Aerospace

2024

Jump to: 2023, 2022, 2021, 2020, 2019, 2018, 2017

21 pages, 5658 KiB

Open AccessArticle

Pilot Fatigue Coefficient Based on Biomathematical Fatigue Model

by Jingqiang Li, Hongyu Zhu and Annan Liu

Aerospace 2024, 11(11), 950; https://doi.org/10.3390/aerospace11110950 - 18 Nov 2024

Viewed by 383

Abstract

The routine assessment of pilot fatigue is paramount to ensuring aviation safety. However, current designs of pilot fatigue factors often lack the comprehensiveness needed to fully account for the dynamic and cumulative nature of fatigue. To bridge this gap, this study introduces a [...] Read more.

The routine assessment of pilot fatigue is paramount to ensuring aviation safety. However, current designs of pilot fatigue factors often lack the comprehensiveness needed to fully account for the dynamic and cumulative nature of fatigue. To bridge this gap, this study introduces a biomathematical fatigue model (BFM) that leverages system dynamics theory, integrating a dynamic feedback mechanism for fatigue information. The novelty of this approach lies in its capability to continuously capture and model fatigue fluctuations driven by varying operational demands. A comparative analysis with international methodologies for evaluating cumulative fatigue on weekly and monthly scales demonstrates that the proposed BFM effectively reproduces variations in pilot fatigue characteristics. Moreover, the pilot fatigue coefficient derived from the model provides a robust differentiation of fatigue profiles across diverse work types, making it particularly suitable for estimating cumulative fatigue over monthly intervals. This BFM-based approach offers valuable insights for the strategic planning of flight schedules and establishes an innovative framework for utilizing BFMs in fatigue management. By employing a scientifically grounded evaluation method rooted in system dynamics and the BFM, this study rigorously assesses cumulative pilot fatigue, confirming the model’s accuracy in replicating fatigue patterns and validating the efficiency and reliability of the derived fatigue coefficient. Full article

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11 pages, 1112 KiB

Open AccessArticle

Fuel Efficiency Evaluation of A380 Aircraft through Comparative Analysis of Actual Flight Data of the A380–800 and A350–900

by Sungwoo Jang, Seongjoo Yoon and Jae Leame Yoo

Aerospace 2024, 11(8), 665; https://doi.org/10.3390/aerospace11080665 - 13 Aug 2024

Viewed by 2764

Abstract

The Airbus A380 was initially expected to replace existing aircraft due to its remarkable fuel efficiency on long-haul routes when operating with a full passenger load. However, recent changes in the commercial aviation environment have resulted in a decrease in demand for four-engine [...] Read more.

The Airbus A380 was initially expected to replace existing aircraft due to its remarkable fuel efficiency on long-haul routes when operating with a full passenger load. However, recent changes in the commercial aviation environment have resulted in a decrease in demand for four-engine aircraft. Rising fuel prices have pushed airlines to focus on more efficient operations, while manufacturers prioritize producing advanced twin-engine aircraft. The debate over the long-term economic viability of A380 operations remains ongoing. This study compares and evaluates the fuel efficiency of the Airbus A380 and the Airbus A350 using actual flight data. The analysis employs a fuel efficiency prediction model to compare scenarios based on identical payload and load factor. Results indicate that the A350 is approximately twice as fuel efficient as the A380 under the same payload and about 1.34 times more efficient under the same load factor. The A380’s economic viability is analyzed by considering the balance between revenue per available ton-kilometer (RASK) and cost per available ton-kilometer (CASK). If the A380’s RASK is significantly higher than 1.34 times the A350’s or exceeds its own CASK, it can sustain operations. Achieving a balance between RASK and CASK is essential for the economic sustainability of A380 operations. Full article

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28 pages, 27790 KiB

Open AccessArticle

A Novel Aircraft Trajectory Generation Method Embedded with Data Mining

by Xuhao Gui, Junfeng Zhang, Xinmin Tang, Daniel Delahaye and Jie Bao

Aerospace 2024, 11(8), 648; https://doi.org/10.3390/aerospace11080648 - 9 Aug 2024

Cited by 1 | Viewed by 917

Abstract

Data mining has achieved great success in air traffic management as a technology for learning knowledge from historical data that benefits people. However, data mining can rarely be embedded into the trajectory optimization process since regular optimization algorithms cannot utilize the functional and [...] Read more.

Data mining has achieved great success in air traffic management as a technology for learning knowledge from historical data that benefits people. However, data mining can rarely be embedded into the trajectory optimization process since regular optimization algorithms cannot utilize the functional and implicit knowledge extracted from historical data in a general paradigm. To tackle this issue, this research proposes a novel data mining-based trajectory generation method that is compatible with existing optimization algorithms. Firstly, the proposed method generates trajectories by combining various maneuvers learned from operation data instead of reconstructing trajectories with generative models. In such a manner, data mining-based trajectory optimization can be achieved by solving a combinatorial optimization problem. Secondly, the proposed method introduces a majorization–minimization-based adversarial training paradigm to train the generation model with more general loss functions, including non-differentiable flight performance constraints. A case study on Guangzhou Baiyun International Airport was conducted to validate the proposed method. The results illustrate that the trajectory generation model can generate trajectories with high fidelity, diversity, and flyability. Full article

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22 pages, 3270 KiB

Open AccessArticle

Multi-Task Dynamic Spatio-Temporal Graph Attention Network: A Variable Taxi Time Prediction Model for Airport Surface Operation

by Xiaoyi Yang, Hongyu Yang, Yi Mao, Qing Wang and Suwan Yin

Aerospace 2024, 11(5), 371; https://doi.org/10.3390/aerospace11050371 - 8 May 2024

Viewed by 1161

Abstract

Variable taxi time prediction is the core of the Airport Collaborative Decision Making (A-CDM) system. An accurate taxi time prediction contributes to enhancing airport operational efficiency, safety and predictability. The deep dynamic spatio-temporal correlation inherent in airport traffic data is critical for taxi [...] Read more.

Variable taxi time prediction is the core of the Airport Collaborative Decision Making (A-CDM) system. An accurate taxi time prediction contributes to enhancing airport operational efficiency, safety and predictability. The deep dynamic spatio-temporal correlation inherent in airport traffic data is critical for taxi time prediction. However, existing machine learning (deep learning) methods have been unable to thoroughly exploit these correlations. To address this issue, we propose a deep learning-based model called the multi-task dynamic spatio-temporal graph attention network (MT-DSTGAN). Our model also predicts future entire airport traffic flow and taxiing segment traffic flow as auxiliary tasks, with the goal of enhancing the accuracy of aircrafts’ taxi time prediction. The proposed MT-DSTGAN model is implemented and assessed through a case study of Beijing Capital International Airport with a real-world dataset. The advantage of the proposed model, which shows better performance in various evaluation metrics, is demonstrated in a comparative study with other baseline works. In summary, the proposed MT-DSTGAN exhibits promising capabilities in perceiving the dynamic changes in the taxiing process of aircraft and demonstrates the ability to capture complex spatio-temporal correlations in airport traffic data. Full article

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26 pages, 8415 KiB

Open AccessArticle

An Autonomous Tow Truck Algorithm for Engineless Aircraft Taxiing

by Stefano Zaninotto, Jason Gauci and Brian Zammit

Aerospace 2024, 11(4), 307; https://doi.org/10.3390/aerospace11040307 - 14 Apr 2024

Cited by 1 | Viewed by 1725

Abstract

The aviation industry has proposed multiple solutions to reduce fuel consumption, air pollution, and noise at airports, one of which involves deploying electric trucks for aircraft towing between the stand and the runway. However, the introduction of tow trucks results in increased surface [...] Read more.

