Uatc, LLC

Uber Technologies, Inc.

Aurora Operations, Inc.

Moslem Kazemi

David McAllister Bradley

Michael Lee Phillips

Chenggang Liu

Sameer Bardapurkar

Eric Michael Perko

Anthony Joseph Stentz

Tianyu Gu

Nicholas Fermin Andrey Sterner

Kalin Vasilev Gochev

Daoyuan Jia

Samuel Philip Marden

Jacob Panikulam

Vijay Subramanian

Charles R Hogg, Iii

Utku Eren

Andy Lee

Systems, methods, tangible non-transitory computer-readable media, and devices for operating an autonomous vehicle are provided. For example, the disclosed technology can include receiving state data that includes information associated with states of an autonomous vehicle and an environment external to the autonomous vehicle. Responsive to the state data satisfying vehicle stoppage criteria, vehicle stoppage conditions can be determined to have occurred. A severity level of the vehicle stoppage conditions can be selected from a plurality of available severity levels respectively associated with a plurality of different sets of constraints. A motion plan can be generated based on the state data. The motion plan can include information associated with locations for the autonomous vehicle to traverse at time intervals corresponding to the locations. Further, the locations can include a current location of the autonomous vehicle and a destination location at which the autonomous vehicle stops traveling.

Autonomous vehicle safe stop

The present disclosure is directed to validating motion plans for autonomous vehicles. In particular, the methods, devices, and systems of the present disclosure can: receive data indicating a motion plan of an autonomous vehicle through an environment of the autonomous vehicle; receive data indicating one or more inputs utilized in generating the motion plan; and determine, based at least in part on the data indicating the motion plan and the data indicating the input(s), whether execution of the motion plan by the autonomous vehicle would violate one or more predetermined constraints applicable to motion plans for the autonomous vehicle.

Motion-plan validator for autonomous vehicle

Systems and methods for autonomous vehicle motion planning are provided. Sensor data describing an environment of an autonomous vehicle and an initial travel path for the autonomous vehicle through the environment can be obtained. A number of trajectories for the autonomous vehicle are generated based on the sensor data and the initial travel path. The trajectories can be evaluated by generating a number of costs for each trajectory. The costs can include a safety cost and a total cost. Each cost is generated by a cost function created in accordance with a number of relational propositions defining desired relationships between the number of costs. A subset of trajectories can be determined from the trajectories based on the safety cost and an optimal trajectory can be determined from the subset of trajectories based on the total cost. The autonomous vehicle can control its motion in accordance with the optimal trajectory.

Systems and methods for costing autonomous vehicle maneuvers

Generally, the present disclosure is directed to systems and methods that include or otherwise leverage an iterative solver as part of optimizing a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can include a warm start generator configured to determine an initial trajectory that respects the dynamics of the autonomous vehicle and that closely tracks a speed profile determined by a constraint solver and one or more nominal paths determined by a route selector. A decision validator can analyze speed profiles and nominal paths to identify potential inconsistencies and validate a decision before optimization and execution. An initial trajectory can be further optimized by an iterative solver to determine an optimized trajectory for execution as a motion plan for the autonomous vehicle.

Initial trajectory generator for motion planning system of autonomous vehicles

The present disclosure is directed to analyzing motion plans of autonomous vehicles. In particular, the methods, devices, and systems of the present disclosure can: receive data indicating a motion plan, of an autonomous vehicle through an environment, based at least in part on multiple different constraints of the environment; and determine, for each constraint of the multiple different constraints, a measure of an influence of the constraint on the motion plan.

Methods, devices, and systems for analyzing motion plans of autonomous vehicles

The present disclosure is directed generating candidate trajectories and selecting one of them to be implemented. In particular, a computing system can obtain an initial travel path for an autonomous vehicle. The computing system can obtain sensor data describing objects within an environment of the autonomous vehicle. The computing system can generate a plurality of trajectories for the autonomous vehicle based on the sensor data and the initial travel path. The computing system can determine whether the initial travel path, an offset profile, and a velocity profile meet flatness criteria. In response to determining that the initial travel path, the offset profile, and the velocity profile meet the flatness criteria, the computing system can combine the initial travel path, the offset profile, and the velocity profile into the respective trajectory. The computing system can determine a trajectory from the plurality of trajectories.

Method for using lateral motion to optimize trajectories for autonomous vehicles

The present disclosure provides autonomous vehicles that include a vehicle intention system that provides intention signals indicative of an intention of the autonomous vehicle. In particular, in one example, the vehicle intention system can obtain one or more operational messages from various systems or components of an autonomous vehicle that operate to control the autonomous vehicle. The operational messages can include operational data regarding the control or operation of the autonomous vehicle. The vehicle intention system can determine an intention of the autonomous vehicle based at least in part on the one or more operational messages. The vehicle intention system can output one or more intention signals that indicate the determined intention of the autonomous vehicle. For example, the vehicle intention system can publish intention messages that indicate the determined intention to one or more components or systems that consume the intention messages.

Autonomous vehicles featuring vehicle intention system

The present disclosure provides systems and methods that enable an autonomous vehicle motion planning system to learn to generate motion plans that mimic human driving behavior. In particular, the present disclosure provides a framework that enables automatic tuning of cost function gains included in one or more cost functions employed by the autonomous vehicle motion planning system.

Growing community of inventors

Allison Park, PA, United States of America

Moslem Kazemi