A dynamic estimation method for aircraft emergency evacuation based on cellular automata

Abstract

To reduce the time of aircraft passenger evacuation in an unplanned emergency and improve passenger safety, this article proposed a dynamic estimation method of an aircraft emergency evacuation process; optimal performance statistics can be estimated efficiently. Then, the emergency guiding model is established based on the cellular automata theory. In this model, multiple factors are considered, such as seat pitch, exit width, and occupant behavior. A total of six categories (target exit choice, movement direction selection, movement speed calculation, behavior representation, crew operation, and exit modeling) and 24 evacuation regulations are included. Two kinds of civil aircraft with 90 seats and 149 seats were tested individually using the proposed model and a traditional model. The total evacuation time can be reduced by more than 5%, and optimal performance statistics can be reduced by more than 30%. The results indicate that with this model, more lives can be saved in the case of an emergency.