State Farm Mutual Automobile Insurance Company

Joseph Robert Brannan

Ryan Michael Gross

Brian N Harvey

Aaron C Williams

Matthew Eric Riley, Sr

J Lynn Wilson

John Donovan

Dana C Hunt

Christopher N Kawakita

Benjamin Joel Tucker

Michael Aaron Myers

Darwin Gene Beachy

Eric R Moore

Jody Ann Thoele

Brian Mark Fields

Scott T Christensen

Nathan Lee Tofte

Vicki King

M Eric Riley, Sr

Justin Davis

Computer-implemented methods and computer systems are disclosed herein as implemented by a controller operatively coupled to a network of electric vehicles. The methods and systems include the controller (i) receiving a notification that an electric vehicle is stranded without sufficient power to operate; (ii) receiving information regarding the stranded electric vehicle; (iii) detecting one or more other electric vehicles in a vicinity of the stranded electric vehicle; (iv) receiving information regarding the detected one or more other electric vehicles; and/or (v) determining, based upon the received information, which of the detected one or more other electric vehicles to send a power source request. Alternatively, the notification may indicate that an electric vehicle has a low state of charge (SOC), or is otherwise has a battery in need of being recharged to facilitate the electric vehicle traveling to a destination.

Electric vehicle charging management system and method

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 user analytics computing device for processing vehicle-based telematics data and generating user offerings responsive to the vehicle-based telematics data includes at least one processor in communication with a memory device. The processor is programmed to: (i) receive, from a vehicle computing device, telematics data associated with a plurality of trips taken by a first driver using a first vehicle, (ii) generate a driver profile of the first driver based at least in part upon the telematics data, (iii) access, from the memory device, contextual data associated with an environment in which the first vehicle travelled during the plurality of trips, (iv) synthesize the driver profile and the contextual data to generate a contextualized driver profile, (v) based upon the contextualized driver profile, generate a user offering to influence the driver profile, and (vi) transmit the user offering to a user computing device associated with the first driver.

Systems and methods for generating user offerings responsive to telematics data

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

A computing device for generating on-demand products based upon real-time geolocation data is configured to receive and store at least one product definition associated with a respective product. Each product definition defines an availability of the product and includes a product availability location. The computing device is also configured to receive real-time location data from a user computing device, and periodically query a memory device with the real-time location data. The computing device detects that the user computing device has entered a first location by retrieving, in response to a successful query of the memory device, a first product definition associated with a first product having a product availability location including the first location. The computing device is also configured to generate a product identification message including at least a portion of the first product definition, and transmit the product identification message to the user computing device.

Systems and methods for generating on-demand products responsive to real-time geolocation and telematics

Systems and methods for an artificial intelligence (AI)/machine learning (ML) chatbot for intelligent negotiation of terms is disclosed herein. An exemplary computing system includes one or more processors; and a memory storing executable instructions thereon. When executed by the one or more processors, these instructions may cause the one or more processors to: receive, from a first contracting party during a negotiating period, a plurality of prospective terms for a contractual agreement; and determine, via an AI chatbot, whether the plurality of prospective terms are acceptable terms based on a plurality of parameters indicated by a second contracting party. Responsive to determining that the plurality of prospective terms are unacceptable terms, the instructions may further cause the processors to generate, via the AI chatbot, a plurality of counter terms based on the plurality of parameters; and transmit the plurality of counter terms to the first contracting party.

AI/ML chatbot for negotiations

A personalized insurance ('PI') computing device for determining an optimal insurance product for a driver operating a vehicle for a transportation network company (“TNC”) during a period of increased demand includes at least one processor in communication with at least one memory. The processor is configured to: (i) receive, from a TNC, data indicating increased demand for transportation services, (ii) retrieve driver data that includes the driver history, (iii) generate an optimal pricing model for the driver based upon the increased demand and the driver data, (iv) execute the model to determine an optimal insurance product having characteristics reflecting at least one risk factor associated with the increased demand for transportation services and a risk profile determined from analyzing the driver data, and (v) transmit an offer to the driver to provide transportation services at an increased earnings rate and with the determined optimal insurance product.

Systems and methods for generating mobility insurance products using ride-sharing telematics data

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

The following relates generally to artificial intelligence (AI)-based responses to social media posts. In some embodiments, one or more processors may be configured to: (1) receive, via a chatbot, a social media post; (2) categorize, via the chatbot, the social media post; (3) determine, via the chatbot, based upon the categorization, an entity to contact; (4) build, via the chatbot, based upon the determined entity to contact, a response to the social media post; and/or (5) send, via the chatbot, the response to the entity.

Chatbot for reviewing social media

Computer-implemented methods and computer systems are disclosed herein as implemented by one or more processors associated with an autonomous recharging vehicle (ARV). The methods and systems include: forming a list of electric vehicles waiting in queue for charging by the ARV; performing an optimization algorithm to rearrange the order of the electric vehicles; scheduling rendezvous points for the ARV to recharge the electric vehicles based upon the rearranged order of the electric vehicles on the list; and automatically routing the ARV to the rendezvous points based upon the scheduling.

Embodiments described herein, inter alia, receive telematics data collected over a period of time, wherein the telematics data is indicative of operation of a vehicle by a potential renter during the period of time; identify, upon analyzing the telematics data, driving behavior(s) of the renter during the period of time; determine, for each driving behavior, a corresponding state of an environment of the vehicle when the driving behavior occurred; determine renter eligibility value(s) for the renter based on the driving behavior(s) and the corresponding state of an environment of the vehicle; compare the renter eligibility value(s) to user preference value(s) of a profile of a vehicle owner, wherein the user preference value(s) define one or more criteria for vehicle renters with whom the vehicle can be shared; and cause an indication of the vehicle associated with the profile to be displayed only if the renter satisfies the criteria.

System and methods for determining rental eligibility based on contextual telematics data

An adaptive mapping (AM) computing device having at least one processor in communication with at least one memory device is provided. The AM computing device may be configured to retrieve a plurality of tasks associated with a user, and retrieve geographic mapping data. The AM computing device may also generate a route model based upon the retrieved plurality of tasks and the retrieved geographic mapping data. The AM computing device may execute the route model to determine an optimal route, and transmit, to the user, an optimized travel plan based upon the optimal route.

Systems and methods for adaptive route optimization for learned task planning

A matching computer system for electronically generating, matching, and providing online user profiles, and determining a trust score for a user based upon at least social media data and insurance data is provided. The matching computer system may be configured to register users within the matching computer system, receive consent from the users to capture the social media data, and collect the social media data and the insurance data from each registered user. The matching computer system may also be configured to retrieve the social media data and the insurance data associated with each registered user. The matching computer system may be further configured to determine a trust score for each registered user based upon each respective social media data and each respective insurance data. Each trust score represents a level of trustworthiness of the user.

Growing community of inventors

Bloomington, IL, United States of America

Joseph Robert Brannan