TY - GEN
T1 - Modeling and managing airport passenger flow under uncertainty
T2 - 9th International Conference on Social Informatics, SocInfo 2017
AU - Yamada, Hiroaki
AU - Ohori, Kotaro
AU - Iwao, Tadashige
AU - Kira, Akifumi
AU - Kamiyama, Naoyuki
AU - Yoshida, Hiroaki
AU - Anai, Hirokazu
N1 - Funding Information:
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.
Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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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U2 - 10.1007/978-3-319-67256-4_33
DO - 10.1007/978-3-319-67256-4_33
M3 - Conference contribution
AN - SCOPUS:85029512555
SN - 9783319672557
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 419
EP - 430
BT - Social Informatics - 9th International Conference, SocInfo 2017, Proceedings
A2 - Ciampaglia, Giovanni Luca
A2 - Yasseri, Taha
A2 - Mashhadi, Afra
PB - Springer Verlag
Y2 - 13 September 2017 through 15 September 2017
ER -