Determining Air Traffic Complexity – Challenges and Future Development

Air traffic complexity is one of the main drivers of the air traffic controllers’ workload. With the forecasted increase of air traffic, the impact of complexity on the controllers\u27 workload will be even more pronounced in the coming years. The existing models and methods for determining air traffic complexity have drawbacks and issues which are still an unsolved challenge. In this paper, an overview is given of the most relevant literature on air traffic complexity and improvements that can be done in this field. The existing issues have been tackled and new solutions have been given on how to improve the determination of air traffic complexity. A preliminary communication is given on the future development of a novel method for determining air traffic complexity with the aim of designing a new air traffic complexity model based on air traffic controller tasks. The novel method uses new solutions, such as air traffic controller tasks defined on pre-conflict resolution parameters, experiment design, static images of traffic situations and generic airspace to improve the existing air traffic complexity models.</p

İstanbul Yeni Havalimanında End-Around Taksi Yollarının Pist Kapasitesine Etkisinin Analizi

Bu çalışmada tamamlanmasıyla 6 bağımsız pisti ile yıllık 150 milyon yolcuya hizmet vermesi planlanan İstanbul Yeni Havaalanı’nda yer alan End-Around taksi yollarının pist kapasitesine olan etkileri incelenmiştir. Yeni hava alanı ilk etapta 2 bağımsız ve 2 bağımlı pist konfigürasyonu ile hizmete alınacaktır. Havaalanında aynı zamanda pist kapasitelerini arttırmak için End-Around taksi yolları da bulunmaktadır. End-Around taksi yolları uçaklara kullanılan pisti kat etmeden taksi imkanı sunmaktadır. Pist kat edişler kullanılan pistin kapasitesini azaltmaktadır. Bu çalışmada pist kat edişlerin pist kapasitesine olan etkisi araştırılmıştır. Çalışmada İstanbul Yeni Havaalanı Simmod kesikli zamanlı simülasyon ortamında temel ve alternatif senaryolar ile modellenmiştir. Temel senaryoda yeni havaalanı End-Around taksi yolları bulunmadığı varsayımı ile modellenmiştir. Alternatif senaryoda ise aynı durum End-Around taksi yolları varken modellemiştir. Bu sayede pist kat edişlerin kapasiteye olan olumsuz etkisi incelenmiş ve bu olumsuz etkinin End-Around taksi yolları ile iyileştirildiği görülmüştür. Analizler pist kat edişler varken ve yokken pist kapasitelerini göstermektedir

EN-ROUTE AIRSPACE CAPACITY AND TRAFFIC FLOW ENHANCEMENT USING GENETIC ALGORITHMS

Air transportation industry has gone under a rapid and continuous growth for the last four decades. International Civil Aviation Organization (ICAO) and airlines anticipate that annual growth rate of air traffic will be 4.5-5.1% until 2030. Airspace capacity management becomes more critical for the safety, efficiency and sustainable growth of the industry. En-route areas cover the largest portion of the controlled airspace and are subdivided into small segments referred to as ‘en-route sectors’ usually monitored and controlled by a single air traffic controller in the relevant Area Control Center (ACC). When air traffic demand reaches or exceeds the available en-route sector capacity, serious aircraft delays occur at airports or in airspace and lead to system-wide congestions and interruptions in air traffic services, airline flight schedules and airport operations, and therefore result in increased operational costs, passenger dissatisfaction and air traffic controller workload. This study presents a multiple entry point assignment model based on a genetic algorithm to minimize delays and increase throughput of a generic high-altitude en-route sector. The proposed approach intends to use more flexible direct route configuration without changing the sector geometry and provide a framework for a decision support system for air traffic flow and capacity planning and management. The available single entry point sector configuration and its multiple entry point assignment alternatives were compared for various traffic scenarios. Multiple entry point configurations provided up to 10% increase in throughput and significant reductions in average delay per aircraft compared to the single point entry configuration

Airside Capacity Analysis and Evaluation of Istanbul Ataturk Airport Using Fast-Time Simulations

ABSTRACT The role of air transport in transportation system is increasing every year. However, there can be difficulties to meet this increase. Therefore, efforts to resolve the problems in air transport become important. Delays and congestions are seen in the air transport system are among these problems. Airports are one of the most critical points of air transportation system facing these problems. One of the measures to be taken to resolve this problem is improving the existing system. Istanbul Ataturk Airport, the busiest airport in Turkey, often experiences delay and congestion problems. To propose a solution to these problems and to reduce runway occupancy time in Istanbul Ataturk Airport, additional fast-exit taxiways to the runway 05 were constructed. In this study, the impact of infrastructure changes made in Istanbul Ataturk Airport is examined, and traffic flow and capacity analysis is carried out comparing three different runway configurations. In consequence of the construction of additional fast-exit taxiways to the runway 05, airport capacity has increased 1.9 per cent. It is also shown that the high average delay time reduces airport capacity

The Impact of Taxiway System Development Stages on Runway Capacity and Delay under Demand Volatility

This study aims to determine the impact of the International Civil Aviation Organization’s (ICAO) taxiway system development stages on runway capacity and delays in a single-runway airport that serves mixed operations by using a combined approach integrating the capacity-demand estimation analyses. We proposed a generic and systematic approach to taxiway development alternatives based on the ICAO guidelines rather than case-specific improvements presented in previous studies. The Samsun Çarşamba Airport (LTFH), which has the most basic level of taxiway layout, was chosen as a case study. The development stages were modeled and run in a fast-time simulation environment for different traffic scenarios based on historical data. As a result of modelling, average airborne and gate waiting delay of arrivals, queue delay of departures, taxi times, and runway occupation times were obtained. In addition, gate sensitivity and cost-benefit analyses were carried out. A triple exponential smoothing forecast was performed for different scenarios including normal, runway closures, COVID-19, and recovery from COVID-19. Practical capacities of the stages were revealed using the results of simulation and traffic demand forecasts. In addition, we evaluated the potential operational improvements of the stages by modifying a previously presented mathematical model. The proposed approach can assist airport operators in predicting the airport capacity saturation and selecting the best capacity improvement strategy for unexpected events