标题： 城市空中交通作为系统之系统：LLM增强的整体方法 显示英文标题

标题： Urban Air Mobility as a System of Systems: An LLM-Enhanced Holonic Approach

摘要： 城市空中 mobility（UAM）是一个新兴的系统之系统（SoS），在系统架构、规划、任务管理和执行方面面临挑战。传统的架构方法在动态和复杂环境中难以实现可扩展性、适应性和资源的无缝整合。本文提出了一种智能全异构体系结构，结合大型语言模型（LLM）来管理UAM的复杂性。全异构体半自主运行，允许空中出租车、地面交通和垂直机场之间实时协调。LLM处理自然语言输入，生成自适应计划，并管理诸如天气变化或空域关闭等干扰。通过一个包括电动滑板车和空中出租车的多式联运案例研究，我们展示了这种架构如何实现实时动态资源配置、实时重新规划和无需集中控制的自主适应，从而创建更具弹性和高效的都市交通网络。通过推进去中心化控制和AI驱动的适应性，这项工作为具有弹性和以人类为中心的UAM生态系统奠定了基础，未来的工作将致力于混合AI集成和现实世界验证。 显示英文摘要

摘要： Urban Air Mobility (UAM) is an emerging System of System (SoS) that faces challenges in system architecture, planning, task management, and execution. Traditional architectural approaches struggle with scalability, adaptability, and seamless resource integration within dynamic and complex environments. This paper presents an intelligent holonic architecture that incorporates Large Language Model (LLM) to manage the complexities of UAM. Holons function semi autonomously, allowing for real time coordination among air taxis, ground transport, and vertiports. LLMs process natural language inputs, generate adaptive plans, and manage disruptions such as weather changes or airspace closures.Through a case study of multimodal transportation with electric scooters and air taxis, we demonstrate how this architecture enables dynamic resource allocation, real time replanning, and autonomous adaptation without centralized control, creating more resilient and efficient urban transportation networks. By advancing decentralized control and AI driven adaptability, this work lays the groundwork for resilient, human centric UAM ecosystems, with future efforts targeting hybrid AI integration and real world validation.