Zendrive, Inc.

Credit Karma, LLC

Pankaj Risbood

Jonathan Arie Matus

Jayanta Pal

Romit Roy Choudhury

Vishal Verma

Bipul Islam

Aditya Karnik

Manish Sachdev

Nikhil Mudaliar

Nitin Dileep Salodkar

Shivam Singh

Jayanta Kumar Pal

Romit Roy Choudhary

A method for monitoring device usage includes: receiving user device information; based on the user interaction data, determining a state associated with the user device; and based on the state of the user device, determining a set of tap parameters. Additionally or alternatively, the method can include any or all of: determining a risk score based on at least on the set of tap parameters; determining an output based on the risk score; and/or any other suitable processes performed in any suitable order.

System and method for assessing device usage

A method for monitoring vehicle motion using a mobile device associated with a user including collecting activity data at a mobile device associated with the user; determining a user activity state based on the activity data; determining motion data collection parameters associated with an operating state of the mobile device, based on the user activity state; and collecting motion data at the mobile device based on the motion data collection parameters.

System and method for vehicle sensing and analysis

A system for accident reconstruction can include and/or be configured to interface with any or all of: a set of models, a set of modules, a processing system, client application, a user device (equivalently referred to herein as a mobile device), a set of sensors, a vehicle, and/or any other suitable components. A method for accident reconstruction includes collecting a set of inputs; detecting a collision and/or one or more features of the collision; reconstructing the collision; and producing an output based on the reconstruction. Additionally or alternatively, the method can include training a set of models and/or modules, and/or any other suitable processes.

Method and system for vehicular collision reconstruction

Embodiments of a method for improving movement characteristic determination using a plurality of mobile devices associated with a vehicle can include: collecting a first movement dataset corresponding to at least one of a first location sensor and a first motion sensor of a first mobile device of the plurality of mobile devices; collecting a second movement dataset corresponding to at least one of a second location sensor and a second motion sensor of a second mobile device of the plurality of mobile devices; determining satisfaction of a device association condition indicative of the first and the second mobile devices as associated with the vehicle, based on the first and the second movement datasets; and after determining the satisfaction of the device association condition, determining a vehicle movement characteristic based on the first and the second movement datasets.

Method for mobile device-based cooperative data capture

A method for primarily sensor-based navigation includes: in a first time period, collecting geophysical position data using a GPS receiver of a navigation device; in the first time period, collecting a first set of accelerometer data using an accelerometer of the navigation device; analyzing the first set of accelerometer data to produce a first set of vertical vehicular motion data; generating a mapping association between the first set of vertical vehicular motion data and the geophysical position data; in a second time period after the first time period, collecting a second set of accelerometer data using the accelerometer; analyzing the second set of accelerometer data to produce a second set of vertical vehicular motion data; and calculating an estimated location of the vehicle by analyzing the second set of vertical vehicular motion data in light of the mapping association.

Method for accelerometer-assisted navigation

A method for adaptive risk modeling for an autonomous vehicle, the method comprising: retrieving parameters of an identified driving mission of the autonomous vehicle; in response to the parameters of the identified driving mission, generating values of: a comparative autonomous parameter, a mix model parameter, a surrounding risk parameter, a geographic operation parameter, and a security risk parameter upon evaluating situational inputs associated with the identified driving mission with a comparative autonomous model, a mix model, a sensor-surrounding model, a geography-dependent model, and a security risk model generated using sensor and supplementary data extraction systems associated with the autonomous vehicle; upon generating values, generating a risk analysis with a rule-based algorithm; and contemporaneously with execution of the identified driving mission, implementing a response action associated with control of the autonomous vehicle, based upon the risk analysis.

Method and system for risk modeling in autonomous vehicles

A method for traffic characterization associated with a vehicle including collecting a movement dataset sampled at least at one of a location sensor and a motion sensor associated with the vehicle, during a driving session associated with movement of the vehicle; extracting a set of features from the movement dataset associated with movement of the vehicle during the driving session; and determining one or more traffic-related characteristics associated with the vehicle based on the set of features.

Method and system for determining traffic-related characteristics

A method for improving vehicular traffic-related communications between devices including: collecting a first movement dataset corresponding to a sensor of a device arranged within a vehicle; collecting a supplementary dataset from the device; transmitting the movement dataset and supplementary dataset from the device to a remote computing system; determining a traffic-related event based upon processing the movement dataset and supplementary dataset with a traffic event model; and transmitting a traffic-related communication from the remote computing system to a second device associated with a second user arranged in a second vehicle.

Method and system for vehicular-related communications

A method and system for detecting an accident of a vehicle, the method including: receiving a movement dataset collected at least at one of a location sensor and a motion sensor arranged within the vehicle, during a time period of movement of the vehicle, extracting a set of movement features associated with at least one of a position, a velocity, and an acceleration characterizing the movement of the vehicle during the time period, detecting a vehicular accident event from processing the set of movement features with an accident detection model, and in response to detecting the vehicular accident event, automatically initiating an accident response action.

Method for smartphone-based accident detection

A method for risk determination of a route includes collecting a set of inputs and determining a set of risk scores. Additionally, the method can include any or all of: processing the set of inputs; organizing the set of inputs; determining a model based on the set of inputs; determining a set of risk scores; producing an outputs based on the set of risk scores; and/or any other suitable processes.

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San Francisco, CA, United States of America

Pankaj Risbood