The global air transport system has seen significant growth rates over recent decades. The growing wealth of the world’s population goes along with a substantial increase in travel needs. Global market forecasts foresee the total number of airline passengers to double within the next 20 years. Already by 2014, many airports around the world are facing substantial capacity constraints. Therefore, accommodating this air traffic growth is highly challenging for many of them. Because areas around the airport are not available and/or because of strong public opposition, necessary infrastructure expansion projects cannot be realised in many cases. Therefore, a more efficient utilisation of the existing infrastructure is regarded as one of the key enablers for future air traffic growth.
Five different airport capacity optimisation measures are selected to be analysed because of their promising potential to optimise airport operations. These are the operation of an novel aircraft equipment type with optimised operational performance, an aircraft wake vortex re-categorisation approach, an optimised air traffic management system, an optimisation of the aircraft mix and a diversion of air traffic to alternative airports. The method developed for this study is based on a comparative evaluation. The potential of these measures is therefore identified by comparing it with the baseline scenario with no optimisation measures in place. For the evaluation basis, the airport capacity utilisation is used. To determine the potential of airport capacity optimisation measures to increase maximum aircraft throughput, fast-time air traffic simulation models are used. Because the number of simulation scenarios is very large, the very powerful simulation engine of Simmod PLUS! was selected. In order to cope with the large number of different airport infrastructure systems, generic models were developed. These reflect the airports’ most important features from a capacity point of view. The selection of airports that are used to analyse the potential of the five capacity optimisation measures is based on a clustering analysis. Hierarchical clustering algorithms (k-means and AgNes) are used to identify those airports that are of particular importance because they serve as an important node of the global airport system. The two clusters of 22 intercontinental and 101 continental airports are therefore selected.
This analysis revealed that the five different measures can significantly contribute to an alleviation of the future congestion situation. However, the potential of each measure highly depends on local conditions. In the best-case scenario, average capacity utilisation can be reduced by 36% for the year 2031, compared to the baseline scenario. Instead of only 31%, a total of 86% of the forecasted air traffic growth can be realised in the best-case scenario. Therefore, following this analysis, airport capacity optimisation measures can significantly contribute to the easing of the future capacity utilisation situation of the global air traffic system but are not sufficient, given the forecasting period selected for this study.
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The global air transport system has seen significant growth rates over recent decades. The growing wealth of the world’s population goes along with a substantial increase in travel needs. Global market forecasts foresee the total number of airline passengers to double within the next 20 years. Already by 2014, many airports around the world are facing substantial capacity constraints. Therefore, accommodating this air traffic growth is highly challenging for many of them. Because areas around th...
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