Gm Global Technolgoy Operations, Inc.

Gm Cruise Holdings LLC

Eric Lujan

Shiva Ghose

Curt Harrington

Ryan Holben

Ted Nitz

Daniel Chen

Christopher Daily-Diamond

Mason Swofford

Christophe Philippona

Benjamin Greer

Francesco Capodieci

Elliot Branson

Benjamin Earle Weinstein-Raun

Stephanie Olivia Engle

Kyle Vogt

Peter Ming Gao

Drew Gross

Jeremy Allan

Wei Mou

Zhizhong Yan

Siddhartho Bhattacharya

Zhichang Yan

Tor Aksel Notland Heirung

Adrian Kit Malaran

William Anthony Silva

Jonathan Uesato

Eva Fornaeus

An autonomous vehicle (AV) is described herein. The AV is configured to identify an occluded region where a portion of a field of view of a sensor is occluded by an object. The AV is further configured to hypothesize that an object exists in the occluded region and is moving in the occluded region. The AV is still further configured to perform a driving maneuver based upon the hypothesized object existing in the occluded region.

Autonomous vehicle maneuvering based upon risk associated with occluded regions

Approaches for top speed dependent operational parameter configuration are disclosed. An operational parameter to be used by an autonomous vehicle is received. Operational modes and corresponding operational regions are determined based on the received operational parameter. A first set of autonomous vehicle parameters are determined and set based on the received operational parameter. A second set of autonomous vehicle parameters are determined and set based on the first set of autonomous vehicle parameters.

Maximum speed dependent parameter management for autonomous vehicles

Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators to distinguish the autonomous vehicle from other autonomous vehicles in a fleet. The autonomous vehicle includes a vehicle propulsion system, a braking system, a notification system, and a computing system. The notification system outputs an indicator that is perceivable external to the autonomous vehicle. The computing system receives data specifying an identity of a passenger to be picked up by the autonomous vehicle. Moreover, the computing system controls at least one of the vehicle propulsion system or the braking system to stop the autonomous vehicle for passenger pickup. Further, the computing system controls the notification system to output the indicator; a characteristic of the indicator outputted by the notification system is controlled based on the identity of the passenger to be picked up and whether the autonomous vehicle is stopped for passenger pickup.

Autonomous vehicle identification

An autonomous vehicle is described herein. The autonomous vehicle comprises a first sensor and a second sensor having limited fields of view, an articulation system, and a computing system. The computing system determines a first region and a second region external to the autonomous vehicle based on a sensor prioritization scheme comprising a ranking of regions surrounding the autonomous vehicle. The computing system then causes the articulation system to orient the first sensor towards the first region and the second region towards the second region. Responsive to receiving a sensor signal from the first sensor indicating that an object has entered a field of view of the first sensor, the computing system determines a third region having a higher ranking than the second region within the sensor prioritization scheme. The computing system then causes the articulation system to orient the second sensor towards the third region.

Controlling articulating sensors of an autonomous vehicle

Various technologies described herein pertain to controlling an autonomous vehicle to provide indicators that signal a driving intent of the autonomous vehicle. The autonomous vehicle includes a plurality of sensor systems that generate a plurality of sensor signals, a notification system, and a computing system. The computing system determines that the autonomous vehicle is to execute a maneuver that will cause the autonomous vehicle to traverse a portion of a driving environment of the autonomous vehicle. The computing system predicts that a person in the driving environment is to traverse the portion of the driving environment based upon the plurality of sensor signals. The computing system then controls the notification system to output a first indicator indicating that the autonomous vehicle plans to yield to the person or a second indicator indicating that the autonomous vehicle plans to execute the maneuver prior to the person traversing the portion of the driving environment.

Autonomous vehicle intent signaling

Systems and method are provided for controlling a vehicle. In various embodiments, a method of path planning for a vehicle includes receiving sensor data relating to an environment associated with the vehicle; defining a region of interest for the vehicle, based on the sensor data; defining a graph comprising a plurality of nodes, each of the plurality of nodes comprising a state of the vehicle and an associated cost, based on a cost function as applied to the state of the vehicle, at one of a plurality of points in time; and performing, via a processor, a search of the graph, based on the associated costs of each node of the graph, to determine a selected path for the vehicle through the region of interest that minimizes a total cost via the graph.

Systems and methods for unprotected maneuver mitigation in autonomous vehicles

Systems and method are provided for controlling a vehicle. In one embodiment, an obstacle management method includes receiving, via one or more sensing devices, sensor data relating to an environment associated with a vehicle, wherein the vehicle is substantially stationary and has an intended path corresponding to entering a traffic flow of a first lane. The method includes determining the presence of an obstacle that at least partially occludes a view of the first lane by a first sensing device of the one or more sensing devices, and positioning, with a processor, the vehicle with respect to the obstacle to improve the view of the first lane by the first sensing device without significantly obstructing the first lane. The first lane is then monitored via the first sensing device to determine when the intended path clear.

Systems and methods for entering traffic flow in autonomous vehicles

Growing community of inventors

San Francisco, CA, United States of America

Eric Lujan