Waymo LLC

Google Inc.

Christopher Kennedy Ludwick

Joshua Seth Herbach

Matthew Paul McNaughton

Nathaniel Fairfield

Andreas Wendel

Michael R James

Renaud-Roland Hubert

Min Li Chan

Jennifer Arden

Ryan Joseph Andrade

Emily Chi

YooJung Ahn

Philip Nemec

Brian Douglas Cullinane

Albert Shane

David Tse-Zhou Lu

Calvin Karl Johnson

Ioan-Alexandru Sucan

Anne Kristina Aula

Laurens Andreas Feenstra

Andrew Barton-Sweeney

Misha Balakhno

Andrew Hughes Chatham

Daniel L Rosenband

Christian Lauterbach

Etai Bruhis

Pieter Kapsenberg

Alexander Zbrozek

Zhuyuan Liu

Charles Bigelow Johnson

Michael James

Anne Kristiina Aula

Matthew Paul Mcnaughton

Yoojung Ahn

Daniel Rosenband

Aspects of the disclosure relate to arranging a pickup between a driverless vehicle and a passenger. For instance, dispatch instructions dispatching the vehicle to a predetermined pickup area in order to pick up the passenger are received by the vehicle which begins maneuvering to the predetermined pickup area. While doing so, the vehicle receives from the passenger's client computing device the device's location. An indication that the passenger is interested in a fly-by pickup is identified. The fly-by pickup allows the passenger to safely enter the vehicle at a location outside of the predetermined pickup area and prior to the one or more processors have maneuvered the vehicle to the predetermined pickup area. The vehicle determines that the fly-by pickup is appropriate based on at least the location of the client computing device and the indication, and based on the determination, maneuvers itself in order to attempt the fly-by pickup.

Arranging passenger pickups for autonomous vehicles

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

Aspects of the disclosure relate to determining and responding to an internal state of a self-driving vehicle. For instance, an image of an interior of the vehicle captured by a camera mounted in the vehicle is received. The image is processed in order to identify one or more visible markers at predetermined locations within the vehicle. The internal state of the vehicle is determined based on the identified one or more visible markers. A responsive action is identified action using the determined internal state, and the vehicle is controlled in order to perform the responsive action.

Determining and responding to an internal status of a vehicle

Aspects of the disclosure relate to determining a next vehicle task for a vehicle of a fleet. Vehicle data from the vehicle, charger data about at least one charger, and demand data may be received and used to determine the next vehicle task. The vehicle may be directed to the next vehicle task. Determining a next vehicle task may further be based on predictions made using the vehicle data, the charger data, and the demand data. Heuristics may also be used in determining a next vehicle task.

Managing a fleet of 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

Aspects of the present disclosure relate to a vehicle for maneuvering a passenger to a destination autonomously. The vehicle includes one or more computing devices and a set of user input buttons for communicating requests to stop the vehicle and to initiate a trip to the destination with the one or more computing devices. The set of user input buttons consisting essentially of a dual-purpose button and an emergency stopping button different from the dual-purpose button configured to stop the vehicle. The dual-purpose button has a first purpose for communicating a request to initiate the trip to the destination and a second purpose for communicating a request to pull the vehicle over and stop the vehicle. The vehicle has no steering wheel and no user inputs for the steering, acceleration, and deceleration of the vehicle other than the set of user input buttons.

Autonomous vehicles

Growing community of inventors

Los Altos, CA, United States of America

Christopher Kennedy Ludwick