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Modeling and Managing Airport Passenger Flow Under Uncertainty: A Case of Fukuoka Airport in Japan

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Social Informatics (SocInfo 2017)

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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.

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Acknowledgement

We appreciate to Fukuoka Airport Building Co., Ltd. for useful comments and considerable efforts. We are grateful to Mr. Daisuke Sunada and Mr. Kazuhiro Tokiwa for developing a simulator implemented our model. Naoyuki Kamiyama was supported by JST PRESTO Grant Number JPMJPR14E1, Japan. Akifumi Kira was supported in part by JSPS KAKENHI Grant Numbers 26730010 and 17K12644.

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Correspondence to Hiroaki Yamada .

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Appendices

Appendix 1

In this appendix, we describe detail of the problem situation. Figure 4 shows passengers flow and management organizations of Fukuoka airport international terminal (FUK int’l terminal) departure floor in Japan. The baggage X-ray inspection consists of 6 inspection units, the check-in consists of 12 check-in counters and each counter having 8 booths, the security check consists of 5 inspection units, and the departure examination consists of 3 counters. The departure floor roughly divide in north area and south area. North-units of baggage X-ray inspection and from A counter to F counter of check-in are placed in north area. South-units of baggage X-ray inspection and from G counter to M counter of check-in are placed in south area. Each check-in counter are managed by each airline, and the passengers use own flight counter. The check-in booth is assigned for business class passenger or economy class passenger. If the passengers use north area check-in counter, they have to use north-units of baggage X-ray inspection. It is the same in the south area. The security checks counters and departure examinations are used by all passengers freely.

Fig. 4.
figure 4

Passengers’ flow and management organizations of FUK int’l terminal departure floor.

The boarding process at the terminal departure floor is composed of the following steps: a passenger (i) has the examination of his/her check in baggage at the baggage X-ray inspection facility; (ii) checks in at the airport counter facility; (iii) gets the inspection of his/her body and carry-on baggage at the security checks facility; (iv) gets the inspections of his/her passport and flight ticket at departure immigration facility; and (v) proceeds to the boarding gate of his/her flight. In particular, most of passengers advance from the steps (i) to (iv) directly without visiting other facilities such as a restaurant and an exchange counter.

Appendix 2

In this appendix, we describe detail of the model. Figure 5 shows FUK int’l terminal departure floor represented by the Queueing Network. In this paper, we analyze only baggage X-ray inspection, check-in, and security checks. Because data about the departure examination could not be gathered for security reasons.

Fig. 5.
figure 5

FUK int’l terminal departure floor represented by the Queueing Network.

Tables 3 and 4 show values, source of values, and collected date of the each parameter.

Table 3. The values of the facilities’ parameters.
Table 4. The values of the flight’s parameters.

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Yamada, H. et al. (2017). Modeling and Managing Airport Passenger Flow Under Uncertainty: A Case of Fukuoka Airport in Japan. In: Ciampaglia, G., Mashhadi, A., Yasseri, T. (eds) Social Informatics. SocInfo 2017. Lecture Notes in Computer Science(), vol 10540. Springer, Cham. https://doi.org/10.1007/978-3-319-67256-4_33

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  • DOI: https://doi.org/10.1007/978-3-319-67256-4_33

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