Exploring Airplane Boarding

Abstract

The airline industry is crucial to economic growth and the number of passengers is expected to increase by approximately 250 million from 2017 to 2018. IATA believes it is imperative to increase airline efficiency to maintain sustainability. Passenger boarding is known to constitute 60% of airplane turnaround time, identifying this step as rate determining. In this study, we investigate passenger boarding strategies utilized by airline companies and strategies simulated by existing literature. We propose more efficient passenger boarding methods for the Airbus A320/ Boeing 737 and Airbus A380-800/ Boeing 777-300ER airline classes. We use GNU Octave to construct a cellular automaton model that operates on the interaction of a 2-dimensional matrix, representing passenger attributes, and a 4-dimensional matrix, representing the cells of the airplane in consideration. We consider row interferences, aisle interferences, luggage stow away time, and general passenger delays. We find that boarding strategies which minimize passenger interferences are the most efficient for both airline classes. Interestingly, some boarding strategies for the Airbus A320/ Boeing 737 are more efficient when boarding at 30 passengers/ min instead of 60 passengers/ min. However, the Airbus A380-800/ Boeing 777-300ER shows slower boarding rates for any boarding frequency less than 60 passengers/ min, suggesting the size of the airplane layout determines sensitivity to boarding frequency. With the Airbus A380-800/ Boeing 777-300ER having limited documentation, we define and propose new boarding strategies, OBFOIZ and OBFOISA, that improve on the passenger boarding times in the existing literature for this double-aisled airplane.