Real-time optimization of short-term flight profiles to control time of arrival

Gu, Junwei; Tang, Xingmin; Hong, Wangjun; Chen, Ping; Li, Teng

doi:10.1016/j.ast.2018.09.029

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…In numerical experiments, the method in this paper provides significant cost savings over two-stage stochastic programming and deterministic methods. In [19], a nominal flight time optimization strategy through the estimation/solution of delay accumulation was proposed. Through numerical traffic simulation, the feasibility of optimizing the nominal flight time is clearly proven.…”

Section: Overview Of Flight Scheduling Optimization Algorithmsmentioning

confidence: 99%

A Deep Multimodal Fusion and Multitasking Trajectory Prediction Model for Typhoon Trajectory Prediction to Reduce Flight Scheduling Cancellation

Tang,

Qin,

Pan

et al. 2024

J. of Syst. Eng. Electron.

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Natural events have had a significant impact on overall flight activity, and the aviation industry plays a vital role in helping society cope with the impact of these events. As one of the most impactful weather typhoon seasons appears and continues, airlines operating in threatened areas and passengers having travel plans during this time period will pay close attention to the development of tropical storms. This paper proposes a deep multimodal fusion and multitasking trajectory prediction model that can improve the reliability of typhoon trajectory prediction and reduce the quantity of flight scheduling cancellation. The deep multimodal fusion module is formed by deep fusion of the feature output by multiple submodal fusion modules, and the multitask generation module uses longitude and latitude as two related tasks for simultaneous prediction. With more dependable data accuracy, problems can be analysed rapidly and more efficiently, enabling better decision-making with a proactive versus reactive posture. When multiple modalities coexist, features can be extracted from them simultaneously to supplement each other's information. An actual case study, the typhoon Lichma that swept China in 2019, has demonstrated that the algorithm can effectively reduce the number of unnecessary flight cancellations compared to existing flight scheduling and assist the new generation of flight scheduling systems under extreme weather.

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Section: Overview Of Flight Scheduling Optimization Algorithmsmentioning

confidence: 99%

A Deep Multimodal Fusion and Multitasking Trajectory Prediction Model for Typhoon Trajectory Prediction to Reduce Flight Scheduling Cancellation

Tang,

Qin,

Pan

et al. 2024

J. of Syst. Eng. Electron.

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“…The number of passengers carried reaches up to 4.377.670 thousand by increasing 6.9% compared to the previous year whereas the cargo traffic reaches up to 62.487 thousand (The International Air Transport Association [IATA], 2019). In the aviation sector, flight operations, routes and scheduling are planned based on the weather and wind conditions (Franco et al , 2018; González-Arribas et al , 2018; Gu et al , 2019; Cecen et al , 2020; Tatli et al , 2020). Among flight phases, take-off, approach and landing are the most vital stages during air transportation (Carneiro et al , 2016).…”

Section: Introductionmentioning

confidence: 99%

A probabilistic-based analysis for wind distribution determination of a runway

Suzer

Kaba

2021

AEAT

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Purpose The purpose of this study is to describe precisely the wind speed regime and characteristics of a runway of an International Airport, the north-western part of Turkey. Design methodology approach Three different probability distributions, namely, Inverse Gaussian (IG), widely used two-parameter Weibull and Rayleigh distributions in the literature, are used to represent wind regime and characteristics of the runway. The parameters of each distribution are estimated by the pattern search (PS)-based heuristic algorithm. The results are compared with the other three methods-based numerical computation, including maximum-likelihood method, moment method (MoM) and power density method, respectively. To evaluate the fitting performance of the proposed method, several statistical goodness tests including the mostly used root mean square error (RMSE) and chi-squared (X2) are conducted. Findings In the light of the statistical goodness tests, the results of the IG-based PS attain better performance than the classical Weibull and Rayleigh functions. Both the RMSE and X2 values achieved by the IG-based PS method lower than that of Weibull and Rayleigh distributions. It exhibits a better fitting performance with 0.0074 for RMSE and 0.58 × 10−4 for X2 for probability density function (PDF) in 2012 and with RMSE of 0.0084 and X2 of 0.74 × 10−4 for PDF in 2013. As regard the cumulative density function of the measured wind data, the best results are found to be Weibull-based PS with RMSE of 0.0175 and X2 of 3.25 × 10−4 in 2012. However, Weibull-based MoM shows more excellent ability in 2013, with RMSE of 0.0166 and X2 of 2.94 × 10−4. Consequently, it is considered that the results of this study confirm that IG-based PS with the lowest error value can a good choice to model more accurately and characterize the wind speed profile of the airport. Practical implications This paper presents a realistic point of view regarding the wind regime and characteristics of an airport. This study may cast the light on researchers, policymakers, policy analysts and airport designers intending to investigate the wind profile of a runway at the airport in the world and also provide a significant pathway on how to determine the wind distribution of the runway. Originality value Instead of the well-known Weibull distribution for the representing of wind distribution in the literature, in this paper, IG distribution is used. Furthermore, the suitability of IG to represent the wind distribution is validated when compared with two-parameter Weibull and Rayleigh distributions. Besides, the performance and efficiency of PS have been evaluated by comparing it with other methods.

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“…These changes will no doubt impact their operational performance and taskload in terms of tactical radar monitoring, guiding of dynamic aircraft movements while maintaining high operational safety standards [9,26]. To better understand tactical air traffic complexity, researchers have explored various methods such as the study of the aircraft's air route and its conflict characteristics [27][28][29][30], and in the strategic time domain, by studying the air traffic flow patterns via optimisation, mathematical models and network theories in different phases of flight [31][32][33][34][35]. Air traffic complexity is then quantified through methods like the modelling of air traffic flow and analysis of the air transportation network mathematically, so as to better aid [37].…”

Section: Motivationmentioning

confidence: 99%

An eye-hand movement Model for traffic complexity evaluation and monitoring enhancement for air traffic controllers

Wee¹

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Dynamic changes in the field of Air Traffic Management in recent years, coupled with the increasing use of automation and new concepts like 4-Dimensional Trajectory Based Operations (4D-TBO) are being investigated. It is therefore postulated that future Air Traffic Controller (ATCO) tasks would likely be dedicated to performing more tactical monitoring activities presented on radar displays with lesser communication with the flight crew under regular circumstances, changing the way how ATCOs operate. This brings about a new set of challenges to ATCOs, as current approaches to address issues related to an ATCO's tactical control activity both operationally and in training, remain limited, due to the lack of knowledge

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Real-time optimization of short-term flight profiles to control time of arrival

Cited by 10 publications

References 14 publications

A Deep Multimodal Fusion and Multitasking Trajectory Prediction Model for Typhoon Trajectory Prediction to Reduce Flight Scheduling Cancellation

A Deep Multimodal Fusion and Multitasking Trajectory Prediction Model for Typhoon Trajectory Prediction to Reduce Flight Scheduling Cancellation

A probabilistic-based analysis for wind distribution determination of a runway

An eye-hand movement Model for traffic complexity evaluation and monitoring enhancement for air traffic controllers

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