Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/145627
Title: Temporal patterns underlying domestic departure passengers behavior in the airport
Authors: Wang, Yanjun
Liu, Tongdan
Hu, Minghua
Alam, Sameer
Duong, Vu
Keywords: Engineering::Aeronautical engineering
Issue Date: 2020
Source: Wang, Y., Liu, T., Hu, M., Alam, S., & Duong, V. (2020). Temporal patterns underlying domestic departure passengers behavior in the airport. IEEE Access, 8, 127969-127980. doi:10.1109/ACCESS.2020.3008438
Journal: IEEE Access
Abstract: Air travelers' behavior is closely related to the operational performance of any airport terminal. Much of previous research has focused on how airport operators balance the number of facilities in a terminal and the Level of Service (LOS), while the behavior of passengers is less considered. Not much is known, however, about passenger's behavior during the entire departure process in an airport. In this study, we analyze empirical departure passenger's data to gain an insight into the regular patterns of their activities in an airport. We find that there exist two distinguished temporal patterns during two discretionary periods- post check-in and pre-security check, post security check and pre-boarding. The time that departure passengers spend in these two periods is well approximated by a double power-law distribution and an exponential truncated power-law distribution respectively. The two distinguished distributions suggest that there may be different mechanisms underlying passengers' behavior as indicated by previous studies on human mobility. We introduce a stochastic model that considers traveling experience and time pressure to capture the decision dynamics of human behavior. Simulation results suggest that traveling experience and time pressure dominate passenger's decisions before and after security respectively. Our findings contribute to a better understanding of human dynamics, and also offer the potential for optimizing and simulation of airport terminal operation.
URI: https://hdl.handle.net/10356/145627
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2020.3008438
Schools: School of Mechanical and Aerospace Engineering 
Research Centres: Air Traffic Management Research Institute 
Rights: © 2020 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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