Simulation-based capacity analysis for a future airport

Mota, Miguel Mújica; Scala, Paolo; Boosten, Geert

doi:10.1109/apcase.2014.6924479

Cited by 4 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…RETs are taxiways that allow a landing aircraft to vacate the runway earlier and at a higher speed rather than leaving the runway in the end. Thus, the runway occupancy time can be decreased and more efficient use of the runway can be achieved [24]. Cetek et al proposed a new RET in LTBA on the left side of runway 05, and they concluded that some improvements were achieved in the arrival runway occupancy time, the departure and arrival taxi delays, the departure queue delay and the maximum departure queue length in the examined runway configurations [25].…”

Section: Rapid-exit Taxiwaysmentioning

confidence: 99%

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

Özdemir¹,

Çetek²,

Usanmaz³

2018

ANADOLU UNIVERSITY JOURNAL OF SCIENCE AND TECHNOLOGY a - Applied Sciences and Engineering

View full text Add to dashboard Cite

The demand for air transportation increases rapidly each year and introduces serious problems such as system-wide delays and congestions in air traffic operations. Airports, one of the most critical points of the air transportation system, are affected most by these problems. One of the most effective approach to reduce delays and congestions is to improve existing airside capacity of airports through the enhancement of taxiway network around runways. This study investigates the impacts of various rapid-exit and end-around taxiway combinations on capacity and delays for İstanbul Atatürk Airport. Four different runway configurations are analyzed using fast-time simulations for the existing (baseline) and improved (alternative) taxiway network of the airport. The results show that end-around taxiways can decrease departure taxi times up to 52% and rapid-exit taxiways reduce arrival runway occupancy time by 10.6%. Besides, implementations of end-around taxiways can improve runway capacity especially when the airport experiences intense arriving traffic while rapid-exit taxiways improves runway utilization for arrivals.

show abstract

Section: Rapid-exit Taxiwaysmentioning

confidence: 99%

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

Özdemir¹,

Çetek²,

Usanmaz³

2018

ANADOLU UNIVERSITY JOURNAL OF SCIENCE AND TECHNOLOGY a - Applied Sciences and Engineering

View full text Add to dashboard Cite

show abstract

“…23 Based on the SIMMOD simulation system, an airport operation under different weather conditions and runway configurations was simulated. 24 Based on the NetLogo simulation tools, a cell transmission model of air traffic flow was established for terminal area, and its basic congestion evaluation rules were discussed. 25,26 Air traffic system is a complex human-centered system, which consists of air traffic controllers, air traffic flow, and airspace environment.…”

Section: Introductionmentioning

confidence: 99%

Forecasting traffic congestion status in terminal areas based on support vector machine

Zhang

Jiang

Yang

2016

Advances in Mechanical Engineering

View full text Add to dashboard Cite

This article researches on a traffic congestion status forecasting method to improve the real-time monitoring and controlling of air traffic in terminal areas. First, a traffic congestion status evaluation method was introduced based on a fuzzy Cmeans clustering algorithm, as well as several traffic congestion status evaluation metrics. And then, a traffic congestion status forecasting model was proposed based on support vector machine. Finally, a real case study from a terminal area in China was provided to test and verify the proposed evaluation method and forecasting model. The evaluation results show that traffic congestion status of the terminal area can be classified into five levels: free, smooth, slightly congested, moderately congested, and severely congested. The forecasting results show that the mean absolute error and the cluster accuracy are 0.041% and 92.2%, respectively, which indicate that the forecasting model is very effective and accurate. In addition, it is also found that the parameters of forecasting period and size of training set have some influence on forecasting results, and the optimal results can be found when the two parameters values are 15 and 3, respectively.

show abstract

Network Effects from Local Performance Improvements in Europe’s Air Transport System

Lubig,

Fricke,

Desart

2024

Communications in Computer and Information Science

View full text Add to dashboard Cite

Simulation-based capacity analysis for a future airport

Cited by 4 publications

References 10 publications

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

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

Forecasting traffic congestion status in terminal areas based on support vector machine

Network Effects from Local Performance Improvements in Europe’s Air Transport System

Contact Info

Product

Resources

About