Topical Collection "Air Transportation—Operations and Management"

Editors

Guest Editor
Dr. Michael Schultz

Department of Air Transportation, Institute of Flight Guidance, German Aerospace Center (DLR), 38108 Braunschweig, Germany
Website | E-Mail
Interests: air transport; ATM; integrated airport management; complexity; pedestrian dynamics
Guest Editor
Dr. Judith Rosenow

Institute of Logistics and Aviation, Technische Universität Dresden, 01062 Dresden, Germany
Website | E-Mail
Interests: contrails; ATM; air traffic; trajectory optimization; flight performance

Topical Collection Information

Dear Colleagues,

Future air traffic demand requires air traffic providers, operators, and researchers, implementing new procedures and technologies to handle the dense air traffic network. The bottlenecks in capacity, which are already partly present, challenge air traffic control on landside, ground, and airside. The economic pressure further forces air traffic stakeholders to sustainably increase the transport efficiency considering upcoming societal and environmental issues without a deterioration of the safety level. Inefficiencies indicating a high improvement potential have been identified in the time-based operations of aircraft, of interdependencies aircraft and passenger trajectories, economic and ecology impact of air traffic, network operations and handling of uncertainties, disturbances, and disruptions in the aviation system. Current approaches will provide solutions, such as resilient air transport network management, green airport taxi procedures, optimal control of scarce resources (e.g., slots, runway or apron capacity, fleet allocation), and mitigation of impact of severe weather conditions. Focusing aircraft operations, new optimization algorithms deal with time based trajectory management considering conflicting goals of increased efficiency and environmental awareness, noise abatement strategies, efficient air space design and increased target levels of safety. This collection invites papers that present solutions for the areas of air traffic operations and economics. Of interest are papers that address solutions to deal with challenges of all air traffic stakeholders. In particular, the collection wants to focus on dynamic airspace management, flight centered operations, turnaround management, air transport performance (e.g., new metrics, inter-airport coordination), trajectory management, eco-efficient aircraft operations (e.g., formation flight, contrail avoidance), airport management (e.g., integrated approaches, pre-tactical planning), delay mitigation in the transport network, and holistic optimization approaches. Innovative solutions are being sought to enable versatile investigations of the air transport domain and provide multi-disciplinary approaches.

Dr. Michael Schultz
Dr. Judith Rosenow
Guest Editors

Manuscript Submission Information

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Keywords

  • aviation
  • transportation
  • airport
  • air space
  • traffic management
  • operations

Published Papers (13 papers)

2018

Jump to: 2017

Open AccessArticle Simulation Model to Calculate Bird-Aircraft Collisions and Near Misses in the Airport Vicinity
Aerospace 2018, 5(4), 112; https://doi.org/10.3390/aerospace5040112
Received: 23 September 2018 / Revised: 16 October 2018 / Accepted: 21 October 2018 / Published: 25 October 2018
PDF Full-text (796 KB) | HTML Full-text | XML Full-text | Supplementary Files
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
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Open AccessArticle Weather Impact on Airport Performance
Aerospace 2018, 5(4), 109; https://doi.org/10.3390/aerospace5040109
Received: 7 September 2018 / Revised: 5 October 2018 / Accepted: 8 October 2018 / Published: 15 October 2018
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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
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Open AccessArticle A Cooperative Co-Evolutionary Optimisation Model for Best-Fit Aircraft Sequence and Feasible Runway Configuration in a Multi-Runway Airport
Received: 16 July 2018 / Revised: 4 August 2018 / Accepted: 5 August 2018 / Published: 9 August 2018
PDF Full-text (1425 KB) | HTML Full-text | XML Full-text
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
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Open AccessArticle Robust Optimization of Airplane Passenger Seating Assignments
Received: 26 June 2018 / Revised: 17 July 2018 / Accepted: 23 July 2018 / Published: 1 August 2018
Cited by 2 | PDF Full-text (409 KB) | HTML Full-text | XML Full-text | Supplementary Files
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
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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
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Open AccessArticle Uncertainty Management at the Airport Transit View
Received: 28 January 2018 / Revised: 16 May 2018 / Accepted: 21 May 2018 / Published: 1 June 2018
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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
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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
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Open AccessArticle Faster Command Input Using the Multimodal Controller Working Position “TriControl”
Received: 6 April 2018 / Revised: 27 April 2018 / Accepted: 4 May 2018 / Published: 8 May 2018
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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
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Open AccessArticle Simulation of Random Events for Air Traffic Applications
Received: 23 March 2018 / Revised: 27 April 2018 / Accepted: 28 April 2018 / Published: 3 May 2018
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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
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Open AccessArticle The Public Safety Zones around Small and Medium Airports
Received: 27 March 2018 / Revised: 16 April 2018 / Accepted: 20 April 2018 / Published: 23 April 2018
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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
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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
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Open AccessArticle Simulation-Based Virtual Cycle for Multi-Level Airport Analysis
Received: 11 February 2018 / Revised: 15 April 2018 / Accepted: 16 April 2018 / Published: 19 April 2018
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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
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Open AccessArticle Fast Aircraft Turnaround Enabled by Reliable Passenger Boarding
Received: 24 November 2017 / Revised: 31 December 2017 / Accepted: 9 January 2018 / Published: 15 January 2018
Cited by 6 | PDF Full-text (4281 KB) | HTML Full-text | XML Full-text
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
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2017

Jump to: 2018

Open AccessArticle Comparative Study of Aircraft Boarding Strategies Using Cellular Discrete Event Simulation
Received: 6 November 2017 / Revised: 23 November 2017 / Accepted: 25 November 2017 / Published: 28 November 2017
Cited by 5 | PDF Full-text (6553 KB) | HTML Full-text | XML Full-text
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
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Open AccessArticle An Efficient Application of the MOEA/D Algorithm for Designing Noise Abatement Departure Trajectories
Received: 2 October 2017 / Revised: 24 October 2017 / Accepted: 27 October 2017 / Published: 1 November 2017
Cited by 3 | PDF Full-text (3885 KB) | HTML Full-text | XML Full-text
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.
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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
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Open AccessArticle Optimization of Air Traffic Control Training at the Federal Aviation Administration Academy
Received: 23 September 2017 / Revised: 15 October 2017 / Accepted: 25 October 2017 / Published: 28 October 2017
Cited by 1 | PDF Full-text (522 KB) | HTML Full-text | XML Full-text
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
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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
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