Gm Global Technolgoy Operations, Inc.

Peter Ming Gao

Siddhartho Bhattacharya

Eric Lujan

Elliot Branson

Wei Mou

Stuart Glaser

Shiva Ghose

Jeremy Allan

Gautier Minster

Matthias Wisniowski

Thomas E Scott

Zhichang Yan

Zhizhong Yan

Yiqi Gao

Gautier Etienne Guillaume Minster

Jonathan Uesato

An autonomous vehicle is described herein. The autonomous vehicle is configured to determine that a person is proximate the autonomous vehicle at a location that is external to the autonomous vehicle. The autonomous vehicle is further configured to determine that the person is attempting to hail the autonomous vehicle through use of a gesture. The autonomous vehicle identifies the gesture being performed by the person, and responsive to identifying the gesture, identifies a travel intent that the person is imparting to the autonomous vehicle by way of the gesture. The autonomous vehicle then operates based upon the travel intent.

Autonomous vehicle that is configured to identify a travel characteristic based upon a gesture

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

An autonomous vehicle is described herein. The autonomous vehicle includes several sensor systems that asynchronously generate sensor system outputs. A batch generator system, executed by a processor, identifies batches of sensor system outputs to provide to an object classifier system, wherein the batches of sensor system outputs are identified based upon timing estimates, wherein the timing estimates include first timing estimates and second timing estimates. The first timing estimates include estimates of amounts of time needed by the object classifier system to complete processing of batches of different sizes. The second timing estimates includes estimates of when sensor system outputs are expected to be received from the several sensor systems.

Autonomous vehicle that includes sensor output batching system

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

Systems and method are provided for controlling an autonomous vehicle. A camera configured to capture an image, and a controller can execute an autonomous driving system (ADS) that classify that image. The ADS comprises a classification system for classifying objects in an environment within a driveable area of the autonomous vehicle. The classification system comprises a processor configured to execute a region proposal generator module and an image classification module. The region proposal generator module generates a set of bounding box region proposals for the image. The bounding box region proposals are selected areas of the image that include objects to be classified. The image classification module classifies, via a neural network executed by the processor, the objects from the image that are within one of the bounding box region proposals.

Systems and methods for visual classification with region proposals

Methods and systems are provided for tracking an object. The system includes a data receiving module configured to receive three dimensional imaging data and two dimensional imaging data. A three dimensional object identification module is configured to demarcate a three dimensional object and to output three-dimensional object data. An adjustment module is configured to adjust the three dimensional object data based on the two dimensional imaging data and to output adjusted three dimensional object data. A tracking module is configured to track at least one object using the adjusted three dimensional object data.

Methods and systems for object tracking using bounding boxes

Systems and method are provided for controlling a vehicle. In one embodiment, an obstacle management method includes receiving, via sensing devices, sensor data relating to an environment associated with a vehicle, and determining, with the sensor data, the presence of an obstacle that at least partially obstructs an intended path of the vehicle in a first lane adjacent to a second lane and at least partially occludes a view of the second lane by a first sensing device. The method further includes positioning the vehicle with respect to the obstacle to improve the view of the second lane by the first sensing device without significantly obstructing the second lane, determining a second path that circumnavigates the obstacle and rejoins the intended path, and monitoring the opposing lane via the first sensing device to determine when the second path is clear.

Systems and methods for maneuvering around obstacles in autonomous vehicles

Methods and systems are provided for tracking an object. The system includes a data receiving module receiving two dimensional imaging data including an object and height map data correlating ground height and location. A two dimensions to three dimensions transformation module determines a location of the object in three dimensional space based on the two dimensional imaging data and the height map data. A tracking module tracks the object using the location of the object.

Object tracking

A system and method for locating and identifying a potential passenger by an autonomous vehicle includes: receiving a pickup request for the potential passenger, where the pickup request includes a geographic location for locating and picking up the potential passenger by the autonomous vehicle; locating the potential passenger based on the geographic location and using data from one or more sensors of the autonomous vehicle; and in response to locating the potential passenger, controlling the autonomous vehicle to a position to enable pickup of the potential passenger.

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San Francisco, CA, United States of America

Peter Ming Gao