Uatc, LLC

Argo Ai Gmbh

Uber Technologies, Inc.

Ford Global Technolgoies, LLC

Volkswagen Group of America Investments, LLC

Brett Browning

Thomas M Petroff

Ethan Eade

Bryan John Nagy

Peter Hansen

Mark Ollis

Albert Costa

Robert Zlot

David Prasser

Adam Milstein

William Payne Ross

Anthony Joseph Stentz

David LaRose

Andrew Thomas Hartnett

Brett Bavar

Narek Melik-Barkhudarov

Peter W Rander

Adam Cole Panzica

Michel Laverne

Xxx Xinjilefu

Ilan Biala

Adam Henry Polk Milstein

George Peter Kenneth Carr

Michael Pacilio

Gordon Peter Bailey

James Andrew Bagnell

Ramadev Burigsay Hukkeri

Guy Hotson

Neal Andrew Seegmiller

Constantin Savtchenko

Christopher Cunningham

Richard L Kwant

Shubhashree Venkatesh

James Hays

Deva K Ramanan

Scott Plant

Shenglong Gao

Nikolai Popov

Sean Foley

Shawn Cook

Israel Marc Kositsky

David Larose

Peter Rander

Disclosed herein are system, method, and computer program product aspects for testing autonomous vehicle intent using protolanes. For example, the method includes selecting a first lane segment of a roadway within a geonet, wherein the geonet comprises a plurality of lane segments. It is determined that the first lane segment corresponds to a protolane of a set of protolanes, wherein the protolane is associated with one or more additional lane segments of the plurality of lane segments. The protolane is associated with the first lane segment based on the determination that the first lane segment corresponds to the protolane.

Protolanes for testing autonomous vehicle intent

Devices, systems, and methods are provided for enhanced rider pairing of an autonomous vehicle (AV). A system may pair a first user profile of a first user located at a first location with a first autonomous vehicle (AV) to complete a trip to a destination selected by the first user. The system may detect a second AV at the first location, wherein the second AV is associated with a second user profile. The system may connect the second AV with the first user using a connection mechanism. The system may select a profile status of the first user profile based on the connection to the second AV. The system may pair the first user profile with the second AV based on the profile status.

Enhanced rider pairing for autonomous vehicles

Disclosed herein are system, method, and computer program product aspects for validating protolanes. For example, the method includes determining a protolane level flowchart from one or more flowcharts corresponding to one or more gates of a protolane selected from a set of protolanes of a geonet, wherein the one or more flowcharts correspond to conditions that can be encountered by an actor approaching the corresponding one or more gates, and wherein the geonet comprises a plurality of lane segments associated with the set of protolanes. A graph through the protolane level flowchart is generated that corresponds to actions of an actor. Reasoning of the actor is validated by testing the actions of the actor against the graph through the protolane level flowchart.

Validating protolanes with actor behavior flowcharts

Systems and methods for operating a vehicle. The methods comprise: generating, by a computing device, a vehicle trajectory for the vehicle that is in motion; detecting an object within a given distance from the vehicle; generating, by the computing device, at least one possible object trajectory for the object which was detected; performing, by the computing device, a collision check to determine that there remains time to react safely to worst-case behavior by the object (the collision check being based on the vehicle trajectory and at least one possible object trajectory); and performing operations, by the computing device, to selectively cause the vehicle to perform an emergency maneuver based on results of the collision check.

Systems and methods for trajectory based

Systems and methods for operating a vehicle are disclosed. The methods comprise: generating, by a computing device, a vehicle trajectory for the vehicle while the vehicle is in motion; detecting an object within a given distance from the vehicle; generating at least one possible object trajectory for the object which was detected; performing a collision check to determine whether a collision between the vehicle and the object can be avoided based on the vehicle trajectory and the at least one possible object trajectory; performing a plausibility check to determine whether the collision is plausible based on content of a map, when a determination is made in the collision check that a collision between the vehicle and the object cannot be avoided; and performing operations to selectively cause the vehicle to perform an emergency maneuver based on results of the plausibility check.

