Simulation of a New Airport Security Design Concept

Jung, Martin H.; Claßen, Axel B.; Castro, Andre; Ferreira, Catarina

doi:10.1007/978-3-030-25629-6_55

Cited by 1 publication

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“…The baseline that we used was elaborated and validated under pre-COVID-19 conditions in a former project (Jung et al, 2015) together with airport practitioners of an international medium sized Europe serving 12 million passengers p.a. (as of 2019).…”

Section: Methodsmentioning

confidence: 99%

Post-Pandemic Impact Analysis for airport processes from security to boarding – How to respond to the next pandemic

Jung¹,

Claßen²,

Rudolph³

2023

Human Interaction &Amp; Emerging Technologies (IHIET 2023): Artificial Intelligence &Amp; Future Applicatio

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The COVID-19 pandemic globally affected the complete transport sector and especially passenger air transport with nosediving traffic numbers, wide-ranging travel restrictions and long-lasting uncertainties (see IATA, 2020). As air travel starts to recover cautiously from severe losses of traffic volumes over the pre-pandemic year 2019 and travel restrictions are relaxing, air transport providers have to ensure that passengers as well as people working within the air transport sector will remain safe and be prepared for the next Pandemic. For Example, arboviruses have the potential to spark the next epidemic, warns the World Health Organisation (WHO) and it might only be a question of time when the next pandemic will rise. Airports need to prepare to cope with the next pandemic efficiently and effectively. For this purpose, we develop a toolbox to analyse and evaluate operational measures along the process chain of travelling at an airport.This paper examines the contamination risks at airports covering the travel process from security checks to aircraft seat. In our study we examine the possibility of an infection by dint of simulation with the Pandemic Simulation Model (Pandemic SiM). For this purpose, we advanced an earlier version of Pandemic SiM that only covered the security check area by adding typical boarding processes of a medium sized European airport. The model is based on a real European airport serving around 12 million passengers per year (in 2019). The simulation model incorporates a new algorithm calculating the probability of spreading a virus (like COVID-19) via droplet, airborne or contact transmission during different airport travel processes along the travel chain. The algorithm considers different infection situations and incidence values and allows for a quantification of infection risks per individual simulated passenger. Based on the output of the simulations of the process chain in combination with that algorithm we can show the effectiveness of measures like social distancing and their consequences to minimize contamination risks along travel processes at airports. The paper describes the modelling, the algorithm to calculate contamination risks, as well as results and findings of the simulation runs. It will show how contamination risks, capacity, waiting times and waiting space are affected. This will provide airport operators with decision support for challenges arising from the need to be prepared for the next pandemic.

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Section: Methodsmentioning

confidence: 99%