Passenger-centric airport management via new terminal interior design concepts

Milbredt, Olaf; Castro, André; Ayazkhani, Amir; Christ, Thomas

doi:10.1016/j.trpro.2017.12.008

Cited by 7 publications

(5 citation statements)

References 12 publications

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“…The air transport industry is also trying to mitigate the negative effect of propagated delays by introducing new operational concepts, such as A-CDM and TAM [ 28 ]. Airports need to evolve from today’s perspective where they behave as individual support tools and become components of an integrated airport information architecture to act as holistic decision–support tools for all airport partners [ 29 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of Aircraft Delays on Population Noise Exposure in Airport’s Surroundings

Zijadić

Ganić

Bračić

et al. 2022

IJERPH

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The motivation behind this research was to analyse the consequences of aircraft operations’ delays on cumulative noise levels produced upon the neighbouring communities and to estimate the relative change in the number of people annoyed by aircraft noise. Many studies showed that residents’ reactions to abrupt changes in noise exposure were more intense compared to the anticipated ones. Aircraft delays may cause such abrupt changes in noise exposure by increasing the traffic in some periods compared to the scheduled traffic. The methodology applied includes noise contour development for two different scenarios for intervals where aircraft delays occur. Only delays connected with the Total Airport Management (TAM) were analysed, since such delays can be influenced by airports. The first scenario considered the influence of aircraft operations on population noise exposure without TAM delays, whereas the second one included all delayed flights (actual traffic). The proposed method was tested through case studies of three southeast European airports. The results showed that the highest potential of decrease in the number of people annoyed by the noise was recorded at Niš Airport (59%), followed by Zadar Airport (49%) and Sarajevo Airport (25%). Similar results were obtained in the context of highly annoyed people.

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Section: Literature Reviewmentioning

confidence: 99%

Impact of Aircraft Delays on Population Noise Exposure in Airport’s Surroundings

Zijadić

Ganić

Bračić

et al. 2022

IJERPH

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“…What passengers demand depends on their specific needs. Meeting these needs will become an increasingly competitive endeavour [10]. Online information and electronic booking and payment systems integrating all means of transport should facilitate multimodal travel.…”

Section: Introductionmentioning

confidence: 99%

Passenger Dimensions in Sustainable Multimodal Mobility Services

Duca¹,

Trincone²,

Bagamanova

et al. 2022

Sustainability

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Seamless integration of air segment in the overall multimodal mobility chain is a key challenge to provide more efficient and sustainable transport services. Technology advances offer a unique opportunity to build a new generation of transport services able to match the evolving expectations and needs of society as a whole. In this context, the passenger-centric approach represents a method to inform the design of future mobility services, supporting quality of life, security and services to citizens traveling across Europe. Relying on the concepts of inclusive design, context of use and task analysis, in this article, we present a comprehensive methodological framework for the analysis of passenger characteristics to elicit features and requirements for future multimodal mobility services, including air leg, that are relevant from the perspective of passengers. The proposed methodology was applied to a series of specific use cases envisaged for three time horizons, 2025, 2035 and 2050, in the context of a European research project. Then, passenger-focused key performance indicators and related metrics were derived to be included in a validation step, with the aim of assessing the extent of benefit for passengers that can be achieved in the forecasted scenarios. The results of the study demonstrate the relevance of human variability in the design of public services, as well as the feasibility of personalized performance assessment of mobility services.

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“…Different approaches have been proposed to avoid congestions at airports, most of them focused on strategies to reduce waiting times at different points such as check-in and security control (Alodhaibi, Burdett, & Yarlagadda, 2017;Gatersleben & Weij, 1999;Kalakou & Moura, 2015;Milbredt, Castro, Ayazkhani, & Christ, 2017;Nikoue, Marzouli, Clarke, Feron, & Peters, 2015;Wu & Chen, 2019;S.-Z. Zhao, Ni, Wang, & Gao, 2011).…”

Section: Introductionmentioning

confidence: 99%

Airport passenger flow prediction using simulation data farming and machine learning

2021

Proceedings of the 33rd European Modeling &Amp; Simulation Symposium

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Passenger flow management is an important issue at many airports around the world. There are high concentrations of passengers arriving and leaving the airport in waves of large volumes in short periods, particularly in big hubs. This might cause congestion in some locations depending on the layout of the terminal building. With a combination of real airport data, as well as synthetic data obtained through an airport simulator, a Long Short-Term Memory Recurrent Neural Network has been implemented to predict the possible trajectories that passengers may travel within the airport depending on user-defined passenger profiles. The aim of this research is to improve passenger flow predictability and situational awareness to make a more efficient use of the airport, that could also positively impact communication with public and private land transport operators.

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Passenger-centric airport management via new terminal interior design concepts

Cited by 7 publications

References 12 publications

Impact of Aircraft Delays on Population Noise Exposure in Airport’s Surroundings

Impact of Aircraft Delays on Population Noise Exposure in Airport’s Surroundings

Passenger Dimensions in Sustainable Multimodal Mobility Services

Airport passenger flow prediction using simulation data farming and machine learning

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