Argo Ai Gmbh

Carnegie Mellon University

Applied Perception, Inc.

Ford Global Technolgoies, LLC

Other

Mark Ollis

Anthony Joseph Stentz

Brett Browning

Thomas M Petroff

Albert Costa

Todd Jochem

Neal Andrew Seegmiller

Christopher Cunningham

Parag Batavia

Herman Herman

William L Whittaker

Christopher Chandler Fromme

John E Bares

Alonzo James Kelly

Kerien W Fitzpatrick

Frank Higgins

Bryan G Campbell

David K Herdle

G Peter K Carr

Andrew Thomas Hartnett

Constantin Savtchenko

Michael Happold

Arek V Sredzki

Basel Alghanem

Patrick Stirling Barone

George Peter Kenneth Carr

Thomas E Pilarski

Russell Schloss

Robert Craig Coulter

Benjamin D Ballard

Timothy Ennis Hegadorn

Henning M Pangels

Christian Höeppner

Richard McCargo Moore, Jr

Steven John Scheding

Jorgen Pederson

Regis Hoffman

Systems and methods are described for measuring velocity of an object detected by a light detection and ranging (lidar) system. According to some aspects a method may include receiving a lidar dataset generated by the lidar system, transforming the lidar dataset into a first layer dataset and a second layer dataset, and converting the first layer dataset into a first image and the second layer dataset into a second image. The method may also include performing a feature detection operation that identifies at least one feature in the first image and the same feature in the second image, locating a first location of the feature in the first image and a second location of the feature in the second image, and generating a velocity estimate of the feature based on a difference between the first location and the second location and a difference between the different time intervals.

Systems and method for lidar grid velocity estimation

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

Provided are autonomous vehicles (AV), computer program products, and methods for maneuvering an AV in a roadway, including receiving forecast information associated with predicted trajectories of one or more actors in a roadway, determining a relevant trajectory of an actor based on correlating a forecast for predicted trajectories of the actor with the trajectory of the AV, regenerate a distance table for the relevant trajectory previously generated for processing constraints, generate a plurality of margins for the AV to evaluate, the margins based on a plurality of margin types for providing information about risks and effects on passenger comfort associated with a future proximity of the AV to the actor, classifying an interaction between the AV and the actor based on a plurality of margins, and generating continuous scores for each candidate trajectory that is also within the margin of the actor generated for the relevant trajectory.

System, method, and computer program product for trajectory scoring during an autonomous driving operation implemented with constraint independent margins to actors in the roadway

Systems and methods for controlling navigation of an autonomous vehicle for making an unprotected turn while traversing an intersection. The methods may include identifying a loiter pose of an autonomous vehicle for stopping at a point in an intersection before initiating an unprotected turn, initiating navigation of the autonomous vehicle to the loiter pose when a traffic signal is at a first state, determining whether the traffic signal has changed to a second state during or after navigation of the autonomous vehicle to the loiter pose, and in response to determining that the traffic signal has changed to the second state, generating a first trajectory for navigating the autonomous vehicle to execute the unprotected turn if the expected time for moving the autonomous vehicle from a current position to a position when the autonomous vehicle has fully exited an opposing conflict lane is less than a threshold time.

Methods and systems for asserting right of way for traversing an intersection

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

Systems and methods are provided for navigating a vehicle to veer around a lane obstruction safely into a neighboring lane. The system may plan a trajectory around the obstructed lane. Over a temporal horizon, the system determines temporal margins by measuring an amount of time between a predicted state of a moving actor in the neighboring lane and a predicted state of the vehicle. The system identifies a minimum temporal margin of the temporal margins and determines whether the minimum temporal margin is equal to or larger than a required temporal buffer. If the minimum temporal margin is equal to or larger than the required temporal buffer, the system generates a motion control signal to cause the vehicle to follow the trajectory to veer around the obstruction into the neighboring lane. Otherwise, the system generates a motion control signal to cause the vehicle to reduce speed or stop.

