论文标题
D-vine回归的应用用于识别跑道超支危险的航班
An Application of D-vine Regression for the Identification of Risky Flights in Runway Overrun
论文作者
论文摘要
在航空安全中，跑道超支非常重要，因为它们是最常见的着陆事故类型。识别导致跑道超支发生的因素可以帮助减轻风险并防止此类事故。过去提出了诸如基于物理和基于统计的模型之类的方法来估计跑道超支概率。但是，它们要么是昂贵的，要么需要专家的知识。我们提出了一种统计方法，以量化飞机以80节的速度超过阈值的风险概率，并给定一组影响因素。这种基于副群的D-vine回归方法之所以使用，是因为它允许复杂的尾巴依赖性并且可以在计算上进行处理。分析了从快速访问录音机（QAR）获得711航班的数据。我们确定了41次飞行，其估计的风险概率> 0.001对于选定的阈值，并对这些飞行的每个影响因素的影响进行排名。同样，这41次飞行的某些影响因素之间的复杂依赖模式被证明是非对称的。与基于物理和基于统计的方法相比，D-vine回归方法具有分析解决方案，不是基于模拟的，并且可用于有效地估计非常小或大概率。
In aviation safety, runway overruns are of great importance because they are the most frequent type of landing accidents. Identification of factors which contribute to the occurrence of runway overruns can help mitigate the risk and prevent such accidents. Methods such as physics-based and statistical-based models were proposed in the past to estimate runway overrun probabilities. However, they are either costly or require experts' knowledge. We propose a statistical approach to quantify the risk probability of an aircraft to exceed a threshold at the speed of 80 knots given a set of influencing factors. This copula based D-vine regression approach is used because it allows for complex tail dependence and is computationally tractable. Data obtained from the Quick Access Recorder (QAR) for 711 flights are analyzed. We identify 41 flights with an estimated risk probability > 0.001 for a chosen threshold and rank the effects of each influencing factor for these flights. Also, the complex dependency patterns between some influencing factors for the 41 flights are shown to be non symmetric. The D-vine regression approach, compared to physics-based and statistical-based approaches, has an analytical solution, is not simulation based and can be used to estimate very small or large probabilities efficiently.
