Ford Global Technolgoies, LLC

Argo Ai Gmbh

Volkswagen Group of America Investments, LLC

Ed Venator

Neal Andrew Seegmiller

Christopher Cunningham

Patrick Stirling Barone

Xi Cai

Systems and methods for operating an autonomous vehicle (AV) are provided. The method includes detecting one or more objects in an environment, predicting a first set of predicted object trajectories comprising one or more trajectories for each of the detected one or more objects, generating a plurality of candidate AV trajectories for the AV, scoring each of the candidate AV trajectories according to a cost function, using the scoring to select a final AV trajectory for execution, determining which of the predicted object trajectories affected the final AV trajectory and which did not do so, adding the predicted object trajectories that affected the final AV trajectory to a persisted prediction cache, excluding from the persisted prediction cache any predicted object trajectories that did not affect the final AV trajectory, and executing the final AV trajectory to cause the AV to move along the final AV trajectory.

Persisting predicted objects for robustness to perception issues in autonomous driving

Methods for planning a trajectory for an autonomous vehicle are disclosed. A vehicle motion planning system will determine a reference curve that represents a path via which the vehicle may travel. The system will detect an actor that is moving in the environment. The system will segment the reference curve according to time intervals. For each of the time intervals, the system will identify a bounding geometry for the actor, predict a lateral offset distance between the reference curve and the actor, and use the predicted lateral offset distance to determine whether to alter a planned trajectory for the autonomous vehicle.

Motion planning in curvilinear coordinates for autonomous vehicles

Growing community of inventors

Pittsburgh, PA, United States of America

Ed Venator