Methods and systems for safe out-of-lane driving

A method of determining a trajectory for an autonomous vehicle is disclosed. An ego-vehicle may detect a moving actor in an environment. To choose between candidate trajectories for the ego-vehicle, the system will consider the cost of each candidate trajectory to the moving actor. The system will use the candidate trajectory costs for the candidate trajectories to select one of the candidate trajectories via which to move the ego-vehicle. An autonomous vehicle system of the ego-vehicle may then move the ego-vehicle in the environment along the selected trajectory.

Method and system for using a reaction of other road users to ego-vehicle actions in autonomous driving

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 system and method of identifying a position of a crop row in a field, where an image of two or more crop rows is transmitted to a vision data processor. The vision data processor defines a candidate scan line profile for a corresponding heading and pitch associated with a directional movement of a vehicle, for example, traversing the two or more crop rows. The candidate scan line profile comprises an array of vector quantities, where each vector quantity comprises an intensity value and a corresponding position datum. A preferential scan line profile in a search space about the candidate scan line profile is determined, and the candidate scan line profile is identified as a preferential scan line profile for estimating a position (e.g., peak variation) of one or more crop rows if a variation in the intensity level of the candidate scan line profile exceeds a threshold variation value. In addition, a template scan line profile may be utilized, where a candidate scan line profile is identified to be a preferential scan line profile if it is consistent with the template scan line profile.

Vision guidance system and method for identifying the position of crop rows in a field

A system and method of identifying a position of a crop row in a field, where an image of two or more crop rows is transmitted to a vision data processor. A preferential scan line profile in a search space about a candidate scan line profile is determined, and the candidate scan line profile is identified as a preferential scan line profile for estimating a position (e.g., peak variation) of one or more crop rows if a variation in the intensity level of the candidate scan line profile exceeds a threshold variation value. Alternatively, a position datum associated with a highest intensity value within the array of vector quantities can be selected as being indicative of a candidate position of a crop row. The candidate position is then identified as a preliminary row position if a variation in intensity level of the candidate scan line profile exceeds a threshold variation value.

A system and method of identifying a position of a crop row in a field, where an image of two or more crop rows is transmitted to a vision data processor. The vision data processor defines a candidate scan line profile for a corresponding heading and pitch of associated with a directional movement of a vehicle, for example, traversing the two or more crop rows. The candidate scan line profile comprises an array of vector quantities, where each vector quantity comprises an intensity value and a corresponding position datum. A preferential scan line profile in a search space about the candidate scan line profile is determined, and the candidate scan line profile is identified as a preferential scan line profile for estimating a position (e.g., peak variation) of one or more crop rows if a variation in the intensity level of the candidate scan line profile exceeds a threshold variation value.

A system and method of constructing a density map is disclosed. The density map is a cellular grid representing local terrain, wherein each cell contains a density vector representing the density of portion of the terrain corresponding to the cell. The density map can be used to classify and characterize the surrounding terrain, which is useful in making a determination of the traversability of the terrain to mobile vehicles.

System and method for the creation of a terrain density model

A computer-assisted method for determining a position and orientation a sensor relative to a scene. The sensor has a plurality of degrees of freedom in position and orientation relative to the scene. The method includes sensing an image of the scene, the sensed image having a plurality of regions such that a sum of degrees of independent constraint of the plurality of regions equals or exceeds the degrees of freedom in position and orientation of the sensor relative to the scene, comparing the plurality of regions of the sensed image to a plurality of regions of a first image of the scene stored in a map, the first stored image representative of a position and orientation of the sensor relative to the scene, and determining sensor position and orientation based on the comparing.

Infrastructure independent position determining system

An agricultural harvesting machine (harvester) is automatically controlled and steered so as to completely harvest all crop in a field. A Global Positioning System (GPS) and an Inertial Navigation System provide data regarding the position and orientation of the harvester in a field. A Field Coverage Planner constructs a field coverage plan which defines a path for the harvester to follow in cutting crop from a field. Video images of the field in front of the harvester are derived alternately from two video cameras mounted on opposite sides of the harvester. The video images are processed in a Video Processing Computer to detect the crop line between cut and uncut crop and generate steering signals for steering the harvester along the crop line. Video images are also processed to detect the end of a row at the end of a field and supply a measure of the distance to the end of the row. When the end of a row is reached, the harvester executes a 180&deg; spin turn and traverses the field in the opposite direction.

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Pittsburgh, PA, United States of America

Mark Ollis