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Keywords = trajectory-based operations (TBOs)

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25 pages, 6136 KiB  
Article
Supply and Demand Analysis of Aeronautical Data Link Communications Based on the Scenario of the MR TBO Demonstration: Focusing on Trajectory-Based Operations in the Digital Era
by Nobuo Hongo and Terumitsu Hirata
Aerospace 2025, 12(6), 522; https://doi.org/10.3390/aerospace12060522 - 10 Jun 2025
Viewed by 394
Abstract
This study conducted a basic analysis of the supply and demand of aeronautical data communications, focusing on trajectory-based operation (TBO), which is one of the methods used for improving the efficiency of air traffic in the digital transformation era using a scenario analysis. [...] Read more.
This study conducted a basic analysis of the supply and demand of aeronautical data communications, focusing on trajectory-based operation (TBO), which is one of the methods used for improving the efficiency of air traffic in the digital transformation era using a scenario analysis. Based on a multi-regional TBO project conducted in June 2023, this study estimated the communication demand in the TBO era using scenario analysis, analyzed supply capacity using the aeronautical data communication infrastructure that is in use at present and also in the future, and considered the feasibility and challenges of implementation. We found that it is feasible to use a satellite communication system with internet technology for digital flight plans and air traffic control (ATC) instructions such as altitude and speed changes, as exchanged during TBO. We quantitatively clarified that further development of communication technology and ingenuity of transmission methods are necessary for larger-volume data, such as weather images, which is useful for situational awareness. By clarifying the communication performance requirements of the on-board and terrestrial communication systems required in the TBO era, this study contributes to the realization of TBO for stakeholders who make reasonable and timely decisions regarding the investment needed to introduce this technology. Full article
(This article belongs to the Section Air Traffic and Transportation)
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19 pages, 16987 KiB  
Article
Trajectory Planning Method in Time-Variant Wind Considering Heterogeneity of Segment Flight Time Distribution
by Man Xu, Jian Wang and Qiuqi Wu
Systems 2024, 12(12), 523; https://doi.org/10.3390/systems12120523 - 25 Nov 2024
Viewed by 734
Abstract
The application of Trajectory-Based Operation (TBO) and Free-Route Airspace (FRA) can relieve air traffic congestion and reduce flight delays. However, this new operational framework has higher requirements for the reliability and efficiency of the trajectory, which will be significantly influenced if the analysis [...] Read more.
The application of Trajectory-Based Operation (TBO) and Free-Route Airspace (FRA) can relieve air traffic congestion and reduce flight delays. However, this new operational framework has higher requirements for the reliability and efficiency of the trajectory, which will be significantly influenced if the analysis of wind uncertainty during trajectory planning is insufficient. In the literature, trajectory planning models considering wind uncertainty are developed based on the time-invariant condition (i.e., three-dimensional), which may potentially lead to a significant discrepancy between the predicted flight time and the real flight time. To address this problem, this study proposes a trajectory planning model considering time-variant wind uncertainty (i.e., four-dimensional). This study aims to optimize a reliable and efficient trajectory by minimizing the Mean-Excess Flight Time (MEFT). This model formulates wind as a discrete variable, forming the foundation of the proposed time-variant predicted method that can calculate the segment flight time accurately. To avoid the homogeneous assumption of distributions, we specifically apply the first four moments (i.e., expectation, variance, skewness, and kurtosis) to describe the stochasticity of the distributions, rather than using the probability distribution function. We apply a two-stage algorithm to solve this problem and demonstrate its convergence in the time-variant network. The simulation results show that the optimal trajectory has 99.2% reliability and reduces flight time by approximately 9.2% compared to the current structured airspace trajectory. In addition, the solution time is only 2.3 min, which can satisfy the requirement of trajectory planning. Full article
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17 pages, 5317 KiB  
Article
Seamless Weather Data Integration in Trajectory-Based Operations Utilizing Geospatial Information
by Sang-Il Kim, Donghyun Jin, Jiyeon Kim, Do-Seob Ahn and Kyung-Soo Han
Remote Sens. 2024, 16(19), 3573; https://doi.org/10.3390/rs16193573 - 25 Sep 2024
Cited by 2 | Viewed by 1924
Abstract
In this study, a 4D trajectory weather (4DT-Wx) prototype system was developed and evaluated for effective weather information integration in trajectory-based operation (TBO) environments. The system has two key distinguishing features: multi-model-based trajectory services and buffer zone information provision. We constructed a distributed [...] Read more.