The aviation industry has proposed multiple solutions to reduce fuel consumption, air pollution, and noise at airports, one of which involves deploying electric trucks for aircraft towing between the stand and the runway. However, the introduction of tow trucks results in increased surface traffic, posing challenges from the perspective of air traffic controllers (ATCOs). Various solutions involving automated planning and execution have been proposed, but many are constrained by their inability to manage multiple active runways simultaneously, and their failure to account for the tow truck battery state of charge during assignments. This paper presents a novel system for taxi operations that employs autonomous tow trucks to enhance ground operations and address deficiencies in existing approaches. The system focuses on identifying conflict-free solutions that minimise taxi-related delays and route length while maximising the efficient use of the tow trucks. The algorithm operates at a strategic level and uses a centralised approach. It has the capacity to cater for multiple active runways and considers factors such as the tow truck battery state of charge and availability of charging stations. Furthermore, the proposed algorithm is capable of scheduling and routing tow trucks for aircraft taxiing without generating traffic conflicts. Full article

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2023

Jump to: 2024, 2022, 2021, 2020, 2019, 2018, 2017

17 pages, 2988 KiB

Open AccessArticle

Untangling Complexity in ASEAN Air Traffic Management through Time-Varying Queuing Models

by Eri Itoh, Koji Tominaga, Michael Schultz and Vu N. Duong

Aerospace 2024, 11(1), 11; https://doi.org/10.3390/aerospace11010011 - 22 Dec 2023

Cited by 1 | Viewed by 1599

Abstract

Free route airspace allows airspace users to freely plan a route in en-route airspaces within certain restrictions. It is anticipated to offer the benefit of fuel saving and operational flexibility. Regarding its efficient implementation into the ASEAN airspace, the key challenge would be [...] Read more.

Free route airspace allows airspace users to freely plan a route in en-route airspaces within certain restrictions. It is anticipated to offer the benefit of fuel saving and operational flexibility. Regarding its efficient implementation into the ASEAN airspace, the key challenge would be reducing hotspots with clusters of potential conflicts. This paper designed a time-varying queuing network model, which contributed to untangle trajectory complexity in the most congested hotspot area. A series of fast-time simulation experiments were conducted to identify hotspots in en-route airspace in Singapore FIR. The application of departure time control using time-varying queuing networks successfully reduced up to 45% of potential conflicts. This was achieved within an average delay of 30 min by controlling time of less than 60% of candidate flights. The original contribution of this paper is to develop a novel modeling and simulation framework for composing ideal air traffic patterns. Lastly, we discussed the extension of this study toward a generalized application of the proposed approach in future air traffic management. Full article

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24 pages, 8189 KiB

Open AccessArticle

Delay in the Air or Detour on the Ground?—A Case Study in Guangzhou Baiyun International Airport

by Zhuoming Du, Junfeng Zhang, Zhao Ma and Jiaxin Xu

Aerospace 2024, 11(1), 10; https://doi.org/10.3390/aerospace11010010 - 22 Dec 2023

Viewed by 1453

Abstract

Collaboration between terminal airspace and airport surface operation shows an increasing significance for the best efficiency of both parts of the air traffic management domain. Runways play a critical role in connecting the two parts for departure and arrival aircraft. Suppose the gate [...] Read more.

Collaboration between terminal airspace and airport surface operation shows an increasing significance for the best efficiency of both parts of the air traffic management domain. Runways play a critical role in connecting the two parts for departure and arrival aircraft. Suppose the gate and the entry fix of an aircraft are predetermined according to the flight plan, and they are on the opposite side of the airport terminal. The aircraft will either spend more time (i.e., delay in the air) landing on a runway close to its gate or take a longer distance (i.e., detour on the ground) taxiing to its gate if a runway close to its entry fix is assigned. This paper proposes a runway assignment model considering terminal airspace operation and airport surface movement simultaneously to discover how runway assignments can affect integrated operations. Four different runway assignment schemes are applied in this model. Subsequently, a metaheuristic method is proposed to solve the model. Furthermore, the historical taxiing and flight time data are analyzed to demonstrate the potential benefits of runway reassignment. Finally, the results show that the free assignment of the runway stands out among the four schemes, not only in the performance of terminal airspace operation (lower flight time) but also in airport surface movement (lower pushback delay, taxi time). Full article

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26 pages, 2404 KiB

Open AccessArticle

Integrating Flight Scheduling, Fleet Assignment, and Aircraft Routing Problems with Codesharing Agreements under Stochastic Environment

by Kübra Kızıloğlu and Ümit Sami Sakallı

Aerospace 2023, 10(12), 1031; https://doi.org/10.3390/aerospace10121031 - 14 Dec 2023

Viewed by 1839

Abstract

Airlines face the imperative of resource management to curtail costs, necessitating the solution of several optimization problems such as flight planning, fleet assignment, aircraft routing, and crew scheduling. These problems present some challenges. The first pertains to the common practice of addressing these [...] Read more.

Airlines face the imperative of resource management to curtail costs, necessitating the solution of several optimization problems such as flight planning, fleet assignment, aircraft routing, and crew scheduling. These problems present some challenges. The first pertains to the common practice of addressing these problems independently, potentially leading to locally optimal outcomes due to their interconnected nature. The second challenge lies in the inherent uncertainty associated with parameters like demand and non-cruise time. On the other hand, airlines can employ a strategy known as codesharing, wherein they operate shared flights, in order to minimize these challenges. In this study, we introduce a novel mathematical model designed to optimize flight planning, fleet assignment, and aircraft routing decisions concurrently, while accommodating for codesharing. This model is formulated as a three-stage non-linear mixed-integer problem, with stochastic parameters representing the demand and non-cruise time. For smaller-scale problems, optimization software can effectively solve the model. However, as the number of flights increases, conventional software becomes inadequate. Moreover, considering a wide array of scenarios for stochastic parameters leads to more robust results; however, it is not enabled because of the limitations of optimization software. In this work, we introduce two new simulation-based metaheuristic algorithms for solving large-dimensional problems, collectively called “simheuristic.” These algorithms integrate the Monte Carlo simulation technique into Simulated Annealing and Cuckoo Search. We have applied these simheuristic algorithms to various problem samples of different flight sizes and scenarios. The results demonstrate the efficacy of our proposed modeling and solution approaches in efficiently addressing flight scheduling, fleet assignment, and aircraft routing problems within acceptable timeframes. Full article

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26 pages, 2535 KiB

Open AccessArticle

Multiple UAS Traffic Planning Based on Deep Q-Network with Hindsight Experience Replay and Economic Considerations

by Shao Xuan Seah and Sutthiphong Srigrarom

Aerospace 2023, 10(12), 980; https://doi.org/10.3390/aerospace10120980 - 22 Nov 2023

Cited by 1 | Viewed by 1347

Abstract

This paper explores the use of deep reinforcement learning in solving the multi-agent aircraft traffic planning (individual paths) and collision avoidance problem for a multiple UAS, such as that for a cargo drone network. Specifically, the Deep Q-Network (DQN) with Hindsight Experience Replay [...] Read more.

This paper explores the use of deep reinforcement learning in solving the multi-agent aircraft traffic planning (individual paths) and collision avoidance problem for a multiple UAS, such as that for a cargo drone network. Specifically, the Deep Q-Network (DQN) with Hindsight Experience Replay framework is adopted and trained on a three-dimensional state space that represents a congested urban environment with dynamic obstacles. Through formalising a Markov decision process (MDP), various flight and control parameters are varied between training simulations to study their effects on agent performance. Both fully observable MDPs (FOMDPs) and partially observable MDPs (POMDPs) are formulated to understand the role of shaping reward signals on training performance. While conventional traffic planning and optimisation techniques are evaluated based on path length or time, this paper aims to incorporate economic analysis by considering tangible and intangible sources of cost, such as the cost of energy, the value of time (VOT) and the value of reliability (VOR). By comparing outcomes from an integration of multiple cost sources, this paper is better able to gauge the impact of various parameters on efficiency. To further explore the feasibility of multiple UAS traffic planning, such as cargo drone networks, the trained agents are also subjected to multi-agent point-to-point and hub-and-spoke network environments. In these simulations, delivery orders are generated using a discrete event simulator with an arrival rate, which is varied to investigate the effect of travel demand on economic costs. Simulation results point to the importance of signal engineering, as reward signals play a crucial role in shaping reinforcements. The results also reflect an increase in costs for environments where congestion and arrival time uncertainty arise because of the presence of other agents in the network. Full article

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20 pages, 2960 KiB

Open AccessArticle

A STAM Model Based on Spatiotemporal Airspace Sector Interdependencies to Minimize Tactical Flow Management Regulations

by Gonzalo Martin, Laura Calvet and Miquel Angel Piera

Aerospace 2023, 10(10), 847; https://doi.org/10.3390/aerospace10100847 - 28 Sep 2023

Cited by 2 | Viewed by 1867

Abstract

The lack of airspace capacity poses a significant challenge for a sustainable air transport system, particularly in scenarios of future growing demand. Air traffic management digitalization opens pathways for innovative and efficient solutions to tackle existing inefficiencies arising from spatially fragmented airspace. While [...] Read more.

