Smooth Skies and Swift Boarding: Analysing the Influence of Family, Priority, and Luggage on Common Boarding Strategies

Iliescu, Astrid (2023) Smooth Skies and Swift Boarding: Analysing the Influence of Family, Priority, and Luggage on Common Boarding Strategies. Bachelor's Thesis, Artificial Intelligence.

Preview	Text AI_2023_IliescuAM.pdf Download (487kB) | Preview
	Text toestemming.pdf Restricted to Registered users only Download (126kB)

Abstract

While aircraft boarding may seem like a routine part of air travel, the efficiency of the boarding process plays a crucial role in ensuring on-time departures and a smooth passenger experience. In this paper, we will examine the impact of in-cabin luggage handling alongside family and priority boarding on the overall boarding time of five common boarding strategies (random, window-middle-aisle, back-to-front, front-to-back, and window-middle-aisle combined with back-to-front). The research employs an agent-based modeling approach using the NetLogo platform to simulate and analyze the different boarding scenarios. The study begins by establishing a baseline scenario without any special considerations, where passengers board the plane according to the desired strategy. Subsequently, family boarding is introduced, allowing families with young children to board first. Priority boarding is then incorporated, giving priority to passengers with special needs or premium status. Finally, the influence of luggage management is examined, considering the time required for passengers to stow their carry-on bags. The simulations revealed that when all mentioned factors are present, the window-middle-aisle strategy provides the least boarding delay, closely followed by the random strategy, and that luggage affects boarding time the most. The results suggest that airline companies should focus on allowing concurrent luggage stowing, without piling up groups of passengers into one zone.

Item Type:	Thesis (Bachelor's Thesis)
Supervisor name:	Weerd, H.A. de
Degree programme:	Artificial Intelligence
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	17 Jul 2023 09:43
Last Modified:	17 Jul 2023 09:43
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/30660

Actions (login required)

View Item