Waymo LLC

Google Inc.

Joshua Seth Herbach

Nathaniel Fairfield

Peter Colijn

Philip Nemec

Renaud-Roland Hubert

Matthew Paul McNaughton

Michael Epstein

Min Li Chan

Jennifer Arden

Christopher Kennedy Ludwick

John Wesley Dyer

Michael Steven Montemerlo

Andrew Hughes Chatham

Ioan-Alexandru Sucan

Salil Pandit

Guillaume Dupre

Juliet Rothenberg

Katharine Patterson

Vadim Furman

Dmitri A Dolgov

Brian Douglas Cullinane

Michael R James

David Tse-Zhou Lu

Laurens Andreas Feenstra

Andrew Barton-Sweeney

Mishika Vora

Calvin Karl Johnson

Collin Winter

Ryan Joseph Andrade

Kevin Rawlings

Emily Chi

Misha Balakhno

David Harrison Silver

David Yonchar Margines

Luis Torres

Anne Kristiina Aula

Dietmar Ebner

Anne Kristina Aula

Ajay Joshi

Michael James

Austin Daniel Abrams

Xiang Gao

Andrew Chan

Matthew Paul Mcnaughton

Igor Tufanov

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

The technology relates to actively looking for an assigned passenger prior to a vehiclereaching a pickup location. For instance, information identifying the pickup location and client device information for authenticating the assigned passenger is received. Sensor data is received from a perception system of the vehicle identifying objects in an environment of the vehicle. When the vehicle is within a predetermined distance from the pickup location, authenticating a client device using the client device information is attempted. When the client device has been authenticated, the sensor data is used to determine whether a pedestrian is within a first threshold distance of the vehicle. When a pedestrian is determined to be within the first threshold distance of the vehicle, the vehicle is stopped prior to reaching the pickup location, to wait for the pedestrian within the first threshold distance of the vehicle to enter the vehicle.

Early boarding of passengers in autonomous vehicles

Aspects of the disclosure relate to generating scouting objectives in order to update map information used to control a fleet of vehicles in an autonomous driving mode. For instance, a notification from a vehicle of the fleet identifying a feature and a location of the feature may be received. A first bound for a scouting area may be identified based on the location of the feature. A second bound for the scouting area may be identified based on a lane closest to the feature. A scouting objective may be generated for the feature based on the first bound and the second bound.

Generating scouting objectives

Aspects of the disclosure relate to a system that includes a memory storing a queue for arranging tasks, a plurality of self-driving systems for controlling an autonomous vehicle, and one or more processors. The one or more processors may receive a non-passenger task request with a priority level of the non-passenger task request. When the non-passenger task request is accepted, the one or more processors may insert the task in the queue based on the priority level of the task request. Then, the one or more processors may provide instructions to one or more self-driving systems according to the non-passenger task request. Having received updates of the status of the autonomous vehicle, the one or more processors may determine that the task is completed based on the updates. After determining that the task is completed, the one or more processors may remove the task from the queue.

Non-passenger requests for autonomous vehicles

Examples described may enable provision of remote assistance for an autonomous vehicle. An example method includes a computing system operating in a rewind mode. In the rewind mode, the system may be configured to provide information to a remote assistance operated based on a remote-assistance triggering criteria being met, such as determining that the autonomous vehicle has been stopped for a period of time. When the triggering criteria is met, the remote assistance system may provide data from the time leading up to when the remote-assistance triggering criteria was met that was capture of the environment of autonomous vehicle to the remote assistance operator. Based on viewing the data, the remote assistance operator may provide and input to the system that causes a command to be issued to the autonomous vehicle.

Methods and systems for providing remote assistance to a stopped vehicle

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 provide systems and methods for providing suggested locations for pick up and destination locations. Pick up locations may include locations where an autonomous vehicle can pick up a passenger, while destination locations may include locations where the vehicle can wait for an additional passenger, stop and wait for a passenger to perform some task and return to the vehicle, or for the vehicle to drop off a passenger. As such, a request for a vehicle may be received from a client computing device. The request may identify a first location. A set of one or more suggested locations may be selected by comparing the predetermined locations to the first location. The set may be provided to the client computing device.

