Sensitivity of Trajectory Prediction in Air Traffic Management

1999 ◽  
Vol 22 (2) ◽  
pp. 219-228 ◽  
Author(s):  
Michael R. Jackson ◽  
Yiyuan J. Zhao ◽  
Rhonda A. Slattery
Keyword(s):  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Trajectory Prediction

A Trajectory Prediction Tool to Support Air Traffic Management

2009 ◽  
Author(s):  
Domenico Accardo ◽  
Antonio Moccia ◽  
Luigi Fiorillo ◽  
Alberto Leardi ◽  
Giuseppe Maresca
Keyword(s):  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Prediction Tool ◽  
Trajectory Prediction

scholarly journals Trajectory prediction for future air traffic management – complex manoeuvres and taxiing

2015 ◽  
Vol 119 (1212) ◽  
pp. 121-143 ◽  
Author(s):  
W. Schuster
Keyword(s):  
Decision Making ◽  
Traffic Management ◽  
Model Performance ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Optimal Decision ◽  
Trajectory Prediction ◽  
Potential Conflict ◽  
Flight Data ◽  
The Future

AbstractThe future air traffic management (ATM) concept envisaged by the Single European Sky ATM Research – SESAR – and the USA equivalent NextGen, mark a paradigm shift from the current reactive approach of ATM towards holistic strategic collaborative decision making. The core of the future ATM concept relies on common situational awareness over potentially large time-horizons, based upon the user operational intent. This is beyond human capabilities and requires the support of automation tools to predict aircraft state throughout the operation and provide support to optimal decision making long before any potential conflict may arise. This is achieved with trajectory predictors and conflict detectors and resolvers respectively. Numerous tools have been developed, typically geared towards addressing specific airborne applications. However, a comprehensive literature search suggests that none of the tools was designed to predict trajectories throughout the entire operation of an aircraft, i.e. gate-to-gate. Yet, such functionality is relevant in the holistic optimisation of aircraft operations. To address this gap, this paper builds on an existing en route trajectory prediction (TP) model and develops novel techniques to predict aircraft trajectories for the transitions between the ground- and enroute-phases of operation and for the ground-phase, thereby enabling gate-to-gate (or enroute -to-enroute) TP. The model is developed on the basis of Newtonian physics and operational procedures. Real recorded data obtained from a flight data record (FDR) were used to estimate some of the input parameters required by the model. The remaining parameters were taken from the BADA 3.7 model. Performance results using these flight data demonstrate that the proposed TP model has the potential to accurately predict gate-to-gate trajectories and to support future ATM applications such as gate-to-gate synchronisation.

scholarly journals An improved 4D trajectory modeling approach for traffic management

2021 ◽  
Author(s):  
Zhou Shen ◽  
Xiaomo Yu
Keyword(s):  
Traffic Flow ◽  
Traffic Safety ◽  
Data Model ◽  
Traffic Management ◽  
Air Transportation ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Trajectory Prediction ◽  
Air Traffic Flow ◽  
Aircraft Performance

Abstract Under the premise that the capability of existing air transportation system can no longer meet the demand of air traffic flow, 4D trajectory operation based on accuracy is the basis of future air traffic management (ATM) system to achieve the optimization of flight trajectory. This article investigates the establishment of a data model system based on aircraft performance and operation procedures, which can be applied to 4D trajectory prediction to greatly reduce or avoid the possibility of flight conflicts in the air, enhance air traffic safety and improve air traffic flow.

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