Short/medium-term prediction for the aviation emissions in the en route airspace considering the fluctuation in air traffic demand

2016 ◽  
Vol 48 ◽  
pp. 46-62 ◽  
Author(s):  
Dan Chen ◽  
Minghua Hu ◽  
Ke Han ◽  
Honghai Zhang ◽  
Jianan Yin
Keyword(s):  
Air Traffic ◽  
Medium Term ◽  
Traffic Demand ◽  
Term Prediction ◽  
Aviation Emissions

Potential Traffic Demand in the London Area

1965 ◽  
Vol 69 (652) ◽  
pp. 211-215 ◽  
Author(s):  
A. H. Watson
Keyword(s):  
Air Traffic ◽  
Traffic Demand ◽  
The Third ◽  
Air Space

The June 1963 Report of the Inter-Departmental Committee on the Third London Airport concluded that a third London Airport would be required in the early 1970's, and possibly a fourth soon after 1980. It also brought out that because of the large amounts of air space required for the sequencing areas and approach paths of each airport, and because of limitations imposed by the positioning of the main air traffic routeings, the choice of possible sites within reasonable distance of Central London for the third airport was severely restricted. In a postscript to the Report, it was recognised that after the third airport has taken over a further block of air space, the difficulty of siting a fourth airport would be even more severe.

Medium-Term Prediction of Chaos

2006 ◽  
Vol 96 (4) ◽  
Author(s):  
Christopher C. Strelioff ◽  
Alfred W. Hübler
Keyword(s):  
Medium Term ◽  
Term Prediction

scholarly journals A Method Framework for Automatic Airspace Reconfiguration-Monte Carlo Method for Eliminating Irregular Sector Shapes Generated by Region Growth Method

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3934
Author(s):  
Zhijian Ye ◽  
Fanhe Kong ◽  
Baocheng Zhang ◽  
Wei Gao ◽  
Jianfeng Mao
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Simulated Annealing Algorithm ◽  
Air Traffic ◽  
Traffic Demand ◽  
Dynamic Monte Carlo ◽  
Growth Method ◽  
Annealing Algorithm ◽  
Region Growth ◽  
Irregular Sector

With the growth of air traffic demand in busy airspace, there is an urgent need for airspace sectorization to increase air traffic throughput and ease the pressure on controllers. The purpose of this paper is to develop a method framework that can perform airspace sectorization automatically, reasonably, which can be used as an advisory tool for controllers as an automatic system, especially for eliminating irregular sector shapes generated by simulated annealing algorithm (SAA) based on the region growth method. The two graph cutting method, dynamic Monte Carlo method by changing location of flexible vertices (MC-CLFV) and Monte Carlo method by radius changing (MC-RC) were developed to eliminate irregular sector shapes generated by SAA in post-processing. The experimental results show that the proposed method framework of airspace sectorization (AS) can automatically and reasonably generate sector design schemes that meet the design criteria. Our methodology framework and software can provide assistant design and analysis tools for airspace planners to design airspace, improve the reliability and efficiency of airspace design, and reduce the burden of airspace planners. In addition, this lays the foundation for reconstructing airspace with the more intelligent method.

The Air Traffic Capacity of Two-Dimensional Airspace

1994 ◽  
Vol 47 (1) ◽  
pp. 33-40 ◽  
Author(s):  
S. Ratcliffe
Keyword(s):  
Flow Regulation ◽  
Air Traffic ◽  
Autonomous Control ◽  
Two Dimensional ◽  
Traffic Demand ◽  
Flight Plan ◽  
Traffic Capacity ◽  
Point Of Departure

At the present day European ATC is exercised by a multiplicity of more-or-less autonomous control centres. ‘Flow Regulation’ is used roughly to match traffic demand to the capacity of the en-route ATC and of the destination airport. The ATC authority at the point of departure for a remote destination cannot however give any guarantee that the pilot will be able to follow his chosen trajectory. The filed flight plan and the departure clearance have been described as a ‘licence to get into the sky and see what happens’.

scholarly journals Airspace Capacity Assessment with Augmented Cell Transmission Model

2021 ◽  
Author(s):  
Wei Gao ◽  
Man Liang
Keyword(s):  
Air Traffic ◽  
Mixed Integer ◽  
Transmission Model ◽  
Capacity Assessment ◽  
Fast Time ◽  
Cell Transmission Model ◽  
Traffic Demand ◽  
Airport Capacity ◽  
Cell Transmission ◽  
The Impact

Air traffic congestion is caused by the unbalance between increasing traffic demand and saturating capacity. Flight delay not only causes huge economical lost, but also has very negative environmental impact in the whole air transportation system. In order to identify the impact of extended TMA on airport capacity, an airspace capacity assessment method based on augmented cell transmission model was proposed. Firstly, the airspace structure was modeled with points, segments, layers, and cells. Secondly, mixed integer linear programming model was built up with maximum throughput or capacity as the objective function. Finally, genetic algorithm was used to find the optimal result, and the results were validated by comparing with the fast-time simulation results generated by total airspace and airport modeler (TAAM) software. It is found that the proposed method could achieve a relatively accurate result in a much affordable and fast way. The numerical results could be very helpful for air traffic controllers to analyze the dynamic traffic flow entering and exiting TMA, so as to make decisions via reasonable analysis and do planning in advance by referring to the airport capacity.

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