Determining pickup and destination locations for autonomous vehicles

Example systems and methods allow for reporting and sharing of information reports relating to driving conditions within a fleet of autonomous vehicles. One example method includes receiving information reports relating to driving conditions from a plurality of autonomous vehicles within a fleet of autonomous vehicles. The method may also include receiving sensor data from a plurality of autonomous vehicles within the fleet of autonomous vehicles. The method may further include validating some of the information reports based at least in part on the sensor data. The method may additionally include combining validated information reports into a driving information map. The method may also include periodically filtering the driving information map to remove outdated information reports. The method may further include providing portions of the driving information map to autonomous vehicles within the fleet of autonomous vehicles.

Reporting road event data and sharing with other vehicles

Example embodiments relate to using remote assistance to maneuver an autonomous vehicle to a location. A computing device used by a remote operator may receive a request for assistance from a vehicle that indicates the vehicle is stopped at a first location with one or more navigation options for enabling the vehicle to navigate from the first location to a second location. At least one navigation option includes a maneuver technique that requires operator approval prior to execution. The computing device may then display a graphical user interface (GUI) that conveys the one or more navigation options. Based on detecting a selection of a particular navigation option, the computing device may transmit instructions to the vehicle to perform the particular navigation option. The vehicle may configured to navigate from the first location to the second location by performing the particular navigation option while monitoring for changes in the environment.

Methods and systems for using remote assistance to maneuver an autonomous vehicle to a location

Aspects of the disclosure provide for the selection of a route for a vehicle having an autonomous driving mode. For instance, an initial location of the vehicle may be identified. This location may be used to determine a set of possible routes to a destination location. A cost for each route of the plurality is determined by inputting time of day information, map information, and details of that route into one or more models in order to determine whether the vehicle is likely to be stranded along that route and assessing the cost based at least in part on the determination of whether the vehicle is likely to be stranded along that route. One of the routes of the set of possible routes may be selected based on any determined costs. The vehicle may be controlled in the autonomous driving mode using the selected one.

Model-based routing for autonomous vehicles

Aspects of the present disclosure relate to a system having a memory, a plurality of self-driving systems for controlling a vehicle, and one or more processors. The processors are configured to receive at least one fallback task in association with a request for a primary task and at least one trigger of each fallback task. Each trigger is a set of conditions that, when satisfied, indicate when a vehicle requires attention for proper operation. The processors are also configured to send instructions to the self-driving systems to execute the primary task and receive status updates from the self-driving systems. The processors are configured to determine that a set of conditions of a trigger is satisfied based on the status updates and send further instructions based on the associated fallback task to the self-driving systems.

Fallback requests for autonomous vehicles

Aspects of the disclosure relate to controlling a vehicle in an autonomous driving mode. For instance, a first location corresponding to a location where the vehicle is to pick up or drop off a passenger is received. A first cost for the vehicle to reach the first location is determined. A second location based on the first location is identified, and a second cost is determined based on a cost for the vehicle to reach the second location and a cost for the passenger to reach the second location. The first cost is compared to the second cost, and a notification is sent based on the notification. In response to sending the notification, instructions to proceed to the second location are received, and in response to receiving the instructions, the vehicle is controlled in the autonomous driving mode to the second location to pick up or drop off the passenger.

Suggesting alternative pickup and drop off locations for autonomous vehicles

Example implementations relate to vehicle occupancy confirmation. An example implementation involves receiving, at a computing system from a camera positioned inside a vehicle, an image representing an occupancy within the vehicle. The implementation further involves, responsive to receiving the image, displaying the image on a display interface, and receiving an operator input confirming the occupancy meets a desired occupancy. The implementation additionally includes transmitting an occupancy confirmation from the computing system to the vehicle. In some instances, in response to receiving the occupancy confirmation, the vehicle executes an autonomous driving operation.

Methods and systems for vehicle occupancy confirmation

Growing community of inventors

San Francisco, CA, United States of America

Joshua Seth Herbach