Date of Award

Fall 2009

Document Type

Thesis - Open Access

Degree Name

Master of Science in Human Factors & Systems

Department

Human Factors and Systems

Committee Chair

Jonathan French, Ph.D.

First Committee Member

Amy Bradshaw, Ph.D.

Second Committee Member

Dianne McMullin, Ph.D.

Abstract

The number of passengers carried by commercial aircraft has increased dramatically over the past 50 years, closely in-step with advances in aircraft design. This makes unloading and loading an aircraft, called turn-around time, critical to the success of the airport, the aircraft and the airlines. A number of mathematical algorithms have been developed over the years that purport to determine the most efficient boarding strategy for passengers by decreasing turn time. This thesis evaluated the boarding strategies most often used by the airlines and algorithms used to predict boarding efficiency. The models used were obtained from the literature and from personal communication with the authors. The strategy and the model associated with the greatest predicted reduction in turn-around time, and the amount of time to deplane and enplane commercial airliners was determined. The Kruskal-Wallis one way analysis of variance test was used to determine that the Random boarding strategy had the greatest boarding rate and the rotating zone strategy had the slowest. It was also determined that one of the models, the Ferarri and Nagel sensitivity analysis algorithm, was consistently predictive of the empirical observations of boarding strategies.

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