Sensitivity of Trajectory Prediction in Air Traffic Management

Jackson, Michael R.; Zhao, Yiyuan; Slattery, Rhonda

doi:10.2514/2.4398

Cited by 76 publications

(27 citation statements)

References 11 publications

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“…Covariance analyses provide the standard deviation of the distribution that characterizes the variation between the nominal and stochastic predictions as a function of the statistical properties of the inputs. The covariance of the parametric and time-varying disturbances, and the autocorrelation of time-varying ones, can be used to build the covariance matrix of any state variable throughout the trajectory prediction [11].…”

Section: Quantification Of Trajectory Prediction Uncertaintymentioning

confidence: 99%

Quantification of aircraft trajectory prediction uncertainty using polynomial chaos expansions

Casado

Civita

Vilaplana

et al. 2017

2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)

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Abstract-A novel approach to quantify the uncertainty associated with any aircraft trajectory prediction based on the application of the Polynomial Chaos (PC) theory is presented. The proposed method relies on univariate polynomial descriptions of the uncertainty sources affecting the trajectory prediction process. Those descriptions are used to build the multivariate polynomial expansions that represent the variability of the aircraft state variables along the predicted trajectory. A case study compares the results obtained by a classical Monte Carlo approach with those generated by applying the so-called arbitrary Polynomial Chaos Expansions (aPCE). The results provided herein lead to conclude that this new methodology can be used to accurately quantify trajectory prediction uncertainty with a very low computational effort, enabling the capability of computing the uncertainty of the individual trajectories of a traffic sample of thousands flights within very short time intervals.

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Section: Quantification Of Trajectory Prediction Uncertaintymentioning

confidence: 99%

Quantification of aircraft trajectory prediction uncertainty using polynomial chaos expansions

Casado

Civita

Vilaplana

et al. 2017

2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)

View full text Add to dashboard Cite

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“…Trajectory planning problems have also been studied in the context of air traffic management (ATM) and automation. Reference [40] performed a sensitivity analysis of trajectory prediction for ATM. The aircraft trajectory synthesis problem is studied in [76] to provide some basic tools for air traffic automation.…”

Section: Emergency Aircraft Trajectory Designmentioning

confidence: 99%

Mathematical Models for Aircraft Trajectory Design: A Survey

Delahaye

Puechmorel

Tsiotras

et al. 2014

Lecture Notes in Electrical Engineering

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Air traffic management ensures the safety of flight by optimizing flows and maintaining separation between aircraft. After giving some definitions, some typical feature of aircraft trajectories are presented. Trajectories are objects belonging to spaces with infinite dimensions. The naive way to address such problem is to sample trajectories at some regular points and to create a big vector of positions (and or speeds). In order to manipulate such objects with algorithms, one must reduce the dimension of the search space by using more efficient representations. Some dimension reduction tricks are then presented for which advantages and drawbacks are presented. Then, front propagation approaches are introduced with a focus on Fast Marching Algorithms and Ordered upwind algorithms. An example of application of such algorithm to a real instance of air traffic control problem is also given. When aircraft dynamics have to be included in the model, optimal control approaches are really efficient. We present also some application to aircraft trajectory design. Finally, we introduce some path planning techniques via natural language processing and mathematical programming.

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“…Moreover, the modelling can either be based on the time evolution of the position and velocity of the centre of gravity and of the aircraft attitude and angular velocities (kinematical approach) or based on the forces and moments acting on the aircraft as the direct causes of its motion (kinetic approach). In the ATM environment, a point-mass model has been shown to be the most appropriate approach from the point of view of an air traffic controller [5] For the TP model developed herein, the aircraft is considered as a variable-mass rigid body with a fixed centre of gravity and its motion is modelled using a kinetic approach.…”

Section: The Trajectory Prediction Conceptmentioning

confidence: 99%