Construction and Analysis of a Taxiing Conflict Prediction Model in Airport Scene Based on Digital Twin

The traditional airport scene taxiing conflict detection mainly relies on the controllers to visually judge the conflict risk. With the increase of air traffic volume, the shortcomings of relying on manual judgment are increasingly prominent, and a conflict judgment method is urgent to reduce manual dependence. At present, most conflict models have some problems, such as the lack of timely interaction between the model and the real situation of the scene. Consequently, based on digital twin, a taxiing conflict prediction model in airport scene is proposed in this paper. The scene conflict can be predicted timely in this model through the data interaction between the physical system and the twin system. Further, considered the delay requirement of the twin system, the delay modeling and analysis are carried out based on the mainstream communication methods 4G, 5G and AeroMACS(aeronautical mobile airport communications system) in airport scene. The simulation results show that the delay of 5G and AeroMACS is between 0.5 and 20 ms, which meets the requirement of communication delay.