State Farm Mutual Automobile Insurance Company

Blueowl, LLC

Other

Quanata, LLC

Aaron Scott Chan

Kenneth Jason Sanchez

Brian Mark Fields

Mohamed A Wazeer

Steven C Cielocha

Todd Binion

Ronny S Bryant

Torri Wollenschlager

Shawn C Bennett

Weixin Wu

Stacey Gorsuch

Carol Marie Csanda

Terry Quakenbush

Craig M Main

Richard A Novak

Chien Che Huang

Stephen A Kohaus

John Adrian Nepomuceno

Christina P Mullen

Rosemarie Geier Grant

Cynthia L Garretson

Matthew Christopher Jon Donovan

Steve Cielocha

Matthew Zettinger

Matthew R Baker

Steve Roberson

Taylor Michael Thiel

Mihir Dilip Angal

Alisha Deshmukh

Allison Lynne Diaz

Kelsey Catherine Yoshie Stiles

Akash Duseja

Thasphon Chuenchujit

Gina Taylor

Saivikas Thalluri

Jie Yan

Samuel C Weeks

Utku Pamuksuz

Jeremy Shawn Fogg

Lynn Splittstoesser

William Cho Hseih

Muhammad Ibrahim Saeed

Richard Zhou

Sanjay Jayaswal

Sukeerthi Khadri

Dirk Patrick Maloney

Chase Southwood

Narendra Anilal

Yue Liu

Scott T Christensen

Anuj Dahiya

Yuetong Xing

Yuhao Zhou

Keely Renwick

Abhinav Rai

Shashwat Gupta

Vibhakar V S Vemulapati

Sanjiv Kumar

Harshit Agarwal

Pravita Tolanavar

Jackie O Jordan, Ii

Justin Davis

Sripriya Sundararaman

Aditya Subramanian

Ben Blaisdell

Mary Kay Gonet Quist

Ashley Anne Pettit

Simon Reed

Vibhakar Vemulapati

Systems and methods detecting onboard sensor tampering are disclosed. According to embodiments, data captured by interior sensors within a vehicle may be analyzed to determine an indication that the activity of the vehicle operator either cannot be sufficiently detected or cannot be sufficiently identified using the captured data (e.g., that the captured data may be compromised). A date and time associated with the indication may be recorded, and a vehicle operator associated with the indication may be identified. A possible cause for the compromised data may be diagnosed, and notification may be generated indicating that the activity of the vehicle operator either cannot be sufficiently detected or cannot be sufficiently identified, and/or the possible cause. Additionally, a recommendation for restoring sensor functionality may be generated for the vehicle operator based the possible cause.

Technology for detecting onboard sensor tampering

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

Systems and methods for improving vehicular safety are provided. According to certain aspects, an electronic device may receive and analyze image data depicting an individual located within a vehicle. The electronic device may also access certain data related to a condition of the individual, and may accordingly determine whether the individual is fit to operate the vehicle. If the individual is unfit to operate the vehicle, the electronic device may alter autonomous operation of the vehicle.

Apparatuses, systems and methods for improving operation of autonomous vehicles

An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.

Systems and methods for evaluating autonomous vehicle software interactions for proposed trips

An insurance computing device is provided. The insurance computing device may include a processor and a memory. The processor may be programmed to receive a registration request from a vehicle computing device associated with a vehicle and/or a covered parking location (CPL) computing device associated with a covered parking location, generate a usage profile associated with at least one of the vehicle and the covered parking location, monitor the vehicle computing device and/or the CPL computing device for any requests to reserve an available parking spot of the covered parking location, update the usage profile, determine if an insurance policy associated with the vehicle and/or the covered parking location is eligible for insurance-related benefits based upon the usage profile.

Systems and methods for weather-related vehicle damage prevention

A computer-implemented method is provided for predicting occupant location based on vehicular collision. The method includes receiving, at a computing system including one or more processors, information indicative of a vehicle crash involving a vehicle occupant. The method also includes receiving, at the computing system, information indicative of a position of the vehicle occupant within the vehicle prior to the vehicle crash. The method also includes determining, by the one or more processors, a probability of ejection of the vehicle occupant according to (i) the information indicative of the vehicle crash and (ii) the position of vehicle occupant. The method also includes providing, by the computing system, the probability of ejection of the vehicle occupant to one or more emergency responders.

Systems and methods for predicting occupant location based on vehicular collision

Apparatuses, systems and methods are provided for generating and transmitting data representative of a vehicle operation mode. More particularly, apparatuses, systems and methods are provided for generating data representative of a vehicle operation mode based on vehicle interior image data.

Apparatuses, systems and methods for generation and transmission of vehicle operation mode data

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

A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations including: receiving sensor data detected by one or more image sensors in a vehicle, wherein the sensor data is representative of driver movements of a driver in the vehicle; categorizing the sensor data as driver postures representative of actions of the driver in the vehicle; rotating and scaling the driver postures to be standardized for different drivers and for different locations of the one or more image sensors within different vehicles; analyzing the sensor data to determine a reference position of the driver in the vehicle; and storing, in a database, the driver postures, as rotated and scaled, and the reference position of the driver in the vehicle. Other embodiments are disclosed.

Apparatuses, systems, and methods for detecting vehicle occupant actions

The present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle by comparing current image feature data to previously classified image features.

Apparatus, systems and methods for classifying digital images

Systems and methods for transferring autonomous driving preferences between vehicles are provided. For example, a vehicle operator may borrow a friend's or spouse's vehicle, or may rent a vehicle, and may wish to transfer his or her autonomous driving preferences to the vehicle he or she is currently operating. An autonomous driving preference associated with an operator of a first vehicle is obtained. The autonomous driving preference includes vehicle controls that the operator prefers to be operated autonomously, semi-autonomously, and/or manually. When the operator of the first vehicle is to operate a second vehicle or is currently operating a second vehicle, an indication of the autonomous driving preference associated with the operator is transmitted to the second vehicle, and the vehicle controls associated with the second vehicle are modified based on the autonomous driving preference associated with the operator.

System and method for transferring preferences for autonomous driving

An interaction detection and analysis ('IDA') computing device that includes at least one processor in communication with at least one memory device is provided. The at least one processor being configured to store software ecosystem data, environmental condition data, and performance data in a plurality of data records in a database, wherein each data record i) is associated with one autonomous vehicle (AV) of a plurality of AVs and ii) includes the software ecosystem data, the environmental condition data, and the performance data of the corresponding AV; apply at least one machine learning algorithm to a set of the plurality of data records to identify an interaction between at least one software application and at least one environmental condition resulting in a particular outcome; and transmit, to at least one AV associated with the set of data records, at least one alert message advising of the particular outcome.

Systems and methods for detecting software interactions for autonomous vehicles within changing environmental conditions

The present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle by comparing current image data to previously classified image data.

Apparatuses, systems and methods for classifying digital images

A vehicle weather damage-prevention system is provided. The system may include a vehicle computing device associated with a vehicle, a covered parking location (CPL) computing device associated with a covered parking location, and an insurance computing device. The vehicle computing device may receive weather data and determine whether the vehicle is affected by inclement weather. The vehicle computing device may receive from the CPL computing device information indicating whether the covered parking location has available parking spots. The vehicle computing device may transmit a request to the CPL computing device to reserve a parking spot. The CPL computing device may selectively permit the vehicle access to the covered parking location. The insurance computing device may monitor the vehicle computing device and/or the CPL computing device and determine if an insurance policy is eligible for insurance-related benefits based upon a usage profile of the vehicle or the covered parking location.

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

Growing community of inventors

Lisle, IL, United States of America

Aaron Scott Chan