Zoox, Inc.

Sandra Ruiz

Nathaniel John Villaume

Subasingha Shaminda Subasingha

Ryan McMichael

Turhan Karadeniz

Collin MacGregor

Andrew Lewis King

Nehemia Girma Terefe

He Yi

Aaron Rosekind

Christopher David Canady

Irene Perali

Darrin Sammons Willis

Maxwell Ethan Mckenzie Yaron

Janakan Chandrakumar

Timothy Henry Jung

Matthew Ambrose Romlewski

Joshua Paul Munic

Techniques are discussed herein for detecting and managing faults occurring within various vehicle systems, to enable the vehicle to respond safely and appropriately to the faults. In examples, a constraint generator may receive sensor data associated with the operation of a vehicle in an environment. The constraint generator may perturb the sensor data to mimic particular sensor faults, and execute simulations to determine performance degradations of the vehicle systems associated with the particular sensor faults. Based on the performance degradations associated with sensor faults, the constraint generator may determine the appropriate constraints with limitations on the operation of the vehicle, and communicate the constraint parameters to the appropriate vehicle systems accordingly.

Vehicle constraint generation

Techniques for image data protection using cyclic redundancy checks are disclosed herein. Some of the techniques may include, at a processor, receiving image data that includes multiple lines of pixel data. The processor may also determine at least a first hash value representing a first line of pixel data of the multiple lines of pixel data and a second hash value representing a second line of pixel data of the multiple lines of pixel data. The processor may also send the image data to a computing device that is configured to determine, based at least in part on the first hash value and the second hash value, whether the image data is corrupt.

Image data protection using data integrity checks

Techniques for determining a degraded state associated with a sensor are discussed herein. For example, a sensor associated with vehicle may captured data of an environment. A portion of the data may represent a portion of the vehicle. Data associated with a region of interest can be determined based on a calibration associated with the sensor. For example, in the context of image data, image coordinates may be used to determine a region of interest, while in the context of lidar data, a beam and/or azimuth can be used to determine a region of interest. A data metric can be determined for data in the region of interest, and an action can be determined based on the data metric. For example, the action can include cleaning a sensor, scheduling maintenance, reducing a confidence associated with the data, or slowing or stopping the vehicle.

Sensor degradation monitor

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Newark, CA, United States of America

Sandra Ruiz