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 266

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

► Show Figures

Figure 1

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 2361

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

► Show Figures

Figure 1

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

Viewed by 832

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

► Show Figures

Figure 1

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 1105

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

► Show Figures

Figure 1

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 1603

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

► Show Figures

Figure 1

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

Viewed by 1544

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

► Show Figures

Figure 1

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 1388

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

► Show Figures

Figure 1

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 1763

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

► Show Figures

Figure 1

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 1300

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

► Show Figures

Figure 1

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 1796

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

► Show Figures

Figure 1

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 1682

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

► Show Figures

Figure 1

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 2299

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

► Show Figures

Figure 1

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 1 | Viewed by 2128

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

► Show Figures

Figure 1

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 9 | Viewed by 4669

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

► Show Figures

Figure 1

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 1965

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

► Show Figures

Figure 1

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 1549

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

► Show Figures

Figure 1

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 2220

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

► Show Figures

Figure 1

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 2690

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

► Show Figures

Figure 1

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 3209

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

► Show Figures

Figure 1

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 2082

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

► Show Figures

Figure 1

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 1787

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

► Show Figures

Figure 1

2022

Jump to: 2024, 2023, 2021, 2020, 2019, 2018, 2017

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 2356

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

► Show Figures

Figure 1

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 3742

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

► Show Figures

Figure 1

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 1730

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

► Show Figures

Figure 1

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 9 | Viewed by 3241

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

► Show Figures

Figure 1

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 1891

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

► Show Figures

Figure 1

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 2695

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

► Show Figures

Figure 1

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 1926

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

► Show Figures

Figure 1

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 1940

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

► Show Figures

Figure 1

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 2582

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

► Show Figures

Figure 1

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 3819

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

► Show Figures

Figure 1

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 2501

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

► Show Figures

Figure 1

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 13 | Viewed by 3367

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

► Show Figures

Figure 1

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 2232

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

► Show Figures

Figure 1

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 4763

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

► Show Figures

Figure 1

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 3247

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

► Show Figures

Figure 1

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 3687

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

► Show Figures

Figure 1

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 4266

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

► Show Figures

Figure 1

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 3929

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

► Show Figures

Figure 1

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 2763

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

► Show Figures

Figure 1

2021

Jump to: 2024, 2023, 2022, 2020, 2019, 2018, 2017

19 pages, 2321 KiB

Open AccessArticle

A System Dynamics Prediction Model of Airport Environmental Carrying Capacity: Airport Development Mode Planning and Case Study

by Qiuping Peng, Lili Wan, Tianci Zhang, Zhan Wang and Yong Tian

Aerospace 2021, 8(12), 397; https://doi.org/10.3390/aerospace8120397 - 14 Dec 2021

Cited by 8 | Viewed by 3126

Abstract

Airport environmental carrying capacity (AECC) provides the fundamental conditions for airport development and operation activities. The prediction of AECC is a necessary condition for planning an appropriate development mode for the airport. This paper studies the dynamic prediction method of the AECC to [...] Read more.

Airport environmental carrying capacity (AECC) provides the fundamental conditions for airport development and operation activities. The prediction of AECC is a necessary condition for planning an appropriate development mode for the airport. This paper studies the dynamic prediction method of the AECC to explore the development characteristics of AECC in different airports. Based on the driving force-pressure-state-response (DPSR) framework, the method selects 17 main variables from economic, social, environmental and operational dimensions, and then combines the drawing of causal loop diagrams and the establishment of system flow diagrams to construct the system dynamics (SD) model of AECC. The predicted values of AECC are obtained through SD model simulation and accelerated genetic algorithm projection pursuit (AGA-PP) model calculation. Considering sustainable development needs, different scenarios are set to analyze the appropriate development mode of the airport. The case study of the Pearl River Delta airports resulted in two main conclusions. First, in the same economic zone, different airports with similar aircraft movements have similar development characteristics of AECC. Second, the appropriate development modes for different airports are different, and the appropriate development modes for the airport in different periods are also different. The case study also proves that the AECC prediction based on SD model and AGA-PP model can realize short-term policy formulation and long-term planning for the airport development mode, and provide decision-making support for relevant departments of airport. Full article

► Show Figures

Figure 1

22 pages, 2527 KiB

Open AccessArticle

Spatiotemporal Graph Indicators for Air Traffic Complexity Analysis

by Ralvi Isufaj, Thimjo Koca and Miquel Angel Piera

Aerospace 2021, 8(12), 364; https://doi.org/10.3390/aerospace8120364 - 25 Nov 2021

Cited by 19 | Viewed by 3025

Abstract

There has been extensive research in formalising air traffic complexity, but existing works focus mainly on a metric to tie down the peak air traffic controllers workload rather than a dynamic approach to complexity that could guide both strategical, pre-tactical and tactical actions [...] Read more.

There has been extensive research in formalising air traffic complexity, but existing works focus mainly on a metric to tie down the peak air traffic controllers workload rather than a dynamic approach to complexity that could guide both strategical, pre-tactical and tactical actions for a smooth flow of aircraft. In this paper, aircraft interdependencies are formalized using graph theory and four complexity indicators are described, which combine spatiotemporal topological information with the severity of the interdependencies. These indicators can be used to predict the dynamic evolution of complexity, by not giving one single score, but measuring complexity in a time window. Results show that these indicators can capture complex spatiotemporal areas in a sector and give a detailed and nuanced view of sector complexity. Full article

► Show Figures

Figure 1

22 pages, 1444 KiB

Open AccessArticle

Impact of Chinese and European Airspace Constraints on Trajectory Optimization

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

Aerospace 2021, 8(11), 338; https://doi.org/10.3390/aerospace8110338 - 10 Nov 2021

Cited by 6 | Viewed by 2962

Abstract

Air traffic trajectory optimization is a complex, multidimensional and non-linear optimization problem and requires a firm focus on the essential criteria. The criteria cover operational, economical, environmental, political, and social factors and differ from continent to continent. Since air traffic is a transcontinental [...] Read more.

Air traffic trajectory optimization is a complex, multidimensional and non-linear optimization problem and requires a firm focus on the essential criteria. The criteria cover operational, economical, environmental, political, and social factors and differ from continent to continent. Since air traffic is a transcontinental transport system, the criteria may also change during a single flight. Historic flight track data allow observation and assess real flights, to extract essential criteria and to derive optimization strategies to increase air traffic efficiency. Real flight track data from the Chinese and European air traffic show significant differences in the routing structure in both regions. For that reason, reference trajectories of historic ADS-B 24-h air traffic data in China and Europe have been extracted and analyzed regarding horizontal flight efficiency and the most restrictive criteria of trajectory optimization. We found that prohibited areas might be the most powerful reason to describe deviations from the great circle distance in the Chinese air traffic system. 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 flown ground distances could be reduced by 255 km in the Chinese airspace and 2.3 km in the European airspace. The resultant reference trajectories can be used for further analysis to increase the efficiency of continental air traffic flows. Full article

► Show Figures

Figure 1

18 pages, 3688 KiB

Open AccessArticle

Aircraft Trajectory Clustering in Terminal Airspace Based on Deep Autoencoder and Gaussian Mixture Model

by Weili Zeng, Zhengfeng Xu, Zhipeng Cai, Xiao Chu and Xiaobo Lu

Aerospace 2021, 8(9), 266; https://doi.org/10.3390/aerospace8090266 - 16 Sep 2021

Cited by 37 | Viewed by 7786

Abstract

The aircraft trajectory clustering analysis in the terminal airspace is conducive to determining the representative route structure of the arrival and departure trajectory and extracting their typical patterns, which is important for air traffic management such as airspace structure optimization, trajectory planning, and [...] Read more.

