#trajectory-planning2 articles

2 articles

AIBullisharXiv – CS AI · 4h ago10

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BEV-VLM: Trajectory Planning via Unified BEV Abstraction

Researchers introduced BEV-VLM, a new autonomous driving trajectory planning system that combines Vision-Language Models with Bird's-Eye View maps from camera and LiDAR data. The approach achieved 53.1% better planning accuracy and complete collision avoidance compared to vision-only methods on the nuScenes dataset.

AIBullisharXiv – CS AI · 4h ago6

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Less is More: Lean yet Powerful Vision-Language Model for Autonomous Driving

Researchers introduce Max-V1, a novel vision-language model framework that treats autonomous driving as a language problem, predicting trajectories from camera input. The model achieved over 30% performance improvement on the nuScenes dataset and demonstrates strong cross-vehicle adaptability.