Traffic synchronization in terminal airspace to enable continuous descent operations in trombone sequencing and merging procedures: An implementation study for Frankfurt airport

Sáez, Raúl; Prats, Xavier; Polishchuk, Tatiana; Polishchuk, Valentin

doi:10.1016/j.trc.2020.102875

Cited by 34 publications

(20 citation statements)

References 24 publications

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“…• Timeliness constraint Time efficiency is another important dimension from airline's perspective. Therefore, when planning a trajectory, the city-pair flight time should be kept within an acceptable range, as shown in Formula (21).…”

Section: • Climb and Descent Performance Constraintsmentioning

confidence: 99%

“…The meanings and expressions of altitude constraints, speed constraints, climb and descent constraints, and time constraints in Model II are the same as those in Model I, as shown in Formulas ( 15)- (21). Due to capacity limitation, this model shall guarantee that all the aircraft enter the sectors within available time slots, as shown in Formula (22).…”

Section: Constraintsmentioning

confidence: 99%

“…In order to reduce fuel consumption and exhaust emissions during taxiing on the airport surface, push-back control strategy [11,12], taxiing trajectory and speed profile optimizations [13,14], and improvement of taxiing mode (e.g., single-engine taxiing, operational tow-outs, and electric taxiing) [15,16] have been comprehensively investigated. During climb and descent, especially in high-density terminal airspace, prior research has focused more on how to make full use of runway capacity, while minimizing noise, total fuel consumption, emissions, and delays [17][18][19], and put forward operating concepts and operating procedures such as Continuous Climbing Operation (CCO) [20], Continuous Descending Operation (CDO) [21], Point Merge (PM) [22], etc. Prats et al [23] presented a non-linear multi-objective optimal control methodology to design noise abatement procedures aimed at reducing the global annoyance perceived by the population living around the airports.…”

Section: Introductionmentioning

confidence: 99%

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Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Liu

Xie

et al. 2021

Sustainability

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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.

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Section: • Climb and Descent Performance Constraintsmentioning

confidence: 99%

Section: Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Liu

Xie

et al. 2021

Sustainability

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“…The results shown in this paper could become an important technical enabler for future FMS capable of advanced 4D trajectory negotiation and synchronization with enhanced AMAN systems, which would ultimately aim to maximize the number of executed CDOs, even during high peaks of incoming traffic. See for instance the research done in [36], where accurate CTA fulfillment is a key element to schedule traffic in a 4D trajectory synchronization paradigm based on tromboning procedures; or more recently in [37], where a novel methodology is proposed based on a pre-sequencing area used to assign CTA to all incoming traffic, followed by a dynamic-trajectories area designed to optimize the sequencing and merging operations. Funding: This research was funded by "la Caixa" Foundation: International mobility grant for students.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity-Based Non-Linear Model Predictive Control for Aircraft Descent Operations Subject to Time Constraints

2021

Self Cite

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The ability to meet a controlled time of arrival while also flying a continuous descent operation will enable environmentally friendly and fuel efficient descent operations while simultaneously maintaining airport throughput. Previous work showed that model predictive control, a guidance strategy based on a reiterated update of the optimal trajectory during the descent, provides excellent environmental impact mitigation figures while meeting operational constraints in the presence of modeling errors. Despite that, the computational delay associated with the solution of the trajectory optimization problem could lead to performance degradation and stability issues. This paper proposes two guidance strategies based on the theory of neighboring extremals that alleviate this problem. Parametric sensitivities are obtained by linearization of the necessary conditions of optimality along the active optimal trajectory plan to rapidly update it for small perturbations, effectively converting the complex and time consuming non-linear programming problem into a manageable quadratic programming problem. Promising results, derived from more than 4000 simulations, show that the performance of this method is comparable to that of instantaneously recalculating the optimal trajectory at each time sample.

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“…Yang et al ( 1 ) proposed a formulation and solution approach to address the flight arrival and departure scheduling (FAADS) problem under a Performance Based Navigation (PBN) environment. Sáez et al ( 2 ) sequenced traffic in the terminal maneuvering area by means of 4D closed-loop instructions. Xu et al ( 3 ) proposed a collaborative air traffic flow management framework to synchronize demand–capacity balancing.…”

mentioning

confidence: 99%

Data-Driven Method for the Prediction of Estimated Time of Arrival

Gui

Zhang

Peng

et al. 2021

Transportation Research Record: Journal of the Transportation R

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Predicting the estimated time of arrival (ETA) plays an essential role in decision support (conflict detection, arrival sequencing, or trajectory optimization) for air traffic controllers. In this paper, a new multiple stages strategy for ETA prediction is proposed based on radar trajectories, including arrival pattern identification, arrival pattern classification, and flight time estimation. First, an intention-oriented trajectory clustering method is developed based on a new trajectory representation technique. Such a proposed trajectory clustering method can group trajectories into different arrival patterns in an efficient way. Second, an arrival pattern classification model is constructed based on random forest and XGBoost algorithms. Then, a flight time regression model is trained for each arrival pattern by using the XGBoost algorithm. Information on current states, historical states, and traffic situations is considered to build the feature set during these processes. Finally, the arrival operation toward Guangzhou International Airport is chosen as a case study. The results illustrate that the proposed method and feature engineering approach could improve the performance of ETA prediction. The proposed multiple stages strategy is superior to the single-model-based ETA prediction.

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Traffic synchronization in terminal airspace to enable continuous descent operations in trombone sequencing and merging procedures: An implementation study for Frankfurt airport

Cited by 34 publications

References 24 publications

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Sensitivity-Based Non-Linear Model Predictive Control for Aircraft Descent Operations Subject to Time Constraints

Data-Driven Method for the Prediction of Estimated Time of Arrival

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