Ford Global Technolgoies, LLC

David Michael Herman

Ashwin Arunmozhi

Stephen Jay Orris, Jr

Venkatesh Krishnan

David Joseph Orris

Nunzio Decia

Nicholas Alexander Scheufler

Yashanshu Jain

David A Herman

Aaron Lesky

Akshay Vaidya

Sunil Reddy Patil

Ronald Beras

Brian Quinn Kettlewell

Larry Sanders

Grant Inskeep

Catherine M Amodeo

Alexander George Shanku

Jon M Speigle

Binduhasini Sairamesh

Daniel A Makled

Michael Mcquillen

Brian Tamm

Christopher Colarusso

Ryan Sorsby

Ali Husain

Kyle B Sorensen

Michael Robertson, Jr

Aaron Lewis Mills

Scott Andrew Amman

Ray C Siciak

Tyler D Hamilton

Bo Wu

Michael Adel Awad Alla

David Alfred Ostrowski

Nicholas Colella

Andrea Bowes Chowanic

John Craig Elson

Maher Ghneim

Leopoldo Urbina

Geoffrey Horowitz

Nikhitha Bekkanti

Akshat Rajvanshi

Avrokin Surnilla

Christopher Leon Jones

Sheida Malekpour

Nicolas Salciccioli

Sanjay Abhyankar

Larry D Sanders, Jr

Michael Monforton

Keith Van Gorder

Manvi Kamboj

Gregg William Byrne

Antonios Koumpias

Yogendra Singh

Katharina Mitschker

Katharina Ines Mitschker

Catherine Marie Amodeo

A computer includes a processor and a memory. The memory stores instructions executable by the processor. The computer identifies personally identifiable information (PII) in an initial image frame. The computer encodes a region containing the PII of the initial image frame to a latent vector with a lower dimensionality than the region. The computer anonymizes the region from the initial image frame, resulting in a modified image frame. The computer associates: the latent vector with the modified image frame.

Anonymizing personally identifiable information in image data

A computer includes a processor and a memory, and the memory stores instructions executable by the processor to receive lidar data from a lidar device, generate a point cloud from the lidar data, identify an object in the point cloud, and, upon identifying the object, delete a portion of the lidar data that is from a region encompassing the object. The object includes personally identifiable information.

Anonymizing personally identifiable information in sensor data

A system includes a processor programmed to: identify, based on data from first sensors included in a first vehicle, a second vehicle moving within a first threshold distance of a travel path of the first vehicle and within a second threshold distance of the first vehicle. The processor is further programmed to receive, from second sensors included in the first vehicle, transient velocity data of the second vehicle; and determine an operating condition of the second vehicle based on the transient velocity data.

Detection of vehicle operating conditions

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 computer that includes a processor and a memory, the memory including instructions executable by the processor can activate a plurality of light sources in an alternating pattern at an illumination frequency and acquire image data depicting light reflected from an object at a timing corresponding to the alternating pattern at the illumination frequency. In response to variations in the light impinging upon the object from the alternating pattern, an object contour can be determined based on estimating one or more object surface normals based on photometric stereo. One or more of object identity and object depth can be determined based on combining the object contour with the image data.

Object detection

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

A system can include a computer having a processor coupled to a memory, the memory storing instructions executable by the processor to capture an image of an operator positioned in a steering position. The instructions can additionally be to determine, based on parameters extracted from the captured image, a confidence level that output data from a torque sensor represents torque applied by an operator to a steering element. The instructions can additionally be to actuate a component in a vehicle based on the confidence level.

Prediction of operator input to a steering element

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 determine a value over time derived from a region of sensor data from an optical sensor of a host vehicle; determine that the value over time matches a stored temporal pattern; upon determining that the value over time matches the stored temporal pattern, classify an object at the region as a surface reflecting a signal from an illuminator of an origin vehicle; and actuate a component of the host vehicle based on a classification of the object at the region.

Vehicle reflection identification

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

A computer includes a processor and a memory, and the memory stores instructions executable by the processor to sequentially activate a plurality of lamps aimed at a scene, the lamps mounted to a vehicle; receive image data of the scene generated while sequentially activating the lamps; generate a map of surface normals of the scene by executing a photometric stereo algorithm on the image data; and in response to a speed of the vehicle being below a speed threshold, navigate the vehicle based on the map of the surface normals.

Photometric stereo for vehicle navigation

Captured PII is identified in sensor data, the sensor data being captured over time by a sensor of a vehicle of an environment surrounding the vehicle. The sensor data includes captured PII and non-PII. A notice zone surrounding the vehicle is identified, the notice zone defining an area in which a notice device of the vehicle provides notice to pedestrians that the sensor data is being captured. Any instances of the captured PII in the sensor data are obscured that are captured from the pedestrians that, over the time of the capture, did not enter the notice zone and receive the notice. The sensor data, as processed, is sent to a cloud server for storage.

Adaptive PII obscuring based on PII notification visibility range

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 includes a processor and a memory storing instructions executable by the processor to predict a quantity of misalignment of an optical sensor based on a projected motion of a vehicle, predict an error of the predicted quantity of misalignment, and actuate the vehicle based on the predicted quantity of misalignment and the predicted error. The vehicle includes the optical sensor.

Sensor misalignment correction

The disclosure is generally directed to systems and methods associated with communicating privacy rights pertaining to data captured from a vehicle. An example method executed by a processor of a data capture apparatus in a vehicle can include capturing an image. In an example scenario, the image may include an individual who is located outside the vehicle. Furthermore, in some cases, the image can be a part of a video clip containing multiple images. The method further includes generating an identifier for identifying the image(s). The identifier can be a machine-readable symbol such as, for example, a QR-code symbol or a barcode. A notification that includes the identifier may be generated and conveyed to the individual for use by the individual to exercise his/her rights to privacy with respect to the images in which he/she is present.

Communicating privacy rights pertaining to data captured by a vehicle

Growing community of inventors

Oak Park, MI, United States of America

David Michael Herman