The aircraft trajectory clustering analysis in the terminal airspace is conducive to determining the representative route structure of the arrival and departure trajectory and extracting their typical patterns, which is important for air traffic management such as airspace structure optimization, trajectory planning, and trajectory prediction. However, the current clustering methods perform poorly due to the large flight traffic, high density, and complex airspace structure in the terminal airspace. In recent years, the continuous development of Deep Learning has demonstrated its powerful ability to extract internal potential features of large dataset. Therefore, this paper mainly tries a deep trajectory clustering method based on deep autoencoder (DAE). To this end, this paper proposes a trajectory clustering method based on deep autoencoder (DAE) and Gaussian mixture model (GMM) to mine the prevailing traffic flow patterns in the terminal airspace. The DAE is trained to extract feature representations from historical high-dimensional trajectory data. Subsequently, the output of DAE is input into GMM for clustering. This paper takes the terminal airspace of Guangzhou Baiyun International Airport in China as a case to verify the proposed method. Through the direct visualization and dimensionality reduction visualization of the clustering results, it is found that the traffic flow patterns identified by the clustering method in this paper are intuitive and separable. Full article

► Show Figures

Figure 1

21 pages, 4129 KiB

Open AccessArticle

The Impact of Automation on Air Traffic Controller’s Behaviors

by Yanjun Wang, Rongjin Hu, Siyuan Lin, Michael Schultz and Daniel Delahaye

Aerospace 2021, 8(9), 260; https://doi.org/10.3390/aerospace8090260 - 13 Sep 2021

Cited by 9 | Viewed by 5136

Abstract

Air traffic controllers have to make quick decisions to keep air traffic safe. Their behaviors have a significant impact on the operation of the air traffic management (ATM) system. Automation tools have enhanced the ATM system’s capability by reducing the controller’s task-load. Much [...] Read more.

Air traffic controllers have to make quick decisions to keep air traffic safe. Their behaviors have a significant impact on the operation of the air traffic management (ATM) system. Automation tools have enhanced the ATM system’s capability by reducing the controller’s task-load. Much attention has been devoted to developing advanced automation in the last decade. However, less is known about the impact of automation on the behaviors of air traffic controllers. Here, we empirically tested the effects of three levels of automation—including manual, attention-guided, and automated—as well as varying traffic levels on eye movements, situation awareness and mental workload. The results showed that there are significant differences in the gaze and saccade behaviors between the attention-guided group and automated group. Traffic affected eye movements under the manual mode or under the attention-guided mode, but had no effect on eye movements under the automated mode. The results also supported the use of automation for enhancing situation awareness while reducing mental workload. Our work has potential implications for the design of automation and operation procedures. Full article

► Show Figures

Figure 1

25 pages, 38718 KiB

Open AccessArticle

A Holistic Approach for Optimal Pre-Planning of Multi-Path Standardized Taxiing Routes

by Lei Yang, Simin Wang, Fengjie Liang and Zheng Zhao

Aerospace 2021, 8(9), 241; https://doi.org/10.3390/aerospace8090241 - 1 Sep 2021

Cited by 4 | Viewed by 3247

Abstract

Standardized Taxiing Routes (STRs) are defined as published taxiing-in and taxiing-out routes for aircraft between gates and runways, aiming at improving ground movement safety at busy or complex airports. Most of the STRs specify only one path between each O–D (Origin–Destination) pair, which [...] Read more.

Standardized Taxiing Routes (STRs) are defined as published taxiing-in and taxiing-out routes for aircraft between gates and runways, aiming at improving ground movement safety at busy or complex airports. Most of the STRs specify only one path between each O–D (Origin–Destination) pair, which compromises the flexibility of route choice in time-varying traffic scenarios. In this paper, we present a holistic approach of planning and validating Multi-Path Standardized Taxiing Routes (MPSTRs) based on System-Optimal Traffic Assignment (SOTA), by firstly defining the flow-based congestion cost of runway, taxiway, and sectorized apron operation at a macroscopic level. A human-in-the-loop experiment comprised of six operation scenarios follows to investigate the impact of the pre-planned MPSTRs on human controllers’ performance. Results confirm the positive effect of the MPSTRs on taxiing performance without increasing the controllers’ workload, which also implies that the MPSTRs would be a promising approach for balancing safety and efficiency for the STRs-based taxiing operation and dynamic routing optimization without substantial investment. Full article

► Show Figures

Figure 1

25 pages, 10249 KiB

Open AccessArticle

Explanation of Machine-Learning Solutions in Air-Traffic Management

by Yibing Xie, Nichakorn Pongsakornsathien, Alessandro Gardi and Roberto Sabatini

Aerospace 2021, 8(8), 224; https://doi.org/10.3390/aerospace8080224 - 12 Aug 2021

Cited by 39 | Viewed by 9594

Abstract

Advances in the trusted autonomy of air-traffic management (ATM) systems are currently being pursued to cope with the predicted growth in air-traffic densities in all classes of airspace. Highly automated ATM systems relying on artificial intelligence (AI) algorithms for anomaly detection, pattern identification, [...] Read more.

Advances in the trusted autonomy of air-traffic management (ATM) systems are currently being pursued to cope with the predicted growth in air-traffic densities in all classes of airspace. Highly automated ATM systems relying on artificial intelligence (AI) algorithms for anomaly detection, pattern identification, accurate inference, and optimal conflict resolution are technically feasible and demonstrably able to take on a wide variety of tasks currently accomplished by humans. However, the opaqueness and inexplicability of most intelligent algorithms restrict the usability of such technology. Consequently, AI-based ATM decision-support systems (DSS) are foreseen to integrate eXplainable AI (XAI) in order to increase interpretability and transparency of the system reasoning and, consequently, build the human operators’ trust in these systems. This research presents a viable solution to implement XAI in ATM DSS, providing explanations that can be appraised and analysed by the human air-traffic control operator (ATCO). The maturity of XAI approaches and their application in ATM operational risk prediction is investigated in this paper, which can support both existing ATM advisory services in uncontrolled airspace (Classes E and F) and also drive the inflation of avoidance volumes in emerging performance-driven autonomy concepts. In particular, aviation occurrences and meteorological databases are exploited to train a machine learning (ML)-based risk-prediction tool capable of real-time situation analysis and operational risk monitoring. The proposed approach is based on the XGBoost library, which is a gradient-boost decision tree algorithm for which post-hoc explanations are produced by SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). Results are presented and discussed, and considerations are made on the most promising strategies for evolving the human–machine interactions (HMI) to strengthen the mutual trust between ATCO and systems. The presented approach is not limited only to conventional applications but also suitable for UAS-traffic management (UTM) and other emerging applications. Full article

► Show Figures

Figure 1

23 pages, 2179 KiB

Open AccessArticle

Data-Driven Simulation for Evaluating the Impact of Lower Arrival Aircraft Separation on Available Airspace and Runway Capacity at Tokyo International Airport

by Katsuhiro Sekine, Furuto Kato, Kota Kageyama and Eri Itoh

Aerospace 2021, 8(6), 165; https://doi.org/10.3390/aerospace8060165 - 13 Jun 2021

Cited by 19 | Viewed by 4529

Abstract

Although the application of new wake turbulence categories, the so-called “RECAT (wake turbulence category re-categorization)”, will realize lower aircraft separation minima and directly increase runway throughput, the impacts of increasing arrival traffic on the surrounding airspace and arrival traffic flow as a whole [...] Read more.

Although the application of new wake turbulence categories, the so-called “RECAT (wake turbulence category re-categorization)”, will realize lower aircraft separation minima and directly increase runway throughput, the impacts of increasing arrival traffic on the surrounding airspace and arrival traffic flow as a whole have not yet been discussed. This paper proposes a data-driven simulation approach and evaluates the effectiveness of the lower aircraft separation in the arrival traffic at the target airport. The maximum runway capacity was clarified using statistics on aircraft types, stochastic distributions of inter-aircraft time and runway occupancy time, and the levels of the automation systems that supported air traffic controllers’ separation work. Based on the estimated available runway capacity, simulation models were proposed by analyzing actual radar track and flight plan data during the 6 months between September 2019 and February 2020, under actual operational constraints and weather conditions. The simulation results showed that the application of RECAT would reduce vectoring time in the terminal area by 7% to 10% under the current airspace and runway capacity when following a first-come first-served arrival sequence. In addition, increasing airspace capacity by 10% in the terminal area could dramatically reduce en-route and takeoff delay times while keeping vectoring time the same as under the current operation in the terminal area. These findings clarified that applying RECAT would contribute to mitigating air traffic congestion close to the airport, and to reducing delay times in arrival traffic as a whole while increasing runway throughput. The simulation results demonstrated the relevance of the theoretical results given by queue-based approaches in the authors’ past studies. Full article

► Show Figures

Figure 1

25 pages, 5003 KiB

Open AccessArticle

Influence of the Apron Parking Stand Management Policy on Aircraft and Ground Support Equipment (GSE) Gaseous Emissions at Airports

by Lucas Sznajderman, Gabriel Ramírez-Díaz and Carlos A. Di Bernardi

Aerospace 2021, 8(3), 87; https://doi.org/10.3390/aerospace8030087 - 19 Mar 2021

Cited by 7 | Viewed by 4502

Abstract

The purpose of this study is to analyze the concept of a hybrid apron with a fixed number of parking positions considering the management model influence for the average delay per aircraft and the gaseous emissions generated by aircraft and ground support equipment [...] Read more.

