Trajectory planning based on tree search expansion

Abstract

Techniques for determining a vehicle trajectory that causes a vehicle to navigate in an environment relative to one or more objects are described herein. In some cases, the techniques described herein relate to selectively expanding a tree structure (e.g., a decision tree structure) to efficiently search for simulation data that can be used to evaluate vehicle control trajectories. The tree structure may include state nodes representing observed and/or predicted environment states, and action nodes representing candidate actions the vehicle may take. By selectively and incrementally expanding the tree using estimated state transition probabilities to focus on higher likelihood scenarios, more optimal trajectories can be determined without exhaustively evaluating every possible outcome.