To solve the problem that a single simulation platform is difficult to balance the authenticity of the scene and the accuracy of traffic flow modeling in the air-ground cooperative traffic control simulation, this paper proposes a joint simulation scheme based on Carla and SUMO: build a custom traffic environment by integrating RoadRunner, rely on Carla to achieve high-fidelity scene rendering and sensor simulation, and use SUMO to complete refined traffic flow modeling, thus forming a virtual experimental scene with both realism and accuracy. At the same time, the YOLOv12 target detection algorithm and Bytetrack tracker are combined to realize the accurate calculation of vehicle speed in BEV traffic video based on multi-frame position information. The experimental results show that the system performs well in traffic flow restoration and target tracking accuracy, achieving an MAE of 0.57 and an MSE of 0.51. It provides a low-cost and reproducible software-in-the-loop simulation environment for BEV traffic image detection algorithm test and traffic control strategy verification.