Multi-aircraft optimal 4D online trajectory planning in the presence of a multi-cell storm in development

Seenivasan, Dinesh Babu; Olivares, Alberto; Staffetti, Ernesto

doi:10.1016/j.trc.2019.11.014

Cited by 21 publications

(8 citation statements)

References 11 publications

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“…The aircraft fuel consumption model is constructed based on BADA 3.11 too, and the relevant performance parameters of B747-400 (as shown in Table 4 ) are used as an example to illustrate the model. Firstly, the drag and the thrust of the aircraft can be calculated by (13). Thus the fuel flow rate (kg/min) of the aircraft can be calculated by ( 14) and the fuel consumption of the aircraft can be calculated by (15).…”

Section: Aircraft Fuel Consumption Modelmentioning

confidence: 99%

“…The objectives of trajectory optimization in the cruise phase are usually to reduce the flight distance, balance the airspace capacity, reduce fuel consumption and control the required time of arrival (RTA) of the aircraft [10]- [12]. Seenivasan et al [13] designed a thundercloud circumnavigation method for random weather, which method can realize the rapid trajectory planning of aircraft in the environment of multi-core cumulonimbus and has good real-time performance. Gardi et al [14] combined the task of aircraft trajectory planning with the air traffic management system and proposed a new theory and method of collaborative trajectory planning.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective Four-Dimensional Trajectory Synergetic Optimization Based on Congestion Prediction and NSGA3-SA

et al. 2022

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Synergetic trajectory planning of flights is one of the important goals of trajectory-based operation (TBO), and it is also a method to further improve the utilization of airspace resources with the increasing number of flights in recent years. In order to plan the four-dimensional trajectory (4DT) pretactically and comprehensively, match the flight traffic with airspace capacity, reduce congestion, potential conflicts, and fuel consumption thus improving the efficiency of flights, this paper conducts a method for synergetic trajectory planning in the en-route phase from the perspective of airlines. Firstly, the aircraft performance model, aircraft fuel consumption model, and atmospheric model are constructed according to the base of aircraft data (BADA3.11), and an airspace congestion prediction model is constructed based on the historical flow data of airspace. Secondly, a multi-objective synergetic trajectory planning model is established, and a solution method based on the non-dominated sorting genetic algorithm and simulated annealing algorithm (NSGA3-SA) for the problem of synergetic trajectory planning is designed. The simulation shows that the optimization model and the solution algorithm of NSGA3-SA can reduce fuel consumption by about 4.5% compared to the original flight plans and has a good effect on reducing congestion and avoiding conflicts. The running time of the NSGA3-SA can meet the operational requirements of the pre-tactical trajectory planning. The multi-objective optimization model and the solution algorithm proposed in this paper have great value for the research of flight plan optimization.

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Section: Aircraft Fuel Consumption Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiobjective Four-Dimensional Trajectory Synergetic Optimization Based on Congestion Prediction and NSGA3-SA

et al. 2022

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“…Sun et al conducted studies on realtime route planning for unmanned aerial vehicles (Sun et al, 2011). Seenivasan et al studied route orbit planning in four dimensions for multiple aircraft which considered avoiding storm formation, the procedures and separation minima in the existing airspace and meteorological conditions (Seenivasan et al, 2020). Lu et al conducted studies for route planning for light category aerobatic aircraft (Lu et al, 2013).…”

Section: Literature Review and Motivationmentioning

confidence: 99%

“…Simulated annealing makes more discoveries with its more flexible structure at high temperatures, while focusing on the best solution at lower temperatures. Each step of the simulated annealing algorithm and their explanations are given below (Sarıçiçek and Çelik, 2011):…”

Section: Simulated Annealing Applicationmentioning

confidence: 99%

Aircraft route optimization with simulated annealing for a mixed airspace composed of free and fixed route structures

