When Digital Twins Meet Large Language Models: Realistic, Interactive, and Editable Simulation for Autonomous Driving
当数字孪生遇见大语言模型:用于自动驾驶的逼真、交互和可编辑的模拟
机构 * Department of Automotive Engineering, Clemson University International Center for Automotive Research (CU-ICAR)(汽车工程系,克莱姆森大学国际汽车研究中心(CU-ICAR))
专题命中 其他LLM :large language model(title,abstract);language model(title,abstract);LLM(abstract)
AI总结 本文提出结合数字孪生与大语言模型的框架,实现自动驾驶场景的逼真、交互和可编辑模拟,提升自动驾驶研究的效率和真实性。
Comments Accepted in IEEE Robotics & Automation Magazine (RAM)