ArticleTransportation research. Part C, Emerging technologies2021
Analytical approach to solve the problem of aircraft passenger boarding during the coronavirus pandemic.
Article in Transportation research. Part C, Emerging technologies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A distributionally robust optimization approach for airline integrated recovery under in-flight pandemic transmission risks.Transportation research. Part C, Emerging technologies · 2023Article
- A combined optimization-simulation approach for modified outside-in boarding under COVID-19 regulations including limited baggage compartment capacities.Journal of air transport management · 2023Article
- Impact of perceptions and attitudes on air travel choices in the post-COVID-19 era: A cross-national analysis of stated preference data.Travel behaviour & society · 2023Article
- Multipath-Assisted Radio Sensing and State Detection for the Connected Aircraft Cabin.Sensors (Basel, Switzerland) · 2022Article
- Health risks of airplane boarding methods with apron buses when some passengers disregard safe social distancing.PloS one · 2022Article
- COVID-19 pandemic and air transportation: Successfully navigating the paper hurricane.Journal of air transport management · 2021Article
- Future aircraft turnaround operations considering post-pandemic requirements.Journal of air transport management · 2020Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The corona pandemic significantly changes the processes of aircraft and passenger handling at the airport. In our contribution, we focus on the time-critical process of aircraft boarding, where regulations regarding physical distances between passengers will significantly increase boarding time. The passenger behavior is implemented in a field-validated stochastic cellular automata model, which is extended by a module to evaluate the transmission risk. We propose an improved boarding process by considering that most of the passengers are travel together and should be boarded and seated as a group. The NP-hard seat allocation of groups with minimized individual interactions between groups is solved with a genetic algorithm. Then, the improved seat allocation is used to derive an associated boarding sequence aiming at both short boarding times and low risk of virus transmission. Our results show that the consideration of groups will significantly contribute to a faster boarding (reduction of time by about 60%) and less transmission risk (reduced by 85%) compared to the standard random boarding procedures applied in the pandemic scenario.
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