Argo Ai Gmbh

Ford Global Technolgoies, LLC

Other

Volkswagen Group of America Investments, LLC

Constantin Savtchenko

Andrew Thomas Hartnett

G Peter K Carr

Greydon Foil

Randall Schur

Neal Andrew Seegmiller

Christopher Cunningham

Jagjeet Singh

Lorenzo Nardi

Pietro Blandizzi

Brett Browning

Mark Ollis

Thomas M Petroff

Gregory Boyd Nichols

George Peter Kenneth Carr

Friederike Schneemann

Michael Pacilio

Matthew Lee Gilson

Alexander Metz

William Tyler Krampe

Shawn Cook

Bangjie Liu

Andreas Eberlein

Elena Corina Grigore

Systems and methods for planning a trajectory for a vehicle are disclosed. The methods include generating first predicted states of an object in an environment of the vehicle at one or more first time steps during a first prediction horizon using a machine learning model and sensor data about the environment. The first predicted states are used as an input to a physical model to generate second predicted states of the object at one or more second time steps during a second prediction horizon where the one or more second time steps are after the one or more first time steps. A trajectory for the vehicle is generated using the first predicted states or the second predicted states of the object.

Methods and systems for long-term trajectory prediction by extending a prediction horizon

Systems and methods for assigning a lane to an object in an environment of an autonomous vehicle are disclosed. The methods include assigning an instantaneous probability to each of a plurality of lanes in the environment based on a current state of the object, generating a transition matrix for each of the plurality of lanes, and identifying the lane in which the object is moving at the current time t based on the instantaneous probability and the transition matrix. The instantaneous probability is a measure of likelihood that the object is in that lane at a current time. The transition matrix encodes one or more probabilities that the object transitioned either into that lane or out of that lane at the current time.

Methods and systems for tracking a mover's lane over time

This document discloses system, method, and computer program product embodiments for operating a vehicle, comprising: using kinematic models to generate forecasted trajectories of an actor (the kinematic models being respectively associated with different actor types that are assigned to an actor detected in an environment of the vehicle); selecting a first kinematic model based on the forecasted trajectories and a kinematic state of the actor; using the first kinematic model to predict a first path for the actor; selecting a second kinematic model responsive to movement of the actor no longer being consistent with typical movement of an object of one of the different actor types that is associated with the first kinematic model; using the second kinematic model to predict a second path for the actor; and controlling operations of the vehicle based on the first and second paths.

Method and system for determining a mover model for motion forecasting in autonomous vehicle control

Systems and methods for operating a robot. The methods comprise: performing, by a processor, operations to detect an object that is moving; identifying, by the processor, detected behavior of the object that constitutes an unrecognized behavior; predicting, by the processor, future movement of the object based on a circle having a radius that is function of a velocity of the object; and controlling operations of the robot based on the predicting.

Methods and systems for autonomous vehicle inference of routes for actors exhibiting unrecognized behavior

This document discloses system, method, and computer program product embodiments for operating a robot. For example, the method includes: detecting an object in proximity to the robot; generating a path of travel for the object that is defined by a plurality of first data points representing different object locations in an area; generating cost curves respectively associated with the plurality of first data points; generating a polyline comprising a plurality of second data points associated with displacements of the cost curves from a particular location in the area; defining a predicted path of travel for the object based on the polyline; and using the predicted path of travel for the object to facilitate at least one autonomous operation of the robot.

Systems and methods for vehicle motion planning

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 predicting actions of an actor before entering a conflicted area are disclosed. The methods may include detecting the presence of an actor in an environment of an autonomous vehicle while the autonomous vehicle and the actor are approaching the conflicted area, determining whether the autonomous vehicle has precedence over the actor for traversing the conflicted area, assigning a kinematic target to the moving object that requires the moving object to come to a stop at an yield point before entering the conflicted area if the autonomous vehicle has precedence over the actor, determining whether a plurality of forecasted trajectories for the actor need to be generated, and controlling movement of the autonomous vehicle to traverse the conflicted area accordingly.

Methods and systems for predicting actions of an object by an autonomous vehicle to determine feasible paths through a conflicted area

Methods by which an autonomous vehicle may predict actions of other actors are disclosed. A vehicle will assign either a high priority rating or a low priority rating to each actor that it detects. The vehicle will then generate a forecast for each of the detected actors. Some of not all high priority actors will receive a high resolution forecast. Low priority actors, and optionally also some of the high priority actors, will receive a low resolution forecast. The system will the forecasts to predict actions for the actors. The autonomous vehicle will then use the predicted actions to determine its trajectory.

