A distillation framework with a ground-truth-annotation teacher, RL status optimization, and generative distribution interaction improves end-to-end planning collisions and closed-loop scores.
Navsim: Data-driven non-reactive autonomous vehicle simulation and benchmarking
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DistillDrive: End-to-End Multi-Mode Autonomous Driving Distillation by Isomorphic Hetero-Source Planning Model
A distillation framework with a ground-truth-annotation teacher, RL status optimization, and generative distribution interaction improves end-to-end planning collisions and closed-loop scores.