The lack of airspace capacity poses a significant challenge for a sustainable air transport system, particularly in scenarios of future growing demand. Air traffic management digitalization opens pathways for innovative and efficient solutions to tackle existing inefficiencies arising from spatially fragmented airspace. While research has focused on digitalized ATM services to improve airspace capacity, synergies among adjacent sectors to utilize latent capacity remain unexplored. Using a sector network model, in this study, we analyze spatiotemporal sector interdependencies, quantify time-stamp topological interdependencies, and evaluate capacity enhancement possibilities for sectors unable to meet dynamic demand. The occupancy count dynamic evolution and poor correlation among the over-loaded sectors with the occupancy count of its adjacent sectors provide opportunities for a short-term ATM mechanism, ensuring sector-level capacity invulnerability and enhancing airspace capacity at the network level. A computational experiment using real data from the European airspace is carried out to illustrate and validate this innovative solution. Full article

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27 pages, 553 KiB

Open AccessArticle

Impact of Higher Airspace Operations on Air Traffic in Europe

by Oliver Pohling, Lorenz Losensky, Sandro Lorenz and Sven Kaltenhäuser

Aerospace 2023, 10(10), 835; https://doi.org/10.3390/aerospace10100835 - 25 Sep 2023

Cited by 3 | Viewed by 1727

Abstract

Historically, higher airspace has been used for military exercises and as transit for space vehicles. Riding on commercial space operations’ coattails, more and more vehicles are under development that will make use of higher airspace resources. This will lead to increasing interactions with [...] Read more.

Historically, higher airspace has been used for military exercises and as transit for space vehicles. Riding on commercial space operations’ coattails, more and more vehicles are under development that will make use of higher airspace resources. This will lead to increasing interactions with conventional air traffic since these new vehicles will have to transit through lower airspaces. The management of these operations is necessary to ensure the safe and practicable shared usage of these airspaces. This paper outlines an assessment of the impact of higher airspace operations on conventional air traffic in Europe. Initially, a synthesis of possible use cases was performed, and demand scenarios were developed that served as input to a fast-time simulation. The impact on air traffic was measured by means of flight efficiency parameters. The simulation results showed that the impact is dependent on the type of operation. High-altitude platform system flights and orbital launches cause the largest deviations in flight distance, flight duration and fuel consumption. Higher airspace operation parameters, including location, time, and duration, strongly affect the impact on the conventional air traffic. Full article

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14 pages, 1207 KiB

Open AccessArticle

Modeling Airport Choice Using a Latent Class Logit Model

by Luigi dell’Olio, Andrés Rodríguez and Silvia Sipone

Aerospace 2023, 10(8), 703; https://doi.org/10.3390/aerospace10080703 - 10 Aug 2023

Cited by 2 | Viewed by 2371

Abstract

Studying the location of an airport is essential for optimizing its functionality, ensuring safety, and maximizing its economic benefits. There are many airports located within a short distance of each other, and users can often choose to travel between one or the other [...] Read more.

Studying the location of an airport is essential for optimizing its functionality, ensuring safety, and maximizing its economic benefits. There are many airports located within a short distance of each other, and users can often choose to travel between one or the other depending on a number of variables that they value for their final choice. In this paper, we design a stated preference survey and estimate a latent class logit model to study user behavior in the choice of nearby airports. The idea is to study if the choice of airport can indeed depend on the characteristics of the users and the purpose of their trip and if factors such as traveling with family, children, or friends can play a role in determining the preferred airport. It is also investigated whether the presence of low-cost airlines or direct connections to the final destinations of the trip (number of transfers) and other factors influence the choice of airport. It is shown that there are two classes of users who have different travel behavior, and that the perception of certain variables influences the choice of the nearest or furthest airport depending on the type of trip. Full article

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13 pages, 939 KiB

Open AccessArticle

Estimating the Cost of Wildlife Strikes in Australian Aviation Using Random Forest Modeling

by Dan Parsons, Jason Ryan, Michael Malouf and Wayne Martin

Aerospace 2023, 10(7), 648; https://doi.org/10.3390/aerospace10070648 - 19 Jul 2023

Cited by 2 | Viewed by 2190

Abstract

Wildlife strikes in aviation represent a serious economic concern; however, in some jurisdictions, the costs associated with this phenomenon are not collected or shared. This hampers the industry’s ability to quantify the risk and assess the potential benefit from investment in effective wildlife [...] Read more.

Wildlife strikes in aviation represent a serious economic concern; however, in some jurisdictions, the costs associated with this phenomenon are not collected or shared. This hampers the industry’s ability to quantify the risk and assess the potential benefit from investment in effective wildlife hazard management activities. This research project has applied machine learning to the problem by training a random forest algorithm on wildlife strike cost data collected in the United States and predicting the costs associated with wildlife strikes in Australia. This method estimated a mean annual figure of AUD 7.9 million in repair costs and AUD 4.8 million in other costs from 2008 to 2017. It also provided year-on-year estimates showing variability through the reporting period that was not correlated with strike report numbers. This research provides a baseline figure for the Australian aviation industry to assess and review current and future wildlife hazard management practices. It also provides a technique for other countries, airlines, or airports to estimate the cost of wildlife strikes within their jurisdictions or operational environments. Full article

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27 pages, 55934 KiB

Open AccessArticle

Linear Contrails Detection, Tracking and Matching with Aircraft Using Geostationary Satellite and Air Traffic Data

by Rémi Chevallier, Marc Shapiro, Zebediah Engberg, Manuel Soler and Daniel Delahaye

Aerospace 2023, 10(7), 578; https://doi.org/10.3390/aerospace10070578 - 21 Jun 2023

Cited by 10 | Viewed by 4784

Abstract

Climate impact models of the non-

{CO}_{2}

emissions of aviation are still subject to significant uncertainties. Condensation trails, or contrails, are one of these non-

{CO}_{2}

effects. In order to validate the contrail simulation models, a dataset of observations covering the [...] Read more.

Climate impact models of the non-

{CO}_{2}

emissions of aviation are still subject to significant uncertainties. Condensation trails, or contrails, are one of these non-

{CO}_{2}

effects. In order to validate the contrail simulation models, a dataset of observations covering the entire lifetime of the contrails will be required, as well as the characteristics of the aircraft which produced them. This study carries on the work on contrail observation from geostationary satellite by proposing a new way to track contrails and identify the flight that produced it using geostationary satellite infrared images, weather data as well as air traffic data. It solves the tracking and the identification problem as one, each process leveraging information from the other to achieve a better overall result. This study is a new step towards a consistent contrail dataset that could be used to validate contrail models. Full article

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24 pages, 3332 KiB

Open AccessArticle

Data-Driven Modeling of Air Traffic Controllers’ Policy to Resolve Conflicts

by Alevizos Bastas and George A. Vouros

Aerospace 2023, 10(6), 557; https://doi.org/10.3390/aerospace10060557 - 13 Jun 2023

Viewed by 2008

Abstract

With the aim to enhance automation in conflict detection and resolution (CD&R) tasks in the air traffic management (ATM) domain, this article studies the use of artificial intelligence and machine learning (AI/ML) methods to learn air traffic controllers’ (ATCOs) policy in resolving conflicts [...] Read more.

With the aim to enhance automation in conflict detection and resolution (CD&R) tasks in the air traffic management (ATM) domain, this article studies the use of artificial intelligence and machine learning (AI/ML) methods to learn air traffic controllers’ (ATCOs) policy in resolving conflicts among aircraft assessed to violate separation minimum constraints during the en route phase of flights, in the tactical phase of operations. The objective is to model

h o w

conflicts are being resolved by ATCOs. Towards this goal, the article formulates the ATCO policy learning problem for conflict resolution, addresses the challenging issue of an inherent lack of information in real-world data, and presents AI/ML methods that learn models of ATCOs’ behavior. The methods are evaluated using real-world datasets. The results show that AI/ML methods can achieve good accuracy on predicting ATCOs’ actions given specific conflicts, revealing the preferences of ATCOs for resolution actions in specific circumstances. However, the high accuracy of predictions is hindered by real-world data-inherent limitations. Full article

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28 pages, 8008 KiB

Open AccessArticle

Preliminary Feasibility Study of the Ad Hoc Separation Operational Concept

by Lidia Serrano-Mira, Luis Pérez Sanz, Javier A. Pérez-Castán, Fedja Netjasov, Irene García Moreno and Eduardo S. Ayra

Aerospace 2023, 10(6), 539; https://doi.org/10.3390/aerospace10060539 - 5 Jun 2023

Cited by 2 | Viewed by 1590

Abstract

The expected growth of air traffic in the coming decades demands an increase in airspace capacity, which is already close to saturation in many scenarios. One of the limiting factors of this capacity is the separation minima. At present, the separation standards that [...] Read more.

