Keywords

flight delay, on-time performance, airport delay

Abstract

In this research, statistical models of airport delay and single flight arrival delay were developed. The models use the Airline On-Time Performance Data from the Federal Aviation Administration (FAA) and the Surface Airways Weather Data from the National Climatic Data Center (NCDC). Multivariate regression, ANOVA, neural networks and logistic regression were used to detect the pattern of airport delay, aircraft arrival delay and schedule performance. These models are then integrated in the form of a system for aircraft delay analysis and airport delay assessment. The assessment of an airport¡¯s schedule performance is discussed. The results of the research show that the daily average arrival delay at Orlando International Airport (MCO) is highly related to the departure delay at other airports. The daily average arrival delay can also be used to evaluate the delay performance at MCO. The daily average arrival delay at MCO is found to show seasonal and weekly patterns, which is related to the schedule performance. The precipitation and wind speed are also found contributors to the arrival delay. The capacity of the airport is not found to be significant. This may indicate that the capacity constraint is not an important problem at MCO. This research also investigated the delays at the flight level, including the flights with delay ¡Ý0 minute and the flights with delay ¡Ý15min, which provide the delay pattern of single arrival flights. The characteristics of single flight and their effect on flight delay are considered. The precipitation, flight distance, season, weekday, arrival time and the time spacing between two successive arriving flights are found to contribute to the arrival delay. We measure the time interval of two consecutive flights spacing and analyze its effect on the flight delay and find that for a positively delayed flight, as the time space increases, the probability of the flights being delayed will decrease. While it was possible to calculate the immediate impact of originating delays, it is not possible to calculate their impact on the cumulative delay. If a late departing aircraft has no empty space in its down line schedule, it will continue to be late. If that aircraft enters a connecting airport, it can pass its lateness on to another aircraft. In the research we also consider purifying only the arrival delay at MCO, excluding the flights with originating delay >0. The model makes it possible to identify the pattern of the aircraft arrival delay. The weather conditions are found to be the most significant factors that influence the arrival delay due to the destination airport.

Notes

If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu

Graduation Date

2006

Semester

Spring

Advisor

Abdel-Aty, Mohamed

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

Civil and Environmental Engineering

Degree Program

Civil Engineering

Format

application/pdf

Identifier

CFE0001049

URL

http://purl.fcla.edu/fcla/etd/CFE0001049

Language

English

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Download

Share

COinS