Modeling and managing airport passenger flow under uncertainty: A case of fukuoka airport in Japan

Abstract

Airport terminal decision makers in recent years need to deal with unexpected and sudden congestion situations. Although various types of mathematical researchs has analyzed the congestion situations and have succeed to manage a subsystem, they cannot sufficiently describe the variety of phenomena observed in a real airport terminal, because they have not considered the interactions between subsystems of the real airport terminal. A simulation approach enables us to describe the interactions between facilities and passenger behavior in detail as a whole airport system and to find various types of possible congestion situations. The simulation approach, however, cannot directly lead exact prediction that can be useful in practical management and operation for difficulties of modeling a complex airport terminal system and acquiring complete input data. In this paper, (1) we modeled Fukuoka airport international terminal in Japan as Complex Adaptive System and built a passenger flow simulation based on the Discrete Event Model. Validity of the model was confirmed by experiments. Moreover, (2) we confirmed that it is possible to acquire simulation input data from discussing with stakeholders using the simulation. Therefore, we believe that it is possible to reduce uncertainty of the model systematically by continuing modeling, predicting, and discussing with stakeholders, repeatedly.