The expected growth of air traffic in the coming decades demands an increase in airspace capacity, which is already close to saturation in many scenarios. One of the limiting factors of this capacity is the separation minima. At present, the separation standards that apply in a given volume of airspace are fixed, and their values were determined decades ago. Therefore, in order to increase airspace capacity, this is an area in which improvement is sought, namely through the implementation of new operational concepts, which include the redefinition of separation minima and the way they are applied. A key issue in this redefinition of separation minima is the question of the possibility of reducing the current standards. However, a reduction in the separation to a fixed value may not be a valid solution, as not all aircraft and ways of operation are the same. In this paper, the authors propose a new operational concept, the Ad Hoc or Variable separation minima. Ad Hoc separation refers to the application of different separation minima values in the same volume of airspace, depending on a set of factors, e.g., aircraft model and encounter geometry, among others. In this research, the factors that define these Ad Hoc separation minima and their relationships are discussed. A model for their determination is presented. Simulations are performed to analyze the operational feasibility of the Ad Hoc separation minima. The results show that the application of this concept is operationally feasible. Full article

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30 pages, 49090 KiB

Open AccessArticle

GIS-Based Determination of the Optimal Heliport and Water Source Locations for Forest Fire Suppression Using Multi-Objective Programming

by Erdem Emin Maraş, Kadir Dönmez and Yeliz Emecen

Aerospace 2023, 10(3), 305; https://doi.org/10.3390/aerospace10030305 - 19 Mar 2023

Cited by 4 | Viewed by 2290

Abstract

First responders to forest fires, especially in areas that cannot be reached by land, are carried out by helicopters. In large forest lands, the necessity of helicopters to reach fire areas in the shortest time reveals the importance of heliport locations. In this [...] Read more.

First responders to forest fires, especially in areas that cannot be reached by land, are carried out by helicopters. In large forest lands, the necessity of helicopters to reach fire areas in the shortest time reveals the importance of heliport locations. In this study, the set-covering problem is handled by optimizing heliport locations in a heavily forested Milas district of Muğla, Turkey, where forest fires have occurred severely in recent years. The aim is to cover the entire region with a minimum number of heliports within specified response times. The forest density of the relevant region is integrated as weights into the mathematical model based on geographic information systems (GIS) during location-allocation. In addition, several conditions related to the study area, such as their proximity to roads, distance to settlement areas, slope, wetlands, altitude, the existence of heliports or airports, and others, were defined on 2 × 2 km grids and analyzed in ArcGIS for use in mathematical modeling, which was developed as a multi-objective programming model. In the first model, different initial attack (IA) times are considered, and the tradeoffs between IA time coverages and heliport locations are revealed by using the ɛ constraint method. Then, in the second model, the water sources are evaluated to provide recommendations for further extended attack (EA) and additional water sources (pools) considering the existing ones. Mathematical modeling is used to determine Pareto optimal heliport and additional water source locations for both IA and EA in the forest fires, respectively. Finally, the potential savings of the proposed model are quantified by comparing the model results with the current locations of the helicopters and water sources based on historical fire data. Full article

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69 pages, 38982 KiB

Open AccessArticle

Predictive Analysis of Airport Safety Performance: Case Study of Split Airport

by Dajana Bartulović and Sanja Steiner

Aerospace 2023, 10(3), 303; https://doi.org/10.3390/aerospace10030303 - 17 Mar 2023

Cited by 5 | Viewed by 2857

Abstract

A predictive safety management methodology implies steps and tools of predictive safety management in aviation, i.e., use of predictive (forecasting) and causal modeling methods to identify potential and possible hazards in the future, as well as their causal factors which can help define [...] Read more.

A predictive safety management methodology implies steps and tools of predictive safety management in aviation, i.e., use of predictive (forecasting) and causal modeling methods to identify potential and possible hazards in the future, as well as their causal factors which can help define timely and efficient mitigation measures to prevent or restrain emerging hazards turning into adverse events. The focus of this paper is to show how predictive analysis of an organization’s safety performance can be conducted, on the sample airport. A case study regarding implementation of predictive analysis of an organization’s safety performance, was performed at Split Airport. The predictive analysis of an airport’s safety performance was conducted through the analysis of Split Airport safety database, causal modeling of Split Airport organizational and safety performance indicators, outlier root cause analysis of Split Airport safety performance indicators, predictive analysis of safety performance (forecasting of Split Airport organizational and safety performance indicators), and scenario cases that simulate future behavior of Split Airport safety performance indicators. Based on detected future hazards, and their causal factors, the appropriate mitigation measures are proposed for the purpose of improving and maintaining an acceptable level of safety at the airport. Full article

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46 pages, 27390 KiB

Open AccessArticle

Conceptual Model of Predictive Safety Management Methodology in Aviation

by Dajana Bartulović and Sanja Steiner

Aerospace 2023, 10(3), 268; https://doi.org/10.3390/aerospace10030268 - 10 Mar 2023

Cited by 4 | Viewed by 3319

Abstract

Due to the continuous growth of air traffic and the development of aviation systems, the current safety management methodologies should be improved and upgraded. Safety management systems help aviation organizations to manage, maintain and increase safety efficiently. The focus of the research is [...] Read more.

Due to the continuous growth of air traffic and the development of aviation systems, the current safety management methodologies should be improved and upgraded. Safety management systems help aviation organizations to manage, maintain and increase safety efficiently. The focus of the research is on the development of the predictive safety management methodology to upgrade current reactive and proactive safety management methodologies and to improve the overall safety level in aviation organizations. Predictive methods are used in various aviation sectors (air navigation services, airport operations, airline operations) for planning purposes but not in the segment of safety management. Available examples of predictive methods were tested and analyzed. Time series decomposition methods were selected as most suited for implementation in aviation safety management. The paper explicitly emphasizes correlations between safety management methodologies in the sample aviation organization. The paper also shows how causal links among organizational and safety performance indicators can be detected, by developing causal models of mutual influences using causal modeling methods, on the sample organization. This research defined steps and tools of the conceptual model of predictive safety management methodology, which enables an organization to identify and mitigate future adverse events. Full article

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15 pages, 5937 KiB

Open AccessArticle

Multi-Objective 3D Airspace Sectorization Problem Using NSGA-II with Prior Knowledge and External Archive

by Weining Zhang, Minghua Hu, Jianan Yin, Haobin Li and Jinghan Du

Aerospace 2023, 10(3), 216; https://doi.org/10.3390/aerospace10030216 - 24 Feb 2023

Cited by 3 | Viewed by 2121

Abstract

Airspace sectorization is a powerful means to balance the increasing air traffic flow and limited airspace resources, which is related to the efficiency and safety of operations. In order to divide sectors reasonably, a multi-objective optimization framework for 3D airspace sectorization is proposed [...] Read more.

Airspace sectorization is a powerful means to balance the increasing air traffic flow and limited airspace resources, which is related to the efficiency and safety of operations. In order to divide sectors reasonably, a multi-objective optimization framework for 3D airspace sectorization is proposed in this paper, including four core modules: Flight clustering, sector generation, workload evaluation, and sector optimization. Specifically, it clusters flights and generates initial sectors using a Voronoi diagram. To further optimize sector shape, the concept of dynamic density is introduced to evaluate the controller workload, based on which a sector optimization model is constructed. The model not only considers intra-sector and inter-sector workloads as objective functions but also sets hard constraints to meet operation and safety requirements. To solve it, a Non-dominated Sorting Genetic Algorithm II (NSGA-II) with prior knowledge and an external archive is designed. By analyzing the optimization results of actual operational data in the Singapore regional airspace, our approach obtains diverse optimal sectorization schemes for decision makers to choose from. Qualitative and quantitative experimental results confirm that the initial population strategy with prior knowledge significantly accelerates the convergence process. At the same time, the mechanism of the external archive effectively enriches the diversity of solutions. Full article

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21 pages, 11866 KiB

Open AccessArticle

Non-Intersecting Diverging Runways Separation under Emergency Avoidance Situation

by Changcheng Li, Minghua Hu, Zheng Zhao, Yuxin Hu and Ying Peng

Aerospace 2023, 10(2), 131; https://doi.org/10.3390/aerospace10020131 - 31 Jan 2023

Cited by 1 | Viewed by 1833

Abstract

Although runway separation, based on the probability of collision, has been studied for decades, the mathematical methods proposed by the majority of studies cannot handle complex situations, such as the operation of non-intersecting diverging runways at an airport with multiple runways. By applying [...] Read more.

