Statistical Modeling and Analysis of Landing Time Intervals: Case Study of Los Angeles International Airport, California

Abstract

Existing literature suggests that analyses of landing time intervals employ simple statistical models based on time-separation histograms, usually approximated by normal distributions. Although the literature focuses on important issues such as safety, capacity improvements, and separation rules, it does not take into account another important issue: the possible, unique behavior of airlines, pilots, and controllers. In this study such possible, unique behavior is taken into account and a statistical analysis on landing time intervals is performed to find the operational properties of Los Angeles International Airport (LAX), California. On the basis of the properties found, operations of a dominant airline at LAX are compared with those of other airlines by using the Performance Data Analysis and Reporting System (PDARS) database. The PDARS database allows the calculation of landing time intervals on a runway level. A new mathematical model is constructed to fit the probability distribution of landing time intervals, and it is found that the proposed model has the best maximum log likelihood estimations compared with those of existing models. The results also reveal that the behavior of the dominant airline differs from that of the other airlines. The proposed model better approximates the shape of the probability distribution, especially the left-hand side, which usually contains information of greater importance regarding airport operations and especially regarding safety, since all smaller landing time intervals and the landing intervals that fail the safety requirements are concentrated in this part of the probability distribution curve.