Modeling passengers boarding in aircraft using cellular automata

Abstract

Aircraft are profitable to their owners as long as they are in the air transporting passengers to their destinations; therefore it is vital to minimize as much as possible their preparation time on the ground. In this paper we simulate different boarding strategies with the help of a model based on cellular automata parallel computational tool, attempting to find the most efficient way to deliver each passenger to her or his assigned seat. Two seat arrangements are used, a small one based on Airbus A320 U+002F Boeing 737 and a larger one based on Airbus A380 U+002F Boeing 777-300. A wide variety of parameters, including time delay for luggage storing, the frequency by which the passengers enter the plane, different walking speeds of passengers depending on sex, age and height, and the possibility of walking past their seat, are simulated in order to achieve realistic results, as well as monitor their effects on boarding time. The simulation results indicate that the boarding time can be significantly reduced by the simple grouping and prioritizing of passengers. In accordance with previous papers and the examined strategies, the outside-in and reverse pyramid boarding methods outperform all the others for both the small and large airplane seat layout. In the latter, the examined strategies are introduced for first time in an analogous way to the initial small seat arrangement of Airbus A320 U+002F Boeing 737 aircraft family. Moreover, since in real world scenarios, the compliance of all the passengers to the suggested group division and boarding strategy cannot be guaranteed, further simulations were conducted. It is clear that as the number of passengers disregarding the priority of the boarding groups increases, the time needed for the boarding to complete tends towards that of the random boarding strategy, thus minimizing the possible advantages gained by the proposed boarding strategies.