4D-trajectory time windows: definition and uncertainty management

Author:

Rodríguez-Sanz Álvaro,Gómez Comendador Fernando,Arnaldo Valdés Rosa M.,Pérez-Castán Javier A.,González García Pablo,Najar Godoy Mar Najar Godoy

Abstract

PurposeThe use of the 4D trajectory operational concept in the future air traffic management (ATM) system will require the aircraft to meet very accurately an arrival time over a designated checkpoint. To do this, time intervals known as time windows (TW) are defined. The purpose of this paper is to develop a methodology to characterise these TWs and to manage the uncertainty associated with the evolution of 4D trajectories.Design/methodology/approach4D trajectories are modelled using a point mass model and EUROCONTROL’s BADA methodology. The authors stochastically evaluate the variability of the parameters that influence 4D trajectories using Monte Carlo simulation. This enables the authors to delimit TWs for several checkpoints. Finally, the authors set out a causal model, based on a Bayesian network approach, to evaluate the impact of variations in fundamental parameters at the chosen checkpoints.FindingsThe initial results show that the proposed TW model limits the deviation in time to less than 27 s at the checkpoints of an en-route segment (300 NM).Practical implicationsThe objective of new trajectory-based operations is to efficiently and strategically manage the expected increase in air traffic volumes and to apply tactical interventions as a last resort only. We need new tools to support 4D trajectory management functions such as strategic and collaborative planning. The authors propose a novel approach for to ensure aircraft punctuality.Originality/valueThe main contribution of the paper is the development of a model to deal with uncertainty and to increase predictability in 4D trajectories, which are key elements of the future airspace operational environment.

Publisher

Emerald

Subject

Aerospace Engineering

Reference76 articles.

1. Learning the aircraft mass and thrust to improve the ground-based trajectory prediction of climbing flights;Transportation Research Part C: Emerging Technologies,2013

2. BayesFusion (2017), “GeNIe modeler”, available at: www.bayesfusion.com/ (accessed 12 July 2017).

3. A target windows model for managing 4-D trajectory-based operations,2009

4. A particle system for safety verification of free flight in air traffic,2006

5. Parametric sensitivity analysis: a case study in optimal control of flight dynamics,2003

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A market mechanism for multiple air traffic resources;Transportation Research Part E: Logistics and Transportation Review;2023-10

2. Multi-Objective Aircraft Robust Trajectory Optimization Considering Various Predictability Metrics Under Uncertain Wind;IEEE Access;2023

3. Remotely piloted aircraft system flight-plan processing from a risk-based methodology;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2022-09-07

4. Emissions of future conventional aircrafts adopting evolutionary technologies;Journal of Cleaner Production;2022-05

5. A Data-Driven Methodology for Pre-Flight Trajectory Prediction;Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems;2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3