Analyzing airport security checkpoint performance using cognitive agent models

Arthur Knol, Alexei Sharpanskykh*, Stef Janssen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

15 Citations (Scopus)
180 Downloads (Pure)

Abstract

Modern airports operate under high demands and pressures, and strive to satisfy many diverse, interrelated, sometimes conflicting performance goals. Airport performance areas, such as security, safety, and efficiency are usually studied separately from each other. However, operational decisions made by airport managers often impact several areas simultaneously. Current knowledge on how different performance areas are related to each other is limited. This paper contributes to filling this gap by identifying and quantifying relations and trade-offs between the detection performance of illegal items and the average queuing time at airport security checkpoints. These relations and trade-offs were analyzed by simulations with a cognitive agent model of airport security checkpoint operations. By simulation analysis a security checkpoint performance curve with three different regions was identified. Furthermore, the importance of focus on accuracy for a security operator is shown. The results of the simulation studies were related to empirical research at an existing regional airport.

Original languageEnglish
Pages (from-to)39-50
Number of pages12
JournalJournal of Air Transport Management
Volume75
DOIs
Publication statusPublished - 2019

Keywords

  • Agent-based modelling and simulation
  • Airport performance metrics
  • Airport security operations
  • Sociotechnical system modelling
  • Trade-off relations

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