Systems and methods for imminent collision avoidance

A method is disclosed for evaluating a classifier used to determine a traffic light signal state in images. The method includes, by a computer vision system of a vehicle, receiving at least one image of a traffic signal device of an imminent intersection. The traffic signal device includes a traffic signal face including one or more traffic signal elements. The method includes classifying, by a traffic light classifier (TLC), a classification state of the traffic signal face using labeled images correlated to the received at least one image. The classification state controls an operation of the vehicle at the intersection. The method includes evaluating a performance of the classifying of the classification state generated by the TLC. The evaluation is a label-free performance evaluation based on unlabeled images. The method includes training the TLC based on the evaluated performance.

Label-free performance evaluator for traffic light classifier system

A method for receiving autonomous vehicle (AV) map data associated with an AV map of a geographic location and coverage map data associated with a coverage map of the geographic location. The AV map data is associated with an AV lane of a roadway in the geographic location, and the coverage map data is associated with a coverage lane of the roadway in the geographic location. The method includes generating a hybrid map of the geographic location based on the AV map data and the coverage map data and providing hybrid map data associated with the hybrid map for routing of an AV. The hybrid map includes the AV lane linked with the coverage lane of the roadway.

Map creation from hybrid data

A satellite signal calibration system can receive sensor data from one or more sensors provided on a vehicle and detect satellite signal from one or more satellites of a satellite positioning system. Using the sensor data, the system can perform a localization operation to determine a current location of the vehicle. The system may then determine timing offsets of the satellite signals from each of the one or more satellites based at least in part on the current location of the vehicle.

Satellite signal calibration system

A system provides navigational control information to a fleet of vehicles and includes a network of nodes within a geographical area. Each node is located at a different intersection in the geographical area. Each node includes a node vision range and a processor which generates augmented perception data (APD) for each moving object of interest monitored in the node vision range. The system includes a remote server system that includes a database of the APD and receives a query from a vehicle of the fleet for the APD associated with an imminent path of the vehicle. The server system, in response to the query, searches the database for APD associated with the imminent path, and communicates, over a communication network, the resultant APD associated with the imminent path to the vehicle. The APD controls navigation of the vehicle through one or more imminent intersections along the imminent path.

System for augmenting autonomous vehicle perception using smart nodes

A node is provided for capturing information about moving objects at an intersection. The node includes a plurality of first cameras that are positioned to capture first digital images of an intersection from different fields of view and a second camera positioned to capture second digital images in a field of view that is wider than that of each first camera. The node includes a processor that detects in the first and second digital images a set of objects of interest of the intersection, determines motion of each detected object of interest in the set from consecutive images of the first digital images or the second digital images. The node generates, for each object of interest of the set, augmented perception data that includes location data in the global coordinate system and the determined motion of each object of interest in the set.

Method and system for vehicle navigation using information from smart node

Systems and methods for operating a vehicle. The methods comprise: generating, by a computing device, a vehicle trajectory for the vehicle that is in motion; detecting an object within a given distance from the vehicle; generating, by the computing device, at least one possible object trajectory for the object which was detected; using, by the computing device, the vehicle trajectory and the at least one possible object trajectory to determine whether there is an undesirable level of risk that a collision will occur between the vehicle and the object; modifying, by the computing device, the vehicle trajectory when a determination is made that there is an undesirable level of risk that the collision will occur; and automatically causing the vehicle to move according to the modified vehicle trajectory.

Systems and methods for trajectory based safekeeping of vehicles

A control system of a self-driving vehicle (SDV) can process sensor data from the sensor system to autonomously operate acceleration, braking, and steering systems of the SDV throughout a given region. The control system can receive a transport directive from a transport facilitation system to service a pick-up request from a requesting user, the transport directive indicating an inputted pick-up location by the requesting user. The control system can then autonomously operate the acceleration, braking, and steering systems along a current route to a pick-up area encompassing the inputted pick-up location. The control system can further determine a corresponding set of pick-up location options for the pick-up area, and as the SDV approaches the pick-up area, perform a hierarchical operation to identify, via the sensor data, an optimal pick-up location to rendezvous with the requesting user.

Facilitating rider pick-up for a self-driving vehicle

A system to use submaps to control operation of a vehicle is disclosed. A storage system may be provided with a vehicle to store a collection of submaps that represent a geographic area where the vehicle may be driven. A programmatic interface may be provided to receive submaps and submap updates independently of other submaps.

Autonomous vehicle control using submaps

Growing community of inventors

Pittsburgh, PA, United States of America

Brett Browning