Xiao Li

MUSE: Target-Guided Multimodal Scoring Ensemble for Safe Autonomous Planning

Imitation learning planners can behave unsafely under distribution shift, since long-tailed driving data contain few safety-critical events. A common remedy is to generate multimodal candidate trajectories and select them with a hybrid evaluator, but existing methods often suffer from mode collapse and brittle hard con...