Although runway separation, based on the probability of collision, has been studied for decades, the mathematical methods proposed by the majority of studies cannot handle complex situations, such as the operation of non-intersecting diverging runways at an airport with multiple runways. By applying a combination method of computer simulation and collision probability calculation, the arrival and departure window (ADW) separation for non-intersecting diverging runways of a multi-runway airport was studied under the emergency avoidance (EA) situation. Combining the example of runways 01L/19R and 11L of Beijing Daxing Airport, the ADW separation settings for the airport’s northward and southward operations were determined to meet the target level of safety. Moreover, the effects of range-type parameters on the ADW separation were quantified. When the EA maximum speed limit and EA minimum climb rate were 200 kt (102.9 m/s) and 10%, respectively, the results were such that no ADW separation was required for northward operation, and the ADW separation was from 3.2 km to 7.1 km for southward operation. Furthermore, the results showed that the proposed method could more accurately describe the nominal trajectories of aircraft and improve the precision of collision probability calculation. Meanwhile, the sensitivity analysis method for range-type parameters could help airports and air traffic control facilities to set reasonable constraints to improve theoretical runway capacity, while satisfying practical feasibility. Full article

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2022

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30 pages, 8852 KiB

Open AccessArticle

Dynamic Boundary Optimization of Free Route Airspace Sectors

by Lei Yang, Jue Huang, Qi Gao, Yi Zhou, Minghua Hu and Hua Xie

Aerospace 2022, 9(12), 832; https://doi.org/10.3390/aerospace9120832 - 15 Dec 2022

Cited by 4 | Viewed by 2404

Abstract

Free Route Airspace (FRA) permits users to freely plan routes between defined entry and exit waypoints with the possibility of routing via intermediate waypoints, which is beneficial to improve flight efficiency. Dynamic management of sectors is essential for the future promotion of full-time [...] Read more.

Free Route Airspace (FRA) permits users to freely plan routes between defined entry and exit waypoints with the possibility of routing via intermediate waypoints, which is beneficial to improve flight efficiency. Dynamic management of sectors is essential for the future promotion of full-time FRA applications. In this paper, considering the demand uncertainty at the pre-tactical level, we construct an FRA complexity indicator system and use the XGBoost algorithm to predict the ATC workload. A two-stage sector boundary optimization method is proposed, using Binary Space Partition (BSP) to generate sector boundaries and an A*-based heuristic algorithm to automatically tune them to conform to the operational structure and “direct to” characteristics of FRA. Finally, this paper verifies the effectiveness of the proposed method for balancing ATC workload in a pre-designed Lanzhou FRA in China. Full article

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32 pages, 5476 KiB

Open AccessArticle

Helicopter Rescue for Flood Disaster: Scheduling, Simulation, and Evaluation

by Yuanbo Xue, Yuan Gao, Yongliang Tian, Hu Liu and Xiyu Wang

Aerospace 2022, 9(12), 822; https://doi.org/10.3390/aerospace9120822 - 14 Dec 2022

Cited by 2 | Viewed by 3823

Abstract

Frequent severe floods have caused great losses to urban safety and the economy, which raises high requirements for the efficiency and effectiveness of emergency rescue. Due to the flood characteristics, flood rescue requires a more rapid responder and decision-making compared with other kinds [...] Read more.

Frequent severe floods have caused great losses to urban safety and the economy, which raises high requirements for the efficiency and effectiveness of emergency rescue. Due to the flood characteristics, flood rescue requires a more rapid responder and decision-making compared with other kinds of disaster rescue. In recent years, aviation emergency rescue (AER) has attracted much attention for flood applications. In order to evaluate the effectiveness of AER for flood disasters, the present study proposes a conceptual model of helicopter AER scheduling and develops a simulation system of helicopter AER scheduling using multiple agents. Seven elements are considered in the conceptual model: helicopters, the command-and-control center, temporary take-off/landing points, mission demand points, resettlement points, loading points, and unloading points. Furthermore, process-oriented and object-oriented scheduling rules are developed as the general guide for scheduling. In order to efficiently simulate and evaluate an AER mission (assisting the decision maker), the simulation system is designed with multiple agents and a user interface, which can quickly load mission settings, run the simulation, and collect data for further evaluation. A standardized mission makespan is adopted as the evaluation index. Based on that, the minimum integrated index can be derived to finally assess the different rescue schemes and choose the best. In the case study, the comparison results indicate that the rescue efficiency of large helicopters (Mi-26 in the case) could be limited by the capabilities of loading points and unloading points. This problem is solved by scheduling small/medium-size helicopters to transfer the personnel. Alternately, two types of helicopters can be used: one for passenger transfer and the other for goods/material transfer. Anyway, the analyses in the case study illustrate the correlation between effectiveness and scheduling, which demonstrates the significance of decision-making. By using the proposed scheduling and modeling methods, the simulation system can be served as a convenient decision-making support tool for practical rescue applications. Full article

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11 pages, 14184 KiB

Open AccessArticle

Air Traffic Complexity Assessment Based on Ordered Deep Metric

by Haiyan Chen, Linghui Zhang, Ligang Yuan, Weiqi Zhu and Li Liu

Aerospace 2022, 9(12), 758; https://doi.org/10.3390/aerospace9120758 - 26 Nov 2022

Cited by 1 | Viewed by 1769

Abstract

Since air traffic complexity determines the workload of controllers, it is a popular topic in the research field. Benefiting from deep learning, this paper proposes an air traffic complexity assessment method based on the deep metric of air traffic images. An Ordered Deep [...] Read more.

Since air traffic complexity determines the workload of controllers, it is a popular topic in the research field. Benefiting from deep learning, this paper proposes an air traffic complexity assessment method based on the deep metric of air traffic images. An Ordered Deep Metric (ODM) is proposed to measure the similarity of the ordered samples. For each sample, its interclass loss is calculated to keep it close to the mean of the same class and far from the difference. Then, consecutive samples of the same class are considered as a cluster, and the intracluster loss is calculated to make the samples close to the samples within the same cluster and far from the difference. Finally, we present the ODM-based air traffic complexity assessment method (ATCA-ODM), which uses the ODM results as the input of the classification algorithm to improve the assessment accuracy. We verify our ODM algorithm and ATCA-ODM method on the real traffic dataset of south-central airspace of China. The experimental results demonstrate that the assessment accuracy of the proposed ATCA-ODM method is significantly higher than that of the existing similar methods, which also proves that the proposed ODM algorithm can effectively extract high-dimensional features of the air traffic images. Full article

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24 pages, 3723 KiB

Open AccessArticle

A Methodological Framework for the Risk Assessment of Drone Intrusions in Airports

by Domenico Pascarella, Gabriella Gigante, Angela Vozella, Pierre Bieber, Thomas Dubot, Edgar Martinavarro, Giovanni Barraco and Greta Li Calzi

Aerospace 2022, 9(12), 747; https://doi.org/10.3390/aerospace9120747 - 24 Nov 2022

Cited by 10 | Viewed by 3324

Abstract

Drone expansion needs to be considered as a menace in cases of negligent, illicit, or non-cooperative use. In the case of airports, a complete protection against drone intrusion should rely on an intrusion management system, aiming at avoiding the closure of the airport. [...] Read more.

