为解决现有低空交通数字孪生系统在运行管控过程中虚实交互深度不足、预测决策与控制执行链路衔接不畅，从而难以支撑实时闭环管控的问题，构建了一套数字孪生赋能的低空交通关键技术体系与综合管控平台架构。通过对国内典型低空交通数字孪生平台的对比分析，提炼其在预测、决策和协同控制方面的共性技术瓶颈，在此基础上提出贯通“传输—描述—诊断—预测—决策—控制”六个关键环节的虚实闭环技术体系，并将该体系工程化映射为由物理层、数据层、模型层、知识层、交互层和应用层构成的模块化平台架构。通过明确各技术环节的功能定位与数据、控制接口关系，实现从多源数据采集、状态识别与趋势预测，到策略生成与控制执行的完整闭环流程。研究结果表明，所提出的技术体系与平台架构能有效支撑低空交通运行状态的实时感知、风险预测与协同管控，可为实现空域资源动态配置和飞行安全的主动保障提供路径参考。

To address the limited depth of virtual-physical interaction and the fragmented linkage between prediction, decision-making, and control execution in existing low-altitude transportation digital twin systems, which hinder real-time closed-loop operational control, this study develops a digital twin-enabled key technology system and an integrated management and control platform architecture for low-altitude transportation. Through a comparative analysis of representative domestic digital twin platforms, common technical bottlenecks in prediction, decision-making, and coordinated control are identified. On this basis, a virtual-physical closed-loop technical system encompassing six sequential stages—transmission, description, diagnosis, prediction, decision, and control—is proposed and further mapped into a modular platform architecture consisting of the physical, data, model, knowledge, interaction, and application layers. By explicitly defining the functional roles of each stage and the associated data and control interfaces, the proposed approach establishes a complete closed-loop process from multi-source data acquisition and state identification to trend prediction, strategy generation, and control execution. The results demonstrate that the proposed framework can effectively support real-time situational awareness, risk prediction, and coordinated management of low-altitude transportation, and provide path references for achieving dynamic airspace allocation and proactive flight safety assurance.