The convergence of low-altitude economies, embodied intelligence, and air-ground cooperative systems creates growing demand for simulation infrastructure capable of jointly modeling aerial and ground agents within a single physically coherent environment. Existing open-source platforms remain domain-segregated: driving simulators lack aerial dynamics, while multirotor simulators lack realistic ground scenes. Bridge-based co-simulation introduces synchronization overhead and cannot guarantee strict spatial-temporal consistency. We present CARLA-Air, an open-source infrastructure that unifies high-fidelity urban driving and physics-accurate multirotor flight within a single Unreal Engine process. The platform preserves both CARLA and AirSim native Python APIs and ROS 2 interfaces, enabling zero-modification code reuse. Within a shared physics tick and rendering pipeline, CARLA-Air delivers photorealistic environments with rule-compliant traffic, socially-aware pedestrians, and aerodynamically consistent UAV dynamics, synchronously capturing up to 18 sensor modalities across all platforms at each tick. The platform supports representative air-ground embodied intelligence workloads spanning cooperation, embodied navigation and vision-language action, multi-modal perception and dataset construction, and reinforcement-learning-based policy training. An extensible asset pipeline allows integration of custom robot platforms into the shared world. By inheriting AirSim's aerial capabilities -- whose upstream development has been archived -- CARLA-Air ensures this widely adopted flight stack continues to evolve within a modern infrastructure. Released with prebuilt binaries and full source: https://github.com/louiszengCN/CarlaAir

翻译：低空经济、具身智能与空地协同系统的融合，对能够在一个物理一致的环境中联合建模空中与地面智能体的仿真基础设施提出了日益增长的需求。现有开源平台仍存在领域割裂：驾驶模拟器缺乏空中动力学，而多旋翼模拟器缺乏逼真的地面场景。基于中间件的协同仿真存在同步开销，且无法保证严格的时空一致性。我们提出CARLA-Air，一个在单一虚幻引擎进程中统一高保真城市驾驶与精确物理多旋翼飞行的开源基础设施。该平台保留CARLA与AirSim的原生Python接口及ROS 2接口，支持零修改代码复用。在共享物理节拍与渲染管线中，CARLA-Air提供具备规则合规交通流、社会感知行人与空气动力学一致无人机动力学的照片级逼真环境，并在每个节拍同步捕获所有平台上多达18种传感器模态。平台支持涵盖协作、具身导航与视觉-语言行动、多模态感知与数据集构建、以及基于强化学习的策略训练等代表性空地具身智能工作负载。可扩展的资产管线支持将定制机器人平台集成至共享世界。通过继承AirSim（其上游开发已归档）的空中能力，CARLA-Air确保这一广泛采用的飞行技术栈能在现代基础设施中持续演进。已发布预编译二进制文件与完整源码：https://github.com/louiszengCN/CarlaAir