The purpose of this study is to analyze the concept of a hybrid apron with a fixed number of parking positions considering the management model influence for the average delay per aircraft and the gaseous emissions generated by aircraft and ground support equipment (GSE) altogether. The apron is studied based on two gate management models: in the first model, the aircraft are allocated in each gate due to operational factors only; in the second model, the rules of exclusive use of each gate according to the airline are included. The emissions generated by aircraft operations and that of their GSE (produced by the service and movements on the apron) are quantified and compared in the two gate management models: operation in the standard LTO cycle of the studied aircraft, GSE emissions have a similar relation with the compared gasses (NOx and CO), ranging between 1% and 3%. Further, if it compares the emissions between support vehicles and aircraft taking only into account the in-out taxiway, the relation between both CO sources shows similar values to those of the previous comparison, whereas NOx emissions produced by GSE reach an approximately 20%. The study considers different demand conditions obtained from the average day of the peak month of Aeroparque Jorge Newbery airport. Subsequently, through the SIMMOD PLUS software, the aircraft operations are simulated. The gates assignment and the arrival timetables are used as inputs for the GSE study due to an analytical model developed by us. Once the operational dimension is characterized and evaluated, the necessary data to quantify the gaseous emissions from the sources (Aircraft-GSE), based on the International Civil Aviation Organization (ICAO) guidelines, is obtained. Full article

► Show Figures

Figure 1

22 pages, 1179 KiB

Open AccessArticle

Analysis of Risk-Based Operational Bird Strike Prevention

by Isabel C. Metz, Joost Ellerbroek, Thorsten Mühlhausen, Dirk Kügler and Jacco M. Hoekstra

Aerospace 2021, 8(2), 32; https://doi.org/10.3390/aerospace8020032 - 28 Jan 2021

Cited by 16 | Viewed by 6052

Abstract

Bird strike prevention in civil aviation has traditionally focused on the airport perimeter. Since the risk of especially damaging bird strikes outside the airport boundaries is rising, this paper investigates the safety potential of operational bird strike prevention involving pilots and controllers. In [...] Read more.

Bird strike prevention in civil aviation has traditionally focused on the airport perimeter. Since the risk of especially damaging bird strikes outside the airport boundaries is rising, this paper investigates the safety potential of operational bird strike prevention involving pilots and controllers. In such a concept, controllers would be equipped with a bird strike advisory system, allowing them to delay departures which are most vulnerable to the consequences of bird strikes in case of high bird strike risk. An initial study has shown the strong potential of the concept to prevent bird strikes in case of perfect bird movement prediction. This paper takes the research to the next level by taking into account the limited predictability of bird tracks. As such, the collision avoidance algorithm is extended to a bird strike risk algorithm. The risk of bird strikes is calculated for birds expected to cross the extended runway center line and to cause aircraft damage upon impact. By specifically targeting these birds and excluding birds lingering on the runway which are taken care of by the local wildlife control, capacity reductions should be limited, and the implementation remain feasible. The extrapolation of bird tracks is performed by simple linear regression based on the bird positions known at the intended take-off times. To calculate the probability of collision, uncertainties resulting from variability in bird velocity and track are included. The study demonstrates the necessity to limit alerts to potentially damaging strikes with birds crossing the extended runway center line to keep the imposed delays tolerable for airports operating at their capacity limits. It is shown that predicting bird movements based on simple linear regression without considering individual bird behavior is insufficient to achieve a safety-effect. Hence, in-depth studies of multi-year bird data to develop bird behavior models and reliable predictions are recommended for future research. This is expected to facilitate the implementation of a bird strike advisory system satisfying both safety and capacity aspects. Full article

► Show Figures

Figure 1

15 pages, 1945 KiB

Open AccessArticle

The Efficacy of Operational Bird Strike Prevention

by Isabel C. Metz, Joost Ellerbroek, Thorsten Mühlhausen, Dirk Kügler, Stefan Kern and Jacco M. Hoekstra

Aerospace 2021, 8(1), 17; https://doi.org/10.3390/aerospace8010017 - 14 Jan 2021

Cited by 10 | Viewed by 5200

Abstract

Involving air traffic controllers and pilots into the bird strike prevention process is considered an essential step to increase aviation and avian safety. Prior to implementing operational measures such as real-time warning systems, it is vital to evaluate their feasibility. This paper studies [...] Read more.

Involving air traffic controllers and pilots into the bird strike prevention process is considered an essential step to increase aviation and avian safety. Prior to implementing operational measures such as real-time warning systems, it is vital to evaluate their feasibility. This paper studies the efficacy of a bird strike advisory system for air traffic control. In addition to the potential safety benefit, the possible impact on airport operations is analyzed. To this end, a previously developed collision avoidance algorithm underlying the system was tested in fast-time Monte Carlo simulations involving various air traffic and bird densities to obtain representative conclusions for different operational conditions. The results demonstrate the strong safety potential of operational bird strike prevention in case of precise bird movement prediction. Unless airports operate close to their capacity limits while bird abundance is high, the induced delays remain tolerable. Prioritization of hazardous strikes involving large individuals as well as flocks of birds are expected to support operational feasibility in all conditions. Full article

► Show Figures

Figure 1

2020

Jump to: 2024, 2023, 2022, 2021, 2019, 2018, 2017

22 pages, 8010 KiB

Open AccessArticle

Traffic Network Identification Using Trajectory Intersection Clustering

by Ingrid Gerdes and Annette Temme

Aerospace 2020, 7(12), 175; https://doi.org/10.3390/aerospace7120175 - 10 Dec 2020

Cited by 5 | Viewed by 3036

Abstract

The current airspace route system consists mainly of pre-defined routes with a low number of intersections to facilitate air traffic controllers to oversee the traffic. Our aim is a method to create an artificial and reliable route network based on planned or as-flown [...] Read more.

The current airspace route system consists mainly of pre-defined routes with a low number of intersections to facilitate air traffic controllers to oversee the traffic. Our aim is a method to create an artificial and reliable route network based on planned or as-flown trajectories. The application possibilities of the resulting network are manifold, reaching from the assessment of new air traffic management (ATM) strategies or historical data to a basis for simulation systems. Trajectories are defined as sequences of common points at intersections with other trajectories. All common points of a traffic sample are clustered, and, after further optimization, the cluster centers are used as nodes in the new main-flow network. To build almost-realistic flight trajectories based on this network, additional parameters such as speed and altitude are added to the nodes and the possibility to take detours into account to avoid congested areas is introduced. As optimization criteria, the trajectory length and the structural complexity of the main-flow system are used. Based on these criteria, we develop a new cost function for the optimization process. In addition, we show how different traffic situations are covered by the network. To illustrate the capabilities of our approach, traffic is exemplarily divided into separate classes and class-dependent parameters are assigned. Applied to two real traffic scenarios, the approach was able to emulate the underlying route systems with a difference in median trajectory length of 0.2%, resp. 0.5% compared to the original routes. Full article

► Show Figures

Graphical abstract

21 pages, 950 KiB

Open AccessArticle

Evaluation of Strategies to Reduce the Cost Impacts of Flight Delays on Total Network Costs

by Judith Rosenow, Philipp Michling, Michael Schultz and Jörn Schönberger

Aerospace 2020, 7(11), 165; https://doi.org/10.3390/aerospace7110165 - 18 Nov 2020

Cited by 12 | Viewed by 6915

Abstract

Competitive price pressure and economic cost pressure constantly force airlines to improve their optimization strategies. Besides predictable operational costs, delay costs are a significant cost driver for airlines. Especially reactionary delay costs can endanger the profitability of such a company. These time-dependent costs [...] Read more.

