Dynamics short-term prediction of air traffic flow considering controller workload
The commonly used air traffic flow prediction methods neglect the dynamic factors such as the workload of controllers that affect flight flow control,leading to unreasonable flow prediction.Therefore,a dynamic short-term prediction method of air traffic flow was proposed considering con-troller workload.The controller workload is difficult to quantify,so that the control communication time variable positively correlated with the controller workload was introduced.Based on historical statistical data,a fitting model of control communication time and flight flow was established.A vec-tor autoregression model of flight flow and control communication time was established.A vector er-ror correction model(VECM)of flight flow and control communication time was established,and a short-term flow prediction for 2 hours was carried out.The prediction results were compared and an-alyzed with the prediction results of single variable ARIMA.The results show that the accuracy of VECM is 6.88％higher than that of ARIMA,which prove that the proposed prediction method is reasonable and feasible,and provide new methods and ideas for dynamic short-term prediction of air traffic flow.
dynamic short-term traffic predictioncontroller workloadvector autoregressive mod-elvector error correction model
NETL
NSTL
万方数据
