中国民航大学学报

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基于WITI的终端空域短期延误预测

张明1,张明1*,刘凯1,赵敏2   

  1. (1.南京航空航天大学民航学院,南京211106;2.中国民用航空江苏安全监督管理局,南京210022)
  • 收稿日期:2016-06-14 修回日期:2016-07-13 出版日期:2017-04-22 发布日期:2017-06-14
  • 作者简介:张明(1991—),男,山东临沂人,硕士研究生,研究方向为空中交通规划与管理. 张明*(1975—),男,江苏南京人,副教授,博士,研究方向为空中交通管理.
  • 基金资助:

    国家自然科学基金项目(U1233101,71271113);中央高校基本科研业务费专项(NS2016062)

Short-term terminal airspace delay prediction based on weather impacted traffic index

ZHANG Ming1, ZHANG Ming1*, LIU Kai1, ZHAO Min2   

  1. (1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;
    2. Jiangsu Province Safety Oversight Bureau, CAAC, Nanjing 210022, China)
  • Received:2016-06-14 Revised:2016-07-13 Online:2017-04-22 Published:2017-06-14

摘要:

针对终端空域内短期天气条件变化引起的航班延误问题,首先利用雷达回波平面位置显示(PPI)和距离高度显示(RHI)对降水等级分类,通过图像识别方法对不同降水等级的云团进行轮廓提取;其次将对应时间的交通流信息与降水云团的空间范围匹配,提出了不同降水等级条件下的三维天气影响交通指数(WITI)计算方法;最后结合实际管制规则,将WITI指数与管制间隔调整和改航条件下的延误时间作指数回归分析,得到短期延误预测模型。通过算例仿真验证了该模型的拟合优度相比于线性回归模型提高了1.6%~4.3%,且估计标准误差趋近于0,说明指数回归延误预测模型更能反映天气影响下终端空域的实际延误状况。

关键词: 终端空域, 降水等级, 交通流, WITI, 延误预测

Abstract:

Aiming at the flight delay in terminal airspace caused by the changes of short-term weather conditions, radar echo PPI(plane-position indication)and RHI(range-height indication)are firstly used to classify the precipitation grades, then the contour of different grades of convective clouds is extracted by image recognition method.Secondly, the corresponding time of traffic flow information is matched to the convective clouds, and the calculation method of 3D WITI (weather impacted traffic index)based on different levels of precipitation is put forward.Finally, according to air traffic control rules, a short-term delay prediction model is proposed through exponential regression analysis between WITI and delay time under different control intervals or rerouting path distance.Simulation results show that under the condition of control interval adjustment and rerouting, compared with the linear regression model, the fit goodness of exponential regression model increases 1.6%~4.3%, and the standard error of estimate is closed to 0, indicating that the exponential regression delay prediction model can better reflect the actual delay situation of terminal airspace under the influence of precipitation.

Key words: terminal airspace, precipitation grades, air traffic flow, WITI, delay prediction

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