State Farm Mutual Automobile Insurance Company

Aaron C Williams

Joseph Robert Brannan

Brian Mark Fields

Kristopher Keith Gaudin

Joseph P Harr

Leo Nelson Chan

Ryan Michael Gross

Dana C Hunt

Brian N Harvey

John Donovan

Christopher N Kawakita

Nathan Lee Tofte

Vicki King

Craig Benjamin Cope

Andrew Joseph Zeglin

Scott T Christensen

Jeremy Myers

David Turrentine

Erin Ann Olander

Brittany Boyer

Larry Ingrum

Nicole M Blakney

J Lynn Wilson

A computer system for network security vulnerability inspection may include one or more processors configured to: transmit a prompt for network security vulnerability testing code to an ML chatbot (or voice bot) to cause an ML model to generate the network security vulnerability testing code, receive the network security vulnerability testing code from the ML chatbot (or voice bot), scan a network to identify network computing devices, scan one or more of the network computing devices to identify security vulnerabilities and vulnerable network computing devices, and/or communicate the security vulnerabilities and/or vulnerable network computing devices to a user.

Generative artificial intelligence for a network security scanner

Vehicles may have autonomous capabilities that permit the vehicle to navigate according to varying levels of participation by a human operator. A human operator may be associated with a driving capability profile and the environment surrounding a vehicle may be associated with an environmental risk profile. A vehicle, or another party in communication with a vehicle, may determine whether, based on the human operator's driving capability profile and the environmental risk profile, it is likely that the vehicle will be navigated more safely if there is a change to the vehicle's autonomous capabilities and a corresponding change to the human operator's driving responsibilities. If it is determined that a change in autonomous vehicle capability is likely to increase safe navigation of the vehicle, an insurer may offer an insurance premium cost reduction if the human operator agrees to the proposed change in autonomous capabilities.

Determining risk for a user of an autonomous vehicle

A system and computer-implemented method detect and act upon deactivated vehicle components. The system and method include receiving measurements data associated with driving activity. The measurements data includes an indication that at least one feature of an Advanced Driver Assistance System (ADAS) of a vehicle has been deactivated for a driving activity. The system and method may include receiving historical driving data including a history of at least one driving activity aided by activation of the alert from the ADAS feature. The system and method may compare the measurements data to the historical driving data, determine a likelihood level that the feature of the ADAS would have provided the alert had the feature been activated based upon the comparing, and set, based at least upon the determining, at least a portion of an operator profile associated with an operator of the vehicle with the likelihood level.

Automatically tracking driving activity

The following relates generally to providing virtual reality (VR) alerts to a driver of an autonomous vehicle. For example, a vehicle may be driving autonomously while the driver is watching a VR movie (e.g., on a pair of VR goggles); the driver may then receive a VR alert recommending that the driver take control of the vehicle (e.g., switch the vehicle from autonomous to manual mode). The following also relates to generating a VR feed for presenting real-time road conditions so that a user may preview a road segment. The following also relates to generating a VR feed corresponding to an event (e.g., a vehicle collision, a crime, a weather event, and/or a natural disaster).

VR environment for real-time road conditions

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

Methods and systems for power transfer and routing in a compartmentalized electric vehicle (EV) having detachable compartments, and for handing off a load from one EV to another EV for delivering the load to a destination are described herein. Each detachable compartment in the compartmentalized EV may have a separate power supply, motor, set of wheels, and/or autonomous operation features. The detachable compartments may attach to each other, such that each of the detachable compartments combine to form a compartmentalized EV that travels to a particular location.

Compartmentalized electric vehicle (EV) having attached compartments with separate power systems

Delivery hand off procedure when electric vehicle (EV) is about to lose power

The following generally relates to using Augmented Reality (AR) to enhance pedestrian navigation. In some examples, AR techniques are applied to provide AR indications of a location of a group member that includes two or more AR devices. In these examples, AR techniques may be applied to determine a relative position of the group member and/or provide navigational guidance to the group member. In other examples, AR techniques are applied to provide AR-assisted pedestrian guidance. In these examples, AR techniques may be applied to present an AR display that includes information for a point of interest along a route.

Systems and methods for pedestrian guidance via augmented reality

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

Vehicles may have the capability to navigate according to various levels of autonomous capabilities, the vehicle having a different set of autonomous competencies at each level. In certain situations, the vehicle may shift from one level of autonomous capability to another. The shift may require more or less driving responsibility from a human operator. Sensors inside the vehicle collect human operator parameters to determine an alertness level of the human operator. An alertness level is determined based on the human operator parameters and other data including historical data or human operator-specific data. Notifications are presented to the user based on the determined alertness level that are more or less intrusive based on the alertness level of the human operator and on the urgency of an impending change to autonomous capabilities. Notifications may be tailored to specific human operators based on human operator preference and historical performance.

Manual control re-engagement in an autonomous vehicle

The following generally relates to using Augmented Reality (AR) to enhance the in-vehicle experience. In some examples, AR techniques are applied to provide AR indications of vehicle safety indicia to alert vehicle occupants to information that may not otherwise be perceptible. In other example, AR techniques are applied to provide emergency vehicle warnings to improve the likelihood of safe responses thereto. In yet other examples, AR techniques are applied to generated personalized outdoor displays, for example, to ameliorate conditions that may impair safe operation of a vehicle.

Systems and methods for in-vehicle driver assistance via augmented reality

A computer-implemented method of assessing driver capability for operating an autonomous vehicle includes identifying a human operator of the autonomous vehicle, the human operator being associated with a driving capability profile. The method further includes signaling to the human operator with the signal, the signal requesting a response from the human operator. The method also includes updating, based on the response from the human operator to the signal, the driving capability profile to indicate a level of skill of the human operator at responding to the signal.

Assessing driver ability to operate an autonomous vehicle

Systems and methods for identifying a condition associated with an individual in a home environment are provided. Sensors associated with the home environment detect data, which is captured and analyzed by a local or remote processor to identify the condition. In some instances, the sensors are configured to capture data indicative of electricity use by devices associated with the home environment, including, e.g., which devices are using electricity, what date/time electricity is used by each device, how long each device uses electricity, and/or the power source for the electricity used by each device. The processor analyzes the captured data to identify any abnormalities or anomalies, and, based upon any identified abnormalities or anomalies, the processor determines a condition (e.g., a medical condition) associated with an individual in the home environment. The processor generates and transmits a notification indicating the condition associated with the individual to a caregiver of the individual.

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Bloomington, IL, United States of America

Aaron C Williams