State Farm Mutual Automobile Insurance Company

Other

Hyundai Motor Company

Kia Corporation

Scott T Christensen

Gregory L Hayward

Blake Konrardy

Scott Farris

David James Dosher

Steven C Cielocha

Sunish Shreenarayan Menon

Todd Binion

Brian Mark Fields

Steve Roberson

Christopher Edward Gay

Stephen R Prevatt

Taylor Michael Thiel

Anuj Dahiya

Susan M Dunham

Nathan Lee Tofte

Kristopher Keith Gaudin

Jaime Skaggs

John Adrian Nepomuceno

Ryan Michael Gross

Michael L Bernico

Jufeng James Peng

Duane Christiansen

Meghan Sims Goldfarb

William Messner

Shawn M Call

Jackie O Jordan, Ii

Michael Shawn Jacob

Shawn C Bennett

Gregory Dwayne Carter

Jody Ann Thoele

Benjamin Joel Tucker

Kenneth Jason Sanchez

Aaron Scott Chan

Brian N Harvey

Joseph Robert Brannan

Aaron C Williams

Joseph P Harr

Matthew Eric Riley, Sr

Tim G Sanidas

Alexander Cardona

Michael Aaron Myers

Darwin Gene Beachy

James P Rodriguez

Timothy J Nickel

Angela Glusick

Ashish Sawhney

Neill Broadstone

Karthikeyan Srinivasan

Thomas Hilton Jannusch

Pamela Rearden

David Dohrmann

Gustufus Phillip Theofanis

Bryan Scott Wade

Steve Cielocha

James M Gallagher

Gregory Hayward

A computer system for flood monitoring and insurance provider notification, the computer system may include one or more processors configured to: detect a flood event in a structure, transmit information associated with the structure and a prompt for flood reimbursement services to a machine learning (ML) chatbot to cause the ML chatbot to file a flood reimbursement claim with an insurance provider having an insurance policy associated with the structure via telephone by converting a text output into a voice output.

Artificial intelligence for flood monitoring and insurance claim filing

Provided herein is a computing system that includes a processor in communication with a memory. The processor is configured to (1) receive a plurality of data records associated with a plurality of users that include historical user data; (2) generate a model based upon the plurality of data records, wherein the model (i) predicts travel behavior of a user, and/or (ii) outputs an insurance policy and associated premium for the user based upon the predicted travel behavior; (3) retrieve current user data associated with the candidate user; (4) apply the model to (i) determine a user trial travel behavior, and/or (ii) output a trial insurance policy and associated premium for the candidate user; and/or (5) transmit a notification to the user computing device that includes a prompt for the user to register for the insurance policy.

Systems and methods for modeling telematics data

Methods and systems for processing trip-based insurance policies for vehicles. According to aspects, a trip-based insurance policy of a vehicle specifies an amount of trip units for insured vehicle travel and has an associated policy term. In certain cases, a customer may exhaust trip units before an expiration of the policy term. The methods and systems therefore enable the purchase of additional trip units so that the customer remains insured. In other cases, upon expiration of the policy term, an insurance provider may calculate an amount of unused trip units. The insurance provider may determine one or more types of credit that are based on the amount of unused trip units. The insurance provider may also apply the one or more types of credit to an account of the customer.

Systems and methods for processing trip-based insurance policies

Methods and systems for autonomous and semi-autonomous vehicle control relating to malfunctions are disclosed. Malfunctioning sensors or software of autonomous vehicles may be identified from operating data of the vehicle, and a component maintenance requirement status associated with such malfunctioning component may be generated. Based upon such status, usage restrictions may be enacted to limit operation of the vehicle while the component is malfunctioning. This may include disabling or restricting use of certain autonomous or semi-autonomous features of the vehicle until the component is repaired or replaced. Repair may be accomplished by automatically scheduling repair of the vehicle or installing an updated or uncorrupted version of a software program, in various embodiments.

Autonomous vehicle component maintenance and repair

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Malfunctions may be detected by receiving sensor data from a plurality of sensors. One of these sensors may be selected for assessment. An electronic device may obtain from the selected sensor a set of signals. When the set of signals includes signals that are outside of a determined range of signals associated with proper functioning for the selected sensor, it may be determined that the selected sensor is malfunctioning. In response, an action may be performed to resolve the malfunction and/or mitigate consequences of the malfunction.

Smart home sensor malfunction detection

Apparatuses, systems and methods are provided for generating a vehicle driver signature. More particularly, apparatuses, systems and methods are provided for generating a vehicle driver signature based on current image data, previously classified image data, and vehicle dynamics data.

