IEEE Access · 2020 · 33 citations · 48 references
Public HealthInfectious Disease ControlInfectious DiseasesInfection PreventionTransportTransportationEvacuation SimulationPassenger TransportSocial DistanceTransport ModelingTransport SafetyTravel BehaviorBoard Performance MetricsBoarding ArrangementsBus TransportPassenger Boarding DesignRiskSocial Distancing BehaviorStochastic Process SimulationStochastic Simulation
Social distancing reduces the risk of people becoming infected with the novel coronavirus (SARS-CoV-2). When passengers are transported from an airport terminal to an airplane using apron buses, safe social distancing during pandemic times reduces the capacity of the apron buses and has led to the practice of airlines keeping the middle seats of the airplanes unoccupied. This article adapts classical boarding methods so that they may be used with social distancing and apron buses. We conduct stochastic simulation experiments to assess nine adaptations of boarding methods according to four performance metrics. Three of the metrics are related to the risk of the virus spreading to passengers during boarding. The fourth metric is the time to complete boarding of the two-door airplane when apron bus transport passengers to the airplane. Our experiments assume that passengers advancing to their airplane seats are separated by an aisle social distance of 1 m or 2 m. Numerical results indicate that the three variations (adaptations) of the Reverse pyramid method are the best candidates for airlines to consider in this socially distanced context. The particular adaptation to use depends on an airline's relative preference for having short boarding times versus a reduced risk of later boarding passengers passing (and thereby possibly infecting) previously seated window seat passengers. If an airline considers the latter risk to be unimportant, then the Reverse pyramid - Spread method would be the best choice because it provides the fastest time to board the airplane and is tied for the best values for the other two health risk measures.
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How simulation modelling can help reduce the impact of COVID-19
Christine Currie, John Fowler, Kathy Kotiadis et al. · Journal of Simulation · 2020 · 434 citations · Full text
Public Health, Infectious Disease Control, Infectious Diseases +17
Stefano M. Iacus, Fabrizio Natale, Carlos Santamaría et al. · PUBLISSO (German National Library of Medicine) · 2020 · 358 citations · Full text
Milad Haghani, Michiel C.J. Bliemer, Floris Goerlandt et al. · Safety Science · 2020 · 270 citations · Full text