzed to identify hazardous areas associated with an abnormally high amount or severity of vehicle collisions. A virtual navigation map of roads within the hazardous areas may be built or generated. A common cause of several vehicle collisions at a hazardous area may be identified, and a virtual reconstruction of a scenario involving the common cause and/or a road map of collisions locations of may be created. The virtual reconstruction of the scenario may be displayed on a driver education virtual simulator to enhance driver education and reduce the likelihood of vehicle collisions.

System for driver's education

Insurance underwriting and re-underwriting implementing unmanned aerial vehicles (UAVS)

Growing community of inventors

Chenoa, IL, United States of America

Roxane Lyons