Competitive price pressure and economic cost pressure constantly force airlines to improve their optimization strategies. Besides predictable operational costs, delay costs are a significant cost driver for airlines. Especially reactionary delay costs can endanger the profitability of such a company. These time-dependent costs depend on the number of sensitive transfer passengers. This cost component is represented by the number of missed flights and the connectivity of onward flights, i.e., the offer of alternative flight connections. The airline has several options to compensate for reactionary delays, for example, by increasing cruising speeds, shortening turnaround times, rebookings and cancellations. The effects of these options on the cost balance of airline total operating costs have been examined in detail, considering a flight-specific number of transfer passengers. The results have been applied to a 24-h rotation schedule of a large German hub airport. We found, that the fast turnaround and increasing cruise speed are the most effective strategies to compensate for passenger-specific delay costs. The results could be used in a multi-criteria trajectory optimization to find a balance between environmentally-driven and cost-index-driven detours and speed adjustments. Full article

► Show Figures

Figure 1

18 pages, 1367 KiB

Open AccessArticle

In-Flight Aircraft Trajectory Optimization within Corridors Defined by Ensemble Weather Forecasts

by Martin Lindner, Judith Rosenow, Thomas Zeh and Hartmut Fricke

Aerospace 2020, 7(10), 144; https://doi.org/10.3390/aerospace7100144 - 1 Oct 2020

Cited by 19 | Viewed by 4416

Abstract

Today, each flight is filed as a static route not later than one hour before departure. From there on, changes of the lateral route initiated by the pilot are only possible with air traffic control clearance and in the minority. Thus, the initially [...] Read more.

Today, each flight is filed as a static route not later than one hour before departure. From there on, changes of the lateral route initiated by the pilot are only possible with air traffic control clearance and in the minority. Thus, the initially optimized trajectory of the flight plan is flown, although the optimization may already be based upon outdated weather data at take-off. Global weather data as those modeled by the Global Forecast System do, however, contain hints on forecast uncertainties itself, which is quantified by considering so-called ensemble forecast data. In this study, the variability in these weather parameter uncertainties is analyzed, before the trajectory optimization model TOMATO is applied to single trajectories considering the previously quantified uncertainties. TOMATO generates, based on the set of input data as provided by the ensembles, a 3D corridor encasing all resulting optimized trajectories. Assuming that this corridor is filed in addition to the initial flight plan, the optimum trajectory can be updated even during flight, as soon as updated weather forecasts are available. In return and as a compromise, flights would have to stay within the corridor to provide planning stability for Air Traffic Management compared to full free in-flight optimization. Although the corridor restricts the re-optimized trajectory, fuel savings of up to 1.1%, compared to the initially filed flight, could be shown. Full article

► Show Figures

Figure 1

25 pages, 836 KiB

Open AccessArticle

OpenAP: An Open-Source Aircraft Performance Model for Air Transportation Studies and Simulations

by Junzi Sun, Jacco M. Hoekstra and Joost Ellerbroek

Aerospace 2020, 7(8), 104; https://doi.org/10.3390/aerospace7080104 - 23 Jul 2020

Cited by 74 | Viewed by 13450

Abstract

Air traffic simulations serve as common practice to evaluate different concepts and methods for air transportation studies. The aircraft performance model is a key element that supports these simulation-based studies. It is also an important component for simulation-independent studies, such as air traffic [...] Read more.

Air traffic simulations serve as common practice to evaluate different concepts and methods for air transportation studies. The aircraft performance model is a key element that supports these simulation-based studies. It is also an important component for simulation-independent studies, such as air traffic optimization and prediction studies. Commonly, contemporary studies have to rely on proprietary aircraft performance models that restrict the redistribution of the data and code. To promote openness and research comparability, an alternative open performance model would be beneficial for the air transportation research community. In this paper, we introduce an open aircraft performance model (OpenAP). It is an open-source model that is based on a number of our previous studies, which were focused on different components of the aircraft performance. The unique characteristic of OpenAP is that it was built upon open aircraft surveillance data and open literature models. The model is composed of four main components, including aircraft and engine properties, kinematic performances, dynamic performances, and utility libraries. Alongside the performance model, we are publishing an open-source toolkit to facilitate the use of this model. The main objective of this paper is to describe each main component, their connections, and how they can be used for simulation and research in practice. Finally, we analyzed the performance of OpenAP by comparing it with an existing performance model and sample flight data. Full article

► Show Figures

Figure 1

22 pages, 5774 KiB

Open AccessArticle

Evaluation of Asphalt Concrete Airport Pavement Conditions Based on the Airfield Pavement Condition Index (APCI) in Scope of Flight Safety

by Mariusz Wesołowski and Paweł Iwanowski

Aerospace 2020, 7(6), 78; https://doi.org/10.3390/aerospace7060078 - 15 Jun 2020

Cited by 12 | Viewed by 5416

Abstract

Airoport infrastructure development requires care to maintain it in proper technical condition. Due to this, airport pavements should be constantly monitored, and, above all, correctly managed. High-level airport pavement management requires access to reliable information about their current technical condition as well as [...] Read more.

Airoport infrastructure development requires care to maintain it in proper technical condition. Due to this, airport pavements should be constantly monitored, and, above all, correctly managed. High-level airport pavement management requires access to reliable information about their current technical condition as well as proper forecasting of this condition in the future. Obtaining good quality information about the technical condition of airport pavement should be based on a proven methodology, taking into account the introduced quality management system. The authors propose a method of technical pavement condition assessment based on the Airfield Pavement Condition Index (APCI), taking into account not only the results of the surface deterioration inventory, but also repair overviews, load bearing capacity, evenness and roughness of the surface, as well as the surface tensile bond strength. The method was developed during long-term work financed by the Ministry of Science and Higher Education. At the beginning of the article, the authors focus on reviewing the currently available methods of assessing the technical condition of the pavement. Then they briefly present the most popular surface assessment method based on the PCI indicator. Afterwards, a proprietary asphalt pavement assessment method based on the APCI indicator is proposed and an example of how to use the method is presented. Finally, they discuss the results and summarize the work done, and present further directions of work. Full article

► Show Figures

Figure 1

34 pages, 49896 KiB

Open AccessConcept Paper

A Collaborative Approach for an Integrated Modeling of Urban Air Transportation Systems

by Malte Niklaß, Niclas Dzikus, Majed Swaid, Jan Berling, Benjamin Lührs, Alexander Lau, Ivan Terekhov and Volker Gollnick

Aerospace 2020, 7(5), 50; https://doi.org/10.3390/aerospace7050050 - 28 Apr 2020

Cited by 25 | Viewed by 9641

Abstract

The current push in automation, communication, and electrical energy storage technologies has the potential to lift urban mobility into the sky. As several urban air mobility (UAM) concepts are conceivable, all relevant physical effects as well as mutual interrelations of the UAM system [...] Read more.

