School of Mathematical Sciences, Queen Mary University of London, London, E1 4NS, UK.
Sci Rep. 2021 Apr 12;11(1):7855. doi: 10.1038/s41598-021-87279-8.
The aviation industry is of great importance for a globally connected economy. Customer satisfaction with airlines and airport performance is considerably influenced by how much flights are delayed. But how should the delay be quantified with thousands of flights for each airport and airline? Here, we present a statistical analysis of arrival delays at several UK airports between 2018 and 2020. We establish a procedure to compare both mean delay and extreme events among airlines and airports, identifying a power-law decay of large delays. Furthermore, we note drastic changes in plane delay statistics during the COVID-19 pandemic. Finally, we find that delays are described by a superposition of simple distributions, leading to a superstatistics.
航空业对全球经济的互联互通至关重要。航空公司和机场的表现如何在很大程度上受到航班延误的影响。但是，对于每个机场和航空公司的数千个航班，应该如何对延误进行量化呢？在这里，我们对 2018 年至 2020 年间英国几个机场的到达延误进行了统计分析。我们建立了一种程序，可以比较航空公司和机场之间的平均延误和极端事件，确定大延误的幂律衰减。此外，我们注意到在 COVID-19 大流行期间飞机延误统计数据发生了巨大变化。最后，我们发现延误可以用简单分布的叠加来描述，从而产生超统计。
