With the increasing popularity of ChatGPT, large language models (LLMs) have demonstrated their capabilities in communication and reasoning, promising for transportation sector intelligentization. However, they still face challenges in domain-specific knowledge. This paper aims to leverage LLMs' reasoning and recognition abilities to replace traditional user interfaces and create an "intelligent operating system" for transportation simulation software, exploring their potential with transportation modeling and simulation. We introduce Network Generation AI (NGAI), integrating LLMs with road network modeling plugins, validated through experiments for accuracy and robustness. NGAI's effective use has reduced modeling costs, revolutionized transportation simulations, optimized user steps, and proposed a novel approach for LLM integration in the transportation field.

中文翻译：

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基于大语言模型的多模式路网生成

随着ChatGPT的日益普及，大语言模型（LLM）展示了其通信和推理能力，为交通部门的智能化带来了希望。然而，他们仍然面临特定领域知识的挑战。本文旨在利用法学硕士的推理和识别能力取代传统的用户界面，创建交通仿真软件的“智能操作系统”，探索其在交通建模和仿真方面的潜力。我们引入网络生成人工智能（NGAI），将法学硕士与道路网络建模插件集成，并通过实验验证准确性和鲁棒性。 NGAI的有效使用降低了建模成本，彻底改变了交通模拟，优化了用户步骤，并提出了交通领域LLM集成的新方法。