research-article

Agent-Based Modeling and Analysis of Airport Passenger Differentiated Security Strategy

Authors:

Zhonghu LiAuthors Info & Claims

ICCMS '20: Proceedings of the 12th International Conference on Computer Modeling and Simulation

Pages 104 - 108

https://doi.org/10.1145/3408066.3408091

Published: 11 August 2020 Publication History

Abstract

In order to improve the security and efficiency of the airport security system, Anylogic software is used to establish a simulation model for the traditional airport security inspection strategy and differentiated security inspection strategy combined with the actual airport survey data. An algorithm is established for the two strategy security inspection channels with one day operation of an airport. The situation is simulated and the traditional airport security inspection strategy was compared with the differentiated security strategy in terms of true alarm rate, false clear rate, average passenger waiting time, and total length of open time of security inspection channel. The results show that, compared with the traditional airport security inspection channel, the differentiated security strategy true alarm rate improved by 9.6%, the false clear rate decreased by 47.1%, the average waiting time of passengers decreased by 44.5%. The number of security checkpoints required was reduced and the operating time of security inspection channel was reduced by 38.4%.

References

[1]

Kobza J E, Jacobson S H. Probability models for access security system architectures[J]. Journal of the Operational Research Society, 1997, 48(3):255--263.

[2]

Babu V L L, Batta R, Lin L. Passenger Grouping Under Constant Threat Probability in an Airport Security System[J]. European Journal of Operational Research, 2007, 168(2):633--644.

[3]

Jacobson S H, Kobza J E, Easterling A S. A detection theoretic approach to modeling aviation security problems using the knapsack problem[J]. IIE Transactions, 2001, 33(9):747--759.

[4]

Jacobson S H, Kobza J E, Easterling A S. A detection theoretic approach to modeling aviation security problems using the knapsack problem[J]. IIE Transactions, 2001, 33(9):747--759.

[5]

Nie X. Optimization and resource allocation models in an aviation security system[D].Buffalo:State University of New York at Buffalo, 2008.

[6]

Nie X, Batta R, Drury C G, et al. Passenger grouping with risk levels in an airport security system[J]. European Journal of Operational Research, 2009, 194(2):574--584.

[7]

Brunetta L, Jacur G R. A flexible model for the evaluation of an airport terminal[C]. 11th European Simulation Symposium, Erlangen, Germany, 1999:224--226.

[8]

Hafizogullari S, Chinnusamy P, Tunasar C. Transportation applications of simulation: simulation reduces airline misconnections: a case study[C].Proceedings of the 2002 Winter Simulation Conference, San Diego, USA, 2002:1192--1198.

[9]

Takakuwa S, Oyama T. Simulation analysis of international-departure passenger flows in an airport terminal[C].Proceedings of the 2003 Winter Simulation Conference, New Orleans, USA, 2003, 2(1):1627--1634.

[10]

Li Jie, Jin Hua, Xu Hui-chuan. Study on classified security in domestic civil aviation airport [J]. Journal of Liaoning Police College, 2017, 19(5):35--41.

[11]

Zhao Zhen-wu, Tang Yu-li, Ma Jian-jun. Study on airport security system based on passenger classification[J]. Comprehensive Transportation, 2017, 39(3):37--41.

[12]

Ma Jian-jun. Study on the effects of performance of airport security check based on the risk level of passengers[D]. Tianjin: Civil Aviation University of China, 2017.

[13]

Zhang Ya-ping, Jia Guo-yang, Cheng Shao-wu. Terminal screening process modeling and performance analysis based on Petri net [J]. Journal of Wuhan University of Technology: Transportation Science & Engineering, 2015, 39(4):688--691, 697.

[14]

Jiang Xin-xin, ZHOU Hang, CAI Bing-qing. Optimization research on process and layout of terminal security check [J]. Aeronautical ComputerTechnique, 2015, 45(3):25--29, 34.

[15]

Liu Hao. Simulation research on the passenger's departure process from the terminal building based on Anylogic[D]. Guanghan: Civil Aviation Flight University of China, 2016.

[16]

Sun Jian. Modeling and simulation on land passenger service resources of aviation hub based on queuing theory[D]. Beijing: China University of Mining and Technology(Beijing), 2017.

[17]

Huang Yu. Computer Modeling and Application Research on collaborative management of Passenger Process in Terminal[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2016.

[18]

Zhao Xue, Hu Yu-ling. Research on fuzzy modeling and simulation of evacuees' behavior [J]. China Safety Science Journal, 2015, 25(8):56--61.

[19]

Mclay L A, Jacobson S H, Kobza J E. A multilevel passenger screening problem for aviation security[J]. Naval Research Logistics, 2010, 53(3):183--197.

[20]

Benda P. Commentary: Harnessing advanced technology and process innovations to enhance aviation security[J]. Journal of Air Transport Management, 2015, 48:23--25.

Cited By

Satish AMangal AChuri P(2023)A systematic review of passenger profiling in airport security system: Taking a potential case study of CAPPS IIJournal of Transportation Security10.1007/s12198-023-00260-616:1Online publication date: 5-Jul-2023
https://doi.org/10.1007/s12198-023-00260-6
Mujica Mota MScala PMurrieta-Mendoza AOrozco ADi Bernardi A(2021)Analysis of security lines policies for improving capacity in airports: Mexico City CaseCase Studies on Transport Policy10.1016/j.cstp.2021.07.0059:4(1476-1494)Online publication date: Dec-2021
https://doi.org/10.1016/j.cstp.2021.07.005

Index Terms

Agent-Based Modeling and Analysis of Airport Passenger Differentiated Security Strategy
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation types and techniques
      1. Agent / discrete models

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ICCMS '20: Proceedings of the 12th International Conference on Computer Modeling and Simulation

June 2020

219 pages

ISBN:9781450377034

DOI:10.1145/3408066

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Central Queensland University
DUT: Dalian University of Technology
University of Wollongong, Australia
Swinburne University of Technology
University of Technology Sydney
National Tsing Hua University: National Tsing Hua University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 August 2020

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ICCMS '20

ICCMS '20: The 12th International Conference on Computer Modeling and Simulation

June 22 - 24, 2020

QLD, Brisbane, Australia

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Cited By

Satish AMangal AChuri P(2023)A systematic review of passenger profiling in airport security system: Taking a potential case study of CAPPS IIJournal of Transportation Security10.1007/s12198-023-00260-616:1Online publication date: 5-Jul-2023
https://doi.org/10.1007/s12198-023-00260-6
Mujica Mota MScala PMurrieta-Mendoza AOrozco ADi Bernardi A(2021)Analysis of security lines policies for improving capacity in airports: Mexico City CaseCase Studies on Transport Policy10.1016/j.cstp.2021.07.0059:4(1476-1494)Online publication date: Dec-2021
https://doi.org/10.1016/j.cstp.2021.07.005

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