The current push in automation, communication, and electrical energy storage technologies has the potential to lift urban mobility into the sky. As several urban air mobility (UAM) concepts are conceivable, all relevant physical effects as well as mutual interrelations of the UAM system have to be addressed and evaluated at a sufficient level of fidelity before implementation. Therefore, a collaborative system of systems modeling approach for UAM is presented. To quickly identify physical effects and cross-disciplinary influences of UAM, a pool of low-fidelity physical analysis components is developed and integrated into the Remote Component Environment (RCE) workflow engine. This includes, i. a., the disciplines of demand forecast, trajectory, vertiport, and cost modeling as well as air traffic flow and capacity management. The definition and clarification of technical interfaces require intensive cooperation between specialists with different areas of expertise. To reduce this communication effort, the Common Parametric Aircraft Configuration Schema (CPACS) is adapted and used as central data exchange format. The UAM system module is initially applied for a 24-hour simulation of three generic networks in Hamburg City. After understanding the basic system-level behavior, higher level analysis components and feedback loops must be integrated in the UAM system module for evaluation and optimization of explicit operating concepts. Full article

► Show Figures

Figure 1

20 pages, 321 KiB

Open AccessReview

The Bird Strike Challenge

by Isabel C. Metz, Joost Ellerbroek, Thorsten Mühlhausen, Dirk Kügler and Jacco M. Hoekstra

Aerospace 2020, 7(3), 26; https://doi.org/10.3390/aerospace7030026 - 13 Mar 2020

Cited by 59 | Viewed by 16307

Abstract

Collisions between birds and aircraft pose a severe threat to aviation and avian safety. To understand and prevent these bird strikes, knowledge about the factors leading to these bird strikes is vital. However, even though it is a global issue, data availability strongly [...] Read more.

Collisions between birds and aircraft pose a severe threat to aviation and avian safety. To understand and prevent these bird strikes, knowledge about the factors leading to these bird strikes is vital. However, even though it is a global issue, data availability strongly varies and is difficult to put into a global picture. This paper aims to close this gap by providing an in-depth review of studies and statistics to obtain a concise overview of the bird strike problem in commercial aviation on an international level. The paper illustrates the factors contributing to the occurrence and the potential consequences in terms of effect on flight and damage. This is followed by a presentation of the risk-reducing measures currently in place as well as their limitations. The paper closes with an insight into current research investigating novel methods to prevent bird strikes. Full article

► Show Figures

Figure 1

14 pages, 3860 KiB

Open AccessArticle

Go-Around Detection Using Crowd-Sourced ADS-B Position Data

by Simon Richard Proud

Aerospace 2020, 7(2), 16; https://doi.org/10.3390/aerospace7020016 - 21 Feb 2020

Cited by 12 | Viewed by 7768

Abstract

The decision of a flight crew to undertake a go-around, aborting a landing attempt, is primarily to ensure the safe conduct of a flight. Although go-arounds are rare, they do cause air traffic disruption, especially in busy airspace, due to the need to [...] Read more.

The decision of a flight crew to undertake a go-around, aborting a landing attempt, is primarily to ensure the safe conduct of a flight. Although go-arounds are rare, they do cause air traffic disruption, especially in busy airspace, due to the need to accommodate an aircraft in an unusual position, and a go-around can also result in knock-on delays due to the time taken for the aircraft to re-position, fit into the landing sequence and execute a successful landing. Therefore, it is important to understand and alleviate the factors that can result in a go-around. In this paper, I present a new method for automatically detecting go-around events in aircraft position data, such as that sent via the ADS-B system, and apply the method to one year of approach data for Chhatrapati Shivaji Maharaj International Airport (VABB) in Mumbai, India. I show that the method is significantly more accurate than other methods, detecting go-arounds with very few false positives or negatives. Finally, I use the new method to reveal that while there is no one cause for go-arounds at this airport, the majority can be attributed to weather and/or an unstable approach. I also show that one runway (14/32) has a significantly higher proportion of go-arounds than the other (09/27). Full article

► Show Figures

Figure 1

26 pages, 1343 KiB

Open AccessArticle

Operational Feasibility Analysis of the Multimodal Controller Working Position “TriControl”

by Oliver Ohneiser, Marcus Biella, Axel Schmugler and Matt Wallace

Aerospace 2020, 7(2), 15; https://doi.org/10.3390/aerospace7020015 - 20 Feb 2020

Cited by 2 | Viewed by 6088

Abstract

Current Air Traffic Controller working positions (CWPs) are reaching their capacity owing to increasing levels of air traffic. The multimodal CWP prototype TriControl combines automatic speech recognition, multitouch gestures, and eye-tracking, aiming for more natural and improved human interaction with air traffic control [...] Read more.

Current Air Traffic Controller working positions (CWPs) are reaching their capacity owing to increasing levels of air traffic. The multimodal CWP prototype TriControl combines automatic speech recognition, multitouch gestures, and eye-tracking, aiming for more natural and improved human interaction with air traffic control systems. However, the prototype has not yet undergone systematic evaluation with respect to feasibility. This paper evaluates the operational feasibility, focusing on the system usability of the approach CWP TriControl and its fulfillment of operational requirements. Fourteen controllers took part in a simulation study to evaluate the TriControl concept. The active approach controllers among the group of participants served as the main core target subgroup. The ratings of all controllers in the TriControl assessment were, on average, generally in slight agreement, with just a few showing statistical significance. However, the active approach controllers performed better and rated the system much more positively. The active approach controllers were strongly positive regarding the system usability and acceptance of this early-stage prototype. Particularly, ease of use, user-friendliness, and learnability were perceived very positively. Overall, they were also satisfied with the command input procedure, and would use it for their daily work. Thus, the participating controllers encourage further enhancements to be made to TriControl. Full article

► Show Figures

Figure 1

2019

Jump to: 2024, 2023, 2022, 2021, 2020, 2018, 2017

27 pages, 397 KiB

Open AccessReview

Recent Advances in Anomaly Detection Methods Applied to Aviation

by Luis Basora, Xavier Olive and Thomas Dubot

Aerospace 2019, 6(11), 117; https://doi.org/10.3390/aerospace6110117 - 30 Oct 2019

Cited by 125 | Viewed by 18113

Abstract

Anomaly detection is an active area of research with numerous methods and applications. This survey reviews the state-of-the-art of data-driven anomaly detection techniques and their application to the aviation domain. After a brief introduction to the main traditional data-driven methods for anomaly detection, [...] Read more.

Anomaly detection is an active area of research with numerous methods and applications. This survey reviews the state-of-the-art of data-driven anomaly detection techniques and their application to the aviation domain. After a brief introduction to the main traditional data-driven methods for anomaly detection, we review the recent advances in the area of neural networks, deep learning and temporal-logic based learning. In particular, we cover unsupervised techniques applicable to time series data because of their relevance to the aviation domain, where the lack of labeled data is the most usual case, and the nature of flight trajectories and sensor data is sequential, or temporal. The advantages and disadvantages of each method are presented in terms of computational efficiency and detection efficacy. The second part of the survey explores the application of anomaly detection techniques to aviation and their contributions to the improvement of the safety and performance of flight operations and aviation systems. As far as we know, some of the presented methods have not yet found an application in the aviation domain. We review applications ranging from the identification of significant operational events in air traffic operations to the prediction of potential aviation system failures for predictive maintenance. Full article

► Show Figures

Figure 1

20 pages, 5735 KiB

Open AccessArticle

Queue-Based Modeling of the Aircraft Arrival Process at a Single Airport

by Eri Itoh and Mihaela Mitici

Aerospace 2019, 6(10), 103; https://doi.org/10.3390/aerospace6100103 - 20 Sep 2019

Cited by 35 | Viewed by 12252

Abstract

This paper proposes data-driven queuing models and solutions to reduce arrival time delays originating from aircraft arrival processing bottlenecks at Tokyo International Airport. A data-driven analysis was conducted using two years of radar tracks and flight plans from 2016 and 2017. This analysis [...] Read more.

This paper proposes data-driven queuing models and solutions to reduce arrival time delays originating from aircraft arrival processing bottlenecks at Tokyo International Airport. A data-driven analysis was conducted using two years of radar tracks and flight plans from 2016 and 2017. This analysis helps not only to understand the bottlenecks and operational strategies of air traffic controllers, but also to develop mathematical models to predict arrival delays resulting from increased, future aircraft traffic. The queue-based modeling approach suggests that one potential solution is to expand the realization of time-based operations, efficiently shifting from traffic flow control to time-based arrival management. Furthermore, the proposed approach estimates the most effective range of transition points, which is a key requirement for designing extended arrival management systems while offering automation support to air traffic controllers. Full article

► Show Figures

Figure 1

16 pages, 3729 KiB

Open AccessArticle

Interdependent Uncertainty Handling in Trajectory Prediction

by Thomas Zeh, Judith Rosenow and Hartmut Fricke

Aerospace 2019, 6(2), 15; https://doi.org/10.3390/aerospace6020015 - 12 Feb 2019

Cited by 9 | Viewed by 5827

Abstract

The concept of 4D trajectory management relies on the prediction of aircraft trajectories in time and space. Due to changes in atmospheric conditions and complexity of the air traffic itself, the reliable prediction of system states is an ongoing challenge. The emerging uncertainties [...] Read more.