Drone expansion needs to be considered as a menace in cases of negligent, illicit, or non-cooperative use. In the case of airports, a complete protection against drone intrusion should rely on an intrusion management system, aiming at avoiding the closure of the airport. This system requires the setting of proper risk assessment methodologies for airport operations, to explicitly consider the features of drone intrusion, possibly from a quantitative point of view. This work proposes a methodological framework for the risk assessment of drone intrusions in airports, tailored on drone-intrusion features, airport features, and current operations, and considering both safety-related and security-related causes. The framework is based on the combination of model-based and data-driven approaches in order to: (i) estimate an airport vulnerability index, to measure the susceptibility of the airport to drone intrusions, based on reference datasets; (ii) specify a set of event trees to evaluate the risks of the different threat scenarios related to drone intrusions. The proposed methodological framework is applied to a concrete case study, related to Milan Malpensa airport. The achieved results show the effectiveness of the approach and elicit further requirements for counter-drone systems in airports based on the assessed risks. Full article

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18 pages, 2758 KiB

Open AccessArticle

A Delay Prediction Method for the Whole Process of Transit Flight

by Zheng Zhao, Shicheng Feng, Meiwen Song and Qizhao Liang

Aerospace 2022, 9(11), 645; https://doi.org/10.3390/aerospace9110645 - 25 Oct 2022

Cited by 5 | Viewed by 1936

Abstract

In order to strengthen the construction of smart airports and improve the ability of airport managers to identify, intervene and rescue delayed flights, this paper proposes a delay prediction method for the whole process of transit flights through the basic steps of node [...] Read more.

In order to strengthen the construction of smart airports and improve the ability of airport managers to identify, intervene and rescue delayed flights, this paper proposes a delay prediction method for the whole process of transit flights through the basic steps of node time and link time prediction and delayed flight identification. By designing the key node time prediction model (ML-DM), the method predicts the important guaranteed node time involved in the process of flight departure from the outstation to the departure from the current station. By constructing the imbalance data classification model, the delayed flight is identified at each predicted guarantee node. The experimental results for a busy airport show that this prediction method can achieve a maximum recognition rate of 96.5% for delayed flights. Full article

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18 pages, 3409 KiB

Open AccessArticle

A Pixel-Wise Foreign Object Debris Detection Method Based on Multi-Scale Feature Inpainting

by Ying Jing, Hong Zheng, Wentao Zheng and Kaihan Dong

Aerospace 2022, 9(9), 480; https://doi.org/10.3390/aerospace9090480 - 29 Aug 2022

Cited by 7 | Viewed by 2772

Abstract

In the aviation industry, foreign object debris (FOD) on airport runways is a serious threat to aircraft during takeoff and landing. Therefore, FOD detection is important for improving the safety of aircraft flight. In this paper, an unsupervised anomaly detection method called Multi-Scale [...] Read more.

In the aviation industry, foreign object debris (FOD) on airport runways is a serious threat to aircraft during takeoff and landing. Therefore, FOD detection is important for improving the safety of aircraft flight. In this paper, an unsupervised anomaly detection method called Multi-Scale Feature Inpainting (MSFI) is proposed to perform FOD detection in images, in which FOD is defined as an anomaly. This method adopts a pre-trained deep convolutional neural network (CNN) to generate multi-scale features for the input images. Based on the multi-scale features, a deep feature inpainting module is designed and trained to learn how to reconstruct the missing region masked by the multi-scale grid masks. During the inference stage, an anomaly map for the test image is obtained by computing the difference between the original feature and its reconstruction. Based on the anomaly map, the abnormal regions are identified and located. The performance of the proposed method is demonstrated on a newly collected FOD dataset and the public benchmark dataset MVTec AD. The results show that the proposed method is superior to other methods. Full article

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24 pages, 9729 KiB

Open AccessArticle

Evaluation of Homogenization in Metroplex Operations Based on Multi-Dimensional Indicators

by Congcong Guo, Wei Cong, Fengwei Zhong, Di Jiang, Jiaming Su and Yanjun Wang

Aerospace 2022, 9(8), 453; https://doi.org/10.3390/aerospace9080453 - 18 Aug 2022

Cited by 2 | Viewed by 1955

Abstract

The development of a Multiple Airport Region (MAR) could lead to fierce competition. To evaluate the level of homogenization between airports in a MAR, a homogenization evaluation method based on multi-dimensional indicators was developed. A multi-dimensional indicator system is proposed that takes into [...] Read more.

The development of a Multiple Airport Region (MAR) could lead to fierce competition. To evaluate the level of homogenization between airports in a MAR, a homogenization evaluation method based on multi-dimensional indicators was developed. A multi-dimensional indicator system is proposed that takes into account infrastructure, integrated support, operational efficiency and airline networks. Then the Critic method and the Delphi method are used to assign hierarchical weights for each dimension of the indicators. The multi-layer homogenization matrix of the airport pairs within the MAR is derived. For airport pairs with high comprehensive homogenization, suggestions are provided according to analysis of the indicators. This study paper selected three typical MARs internationally to demonstrate the advantage of the proposed approach. The airport pairs with high a homogenous coefficient (greater than 0.5) were selected to analyze the reasons causing high homogeneity. Results show that the multi-dimensional indicators and hierarchical fusion captured the characteristics of the homogenization of MAR. Most airport pairs in New York MAR and in London MAR had strong differentiation of route network layout, airport pairs in Greater Bay MAR had ambiguous division of labor and low homogenization of route network, except CAN and SZX airports. Suggestions are discussed separately to mitigate the homogeneity of the airports in the MAS, thus, to improve the operation performance of the MARs. Full article

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17 pages, 2750 KiB

Open AccessArticle

Aircraft Autonomous Separation Assurance Based on Cooperative Game Theory

by Xinmin Tang, Xiaona Lu and Pengcheng Zheng

Aerospace 2022, 9(8), 421; https://doi.org/10.3390/aerospace9080421 - 2 Aug 2022

Viewed by 1983

Abstract

Transferring part of the separation assurance responsibilities from air traffic controllers to pilots during en route phases of flight can reduce the controllers’ workload while ensuring operational safety and improving operational efficiency in the airspace. For this new generation of distributed air traffic [...] Read more.

Transferring part of the separation assurance responsibilities from air traffic controllers to pilots during en route phases of flight can reduce the controllers’ workload while ensuring operational safety and improving operational efficiency in the airspace. For this new generation of distributed air traffic management mode, firstly use the conflict detection algorithm to determine whether a potential conflict exists between two aircraft, introduce cooperative game theory to autonomous separation assurance model for horizontal cross-conflict in a static wind field by forming a coalition of all aircraft involved in the potential conflict. The convex combination of minimum yaw angle and maneuver flight time is used as the strategic gain of the aircraft, and the welfare function of the coalition is maximized by changing the behavioral strategy of the aircraft. Finally, a horizontal cross-conflict scenario is set up for simulation experiments and compared with a centralized separation assurance strategy. The simulation results show the effectiveness of cooperative game theory, which is applied in distributed autonomous separation assurance. Full article

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14 pages, 10980 KiB

Open AccessArticle

A Queuing Network Model of a Multi-Airport System Based on Point-Wise Stationary Approximation

by Xifan Zhao, Yanjun Wang, Lishuai Li and Daniel Delahaye

Aerospace 2022, 9(7), 390; https://doi.org/10.3390/aerospace9070390 - 19 Jul 2022

Cited by 6 | Viewed by 2637

Abstract

A multiple-airport system (MAS) consists of more than two airports in a metropolitan area under a large block of terminal airspace that is managed by one or two air traffic control units. When the capacity of an airport or of the terminal airspace [...] Read more.

A multiple-airport system (MAS) consists of more than two airports in a metropolitan area under a large block of terminal airspace that is managed by one or two air traffic control units. When the capacity of an airport or of the terminal airspace drops, flight delays occur in the MAS system. A quick estimation and predication of traffic congestion in the MAS is important yet challenging. This paper aims to develop a queuing network model of MAS using point-wise stationary queues. The model analyzes the changes of non-stationary queues under the principle of flow conservation to capture flight delay propagation in the system. Regression analyses are performed to examine the relationship between the arrival and departure efficiencies of different airports. The model is validated with the data of Guangdong–Hong Kong–Macao Greater Bay Area airports. Simulation results show that the model can effectively estimate flight delays in the MAS. Full article

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24 pages, 13387 KiB

Open AccessArticle

OpenAP.top: Open Flight Trajectory Optimization for Air Transport and Sustainability Research

by Junzi Sun

Aerospace 2022, 9(7), 383; https://doi.org/10.3390/aerospace9070383 - 15 Jul 2022

Cited by 3 | Viewed by 3957

Abstract

Trajectory optimization has been an active area of research for air transport studies for several decades. But almost all flight optimizers proposed in the literature remain close-sourced, which presents a major disadvantage for the advancement of scientific research. This optimization depends on aircraft [...] Read more.

