Waymo LLC

Emily Chi

Ryan Joseph Andrade

Michael R James

Christopher Kennedy Ludwick

Joshua Seth Herbach

Ioan-Alexandru Sucan

Andrew Barton-Sweeney

Misha Balakhno

Andreas Wendel

Daniel L Rosenband

Christian Lauterbach

Michael James

Etai Bruhis

Alexander Zbrozek

Pieter Kapsenberg

Zhuyuan Liu

Daniel Rosenband

Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode. The system includes a plurality of sensors configured to generate sensor data. The system also includes a first computing system configured to generate trajectories using the sensor data and send the generated trajectories to a second computing system. The second computing system is configured to cause the vehicle to follow a receive trajectory. The system also includes a third computing system configured to, when there is a failure of the first computer system, generate and send trajectories to the second computing system based on whether a vehicle is located on a highway or a surface street.

Systems for implementing fallback behaviors for autonomous vehicles

The technology relates to partially redundant equipment architectures for vehicles able to operate in an autonomous driving mode. Aspects of the technology employ fallback configurations, such as two or more fallback sensor configurations that provide some minimum amount of field of view (FOV) around the vehicle. For instance, different sensor arrangements are logically associated with different operating domains of the vehicle. Fallback configurations for computing resources and/or power resources are also provided. Each fallback configuration may have different reasons for being triggered, and may result in different types of fallback modes of operation. Triggering conditions may relate, e.g., to a type of failure, fault or other reduction in component capability, the current driving mode, environmental conditions in the vicinity of vehicle or along a planned route, or other factors. Fallback modes may involve altering a previously planned trajectory, altering vehicle speed, and/or altering a destination of the vehicle.

Redundant hardware system for autonomous vehicles

A method for determining a pullover spot for a vehicle is described. The method includes using a computing device to detect information related to a system of the vehicle or an environment surrounding the vehicle using a sensor of a vehicle and determine a local failure of the vehicle based on the information. The computing device may then be used to determine that the vehicle should pullover before completing a current trip related to transporting a passenger or good by comparing vehicle requirements for the trip with the local failure and determine a pullover spot by identifying a first area for the vehicle to park in part based on a second area being available for a second vehicle to pick up the passenger or good. The computing device may operate the vehicle to the pullover spot and transmit a request for a second vehicle.

Autonomous vehicle system for determining a pullover spot in response to detected local failure

The disclosure provides for a method for determining a pullover spot for a vehicle. The method includes using a computing device to detect information related to a system of the vehicle or an environment surrounding the vehicle using a sensor of a vehicle and determine a local failure of the vehicle based on the information. The computing device may then be used to determine that the vehicle should pullover before completing a current trip related to transporting a passenger or good by comparing vehicle requirements for the trip with the local failure and determine a pullover spot by identifying a first area for the vehicle to park in part based on a second area being available for a second vehicle to pick up the passenger or good. The computing device may operate the vehicle to the pullover spot and transmit a request for a second vehicle.

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Los Angeles, CA, United States of America

Emily Chi