Cooperative Route Planning for Multiple Aircraft in a Semifree ATC System

Yang, Yi; Nan, Ying; Tang, Ming

doi:10.1155/2018/3521905

Cited by 3 publications

(5 citation statements)

References 13 publications

(15 reference statements)

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“…When hazardous weather, military activities, space launches, and other activities affect flight conditions, the air traffic control department temporarily designates areas of restricted airspace at various altitudes that cannot be entered by aircraft [ 28 , 29 ]. The restricted airspace is typically defined as a two-dimensional convex or concave polygon [ 30 ]. However, there is a risk that aircraft may enter the suborbital debris hazard zone if they fly along the boundary of a concave polygon.…”

Section: Problem Modelingmentioning

confidence: 99%

Dynamic avoidance decision method for civil aircraft in a suborbital debris hazard zone

Chen,

Diao,

Ren

et al. 2023

PLoS ONE

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Closing the static suborbital debris hazard zone method leads to low airspace resource utilization and long delays for civil aircraft, while the dynamic delineation of suborbital debris hazard zone method can solve the above phenomena. However, the existing research lacks the decision instruction for civil aircraft to avoid the dynamic suborbital debris hazard zone. To address the above problems, this paper creates probability ellipsoids of suborbital debris with different ballistic coefficients in the two-dimensional plane and use the divide-and-conquer algorithm for the dynamic delineation of the suborbital debris hazard zone. The suborbital debris hazard zone is extended outward by 10 km. Subsequently, the standard A* algorithm, the standard Lazy theta* algorithm, the improved Lazy theta* algorithm, and a flight path planning strategy are designed to avoid the suborbital debris hazard zone and provide safe dynamic avoidance commands for civil aircraft with fixed time intervals. The simulation results show that the average area of the dynamically delineated suborbital debris hazard zone is lower than the traditional static no-fly zone; the standard A* algorithm and improved Lazy theta* algorithm provides shorter flight path lengths and flight time and fewer waypoints in windless and windy conditions, respectively.

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Section: Problem Modelingmentioning

confidence: 99%

Dynamic avoidance decision method for civil aircraft in a suborbital debris hazard zone

Chen,

Diao,

Ren

et al. 2023

PLoS ONE

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“…Ruther et al carried out their aircraft route planning studies with a holistic approach that took flight crew and aircraft assignments into account (Ruther et al, 2017). Yang et al worked on real-time route planning that considered all the safety constraints for multiple aircraft (Yang et al, 2018). Sun et al conducted studies on realtime route planning for unmanned aerial vehicles (Sun et al, 2011).…”

Section: Literature Review and Motivationmentioning

confidence: 99%

“…Shudao et al worked on unmanned aerial vehicle route planning and used ant colony optimization methods and simulation methods (Shudao et al , 2012). Xu et al carried out route optimization studies of flights consisting of multiple aircraft types including their aerodynamic effects (Xu et al , 2014). Marzuoli et al developed a data-based optimization process for en route flights (Marzuoli et al , 2014).…”

Section: Literature Review and Motivationmentioning

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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“…Particularly, under the circumstance where passive transducers are loaded on the mobile platform, apart from the solution of target's location, the mobile platform's planning in the maneuvering airspace also exerts great effects on the precision of the target's localization. Based on the different targets and shapes of planned airspace, airspace planning is generally classified into route planning [17][18][19][20][21][22] and region planning [23][24][25][26][27][28][29]. The former one performs the optimal planning of the aircraft's route and tracks by clarifying the starting point and restricting the terminal destination on the basis of the aircraft's overload capacity and GPS localization [18,20] and applying dynamic planning [19], cooperative planning [17,21], etc.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the different targets and shapes of planned airspace, airspace planning is generally classified into route planning [17][18][19][20][21][22] and region planning [23][24][25][26][27][28][29]. The former one performs the optimal planning of the aircraft's route and tracks by clarifying the starting point and restricting the terminal destination on the basis of the aircraft's overload capacity and GPS localization [18,20] and applying dynamic planning [19], cooperative planning [17,21], etc. The latter one conducts graphical or three-dimensional planning of the airspace by confirming the airspace and delimiting restrictions according to the radar's location and range of detection [23,24] on the basis of the application context and purpose, such as cooperative monitoring [24][25][26] or joint air defense [27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

A Novel Airspace Planning Algorithm for Cooperative Target Localization

et al. 2022

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With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and significant role in situation awareness. While, in addition to different passive transducer localization modes and solutions of target’s location, the reasonable planning and optimal layout of passive transducers’ location are other major factors affecting the precision of localization. Planning an optimal airspace for passive transducers is the key problem to improve the monitoring efficiency. This paper proposes the optimal layout algorithm for the cooperative platform in the space based on the geometrical relationship of cooperative localization. For example, the principle of direction location in traditional methods is simple: only two passive sensors can work, but the location accuracy of long-distance targets is low. At the same time, TDOA (Time Difference Of Arrival) location has high accuracy and good stability, but it needs at least three passive sensors to work together, which requires the most resources. In this paper, a platform optimization layout algorithm based on direction and TDOA hybrid positioning is proposed. Compared with direction positioning, it improves the long-distance positioning accuracy, reduces the number of sensors required for TDOA positioning, and reduces the resource occupancy rate. However, the TDOA positioning data mixed with direction positioning data inevitably leads to the decline of overall accuracy. In order to solve these difficulties, the weighted least square method is used to optimize the accuracy. The simulation shows that, within the designated target airspace, the optimal action airspace can be generated automatically based on the platforms’ cooperation mode. If there is no resource limitation, the airspace planning based on TDOA positioning has the highest accuracy for the target. However, in practical application, considering the resource limitation, the hybrid positioning of direction and TDOA can also meet the requirements of high accuracy and high stability. The average error is reduced by more than 45% compared with direction positioning, and the airspace occupancy is reduced by more than 30% compared with TDOA positioning. The goal of minimizing the scope of platform airspace planning is realized.

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Cooperative Route Planning for Multiple Aircraft in a Semifree ATC System

Cited by 3 publications

References 13 publications

Dynamic avoidance decision method for civil aircraft in a suborbital debris hazard zone

Dynamic avoidance decision method for civil aircraft in a suborbital debris hazard zone

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

A Novel Airspace Planning Algorithm for Cooperative Target Localization

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