The concept of 4D trajectory management relies on the prediction of aircraft trajectories in time and space. Due to changes in atmospheric conditions and complexity of the air traffic itself, the reliable prediction of system states is an ongoing challenge. The emerging uncertainties have to be modeled properly and considered in decision support tools for efficient air traffic flow management. Therefore, the subjacent causes for uncertainties, their effects on the aircraft trajectory and their dependencies to each other must be understood in detail. Besides the atmospheric conditions as the main external cause, the aircraft itself induces uncertainties to its trajectory. In this study, a cause-and-effect model is introduced, which deals with multiple interdependent uncertainties with different stochastic behavior and their impact on trajectory prediction. The approach is applied to typical uncertainties in trajectory prediction, such as the actual take-off mass, non-constant true air speeds, and uncertain weather conditions. The continuous climb profiles of those disturbed trajectories are successfully predicted. In general, our approach is applicable to all sources of quantifiable interdependent uncertainties. Therewith, ground-based trajectory prediction can be improved and a successful implementation of trajectory-based operations in the European air traffic system can be advanced. Full article

► Show Figures

Figure 1

2018

Jump to: 2024, 2023, 2022, 2021, 2020, 2019, 2017

16 pages, 796 KiB

Open AccessArticle

Simulation Model to Calculate Bird-Aircraft Collisions and Near Misses in the Airport Vicinity

by Isabel C. Metz, Thorsten Mühlhausen, Joost Ellerbroek, Dirk Kügler, Hans Van Gasteren, Jan Kraemer and Jacco M. Hoekstra

Aerospace 2018, 5(4), 112; https://doi.org/10.3390/aerospace5040112 - 25 Oct 2018

Cited by 6 | Viewed by 6295

Abstract

Annually, thousands of birds collide with aircraft. The impact usually has lethal consequences for the bird, the involved aircraft can experience severe damage. The highest bird strike risk occurs at low altitudes. Therefore, aircraft within the airport area as well as the adjacent [...] Read more.

Annually, thousands of birds collide with aircraft. The impact usually has lethal consequences for the bird, the involved aircraft can experience severe damage. The highest bird strike risk occurs at low altitudes. Therefore, aircraft within the airport area as well as the adjacent approach and departure corridors are especially vulnerable to collisions with birds. To analyse risk-reducing measures in these areas, a fast-time bird strike simulation environment was developed. An open-source Air Traffic Management simulator was enhanced with a model to represent bird movements and to recognize bird strikes. To confirm the reproducibility of the outcome, Monte Carlo simulations were performed. They included bird movement data from one year and air traffic flight plans for various air traffic volumes. The number of strikes and near misses showed an expected variance within the individual replications. The results indicate that the predictability of the number of strikes and near misses increases with rising number of birds, and rising air traffic intensity. Thus, by considering simulation scenarios including bird movement information from all seasons and a sufficient air traffic volume, the described set-up leads to stable results. Full article

► Show Figures

Graphical abstract

19 pages, 1304 KiB

Open AccessArticle

Weather Impact on Airport Performance

by Michael Schultz, Sandro Lorenz, Reinhard Schmitz and Luis Delgado

Aerospace 2018, 5(4), 109; https://doi.org/10.3390/aerospace5040109 - 15 Oct 2018

Cited by 52 | Viewed by 10824

Abstract

Weather events have a significant impact on airport performance and cause delayed operations if the airport capacity is constrained. We provide quantification of the individual airport performance with regards to an aggregated weather-performance metric. Specific weather phenomena are categorized by the air traffic [...] Read more.

Weather events have a significant impact on airport performance and cause delayed operations if the airport capacity is constrained. We provide quantification of the individual airport performance with regards to an aggregated weather-performance metric. Specific weather phenomena are categorized by the air traffic management airport performance weather algorithm, which aims to quantify weather conditions at airports based on aviation routine meteorological reports. Our results are computed from a data set of 20.5 million European flights of 2013 and local weather data. A methodology is presented to evaluate the impact of weather events on the airport performance and to select the appropriate threshold for significant weather conditions. To provide an efficient method to capture the impact of weather, we modelled departing and arrival delays with probability distributions, which depend on airport size and meteorological impacts. These derived airport performance scores could be used in comprehensive air traffic network simulations to evaluate the network impact caused by weather induced local performance deterioration. Full article

► Show Figures

Graphical abstract

26 pages, 1425 KiB

Open AccessArticle

A Cooperative Co-Evolutionary Optimisation Model for Best-Fit Aircraft Sequence and Feasible Runway Configuration in a Multi-Runway Airport

by Md Shohel Ahmed, Sameer Alam and Michael Barlow

Aerospace 2018, 5(3), 85; https://doi.org/10.3390/aerospace5030085 - 9 Aug 2018

Cited by 19 | Viewed by 7374

Abstract

A careful arrival and departure sequencing of aircraft can reduce the inter-arrival/departure time, thereby opening up opportunities for new landing and/or take-off slots, which may increase the runway throughput. This sequence when serviced with a suitable runway configuration may result in an optimal [...] Read more.

A careful arrival and departure sequencing of aircraft can reduce the inter-arrival/departure time, thereby opening up opportunities for new landing and/or take-off slots, which may increase the runway throughput. This sequence when serviced with a suitable runway configuration may result in an optimal aircraft sequence with a runway configuration that can process the maximum number of aircraft within a given time interval. In this paper, we propose a Cooperative Co-evolutionary Genetic Algorithm (CCoGA) to find the combined solution of a best-fit sequence with a feasible runway configuration for a given traffic demand at an airport. The aircraft sequence and the runway configuration are modelled as individual species, which can cooperatively interact with each other. Therefore, we computationally evolve the best possible combination of aircraft sequence (arrival and departure) and the feasible runway configuration. The proposed CCoGA algorithm is evaluated for Chicago O’Hare International Airport runway layout and resulting configurations. Arrival and departure traffic demand is modelled through a Poisson distribution. Two different arrival/departure sequencing methods, i.e., constraint position shifting with one, two and N-position shifting and first come first serve, are modelled. Runway configuration and traffic sequence (arrivals and departure) are modelled as two species, which are evolved co-operatively, through the CCoGA algorithm, to achieve the optimal traffic sequencing with a feasible runway configuration. Time-space diagrams are presented for the best-evolved population of arrival-departure sequence and runway configuration to illustrate the possibility of using available departure slots between arrivals to maximize capacity. Arrival-departure capacity envelopes are then presented to illustrate the trade-off between the arrivals and departures, given a runway configuration for each sequencing method. Results demonstrate the high mutual dependence between arrival-departure sequence and the runway configuration, as well as its effect on overall runway capacity. The results also demonstrate the viability of using evolutionary computation-based methods for modelling and evaluating complex problems in the air transport domain. Full article

► Show Figures

Figure 1

13 pages, 409 KiB

Open AccessArticle

Robust Optimization of Airplane Passenger Seating Assignments

by R. John Milne, Mostafa Salari and Lina Kattan

Aerospace 2018, 5(3), 80; https://doi.org/10.3390/aerospace5030080 - 1 Aug 2018

Cited by 32 | Viewed by 6467

Abstract

We present a method that reduces the time it takes to complete the passenger boarding of an airplane. In particular, we describe a two-stage mixed integer programming (MIP) approach, which assigns passengers to seats on an airplane based on the number of bags [...] Read more.