In this study, a 4D trajectory weather (4DT-Wx) prototype system was developed and evaluated for effective weather information integration in trajectory-based operation (TBO) environments. The system has two key distinguishing features: multi-model-based trajectory services and buffer zone information provision. We constructed a distributed processing system using Apache Spark, enabling the efficient processing of large-scale weather data. The performance evaluation demonstrated excellent scalability and efficiency in processing large-scale data. An analysis of the buffer configurations highlighted that buffer zone information is valuable in decision-making processes and has the potential to enhance the system performance. The system’s practical applicability is presented through visualizations of the extracted weather information. This system is expected to enhance aviation safety and operational efficiency, providing a foundation for addressing increasingly complex weather conditions and flight scenarios in the future. The approach presented in this study marks a significant step toward effective TBO implementation and the advancement of future air traffic management. The evaluation of the 4DT-Wx system analyzed the accuracy of weather data processing and the performance of distributed processing, finding that the temperature (T) estimation had the highest accuracy, and that the parallel processing using Apache Spark was most effectively modeled by Ahmed et al.’s model. The findings suggest the potential for further optimization in integrating various weather models and developing algorithms to enhance their utilization. Full article
(This article belongs to the Special Issue International Symposium on Remote Sensing (ISRS2024))
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21 pages, 4615 KiB  
Article
Data-Driven 4D Trajectory Prediction Model Using Attention-TCN-GRU
by Lan Ma, Xianran Meng and Zhijun Wu
Aerospace 2024, 11(4), 313; https://doi.org/10.3390/aerospace11040313 - 17 Apr 2024
Cited by 8 | Viewed by 3837
Abstract
With reference to the trajectory-based operation (TBO) requirements proposed by the International Civil Aviation Organization (ICAO), this paper concentrates on the study of four-dimensional trajectory (4D Trajectory) prediction technology in busy terminal airspace, proposing a data-driven 4D trajectory prediction model. Initially, we propose [...] Read more.
With reference to the trajectory-based operation (TBO) requirements proposed by the International Civil Aviation Organization (ICAO), this paper concentrates on the study of four-dimensional trajectory (4D Trajectory) prediction technology in busy terminal airspace, proposing a data-driven 4D trajectory prediction model. Initially, we propose a Spatial Gap Fill (Spat Fill) method to reconstruct each aircraft’s trajectory, resulting in a consistent time interval, noise-free, high-quality trajectory dataset. Subsequently, we design a hybrid neural network based on the seq2seq model, named Attention-TCN-GRU. This consists of an encoding section for extracting features from the data of historical trajectories, an attention module for obtaining the multilevel periodicity in the flight history trajectories, and a decoding section for recursively generating the predicted trajectory sequences, using the output of the coding part as the initial input. The proposed model can effectively capture long-term and short-term dependencies and repetitiveness between trajectories, enhancing the accuracy of 4D trajectory predictions. We utilize a real ADS-B trajectory dataset from the airspace of a busy terminal for validation. The experimental results indicate that the data-driven 4D trajectory prediction model introduced in this study achieves higher predictive accuracy, outperforming some of the current data-driven trajectory prediction methods. Full article
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28 pages, 13246 KiB  
Article
Multi-Aircraft Cooperative Strategic Trajectory-Planning Method Considering Wind Forecast Uncertainty
by Man Xu, Minghua Hu, Yi Zhou, Wenhao Ding and Qiuqi Wu
Sustainability 2022, 14(17), 10811; https://doi.org/10.3390/su141710811 - 30 Aug 2022
Cited by 5 | Viewed by 1912
Abstract
We address the issue of multi-aircraft cooperative strategic trajectory planning in free-route airspace (FRA) in this study, taking into consideration the impact of time-varying and altitude-varying wind forecast uncertainty. A bi-level planning model was established in response to the properties of the wind. [...] Read more.
We address the issue of multi-aircraft cooperative strategic trajectory planning in free-route airspace (FRA) in this study, taking into consideration the impact of time-varying and altitude-varying wind forecast uncertainty. A bi-level planning model was established in response to the properties of the wind. The upper level focused on minimizing the flight time, while the lower level aimed to reduce potential conflicts. Meanwhile, a heuristic approach based on conflict severity (CS) within the framework of a cooperative co-evolution evolutionary algorithm (CCEA) was proposed to accelerate the convergence speed in view of the complexity of this optimization issue. In order to conduct the experiments, historical data of 1479 flights over western Chinese airspace were retrieved. The number of conflicts, total flight time, total flight time variance, and deviation were used as indicators to evaluate the safety, efficiency, and predictability of the trajectory. When compared to a trajectory in the structured airspace, the optimal solution was conflict-free and reduced the total flight time by about 17.7%, the variance by 11.7%, and the deviation by 37.5%. Additionally, the contrast with the two-stage model demonstrated that the proposed method was entirely meaningful. The outcome of this survey can provide an effective trajectory-planning method, which is crucial for the sustainable development of future air traffic management (ATM). Full article
(This article belongs to the Special Issue Airspace System Planning and Management)
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33 pages, 9969 KiB  
Article
Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints
by Fangzi Liu, Zihong Li, Hua Xie, Lei Yang and Minghua Hu
Sustainability 2021, 13(13), 7043; https://doi.org/10.3390/su13137043 - 23 Jun 2021
Cited by 8 | Viewed by 3440
Abstract
Investigating potential ways to improve fuel efficiency of aircraft operations is crucial for the development of the global air traffic management (ATM) performance target. The implementation of trajectory-based operations (TBOs) will play a major role in enhancing the predictability of air traffic and [...] Read more.
