scholarly journals A Novel Rerouting Planning Model for the Terminal Arrival Routes under the Influence of Convective Weather

2018 ◽  
Vol 2018 ◽  
pp. 1-21
Author(s):  
Ming Zhang ◽  
Xianglu Kong ◽  
Kai Liu ◽  
Xiangyu Li
Keyword(s):  
Weather Conditions ◽  
Air Traffic ◽  
Planning Model ◽  
Air Traffic Flow Management ◽  
Weather Information ◽  
Route Network ◽  
Traffic Delays ◽  
Route Length ◽  
Traffic Flow Management ◽  
Convective Weather

Under convective weather conditions, aircraft rerouting in terminal airspace is essential to ensure flight safety and reduce air traffic delays. Traditional air traffic rerouting approaches do not combine convective weather information using radar image recognition with controller workload, additional fuel consumption, delay loss, time cost, and route length at terminal airspace in tactical ATFM phase for exact rerouting decision. In accordance with the safety and economic principles of the route network in terminal airspace and in consideration of the changes in the speed and height of aircraft in terminal airspace, a multiobjective rerouting planning model is established in this study for terminal airspace under convective weather conditions in tactical air traffic flow management phase. Then traffic simulation is conducted to analyze the capacity and delays of the rerouting in the approach path in Shanghai terminal area. Experimental results indicate that this model can increase airspace capacity and operational efficiency of air traffic compared with the traditional air traffic rerouting approaches.

scholarly journals Interdependent Uncertainty Handling in Trajectory Prediction

Aerospace ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 15
Author(s):  
Thomas Zeh ◽  
Judith Rosenow ◽  
Hartmut Fricke
Keyword(s):  
Weather Conditions ◽  
Air Traffic ◽  
Successful Implementation ◽  
Atmospheric Conditions ◽  
Trajectory Prediction ◽  
Air Traffic Flow Management ◽  
Traffic Flow Management ◽  
Aircraft Trajectory ◽  
System States ◽  
Aircraft Trajectories

The concept of 4D trajectory management relies on the prediction of aircraft trajectories in time and space. Due to changes in atmospheric conditions and complexity of the air traffic itself, the reliable prediction of system states is an ongoing challenge. The emerging uncertainties have to be modeled properly and considered in decision support tools for efficient air traffic flow management. Therefore, the subjacent causes for uncertainties, their effects on the aircraft trajectory and their dependencies to each other must be understood in detail. Besides the atmospheric conditions as the main external cause, the aircraft itself induces uncertainties to its trajectory. In this study, a cause-and-effect model is introduced, which deals with multiple interdependent uncertainties with different stochastic behavior and their impact on trajectory prediction. The approach is applied to typical uncertainties in trajectory prediction, such as the actual take-off mass, non-constant true air speeds, and uncertain weather conditions. The continuous climb profiles of those disturbed trajectories are successfully predicted. In general, our approach is applicable to all sources of quantifiable interdependent uncertainties. Therewith, ground-based trajectory prediction can be improved and a successful implementation of trajectory-based operations in the European air traffic system can be advanced.

Investigation on Evaluation of Terminal Departure Capacity Based on Route Intersection

2013 ◽  
Vol 655-657 ◽  
pp. 2262-2265
Author(s):  
Jian Guo Kong
Keyword(s):  
Mathematical Model ◽  
Traffic Flow ◽  
Air Traffic ◽  
Flow Management ◽  
Air Traffic Flow Management ◽  
Flight Data ◽  
Proposed Model ◽  
Combining Data ◽  
Traffic Flow Management ◽  
Airport Terminal

Air traffic flow management is the key to evaluate airspace capacity reasonably and accurately. Based on the flight features of terminal route intersection, this paper builds a mathematical model for scattered flight of departure aircraft, and then evaluates the terminal capacity based on this model. By combining data from Flight Data Recorder (FDR) and flight schedule with the model, an example-runway 02R of Guangzhou Baiyun airport terminal was given to show the effectiveness of the proposed model.

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