We present a method that reduces the time it takes to complete the passenger boarding of an airplane. In particular, we describe a two-stage mixed integer programming (MIP) approach, which assigns passengers to seats on an airplane based on the number of bags they carry aboard the plane. The first stage is an MIP that assigns passengers to seats to minimize the time to complete the boarding of the plane. The second-stage MIP also determines seating assignments, while constraining the total boarding time to that determined by the stage-one MIP and maximizing weighted slack times to provide a more robust assignment. Numerical results show that this two-stage approach results in lower average boarding times than the one-stage approach, when the time it takes passengers to walk and sit in their seats is random. Experiments indicate that the magnitude of the improvement is not very sensitive to variations in the slack time weights. Full article

► Show Figures

Graphical abstract

31 pages, 9849 KiB

Open AccessArticle

Uncertainty Management at the Airport Transit View

by Álvaro Rodríguez-Sanz, Fernando Gómez Comendador, Rosa Arnaldo Valdés, Jose Manuel Cordero García and Margarita Bagamanova

Aerospace 2018, 5(2), 59; https://doi.org/10.3390/aerospace5020059 - 1 Jun 2018

Cited by 6 | Viewed by 8412

Abstract

Air traffic networks, where airports are the nodes that interconnect the entire system, have a time-varying and stochastic nature. An incident in the airport environment may easily propagate through the network and generate system-level effects. This paper analyses the aircraft flow through the [...] Read more.

Air traffic networks, where airports are the nodes that interconnect the entire system, have a time-varying and stochastic nature. An incident in the airport environment may easily propagate through the network and generate system-level effects. This paper analyses the aircraft flow through the Airport Transit View framework, focusing on the airspace/airside integrated operations. In this analysis, we use a dynamic spatial boundary associated with the Extended Terminal Manoeuvring Area concept. Aircraft operations are characterised by different temporal milestones, which arise from the combination of a Business Process Model for the aircraft flow and the Airport Collaborative Decision-Making methodology. Relationships between factors influencing aircraft processes are evaluated to create a probabilistic graphical model, using a Bayesian network approach. This model manages uncertainty and increases predictability, hence improving the system’s robustness. The methodology is validated through a case study at the Adolfo Suárez Madrid-Barajas Airport, through the collection of nearly 34,000 turnaround operations. We present several lessons learned regarding delay propagation, time saturation, uncertainty precursors and system recovery. The contribution of the paper is two-fold: it presents a novel methodological approach for tackling uncertainty when linking inbound and outbound flights and it also provides insight on the interdependencies among factors driving performance. Full article

► Show Figures

Graphical abstract

18 pages, 4179 KiB

Open AccessArticle

Faster Command Input Using the Multimodal Controller Working Position “TriControl”

by Oliver Ohneiser, Malte Jauer, Jonathan R. Rein and Matt Wallace

Aerospace 2018, 5(2), 54; https://doi.org/10.3390/aerospace5020054 - 8 May 2018

Cited by 4 | Viewed by 6562

Abstract

TriControl is a controller working position (CWP) prototype developed by German Aerospace Center (DLR) to enable more natural, efficient, and faster command inputs. The prototype integrates three input modalities: speech recognition, eye tracking, and multi-touch sensing. Air traffic controllers may use all three [...] Read more.

TriControl is a controller working position (CWP) prototype developed by German Aerospace Center (DLR) to enable more natural, efficient, and faster command inputs. The prototype integrates three input modalities: speech recognition, eye tracking, and multi-touch sensing. Air traffic controllers may use all three modalities simultaneously to build commands that will be forwarded to the pilot and to the air traffic management (ATM) system. This paper evaluates possible speed improvements of TriControl compared to conventional systems involving voice transmission and manual data entry. 26 air traffic controllers participated in one of two air traffic control simulation sub-studies, one with each input system. Results show potential of a 15% speed gain for multimodal controller command input in contrast to conventional inputs. Thus, the use and combination of modern human machine interface (HMI) technologies at the CWP can increase controller productivity. Full article

► Show Figures

Graphical abstract

17 pages, 4544 KiB

Open AccessArticle

Simulation of Random Events for Air Traffic Applications

by Stéphane Puechmorel, Guillaume Dufour and Romain Fèvre

Aerospace 2018, 5(2), 53; https://doi.org/10.3390/aerospace5020053 - 3 May 2018

Cited by 3 | Viewed by 5480

Abstract

Resilience to uncertainties must be ensured in air traffic management. Unexpected events can either be disruptive, like thunderstorms or the famous volcano ash cloud resulting from the Eyjafjallajökull eruption in Iceland, or simply due to imprecise measurements or incomplete knowledge of the environment. [...] Read more.

Resilience to uncertainties must be ensured in air traffic management. Unexpected events can either be disruptive, like thunderstorms or the famous volcano ash cloud resulting from the Eyjafjallajökull eruption in Iceland, or simply due to imprecise measurements or incomplete knowledge of the environment. While human operators are able to cope with such situations, it is generally not the case for automated decision support tools. Important examples originate from the numerous attempts made to design algorithms able to solve conflicts between aircraft occurring during flights. The STARGATE (STochastic AppRoach for naviGATion functions in uncertain Environment) project was initiated in order to study the feasibility of inherently robust automated planning algorithms that will not fail when submitted to random perturbations. A mandatory first step is the ability to simulate the usual stochastic phenomenons impairing the system: delays due to airport platforms or air traffic control (ATC) and uncertainties on the wind velocity. The work presented here will detail algorithms suitable for the simulation task. Full article

► Show Figures

Figure 1

11 pages, 9423 KiB

Open AccessArticle

The Public Safety Zones around Small and Medium Airports

by Paola Di Mascio, Giuseppe Perta, Giuseppe Cantisani and Giuseppe Loprencipe

Aerospace 2018, 5(2), 46; https://doi.org/10.3390/aerospace5020046 - 23 Apr 2018

Cited by 4 | Viewed by 7765

Abstract

Proper planning around airports safeguards the surrounding territory from risks of air accidents. Many countries have defined Public Safety Zones (PSZs) beyond the runway thresholds as a result of targeted risk assessment methods. Therefore, national aviation Authorities could limit building construction and industrial [...] Read more.

Proper planning around airports safeguards the surrounding territory from risks of air accidents. Many countries have defined Public Safety Zones (PSZs) beyond the runway thresholds as a result of targeted risk assessment methods. Therefore, national aviation Authorities could limit building construction and industrial development in order to contain the risk for dwellers to be involved in aircraft accidents. The number of people who live, work or congregate in these areas should be limited. The procedure to set Public Safety Zones is based on advanced technical analyses for major infrastructures. For smaller airports, simplified schemes are used, but, sometimes, they are not as effective when considering the actual safety conditions. This article aims to identify the shape and size of the Public Safety Zones for small and medium one-runway airports. The influence of the volume and mix of traffic on the PSZ geometry has been evaluated using the program named SARA (Sapienza Airport Risk Analysis); the results are correlated with the current Risk Plans generally adopted in Italy. According to the air traffic, the Risk Plans are characterized by a dynamic definition and fit the results obtained from risk assessment. Full article

► Show Figures

Graphical abstract

18 pages, 2904 KiB

Open AccessArticle

Simulation-Based Virtual Cycle for Multi-Level Airport Analysis

by Miguel Mujica Mota, Alejandro Di Bernardi, Paolo Scala and Gabriel Ramirez-Diaz

Aerospace 2018, 5(2), 44; https://doi.org/10.3390/aerospace5020044 - 19 Apr 2018

Cited by 10 | Viewed by 7360

Abstract

The aeronautical industry is expanding after a period of economic turmoil. For this reason, a growing number of airports are facing capacity problems that can sometimes only be resolved by expanding infrastructure, with the inherent risks that such decisions create. In order to [...] Read more.

