Gm Cruise Holdings LLC

Gm Global Technolgoy Operations, Inc.

Divya Thakur

Stephanie Olivia Engle

Mariya Jacobo

John Logan Anderson

Jacqueline Mary Shannon

Bradley David Ryan

Tejeswara Reddy Pogula

David Hyon Berrios

Michael Frank Schmidt

Cecilia Ziniti

Jeffrey Brandon

Kyle Vogt

Chen Xie

Rajat Basu

Adam Mandel-Senft

Zachary Garcia

Daniel Kan

Michael Rusignola

Robin Yang

Matthew Fox

Jiajian Zhou

Jackie Shannon

Jun Zhou

Robert Tweedy

Alex Van Dorn

Katherine Anne Fotion

Nick Tran

Systems and methods systems provide for client control over an Autonomous Vehicle (AV). The AV can determine sets of mechanical operations that it can take at a future time. The AV can determine a ranking for each of the sets of mechanical operations, including a first ranked set and at least one second ranked set. Client or user selection can be given a certain score, weight, or other value. The AV can apply the value to the second ranked set to determine an adjusted ranking. If the adjusted ranking outranks a ranking of the first ranked set, then the AV can expose the first ranked set and the second ranked set to a client interface. If the AV receives a selection of the second ranked set, the AV can perform that set of mechanical operations. Otherwise, the AV can perform the first ranked set of mechanical operations.

Client control for an autonomous vehicle ridesharing service

Various technologies described herein pertain to causing presentation on a user interface of an immediate portion of a navigation route of an autonomous vehicle. A computing system of the autonomous vehicle determines whether an object detected by sensor(s) of the autonomous vehicle proximate to the immediate portion of the navigation route are of a type and relative position defined as one of consequential and inconsequential for a human passenger. In response to determining that an object has both a type and relative position defined as consequential, the computing system causes presentation on the user interface a representation of the object relative to the immediate portion of the navigation route to provide a confidence engendering indication that the autonomous vehicle has detected the object. Otherwise if inconsequential, presentation on the user interface of any representation of the object is not caused by the computing system to avoid creating a confusing presentation.

Dynamic route information interface

Sensors coupled to a first vehicle are used to measure sensor measurements. Based on the sensor measurements, the first vehicle identifies a risk to the first vehicle and/or to a second vehicle near the first vehicle, for example based on a distance between the first and second vehicle being unsafely low. The first vehicle generates an alert based on the risk and outputs the alert toward the second vehicle, for example visually through a screen and/or audibly using speakers, to warn an operator of the second vehicle about the risk.

Dynamic inter-vehicle communication regarding risk detected based on vehicle sensor measurements

The subject disclosure relates to techniques for implementing conditional automation systems and in particular, for facilitating conditional automation in the context autonomous vehicle (AV) transportation services. Some aspects of the disclosed technology include methods that include steps for receiving an event trigger at a conditional autonomous vehicle (AV) platform, mapping the event trigger onto a conditional output, and sending the conditional output to an autonomous vehicle (AV) associated with the event trigger, wherein the conditional output is configured to update a navigation instruction followed by the AV. Systems and machine-readable media are also provided.

Conditional and connected smart routines for autonomous vehicles

Systems and methods provide for optimizing dispatching of autonomous vehicles (AVs) using an AV fleet management system. The AV fleet management system can receive first data indicative of client application to the AV fleet management system being opened on a client device. The AV fleet management system can determine availability of an AV within proximity of the client device. The AV fleet management system can determine a first route from a first location of the AV to a second location of the client device. The AV fleet management system can dispatch the AV from the first location to the second location via the first route prior to determining a destination of a second route from the second location to the destination.

Autonomous vehicle fleet management system based on application status

A device for hailing a vehicle includes a location sensor outputting location information indicative of a location of the device. The device further includes a device interface configured to receive an input from a user of the device. Responsive to the input, a transmitter of the device transmits the location information, input information, and identification information for the device to a dispatch server system. The transmitter is further configured to route the location information, the input information, and the identification information for the device to only the dispatch server system. The identification information is used by the dispatch server system to set a predefined location associated with the identification information as a destination for a trip for the user in the vehicle. The predefined location is defined in an account corresponding to the identification information of the device maintained by the dispatch server system prior to receipt of the input.

Efficient ride request

Systems, methods, and devices are disclosed for mapping historical information about behaviors of objects (vehicles, bicycles, pedestrians, etc.) at a location. Based on the mapped historical information, a prediction is determined about a behavior of an object proximate to an autonomous vehicle at the location, where the prediction is based on a statistical analysis of the historical information that is applied to the object. One or more behaviors of the AV are affected based on the prediction.

Map prior layer

The subject disclosure relates to ways to authenticate a rider/user of an autonomous vehicle (AV) using biometric data, such as facial recognition. A process of the disclosed technology can facilitate the automatic unlocking of an AV by performing steps that include: receiving a dispatch request associated with a user identifier (ID), receiving a recognition model that corresponds with the user ID, and receiving an image stream including images of pedestrian faces. In some aspects, the process can further include steps for: providing the images to the recognition model, and determining if a user represented in the images corresponds with the user ID. Systems and machine-readable media are also provided.

Unlocking vehicle doors with facial recognition

Autonomous vehicle fleet management system

The present disclosure provides a method comprising, subsequent to arrival of a vehicle at a charging station, establishing communications between a vehicle side autonomous charging system associated with the vehicle and a charging station side autonomous charging system associated with the charging station; receiving by the charging station side autonomous charging system at least one signal from the vehicle side autonomous charging system, wherein the at least one signal is indicative of a location of a charging port of the vehicle; and using the received at least one signal to guide a robotic extension arm of the charging station to a location proximate the vehicle charging port.

System for automated charging of autonomous vehicles

Growing community of inventors

San Francisco, CA, United States of America

Divya Thakur