进离场交通流时距分布特征对比分析

时距分布是空中交通流理论研究的重要概念和组成部分。以中国某机场实测轨迹数据为例,提出一种合适观测点的自动生成方法,该方法能有效提升轨迹数据的利用率,并选择跟驰性较好的轨迹数据用以计算时距。在分别绘制进场和离场交通流时距频率分布直方图的基础上,应用韦布尔、光滑样条和有理函数模型拟合时距分布情况,并从定性和定量的角度对比分析拟合结果。结果表明,在机场运行状态正常时,有理函数模型对离场交通流时距的拟合效果最好,而光滑样条模型对进场交通流时距的拟合效果最好;在机场运行状态不佳时,光滑样条模型和有理函数模型则分别对离场和进场交通流的拟合效果更佳;进场交通流时距分布比离场交通流时距分布特征更明显。

Comparative Analysis on Time Distance Distribution Characteristics of Arrival and Departure Traffic Flow

Time distribution characteristics of air traffic flow is an important part of air traffic flow theory. Based on real trajectory data of domestic airport, a method of automatically generating the appropriate observation points was proposed. This method can effectively avoid the loss of trajectory data, and choose the trajectory data with good tracking property to calculate the time distribution. After calculating the frequency distribution histograms of arrival and departure traffic flow separately, three different distribution models were used to fit the distribution of time distance. The fitting results were analyzed from qualitative and quantitative perspectives. The results show that the fitting result of the rational function model to the departure traffic flow time distance is the best one when the airport operation state is normal, while the smooth spline model is the best one for the time distance of the arrival traffic flow. When the operation state is not good, the smooth spline model has the better fitting effect to the departure traffic flow, and the rational function model has the better fitting effect to the arrival traffic flow. The time distance distribution characteristics of arrival traffic flow is more obvious than that of departure traffic flow.