A dual-track zero-shot benchmark (DeepPlan semantic shift + actuation-noise drift) reveals imitation planners collapse under novel urban density and correlated noise while an RL planner remains more robust.
Deepurban: Interaction-aware trajectory pre- diction and planning for automated driving by aerial imagery,
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Shift & Drift: A Zero-Shot Benchmark for Generalizable and Robust Autonomous Driving Motion Planning
A dual-track zero-shot benchmark (DeepPlan semantic shift + actuation-noise drift) reveals imitation planners collapse under novel urban density and correlated noise while an RL planner remains more robust.