Method and system for predicting behavior of actors in an environment of an autonomous vehicle

Systems/methods for operating an autonomous vehicle. The methods comprise, by a computing device: using sensor data to track an object that was detected in proximity to the autonomous vehicle; classifying the object into at least one dynamic state class of a plurality of dynamic state classes; transforming the at least one dynamic state class into at least one goal class of a plurality of goal classes; transforming the at least one goal class into at least one proposed future intention class of a plurality of proposed future intention classes; determining at least one predicted future intention of the object based on the proposed future intention class; and/or causing the autonomous vehicle to perform at least one autonomous driving operation based on the at least one predicted future intention determined for the object.

Systems and methods for determining future intentions of objects

A system receives a road network map that corresponds to a road network that is in an environment of an autonomous vehicle. For each of the one or more lane segments, the system identifies one or more conflicting lane segments from the plurality of lane segments, each of which conflicts with the lane segment, and adds conflict data pertaining to a conflict between the lane segment and the one or more conflicting lane segments to a set of conflict data. The system analyzes the conflict data to identify a conflict cluster that is representative of an intersection. The system groups predecessor lane segments and the successor lane segments as inlets or outlets of the intersection, generates an outer geometric boundary of the intersection, generates an inner geometric boundary of the intersection, creates a data representation of the intersection and adds the data representation to the road network map.

Methods and system for constructing data representation for use in assisting autonomous vehicles navigate intersections

Methods of forecasting intentions of actors that an autonomous vehicle (AV) encounters in are disclosed. The AV uses the intentions to improve its ability to predict trajectories for the actors, and accordingly making decisions about its own trajectories to avoid conflict with the actors. To do this, for any given actor the AV determines a class of the actor and detects an action that the actor is taking. The system uses the class and action to identify candidate intentions of the actor and evaluating a likelihood of each candidate intention. The system repeats this process over multiple cycles to determine overall probabilities for each of the candidate intentions. The AV's motion planning system can use the probabilities to determine likely trajectories of the actor, and accordingly influence the trajectory that the AV will itself follow in the environment.

Assessing present intentions of an actor perceived by an autonomous vehicle

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

A system includes one or more electronic devices of an autonomous vehicle and a computer-readable storage medium having one or more programming instructions. The system identifies an actor in an environment of the autonomous vehicle that is exhibiting unrecognized behavior or that has exhibited unrecognized behavior within a certain time period, and generates a circle associated with the actor, wherein the circle has a radius that is a function of a velocity of the actor. The system identifies one or more target points associated with the actor, where each target point represents a point along a possible route of the actor, and each target point is located along a circumference of the circle. The system assigns a score to each target point, selects the target point associated with the lowest score, and generates a reference path from the actor to the selected target point.

Systems and methods for monitoring the lane of an object in an environment of an autonomous vehicle are disclosed. The methods include receiving sensor data corresponding to the object, and assigning an instantaneous probability to each of a plurality of lanes based on the sensor data as a measure of likelihood that the object is in that lane at a current time. The methods also include generating a transition matrix for each of the plurality of lanes that encode one or more probabilities that the object transitioned to that lane from another lane in the environment or from that lane to another lane in the environment at the current time. The methods then include determining an assigned probability associated with each of the plurality of lanes based on the instantaneous probability and the transition matrix as a measure of likelihood of the object occupying that lane at the current time.

Systems/methods for operating an autonomous vehicle. The methods comprise: detecting an object in proximity to the autonomous vehicle; determining a path of travel for the object that comprises a number of data points that is equal to a given number of vehicle locations selected based on a geometry of a lane in which the object; generating cost curves respectively associated with the data points, each cost curve representing a displacement cost to be at a particular location along a given cross line that (i) passes through a respective data point of said data points and (ii) extends perpendicular to and between boundary lines of the lane; determining a polyline representing displacements of the cost curves from a center of the lane; defining a predicted path of travel for the object based on the polyline; and using the predicted path of travel for the object to facilitate autonomous driving operation(s).

Growing community of inventors

Sewickley, PA, United States of America

Constantin Savtchenko