Aurora Operations, Inc.

Pengju Jin

Paul Vernaza

Arun Venkatraman

Micol Marchetti-Bowick

J Andrew Bagnell

Venkatraman Narayanan

Sumit Kumar

Yuhang Ma

Carl Wellington

Sanjiban Choudry

The present disclosure provides an example method that includes: (a) obtaining context data descriptive of an environment surrounding an autonomous vehicle, the context data based on map data and perception data; (b) generating, by a proposer and based on the context data: (i) a plurality of candidate trajectories, and (ii) a plurality of actor forecasts for a plurality of actors in the environment; (c) generating, by a ranker and based on the context data, the plurality of candidate trajectories, and the plurality of actor forecasts, a ranking of the plurality of candidate trajectories; and (d) controlling a motion of the autonomous vehicle based on a candidate trajectory selected based on the ranking of the plurality of candidate trajectories, wherein the proposer comprises a first machine-learned model and the ranker comprises a second machine-learned model, and wherein the first machine-learned model and the second machine-learned model use a common backbone architecture.

Autonomous vehicle motion planning

An example method for controlling an autonomous vehicle includes generating, using perception data, a dynamic cost profile associated with an object in the environment; obtaining map data describing lanes of the multilane roadway; generating, using the map data, a lane cost profile that includes a plurality of basins respectively associated with the lanes; generating a candidate trajectory for the autonomous vehicle to traverse in the environment; evaluating the candidate trajectory using an aggregate cost of the candidate trajectory, the aggregate cost computed using the lane cost profile and the dynamic cost profile; determining a selected trajectory for execution by the autonomous vehicle based on the evaluation of the candidate trajectory; controlling the autonomous vehicle according to the selected trajectory.

Lane change architecture for autonomous vehicles

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San Francisco, CA, United States of America

Pengju Jin