Analytical approach to solve the problem of aircraft passenger boarding during the coronavirus pandemic

Abstract: We design an optimal group boarding method using a stochastic cellular automata model for passenger movements, which is extended by a virus transmission approach. Furthermore, a new mathematical model is developed to determine an appropriate seat layout for groups. The proposed seating layout is based on the idea that group members are allowed to have close contact and that groups should have a distance among each other. The sum of individual transmission rates is taken as the objective function to derive scenarios with a low level transmission risk. After the determination of an appropriate seat layout, the cellular automata is used to derive and evaluate a corresponding boarding sequence aiming at both short boarding times and low risk of virus transmission. We find that the consideration of groups in a pandemic scenario will significantly contribute to a faster boarding (reduction of time by about 60%) and less transmission risk (reduced by 85%), which reaches the level of boarding times in pre-pandemic scenarios.