LLM-driven behavioral planning for AVs reaches 68% zero-shot collision-free success in pedestrian scenarios, outperforming deep RL baselines at 17.7% and improving to 96% with few-shot memory.
Doraemongpt: Toward understanding dynamic scenes with large language models (exemplified as a video agent)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Pedestrian-Aware LLM-Driven Behavioral Planning for Autonomous Vehicles
LLM-driven behavioral planning for AVs reaches 68% zero-shot collision-free success in pedestrian scenarios, outperforming deep RL baselines at 17.7% and improving to 96% with few-shot memory.