Gm Cruise Holdings LLC

Gm Global Technolgoy Operations, Inc.

Shiva Ghose

Eric Lujan

Curt Harrington

Ryan Holben

Ted Nitz

Christopher Daily-Diamond

Daniel Chen

Mason Swofford

Christophe Philippona

Benjamin Greer

Francesco Capodieci

Matthias Wisniowski

Drew Gross

Sohrab Haghighat

Elliot Branson

Kevin Chu

Jeremy Allan

Peter Ming Gao

Zhichang Yan

Zhizhong Yan

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

An autonomous vehicle configured to perform a lane change maneuver is described herein. The autonomous vehicle includes several different types of sensor systems, such as image, lidar, radar, sonar, infrared, and GPS. The autonomous vehicle additionally includes a computing system that executes instructions on a lane change detection system and a control system. The lane change detection system includes a region of interest module and an object trajectory module for determining whether the autonomous vehicle will collide with another object if the autonomous vehicle maneuvers into an adjacent lane. An instruction module of the lane change detection system is further used to facilitate operational control of a mechanical system of the autonomous vehicle, such as an engine or a steering system.

Lane change detection system and method for an autonomous vehicle

The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.

Auto exposure using multiple cameras and map prior information

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. The systems and methods calculate lane plan data including a set of lane plans defining a route from a start location to a destination location, solve a motion planning algorithm to produce solved lane plan data defining a solved lane plan and a trajectory therefor, receive forthcoming distance data representing a forthcoming distance, determine a feasible lane based on the solved lane plan data within the forthcoming distance, remove a lane plan from the lane plan data to produce feasible lane plan data including a feasible lane plan defining a route from the start location to the destination location, and control motion of the vehicle based on the feasible lane plan data.

Feasible lane routing

In one embodiment, a method for selecting a parking location for an autonomous vehicle includes: obtaining data pertaining to a current ride of the autonomous vehicle during operation of the autonomous vehicle; determining, by a processor using the data, when the autonomous vehicle is proximate a destination; and, when the autonomous vehicle is proximate the destination: identifying, by the processor using the data, a plurality of potential parking locations proximate the destination; calculating, by the processor using the data, a respective score for each of the potential parking locations using a plurality of factors; and selecting, by the processor using the data, a selected parking location of the potential parking locations based on the respective score of each of the potential parking locations.

Parking scoring for autonomous vehicles

Growing community of inventors

Berkeley, CA, United States of America

Shiva Ghose