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DriveZero: End-to-End Driving Beyond Human Demonstrations

50 upvotes · 5 SEP 2026 · Hao He, Chengcheng Hu, Zirun Su et al.

This paper presents a method for end-to-end driving systems to learn beyond human demonstrations, using a combination of perception and action models that can learn from diverse data and provide goal-conditioned supervision. Practitioners might care about this approach because it allows for more robust and flexible autonomous driving systems.

reinforcement learningclosed-loop feedbackvision foundation modelsgoal-conditioned teachervalue-guided test-time action search