Ford Global Technolgoies, LLC

Yashanshu Jain

David Michael Herman

Brian Quinn Kettlewell

Christopher Colarusso

Ali Husain

Aaron Lewis Mills

Ashwin Arunmozhi

Akshay Vaidya

Catherine M Amodeo

Brian Tamm

Jon M Speigle

Alexander George Shanku

Ryan Sorsby

Nicolas Salciccioli

Kyle B Sorensen

Manvi Kamboj

Yogendra Singh

Catherine Marie Amodeo

Systems and methods for mitigating certain spoofing of vehicle features are disclosed herein. An example method can include determining input torque values obtained from a steering torque sensor associated with a steering wheel of a vehicle, wherein the input torque values are obtained over a period of time, determining road disturbances using a road disturbance model, applying a driver model that is indicative of human driver hands-on-wheel behaviors, determining when input torque values are indicative of a spoof or human interaction with the steering wheel using the input torque values, the road disturbance model, and the driver model, and executing a remediating measure when the input torque values are indicative of the spoof.

Systems and methods for mitigating spoofing of vehicle features

A method and apparatus for protecting vehicle data from a vehicle includes identifying the vehicle data to be included in output from a processor that is designated for protection, selecting a digital watermark based on a manner in which the output is subject to at least one of observation or interception, applying the digital watermark to the vehicle data to obtain watermarked output for output from the processor, and communicating a watermark identifier over a communication link of the vehicle to a location external from the vehicle. Detection of the digital watermark in data outside of the vehicle based upon the watermark identifier may be used to determine misuse of the vehicle data.

Vehicle data protection

An object can be detected in contact with a steering wheel of a vehicle. A first image of the steering wheel at a first angle of rotation and a second image of the steering wheel at a second angle of rotation are then obtained. A type of the object is identified based on at least one of the first image or the second image, as one of a human hand or a foreign object. A vehicle component is controlled based on the type of object.

Steering wheel contact detection

A computer includes a processor and a memory, and the memory stores instructions executable by the processor to receive operation data generated by first components of a vehicle; determine that the vehicle is being operated autonomously by an on-board autonomous-operation module based on the operation data without using output from the on-board autonomous-operation module; and upon determining that the vehicle is being operated autonomously, actuate a second component of the vehicle.

Detection of autonomous operation of a vehicle

Ensuring privacy consent for handling of occupant vehicle data is provided. A feature identification vector indicative of an identity of a vehicle occupant of a vehicle is identified. The feature identification vector is used to identify whether consent for use of vehicle data was provided by the vehicle occupant. The consent is requested responsive to the identity of the vehicle occupant not having consented to data collection. Responsive to the consent being given by the vehicle occupant, the consent and the feature identification vector of the vehicle occupant is stored in a storage of the vehicle. The vehicle data is uploaded in accordance with whether the consent was granted for the vehicle occupant.

Occupant feature recognition to ensure privacy consent

A computer is programmed to receive a plurality of first values for a respective plurality of variables transmitted over a communications network of a vehicle; determine a similarity measure between the first values and a plurality of second values of the variables; determine whether to transmit a collection of data transmitted over the communications network based on the similarity measure; and, upon so determining, transmit the collection of data to a server remote from the vehicle. The second values are a most similar set of values from an activation surface for a feature of the vehicle. The activation surface is a surface in a space defined by the variables dividing the space into regions in which activation of the feature is more or less likely than not, respectively, to have occurred when the variables have values in that region.

Vehicle data storage activation

This disclosure is generally directed to systems and methods for detecting distracted driving. In an example method, a light source identification procedure may be executed for detecting a first device present inside a vehicle and outside a field of view of a driver monitoring camera (such as upon a dashboard). The procedure can include evaluating an image data sample obtained from the driver monitoring camera so as to identify various devices that may be emitting light incident upon the face of the driver. The incident light may include a first pulse pattern corresponding to light emitted by the first device and a second pulse pattern corresponding to light emitted by a second device. The first device can be detected in various ways such as by evaluating a phase relationship between the first pulse pattern and the second pulse pattern and/or by evaluating spectral content present in the image data sample.

Systems and methods for detecting distracted driving by a driver of a vehicle

The present disclosure relates to a system and a method for addressing an error in a localization system that includes monitoring a plurality of sensors of a driver assistance system in real-time, with each sensor generating a data stream. The method further includes identifying a sensor having an anomalous data stream and calculating a primary localization and a backup localization. The primary localization calculation includes the anomalous data stream and the backup localization calculation does not include the anomalous data stream. Further, the method includes executing an action when the backup localization error estimate exceeds a threshold.

System and method for detecting and addressing errors in a vehicle localization

Handling personally identifiable information (PII) in data streams is provided. Processed sensor data is received, from a plurality of vehicles including sensors capturing raw sensor data, the raw sensor data including captured PII and non-PII. The processed sensor data includes simulated PII created based on the captured PII and one or more layers of the captured PII corresponding to the simulated PII. A request is received from a client device for a portion of the processed sensor data. Access keys corresponding to the request are identified. A result is constructed according to the access keys using the processed sensor data. The constructed result is sent to the client device responsive to the request.

Personally identifiable information in encrypted data streams

The disclosure is generally directed to systems and methods for sharing a video feed of a camera among multiple image processing components in a vehicle. A first priority may be applied to a first image processing component that performs a first image processing function. A second priority that is lower than the first priority, is applied to a second image processing component that performs a second image processing function. The first function may be deemed more important than the second function due to various reasons. Consequently, the first image processing component is offered priority to apply a first set of camera settings on the camera. The second image processing component may prefer to apply a different set of camera settings for executing the second image processing function. An access arbitrator allows the second image processing component to do so when the first image processing component relinquishes control of the camera.

Growing community of inventors

Dearborn, MI, United States of America

Yashanshu Jain