空域扇区概率交通需求预测模型

Airspace Sector Probabilistic Traffic Demand Prediction Model

为预测空域扇区在未来一定时段内的交通需求及其变化规律,基于简化的空域运行网络结构,从不确定性角度分析了航空器飞行时间对空域扇区交通需求预测的影响,针对航空器进入、离开扇区和在扇区内飞行过程的随机性,给出了相应概率分布函数.在此基础上,建立了空域扇区概率交通需求预测模型,设计了启发式算法.对实际航班数据的仿真结果表明：本文模型和算法预测时段10：00~11：00扇区发生拥挤,比传统的确定性方法预测的拥挤时段减少了30 min,避免了在时段9：30~10：00采取不必要的流量管理措施,降低了该时段管制员的工作负荷.

In order to predict the traffic demands and variations for a future time interval in an airspace sector,the influence of the aircraft flight time on the probabilistic traffic demand prediction was analyzed from the point of uncertainty with a simplified airspace structure.The probabilistic distribution functions for the sector entry time,sector exit time and sector transit time were established by analysis of the randomicity of the sector entry,exit and transit process.On this basis,an airspace sector probabilistic traffic demand prediction model was developed,and a heuristic algorithm was designed.A simulation was performed to verify the proposed model and algorithm using real flight data.The result shows that the sector congestion predicted by the model and algorithm occurs during 10：00-11：00.Compared with the traditional deterministic methods,the proposed method can reduce 30 min of congestion period avoid unnecessary flow management during the period 9：30-10：00,and thus alleviate the air traffic controllers＇ workload.