An on-board fine-tuned vision-language model with a retrieval-augmented memory converts natural-language driving commands and camera views into MPC and PID controller parameters, reducing takeover rates by up to 76.9 percent in real vehicle tests.
Self-driving like a human driver in- stead of a robocar: Personalized comfortable driving experi- ence for autonomous vehicles, 2022
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On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation
An on-board fine-tuned vision-language model with a retrieval-augmented memory converts natural-language driving commands and camera views into MPC and PID controller parameters, reducing takeover rates by up to 76.9 percent in real vehicle tests.