Apparatuses, systems and methods for generating a vehicle driver signature

Systems and methods are described for analyzing user data to generate a dialogue output. The method may include: (1) receiving, by one or more processors, an indication of a user identity for a user at a generative artificial intelligence (AI) model; (2) retrieving, by the one or more processors and based upon at least the user identity, user data from one or more publicly accessible sources; (3) determining, by the one or more processors and based upon at least the user data, one or more personalization characteristics associated with at least an information retention rate for the user via the generative AI model; and (4) generating, by the one or more processors and based upon at least the one or more personalization characteristics, a personalized dialogue output (or visual or virtual output for display) for the user via the generative AI model.

Systems and methods for analysis of user telematics data using generative AI

Methods and systems for communicating between autonomous vehicles are described herein. Such communication may be performed for signaling, collision avoidance, path coordination, and/or autonomous control. A computing device may receive data for the same road segment from autonomous vehicles, including (i) an indication of a location within the road segment, and (ii) an indication of a condition of the road segment. The computing device may generate, from the data for the same road segment, an overall indication of the condition of the road segment, which may include a recommendation to vehicles approaching the road segment. Additionally, the computing device may receive a request from a computing device within a vehicle approaching the road segment to display vehicle data. The overall indication for the road segment may then be displayed on a user interface of the computing device.

Autonomous vehicle application

Described herein are methods and systems for generating and applying vehicle maintenance models to vehicle telematics data. A vehicle telematics analytics (VTA) computing device is configured to receive vehicle telematics data associated with operation of a subject vehicle, and apply the received vehicle telematics data to a vehicle maintenance model to determine whether the operation of the subject vehicle is better or worse than standard operation of like vehicles. The VTA computing device may adjust a maintenance cost and/or determine if a user of the vehicle is eligible for a reward based upon this determination. The VTA computing device is configured to transmit an itemized report to the user including the adjusted maintenance cost and/or the reward as well as one or more other vehicle costs.

Vehicle telematics systems and methods

Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Autonomous vehicle operation feature monitoring and evaluation of effectiveness

The present disclosure generally relates to generating emergency vehicle warnings, automatic control of autonomous vehicles based upon the emergency vehicle warnings. More particularly, the present disclosure relates to generating data representative of emergency vehicle warnings and alternate autonomous vehicle routing based upon real-time information related to an emergency vehicle. The information related to the emergency vehicle may include emergency vehicle origination location data, emergency vehicle current location data, emergency vehicle route data, and/or emergency vehicle destination location data. An emergency vehicle warning and/or alternate vehicle routing for autonomous vehicles may be generated based further on information related to an autonomous vehicle. In one aspect, an emergency vehicle may wirelessly communicate with the autonomous vehicle and/or an insurance provider remote server. The insurance provider may adjust auto insurance for insured individuals, having vehicles with the vehicle safety functionality discussed herein, to reflect lower risk and provide insurance savings to customers.

Emergency vehicle detection and avoidance systems for autonomous vehicles

Systems and methods for situational modification of autonomous vehicle operation are disclosed. According to aspects, a computing device may detect the occurrence of an emergency event and may determine a current operation of an autonomous vehicle that may be associated with the emergency event. The computing device may determine a modification to operation of the autonomous vehicle, where the modification may represent a violation of a roadway regulation that may enable effective handling of the emergency event. The computing device may generate a set of instructions for the autonomous vehicle to execute to cause the autonomous vehicle to undertake the operation modification.

Technology for situational modification of autonomous vehicle operation

Systems and methods for building a vehicle data repository (VDR) are provided. In some embodiments, the VDR is constructed by adding standardized build sheets to it. The standardized build sheets may be constructed by selecting data from various data sources (e.g., original equipment manufacturer (OEM) databases, National Highway Traffic Safety Administration (NHTSA) databases, Highway Loss Data Institute (HLDI) databases, and/or Insurance Institute for Highway Safety (IIHS) databases). Furthermore, a common ontology may be created and applied to the various data sources to aide in the selection of data between the data sources to construct the standardized build sheets.

Systems and methods of building a consistent vehicle data repository

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Vehicle collision and/or smart home incident monitoring, damage detection, and responses are also described, with particular focus on the particular challenges associated with incident response for unoccupied vehicles and/or smart homes. Operating data associated with the autonomous vehicle and/or smart home may be received. Within the operating, an unusual condition indicative of a likelihood of incident may be detected. Based on the unusual condition, it may be determined that the incident occurred. Accordingly, a response to the incident may be determined. The response may be implemented by the autonomous vehicle and/or smart home.

Detecting and responding to autonomous vehicle incidents and unusual conditions

Growing community of inventors

Salem, OR, United States of America

Scott T Christensen