Zoox, Inc.

Evan David Cook

Daniel Glenn Johnson

Nam Gook Cho

Chang Gi Samuel Hong

Andrew Mark Stieber

Carter William McEathron

Xuan Zhong

Rajith Jayaratne

William Edward Cheringal

Raghuraman Surineedi

Bingchao Han

Caleb Heath Norfleet

George William Sabet Fahmy

MacKenzie Cunningham

Rohan Agrawal

Nigil Lee

Techniques for controlling a vehicle based on a collision avoidance algorithm are discussed herein. The vehicle receives sensor data and can determine that the sensor data represents an object in an environment through which the vehicle is travelling. A computing device associated with the vehicle determines a collision probability between the vehicle and the object at predicted locations of the vehicle and object at a first time. Updated locations of the vehicle and object can be determined, and a second collision probability can be determined. The vehicle is controlled based at least in part on the collision probabilities.

Control system for vehicle doors

An impact is detected with a vehicle having a body comprising parts which are deformable in an impact, by a secondary impact detection system configured to detect an impact that may not trigger a primary impact detection system. The secondary impact detection system comprises a plurality of deformation sensors attached to the deformable parts and configured to detect bending of the deformable parts. One or more processors are configured to receive a plurality of respective outputs from the plurality of deformation sensors, process the respective outputs to increase sensitivity to short-term changes relative to long-term changes and generate an indication of an impact dependent on detecting a processed output meeting a predetermined criterion. Outputs associated with a group of neighboring flex sensors may be used to localize the impact, characterize the source of impact, and/or reduce a likelihood of a false positive associated with the detection.

Detection of an impact with a vehicle

Techniques are described for cleaning sensors of a vehicle. An attribute of the surrounding environment (e.g., type of precipitation, intensity of precipitation, etc.) is determined along with orientations and/or attributes of the sensors (e.g. fields-of-view, focal lengths, spectral ranges, etc). Cleaning frequencies are then be determined based, at least in part, on the attribute of the environment together with the orientations and/or attributes of the sensors. Cleaning elements are then activated at the determined frequencies to clean the sensors. In some examples, the cleaning frequencies may be determined based additionally on an attribute of travel of the vehicle (e.g. direction of travel of the vehicle, speed of the vehicle, etc.).

Cleaning vehicle sensors

A reflector unit may behave as a retroreflector to reflect light of a selected color. The reflector unit may comprise a first reflector having a first color, a second reflector having a second color, and a mask that either allows incoming light to reach the first reflector and not the second reflector or allows incoming light to reach the second reflector and not the first reflector. An active light unit may emit light of a particular color in response to receiving light. In this fashion, the active light unit may simulate the operation of a reflector. The reflector unit and the active light unit may operate on a bi-directional vehicle.

Vehicular lighting using passive and/or active optics

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Woodside, CA, United States of America

Evan David Cook