Investigating potential ways to improve fuel efficiency of aircraft operations is crucial for the development of the global air traffic management (ATM) performance target. The implementation of trajectory-based operations (TBOs) will play a major role in enhancing the predictability of air traffic and flight efficiency. TBO also provides new means for aircraft to save energy and reduce emissions. By comprehensively considering aircraft dynamics, available route limitations, sector capacity constraints, and air traffic control restrictions on altitude and speed, a “runway-to-runway” four-dimensional trajectory multi-objective planning method under loose-to-tight heterogeneous constraints is proposed in this paper. Taking the Shanghai–Beijing city pair as an example, the upper bounds of the Pareto front describing potential fuel consumption reduction under the influence of flight time were determined under different airspace rigidities, such as different ideal and realistic operating environments, as well as fixed and optional routes. In the congestion-free scenario with fixed route, the upper bounds on fuel consumption reduction range from 3.36% to 13.38% under different benchmarks. In the capacity-constrained scenario, the trade-off solutions of trajectory optimization are compressed due to limited available entry time slots of congested sectors. The results show that more flexible route options improve fuel-saving potentials up to 8.99%. In addition, the sensitivity analysis further illustrated the pattern of how optimal solutions evolved with congested locations and severity. The outcome of this paper would provide a preliminary framework for predicting and evaluating fuel efficiency improvement potentials in TBOs, which is meaningful for setting performance targets of green ATM systems. Full article
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25 pages, 3470 KiB  
Article
Impact of Trajectories’ Uncertainty in Existing ATC Complexity Methodologies and Metrics for DAC and FCA SESAR Concepts
by Victor Fernando Gomez Comendador, Rosa María Arnaldo Valdés, Andrija Vidosavljevic, Marta Sanchez Cidoncha and Shutao Zheng
Energies 2019, 12(8), 1559; https://doi.org/10.3390/en12081559 - 24 Apr 2019
Cited by 8 | Viewed by 4302
Abstract
The most relevant SESAR 2020 solutions dealing with future Capacity Management processes are Dynamic Airspace Configuration (DAC) and Flight Centric ATC (FCA). Both concepts, DAC and FCA, rely on traffic flow complexity assessment. For this reason, complexity assessments processes, methods and metrics, become [...] Read more.
The most relevant SESAR 2020 solutions dealing with future Capacity Management processes are Dynamic Airspace Configuration (DAC) and Flight Centric ATC (FCA). Both concepts, DAC and FCA, rely on traffic flow complexity assessment. For this reason, complexity assessments processes, methods and metrics, become one of the main constraints to deal with the growing demand and increasing airspace capacity. The aim of this work is to identify the influence of trajectories’ uncertainty in the quality of the predictions of complexity of traffic demand and the effectiveness of Demand Capacity Balance (DCB) airspace management processes, in order to overcome the limitations of existing complexity assessment approaches to support Capacity Management processes in a Trajectory-Based Operations (TBO) environment. This paper presents research conducted within COTTON project, sponsored by the SESAR Joint Undertaking and EU’s Horizon 2020 research and innovation program. The main objective is to deliver innovative solutions to maximize the performance of the Capacity Management procedures based on information in a TBO environment. Full article
(This article belongs to the Special Issue Modelling of Aerospace Vehicle Dynamics)
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32 pages, 12730 KiB  
Article
Bayesian Network Modelling of ATC Complexity Metrics for Future SESAR Demand and Capacity Balance Solutions
by Victor Fernando Gomez Comendador, Rosa Maria Arnaldo Valdés, Manuel Villegas Diaz, Eva Puntero Parla and Danlin Zheng
Entropy 2019, 21(4), 379; https://doi.org/10.3390/e21040379 - 8 Apr 2019
Cited by 12 | Viewed by 6136
Abstract
Demand & Capacity Management solutions are key SESAR (Single European Sky ATM Research) research projects to adapt future airspace to the expected high air traffic growth in a Trajectory Based Operations (TBO) environment. These solutions rely on processes, methods and metrics regarding the [...] Read more.
Demand & Capacity Management solutions are key SESAR (Single European Sky ATM Research) research projects to adapt future airspace to the expected high air traffic growth in a Trajectory Based Operations (TBO) environment. These solutions rely on processes, methods and metrics regarding the complexity assessment of traffic flows. However, current complexity methodologies and metrics do not properly take into account the impact of trajectories’ uncertainty to the quality of complexity predictions of air traffic demand. This paper proposes the development of several Bayesian network (BN) models to identify the impacts of TBO uncertainties to the quality of the predictions of complexity of air traffic demand for two particular Demand Capacity Balance (DCB) solutions developed by SESAR 2020, i.e., Dynamic Airspace Configuration (DAC) and Flight Centric Air Traffic Control (FCA). In total, seven BN models are elicited covering each concept at different time horizons. The models allow evaluating the influence of the “complexity generators” in the “complexity metrics”. Moreover, when the required level for the uncertainty of complexity is set, the networks allow identifying by how much uncertainty of the input variables should improve. Full article
(This article belongs to the Special Issue Bayesian Inference and Information Theory)
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