Aydoğan

Çetek²

2022

AEAT

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Purpose The purpose of this paper is to create a flight route optimization for all flights that aims to minimize the total cost consists of fuel cost, ground delay cost and air delay cost over the fixed route and free route airspaces. Design/methodology/approach Efficient usage of current available airspace capacity becomes more and more important with the increasing flight demands. The efficient capacity usage of an airspace is generally in contradiction to optimum flight efficiency of a single flight. It can only be achieved with the holistic approach that focusing all flights over mixed airspaces and their routes instead of single flight route optimization for a single airspace. In the scope of this paper, optimization methods were developed to find the best route planning for all flights considering the benefits of all flights not only a single flight. This paper is searching for an optimization to reduce the total cost for all flights in mixed airspaces. With the developed optimization models, the determination of conflict-free optimum routes and delay amounts was achieved with airway capacity and separation minimum constraints in mixed airspaces. The mathematical model and the simulated annealing method were developed for these purposes. Findings The total cost values for flights were minimized by both developed mathematical model and simulated annealing algorithm. With the mathematical model, a reduction in total route length of 4.13% and a reduction in fuel consumption of 3.95% was achieved in a mixed airspace. The optimization algorithm with simulated annealing has also 3.11% flight distance saving and 3.03% fuel consumption enhancement. Research limitations/implications Although the wind condition can change the fuel consumption and flight durations, the paper does not include the wind condition effects. If the wind condition effect is considered, the shortest route may not always cause the least fuel consumption especially under the head wind condition. Practical implications The results of this paper show that a flight route optimization as a holistic approach considering the all flight demand information enhances the fuel consumption and flight duration. Because of this reason, the developed optimization model can be effectively used to minimize the fuel consumption and reduce the exhaust emissions of aircraft. Originality/value This paper develops the mathematical model and simulated annealing algorithm for the optimization of flight route over the mixed airspaces that compose of fixed and free route airspaces. Each model offers the best available and conflict-free route plan and if necessary required delay amounts for each demanded flight under the airspace capacity, airspace route structure and used separation minimum for each airspace.

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“…It was essentially a greedy strategy with subjectively prioritizing the importance of objectives. In addition, real-time CDO trajectory control strategies have been investigated in the presence of abnormal operation deviating from the planned path [18], as well as adverse meteorological factors, such as storm [19] and gust [20].…”

Section: Introductionmentioning

confidence: 99%

Multi-Attributes Decision-Making for CDO Trajectory Planning in a Novel Terminal Airspace

Yang

Wang

et al. 2021

Sustainability

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Continuous Descent Operations (CDO) has been recognized as an effective way to significantly reduce fuel burn and noise impact. Designing efficient and flexible arrival routes for generating conflict-free and economical trajectories is a cornerstone for fully achieving CDO by high-level automation in high-density traffic scenarios. In this research, inspired by the Point Merge (PM), we design the Inverted Crown-Shaped Arrival Airspace (ICSAA) and its operational procedures to support Omni-directional CDO. In order to generate optimal conflict-free trajectories for upcoming aircraft in an efficient manner, we established a multi-objective trajectory optimization model solved by Non-dominated Sorting Genetic Algorithm with Elitist Strategy (NSGA-II). The Pareto solutions of minimal fuel consumption and trip time were achieved in single aircraft and highly complex multi-aircraft scenarios. Among all the elements of Pareto front, we obtained an unique solution with Entropy-Weights Method and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) to strike a better trade-off among collision probability, fuel consumption, and trip time, which incorporates both air traffic controller’s and pilot’s interests. The effectiveness of CDO performance improvement and computational efficiency in different scenarios were verified. The ICSAA would be a promising structure that promotes the application of automated and flexible CDO.

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Multi-aircraft optimal 4D online trajectory planning in the presence of a multi-cell storm in development

Cited by 21 publications

References 11 publications

Multiobjective Four-Dimensional Trajectory Synergetic Optimization Based on Congestion Prediction and NSGA3-SA

Multiobjective Four-Dimensional Trajectory Synergetic Optimization Based on Congestion Prediction and NSGA3-SA

Aircraft route optimization with simulated annealing for a mixed airspace composed of free and fixed route structures

Multi-Attributes Decision-Making for CDO Trajectory Planning in a Novel Terminal Airspace

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