Trajectory optimization has been an active area of research for air transport studies for several decades. But almost all flight optimizers proposed in the literature remain close-sourced, which presents a major disadvantage for the advancement of scientific research. This optimization depends on aircraft performance models, emission models, and operational constraints. In this paper, I present a fully open trajectory optimizer, OpenAP.top, which offers researchers easy access to the complex but efficient non-linear optimal control approach. Full flights can be generated without specifying flight phases, and specific flight segments can also be independently created. The optimizer adapts to meteorological conditions and includes conventional fuel and cost index objectives. Based on global warming and temperature potentials, its climate objectives form the basis for climate optimal air transport studies. The optimizer’s performance and uncertainties under different factors like varying mass, cost index, and wind conditions are analyzed. Overall, this new optimizer brings a high performance for optimal trajectory generations by providing four-dimensional and wind-enabled full-phase optimal trajectories in a few seconds. Full article

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16 pages, 2850 KiB

Open AccessArticle

Quantifying the Resilience Performance of Airport Flight Operation to Severe Weather

by Xinglong Wang, Ziyan Chen and Kenan Li

Aerospace 2022, 9(7), 344; https://doi.org/10.3390/aerospace9070344 - 27 Jun 2022

Cited by 4 | Viewed by 2561

Abstract

The increased number of severe weather events caused by global warming in recent years is a major turbulence factor for airport operation and results in more irregular flights. Quantifying the system response status towards turbulence is critical, in order for airports to deal [...] Read more.

The increased number of severe weather events caused by global warming in recent years is a major turbulence factor for airport operation and results in more irregular flights. Quantifying the system response status towards turbulence is critical, in order for airports to deal with severe weather. For this reason, we propose a resilience framework that is in compliance with resilience theory to evaluate airport flight operations. In this framework, the departure rate (DPR), normal weather baseline (NWB), and nonnegative general resilience (NGR) were defined and used. Meanwhile, the whole process is divided into five phases before and after disturbance, and the system capacities of susceptibility, absorption, adaptation, and recovery are assessed. In order to clarify the performance of the framework towards various severe weather conditions, an analysis was conducted at Beijing Capital Airport in China based on a dataset that includes both the meteorological terminal aviation weather report (METAR) and flight operations from January to July 2021. The results show that the newly proposed resilience framework can commendably reflect airport flight operation performance. The airport flight operation resilience characteristic is different with severe weather. Compared to sandstorms and snow, airport flight operation with stronger robustness was observed during thunderstorm events. The study also confirms that, as the weather warning level increases, the disruption time increases and response time decreases accordingly. The above results could assist researchers and policy makers in clearly understanding the real-world resilience of airport flight operation, in both theory and practice, and responding to emergent disruptive events effectively. Full article

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19 pages, 9300 KiB

Open AccessArticle

Flight Anomaly Detection via a Deep Hybrid Model

by Kun Qin, Qixin Wang, Binbin Lu, Huabo Sun and Ping Shu

Aerospace 2022, 9(6), 329; https://doi.org/10.3390/aerospace9060329 - 19 Jun 2022

Cited by 14 | Viewed by 3441

Abstract

In the civil aviation industry, security risk management has shifted from post-accident investigations and analyses to pre-accident warnings in an attempt to reduce flight risks by identifying currently untracked flight events and their trends and effectively preventing risks before they occur. The use [...] Read more.

In the civil aviation industry, security risk management has shifted from post-accident investigations and analyses to pre-accident warnings in an attempt to reduce flight risks by identifying currently untracked flight events and their trends and effectively preventing risks before they occur. The use of flight monitoring data for flight anomaly detection is effective in discovering unknown and potential flight incidents. In this paper, we propose a time-feature attention mechanism and construct a deep hybrid model for flight anomaly detection. The hybrid model combines a time-feature attention-based convolutional autoencoder with the HDBSCAN clustering algorithm, where the autoencoder is constructed and trained to extract flight features while the HDBSCAN works as an anomaly detector. Quick access record (QAR) flight data containing information of aircraft landing at Kunming Changshui International and Chengdu Shuangliu International airports are used as the experimental data, and the results show that (1) the time-feature-based convolutional autoencoder proposed in this paper can better extract the flight features and further discover the different landing patterns; (2) in the representation space of the flights, anomalous flight objects are better separated from normal objects to provide a quality database for subsequent anomaly detection; and (3) the discovered flight patterns are consistent with those at the airports, resulting in anomalies that could be interpreted with the corresponding pattern. Moreover, several examples of anomalous flights at each airport are presented to analyze the characteristics of anomalies. Full article

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19 pages, 5745 KiB

Open AccessArticle

Effects on Taxiing Conflicts at Intersections by Pilots’ Sensitive Speed Adjustment

by Kai Yang, Hongyu Yang, Jianwei Zhang and Rui Kang

Aerospace 2022, 9(6), 288; https://doi.org/10.3390/aerospace9060288 - 25 May 2022

Cited by 3 | Viewed by 2273

Abstract

The pilot is the main person in charge of taxiing safety while moving on the airport surface. The visual separation and speed adjustment are directly related to safety and efficiency of airport surface operation. According to the actual taxiing procedures and airport control [...] Read more.

The pilot is the main person in charge of taxiing safety while moving on the airport surface. The visual separation and speed adjustment are directly related to safety and efficiency of airport surface operation. According to the actual taxiing procedures and airport control rules in China, this paper proposes a novel microscopic simulation model based on the pilots’ visual separation. This model is also built by refining the aircraft taxiing procedures at intersections. The observation range, the separation judgment, pilots’ visual distance, rate of proximity and the intention for speed governing are discussed as parameters in the model. The rules for aircraft separation judgment, pilots’ autonomous speed governing, and position updates are also set up and discussed. The proposed simulation can accurately simulate the acceleration and deceleration intentions under different motion trends while reproducing the motion process including the following acceleration, following deceleration and delayed deceleration caused by separation changes. The results demonstrate that the number of conflicts can be reduced to 50% based on visual separation adjustment of 50 s when the convergence angle is 30°. The pilot’s visual distance is inversely proportional to the fluctuation range of the speed of the rear aircraft, the proximity rate of the front and rear aircraft and the probability of conflict. The simulation results of this model conform to the actual taxiing routes and control rules, which provides technical support for improving the safety level of airport surface operation and presents certain reference value and practicability. Full article

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21 pages, 6697 KiB

Open AccessArticle

Improvement of Airport Surface Operation at Tokyo International Airport Using Optimization Approach

by Tong Chen and Shinya Hanaoka

Aerospace 2022, 9(3), 145; https://doi.org/10.3390/aerospace9030145 - 7 Mar 2022

Cited by 5 | Viewed by 4841

Abstract

Congestion and delays occur on airport surfaces as a result of a rapid increase in the demand for air transport. The aim of this study is to determine the differences between optimized and observed operations to improve airport surface operation at Tokyo International [...] Read more.

Congestion and delays occur on airport surfaces as a result of a rapid increase in the demand for air transport. The aim of this study is to determine the differences between optimized and observed operations to improve airport surface operation at Tokyo International Airport by using mixed-integer linear programming to minimize the total ground movement distance and time based on real-time flight information. Receding horizon schemes are considered to adapt to dynamic environments. The model obtains results that reduce the taxi distance by 18.54% and taxi time by 29.77% compared with the observed data. A comparison of taxiway usage patterns between the optimization results and observed data provides insight into the optimization process, for example, changes in runway cross strategies and taxiway direction rules. Factors such as the objective function weights and airline–terminal relationship were found to significantly affect the optimization result. This study suggests improvements that can be made at airports to achieve a more efficient surface operation. Full article

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25 pages, 4993 KiB

Open AccessArticle

Investigation of Merge Assist Policies to Improve Safety of Drone Traffic in a Constrained Urban Airspace

by Malik Doole, Joost Ellerbroek and Jacco M. Hoekstra

Aerospace 2022, 9(3), 120; https://doi.org/10.3390/aerospace9030120 - 25 Feb 2022

Cited by 12 | Viewed by 3295

Abstract

Package delivery via autonomous drones is often presumed to hold commercial and societal value when applied to urban environments. However, to realise the benefits, the challenge of safely managing high traffic densities of drones in heavily constrained urban spaces needs to be addressed. [...] Read more.