The aeronautical industry is expanding after a period of economic turmoil. For this reason, a growing number of airports are facing capacity problems that can sometimes only be resolved by expanding infrastructure, with the inherent risks that such decisions create. In order to deal with uncertainty at different levels, it is necessary to have relevant tools during an expansion project or during the planning phases of new infrastructure. This article presents a methodology that combines simulation approaches with different description levels that complement each other when applied to the development of a new airport. The methodology is illustrated with an example that uses two models for an expansion project of an airport in The Netherlands. One model focuses on the operation of the airport from a high-level position, while the second focuses on other technical aspects of the operation that challenge the feasibility of the proposed configuration of the apron. The results show that by applying the methodology, analytical power is enhanced and the risk of making the wrong decisions is reduced. We identified the limitations that the future facility will have and the impact of the physical characteristics of the traffic that will operate in the airport. The methodology can be used for tackling different problems and studying particular performance indicators to help decision-makers take more informed decisions. Full article

► Show Figures

Figure 1

18 pages, 4281 KiB

Open AccessArticle

Fast Aircraft Turnaround Enabled by Reliable Passenger Boarding

by Michael Schultz

Aerospace 2018, 5(1), 8; https://doi.org/10.3390/aerospace5010008 - 15 Jan 2018

Cited by 58 | Viewed by 12138

Abstract

Future 4D aircraft trajectories demand comprehensive consideration of environmental, economic, and operational constraints, as well as reliable prediction of all aircraft-related processes. Mutual interdependencies between airports result in system-wide, far-reaching effects in the air traffic network (reactionary delays). To comply with airline/airport challenges [...] Read more.

Future 4D aircraft trajectories demand comprehensive consideration of environmental, economic, and operational constraints, as well as reliable prediction of all aircraft-related processes. Mutual interdependencies between airports result in system-wide, far-reaching effects in the air traffic network (reactionary delays). To comply with airline/airport challenges over the day of operations, a change to an air-to-air perspective is necessary, with a specific focus on the aircraft ground operations as major driver for airline punctuality. Aircraft ground trajectories primarily consists of handling processes at the stand (deboarding, catering, fueling, cleaning, boarding, unloading, loading), which are defined as the aircraft turnaround. Turnaround processes are mainly controlled by ground handling, airport, or airline staff, except the aircraft boarding, which is driven by passengers’ experience and willingness/ability to follow the proposed boarding procedures. This paper provides an overview of the research done in the field of aircraft boarding and introduces a reliable, calibrated, and stochastic aircraft boarding model. The stochastic boarding model is implemented in a simulation environment to evaluate specific boarding scenarios using different boarding strategies and innovative technologies. Furthermore, the potential of a connected aircraft cabin as sensor network is emphasized, which could provide information on the current and future status of the boarding process. Full article

► Show Figures

Graphical abstract

2017

Jump to: 2024, 2023, 2022, 2021, 2020, 2019, 2018

6553 KiB

Open AccessArticle

Comparative Study of Aircraft Boarding Strategies Using Cellular Discrete Event Simulation

by Shafagh Jafer and Wei Mi

Aerospace 2017, 4(4), 57; https://doi.org/10.3390/aerospace4040057 - 28 Nov 2017

Cited by 27 | Viewed by 8533

Abstract

Time is crucial in the airlines industry. Among all factors contributing to an aircraft turnaround time; passenger boarding delays is the most challenging one. Airlines do not have control over the behavior of passengers; thus, focusing their effort on reducing passenger boarding time [...] Read more.

Time is crucial in the airlines industry. Among all factors contributing to an aircraft turnaround time; passenger boarding delays is the most challenging one. Airlines do not have control over the behavior of passengers; thus, focusing their effort on reducing passenger boarding time through implementing efficient boarding strategies. In this work, we attempt to use cellular Discrete-Event System Specification (Cell-DEVS) modeling and simulation to provide a comprehensive evaluation of aircraft boarding strategies. We have developed a simulation benchmark consisting of eight boarding strategies including Back-to-Front; Window Middle Aisle; Random; Zone Rotate; Reverse Pyramid; Optimal; Optimal Practical; and Efficient. Our simulation models are scalable and adaptive; providing a powerful analysis apparatus for investigating any existing or yet to be discovered boarding strategy. We explain the details of our models and present the results both visually and numerically to evaluate the eight implemented boarding strategies. We also compare our results with other studies that have used different modeling techniques; reporting nearly identical performance results. The simulations revealed that Window Middle Aisle provides the least boarding delay; with a small fraction of time difference compared to the optimal strategy. The results of this work could highly benefit the commercial airlines industry by optimizing and reducing passenger boarding delays. Full article

► Show Figures

Figure 1

3885 KiB

Open AccessArticle

An Efficient Application of the MOEA/D Algorithm for Designing Noise Abatement Departure Trajectories

by Vinh Ho-Huu, Sander Hartjes, Hendrikus G. Visser and Richard Curran

Aerospace 2017, 4(4), 54; https://doi.org/10.3390/aerospace4040054 - 1 Nov 2017

Cited by 23 | Viewed by 7772

Abstract

In an effort to allow to increase the number of aircraft and airport operations while mitigating their negative impacts (e.g., noise and pollutant emission) on near-airport communities, the optimal design of new departure routes with less noise and fuel consumption becomes more important. [...] Read more.

In an effort to allow to increase the number of aircraft and airport operations while mitigating their negative impacts (e.g., noise and pollutant emission) on near-airport communities, the optimal design of new departure routes with less noise and fuel consumption becomes more important. In this paper, a multi-objective evolutionary algorithm based on decomposition (MOEA/D), which recently emerged as a potential method for solving multi-objective optimization problems (MOPs), is developed for this kind of problem. First, to minimize aircraft noise for departure routes while taking into account the interests of various stakeholders, bi-objective optimization problems involving noise and fuel consumption are formulated where both the ground track and vertical profile of a departure route are optimized simultaneously. Second, in order to make the design space of vertical profiles feasible during the optimization process, a trajectory parameterization technique recently proposed is employed. Furthermore, some modifications to MOEA/D that are aimed at significantly reducing the computational cost are also introduced. Two different examples of departure routes at Schiphol Airport in the Netherlands are shown to demonstrate the applicability and reliability of the proposed method. The simulation results reveal that the proposed method is an effective and efficient approach for solving this kind of problem. Full article

► Show Figures

Figure 1

522 KiB

Open AccessArticle

Optimization of Air Traffic Control Training at the Federal Aviation Administration Academy

by Jessica A. Updegrove and Shafagh Jafer

Aerospace 2017, 4(4), 50; https://doi.org/10.3390/aerospace4040050 - 28 Oct 2017

Cited by 23 | Viewed by 10611

Abstract

This paper investigates current and future uses of simulation in the Federal Aviation Administration (FAA) Academy’s Air Traffic Control (ATC) training program to identify potential improvement areas in the areas of simulation technologies and course content. Once identified, recommendations for changes to the [...] Read more.

This paper investigates current and future uses of simulation in the Federal Aviation Administration (FAA) Academy’s Air Traffic Control (ATC) training program to identify potential improvement areas in the areas of simulation technologies and course content. Once identified, recommendations for changes to the current training program are made. A literature review of the current training techniques used at the FAA Academy and training centers was conducted. In addition, interviews were held and surveys were distributed to collect data regarding a variety of ATC training interest areas, such as virtual reality, current maintenance schedules, and simulator features. Finally, a cost-benefit analysis was conducted to determine the potential improvement areas with the highest feasibility for implementation and the highest potential to reduce training costs and/or time. The primary findings of this research revealed three feasible improvement areas to the current training process and simulation technologies: (1) reducing the dependence on instructors during simulation training, (2) utilizing web-based training methods, and (3) updating current simulator systems to include new features, such as recording and playback features. These changes were recommended to be implemented first, with voice recognition and virtual reality improvement areas being recommended as priority focus areas for future studies and/or implementation. Full article

► Show Figures

Figure 1

Journal Menu

Journal Browser

Air Transportation—Operations and Management

Share This Topical Collection

Editors

Topical Collection Information

Keywords

Published Papers (76 papers)

2024

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

2023

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

2022

Jump to: 2024, 2023, 2021, 2020, 2019, 2018, 2017

2021

Jump to: 2024, 2023, 2022, 2020, 2019, 2018, 2017

2020

Jump to: 2024, 2023, 2022, 2021, 2019, 2018, 2017

2019

Jump to: 2024, 2023, 2022, 2021, 2020, 2018, 2017

2018

Jump to: 2024, 2023, 2022, 2021, 2020, 2019, 2017

2017

Jump to: 2024, 2023, 2022, 2021, 2020, 2019, 2018

Further Information

Guidelines

MDPI Initiatives

Follow MDPI