Argo Ai Gmbh

Uatc, LLC

Ford Global Technolgoies, LLC

Uber Technologies, Inc.

Volkswagen Group of America Investments, LLC

Albert Costa

Thomas M Petroff

Michael Lee Phillips

Brett Browning

Neal Andrew Seegmiller

Mark Ollis

Michael Bode

Christopher Cunningham

Ramadev Burigsay Hukkeri

Thomas Carl Ackenhausen

Patrick Michael Carmody

G Peter K Carr

Sameer Bardapurkar

Alexander Allen Nolley

Methods and systems for maneuvering an autonomous vehicle are disclosed. The methods include generating a multi-corridor representation corresponding to a local region around the autonomous vehicle while travelling on a route, and using the multi-corridor representation and perception data corresponding to the local region to generate a trajectory for the autonomous vehicle to traverse the local region. The multi-corridor representation includes a plurality of adjacent corridors that each include one or more lane segments of a road network. A location of executing a lane change along the route is determined dynamically during a trajectory generation phase based on the perception data.

Methods and systems for lane changes using a multi-corridor representation of local route regions

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 controlling the motion of an autonomous are provided. In one example embodiment, a computer implemented method includes obtaining, by one or more computing devices on-board an autonomous vehicle, data associated with one or more objects that are proximate to the autonomous vehicle. The data includes a predicted path of each respective object. The method includes identifying at least one object as an object of interest based at least in part on the data associated with the object of interest. The method includes generating cost data associated with the object of interest. The method includes determining a motion plan for the autonomous vehicle based at least in part on the cost data associated with the object of interest. The method includes providing data indicative of the motion plan to one or more vehicle control systems to implement the motion plan for the autonomous vehicle.

Adaptive vehicle motion control system

Systems and methods of maneuvering an autonomous vehicle in a local region using topological planning, while traversing a route to a destination location, are disclosed. The system includes an autonomous vehicle including one or more sensors and a processor. The processor is configured to determine the local region on the route and receive real-time information corresponding to the local region. The processor performs topological planning to identify on or more topologically distinct classes of trajectories, compute a constraint set for each of the one or more topologically distinct classes of trajectories, optimize a trajectory to generate a candidate trajectory for each constraint set, and select a trajectory for the autonomous vehicle to traverse the local region from amongst the one or more candidate trajectories. Each of the one or more topologically distinct classes is associated with a plurality of trajectories that take the same combination of discrete actions with respect to objects in the local region.

Methods and systems for topological planning in autonomous driving

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 system of creating a simulation scenario definition to simulate behavior of an autonomous vehicle includes a computing device and a computer-readable storage medium having one or more programming instructions. The system identifies an event on which a simulation scenario definition is to be based, identifies one or more log files associated with the event, parses the one or more log files in a time-sequential order and populates the simulation scenario definition with information from the identified log files until an event trigger is detected, identifies an actor from one or more of the log files, infer a shape of the actor, generates one or more simulated tracks that includes the inferred shape for the actor, and adds the simulated tracks to the simulation scenario definition.

Systems and methods for generating simulation scenario definitions for an autonomous vehicle system

A system of creating a simulation to simulate behavior of an autonomous vehicle includes a simulation system having an electronic device and a computer-readable storage medium having one or more programming instructions. When executed, the one or more programming instructions cause the electronic device to identify an event that is to be analyzed, receive from an autonomous vehicle system a first data stream that includes event information from one or more vehicle event log files that corresponds to the event, receive from a vehicle dynamics model a second data stream that includes synthetic event information that corresponds to the event, until a switch point is detected operate in a pure log execution stage, upon detection of the switch point operate in a play-forward execution stage, and cause the new simulation to be executed.

Play-forward planning and control system for an autonomous vehicle

A method and a system for maneuvering an autonomous vehicle is disclosed. The system includes an autonomous vehicle including one or more sensors and a processor. The processor is configured to generate a nominal route from a start position toward a destination with reference to a road network map. The nominal route includes a plurality of consecutive lane segments from the start position to the destination. The processor is further configured to use the road network map to identify at least one candidate lane segment corresponding to one or more of the plurality of consecutive lane segments to generate an expanded route representation, generate a multi-corridor representation of a local region around the autonomous vehicle while travelling on the nominal path, and generate a trajectory for the autonomous vehicle to traverse the local region using the multi-corridor representation and perception data corresponding to the autonomous vehicle.

An autonomous vehicle navigates an intersection in which occlusions block the vehicle's ability to detect moving objects. The vehicle handles this by generating a phantom obstacle behind the occlusion. The vehicle will predict the speed of the phantom obstacle and use the predicted speed to assess whether the phantom obstacle may collide with the vehicle. If a collision is a risk, the vehicle will slow or stop until it confirms that either (a) the phantom obstacle is not a real obstacle or (b) the vehicle can proceed at a speed that avoids the collision. To determine which occlusions shield real objects, the system may use a rasterized visibility grid of the area to identify occlusions that may accommodate the object.

Method of handling occlusions at intersections in operation of autonomous vehicle

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.

Growing community of inventors

Pittsburgh, PA, United States of America

Albert Costa