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Efficient Multi-Modal Planning with Reward-Guided Preference Optimization for Autonomous Driving
Safe and efficient trajectory planning is essential in autonomous driving. However, existing end-to-end approaches often fall short in both computational efficiency and safety guarantees. Methods based on imitation learning suffer from causal confusion, while rule-based scoring approaches often incu
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