Learning a Lattice Planner Control Set for Autonomous Vehicles

This paper introduces a method to compute a sparse lattice planner control set that is suited to a particular task by learning from a representative dataset of vehicle paths. To do this, we use a scoring measure similar to the Fr\'echet distance and propose an algorithm for evaluating a given control set according to the scoring measure... (read more)

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