Package delivery via autonomous drones is often presumed to hold commercial and societal value when applied to urban environments. However, to realise the benefits, the challenge of safely managing high traffic densities of drones in heavily constrained urban spaces needs to be addressed. This paper applies the principles of traffic segmentation and alignment to a constrained airspace in efforts to mitigate the probability of conflict. The study proposes an en-route airspace concept in which drone flights are directly guided along a one-way street network. This one-way airspace concept uses heading-altitude rules to vertically segment cruising traffic as well as transitioning flights with respect to their travel direction. However, transition flights trigger a substantial number of merging conflicts, thus negating a large part of the benefits gained from airspace structuring. In this paper, we aim to reduce the occurrence of merging conflicts and intrusions by using a delay-based and speed-based merge-assist strategy, both well-established methods from road traffic research. We apply these merge assistance strategies to the one-way airspace design and perform simulations for three traffic densities for the experiment area of Manhattan, New York. The results indicate, at most, a 9–16% decrease in total number of intrusions with the use of merge assistance. By investigating mesoscopic features of the urban street network, the data suggest that the relatively low efficacy of the merge strategies is mainly caused by insufficient space for safe manoeuvrability and the inability for the strategies to fully respond and thus resolve conflicts on short-distance streets. Full article

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17 pages, 5614 KiB

Open AccessArticle

Modeling Aircraft Departure at a Runway Using a Time-Varying Fluid Queue

by Eri Itoh, Mihaela Mitici and Michael Schultz

Aerospace 2022, 9(3), 119; https://doi.org/10.3390/aerospace9030119 - 25 Feb 2022

Cited by 13 | Viewed by 3756

Abstract

Reducing the length of departure queues at runway entry points is one of the most important requirements for reducing aircraft traffic congestion and fuel consumption at airports. This study designs an aircraft departure model at a runway using a time-varying fluid queue. The [...] Read more.

Reducing the length of departure queues at runway entry points is one of the most important requirements for reducing aircraft traffic congestion and fuel consumption at airports. This study designs an aircraft departure model at a runway using a time-varying fluid queue. The proposed model enables us to determine the aircraft waiting time in the departure queue and to evaluate effective control approaches for assigning suitable holds at gates rather than runway entry points. As a case study, this study modeled the departure queue at runway 05 of Tokyo International Airport for an entire day of operations. Using actual traffic data of departures at the airport, the model estimates that aircraft spend a total of 2.5 h departure waiting time in a day at runway 05. Considering the stochastic nature of actual departure traffic, the relevance of the proposed model is discussed using validation criteria. The model estimation shows a reasonable, expected order of magnitude compared with the departure queue recorded in the actual traffic data. Furthermore, ecological and economic benefits are quantitatively evaluated assuming a reduction in the departure queue length. Our results show that about one kiloton of fuel oil per year is wasted due to aircraft waiting to depart from a single departure runway. Full article

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25 pages, 880 KiB

Open AccessArticle

Factors Impacting Chinese and European Vertical Fight Efficiency

by Judith Rosenow, Gong Chen, Hartmut Fricke and Yanjun Wang

Aerospace 2022, 9(2), 76; https://doi.org/10.3390/aerospace9020076 - 1 Feb 2022

Cited by 8 | Viewed by 4360

Abstract

Increasing complexity due to a constantly growing number of target functions turns air traffic trajectory optimization into a multidimensional and nonlinear task that in turn necessitates a focus on the case-sensitive most important criteria. The criteria vary by continent and involve operational, economic, [...] Read more.

Increasing complexity due to a constantly growing number of target functions turns air traffic trajectory optimization into a multidimensional and nonlinear task that in turn necessitates a focus on the case-sensitive most important criteria. The criteria vary by continent and involve operational, economic, environmental, political, and social concerns. Furthermore, the requirements may alter for a single flight along its journey since air traffic is a transcontinental, segment-wise differently affected transportation mode. Tracked flight data allow for the observation and evaluation of large numbers of flights, as well as the extraction of criteria relevant to flight efficiency and to derive optimization strategies to improve it. In this study, flight track data of China and Europe were compared toward flight efficiency. We found major disparities in both continents’ routing structures. Historical ADS-B data considered to be reference trajectories were assessed for flight efficiency while putting a dedicated focus on the vertical profile. Criteria to optimize vertical flight efficiency (VFE) were derived. Based on the findings, suggestions for improvement towards trajectories with minimum fuel are formulated. Different optimization strategies were tested to identify important input variables and, if possible, to determine differences between operation in China and in Europe. On average and in both regions, the influence of weather (e.g., wind speed and wind direction) exceeds the influence of aerodynamics (aircraft type, mass), as the weather-optimized vertical profile more often results in minimum fuel consumption than the aerodynamically optimized trajectory. Atmospheric conditions, network requirements, aircraft types and flight planning procedures are similar in China and Europe and only have a minor impact on flight efficiency during the cruise phase. In a multi-criteria trajectory optimization of the extracted reference trajectories considering the weather, operational constraints and prohibited areas, we found that in China, on average, just under

13 %

fuel could be saved through optimal vertical and horizontal routing. In Europe, the figure is a good

10 %

. Furthermore, we calculated a fuel-saving potential of

8 %

in China and

3 %

in Europe through vertical adjustments of the trajectory alone. The resultant reference trajectories will be used for further analysis to increase the efficiency of continental air traffic flows. Full article

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41 pages, 13806 KiB

Open AccessTechnical Note

by Andrew Weinert, Ngaire Underhill, Christine Serres and Randal Guendel

Aerospace 2022, 9(2), 58; https://doi.org/10.3390/aerospace9020058 - 24 Jan 2022

Cited by 6 | Viewed by 3971

Abstract

The integration of new airspace entrants into terminal operations requires design and evaluation of Detect and Avoid systems that prevent loss of well clear from and collision with other aircraft. Prior to standardization or deployment, an analysis of the safety performance of those [...] Read more.

The integration of new airspace entrants into terminal operations requires design and evaluation of Detect and Avoid systems that prevent loss of well clear from and collision with other aircraft. Prior to standardization or deployment, an analysis of the safety performance of those systems is required. This type of analysis has typically been conducted by Monte Carlo simulation with synthetic, statistically representative encounters between aircraft drawn from an appropriate encounter model. While existing encounter models include terminal airspace classes, none explicitly represents the structure expected while engaged in terminal operations, e.g., aircraft in a traffic pattern. The work described herein is an initial model of such operations where an aircraft landing or taking off via a straight trajectory encounters another aircraft landing or taking off, or transiting by any means. The model shares the Bayesian network foundation of other Massachusetts Institute of Technology Lincoln Laboratory encounter models but tailors those networks to address structured terminal operations, i.e., correlations between trajectories and the airfield and each other. This initial model release is intended to elicit feedback from the standards-writing community. Full article

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18 pages, 1219 KiB

Open AccessArticle

Travel Bubbles in Air Transportation: Myth or Reality?

by Xiaoqian Sun, Sebastian Wandelt and Anming Zhang

Aerospace 2022, 9(1), 38; https://doi.org/10.3390/aerospace9010038 - 13 Jan 2022

Cited by 5 | Viewed by 2809

Abstract

Aviation has been hit hard by COVID-19, with passengers stranded in remote destinations, airlines filing for bankruptcy, and uncertain demand scenarios for the future. Travel bubbles are discussed as one possible solution, meaning countries which have successfully constrained the spread of COVID-19 gradually [...] Read more.

Aviation has been hit hard by COVID-19, with passengers stranded in remote destinations, airlines filing for bankruptcy, and uncertain demand scenarios for the future. Travel bubbles are discussed as one possible solution, meaning countries which have successfully constrained the spread of COVID-19 gradually increase their mutual international flights, returning to a degree of normality. This study aims to answer the question of whether travel bubbles are indeed observable in flight data for the year 2020. We take the year 2019 as reference and then search for anomalies in countries’ flight bans and recoveries, which could possibly be explained by having successfully implemented a travel bubble. To the best of our knowledge, this study is the first to try to address the identification of COVID-19 travel bubbles in real data. Our methodology and findings lead to several important insights regarding policy making, problems associated with the concept of travel bubbles, and raise interesting avenues for future research. Full article

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