Search Results (25)

An airport slot is the core resource in the air transportation system. In most busy airports in China, airline demand significantly exceeds the available slot capacity. Scientific and reasonable slot allocation techniques and methods can improve the operational efficiency and benefits of multi-airport systems. Existing research has predominantly addressed slot allocation optimization for individual airports; however, there are differences in the functional positioning and resource allocation during multi-airport slot optimization, which makes cooperative optimization in the context of multi-airport slot allocation difficult. The dynamic sharing of airspace capacity in multi-airport systems is crucial for optimizing airport slot allocation and improving resource utilization efficiency. This study develops a multi-objective optimization model incorporating coupled airspace capacity relationships within multi-airport systems and the fairness of airlines and airports in order to realize the optimal utilization of multi-airport system resources, considering specialized 24 h airport slot coordination parameter patterns and slot firebreaks in China. Finally, the validity and scalability of the model are verified using real flight data from three airports in the Beijing airport terminal area, and simulations are conducted to verify the model. The findings provide a solid reference for the optimization of airport slot timetables in multi-airport systems, having both important theoretical value and practical significance. Full article

The integration of Unmanned Aerial Vehicles (UAVs) into non-segregated airspace has raised critical conflict detection and resolution challenges, especially as UAV applications continue to expand. This paper presents a novel conflict resolution approach for multiple UAVs by segmenting the airspace into discrete altitude intervals. Two vertical maneuvering algorithms are proposed: one employing random selection and the other based on occupancy awareness. The simulation results demonstrate that the proposed method effectively resolves conflicts, reduces the likelihood of future encounters, and optimizes resource usage, contributing to safer and more efficient UAV operations in shared airspace. Full article

With increasing air traffic, the workload of air traffic controllers (ATCOs) and their limited number is again a restricting factor for the evolution of airspace management. Currently, possibilities to apply artificial intelligence for improving the support of ATCOs are widely discussed. By introducing a digital ATCO as a team partner for a human ATCO, we can expand capabilities. It can be trained to manage traffic across various airspace sectors without the limitations imposed by required licenses. This way, shortages of human ATCOs may be absorbed, and flexible assignment to sectors is facilitated with a digital ATCO partner. To be effective, the digital ATCO needs an understanding of current and future traffic situations to share the situation awareness of the human ATCO. The goal is to equip the digital ATCO with a comparable understanding—referred as a “mental model”—of the traffic situation and human actions, thereby improving decision-making and build up adequate trust with humans. In this work, decisive factors of traffic and management for the creation of digital situation awareness are identified and examined for their relevance and applicability for digital ATCOs. Within this study, a data-driven process of building up digital situation awareness including the influencing factors are suggested, and the usability of factors like the airspace complexity for indicating digital situation awareness are proposed. Finally, an example is presented and discussed to showcase our approach with focus on the integration of digital and human ATCOs through shared situation awareness. Full article

The complexity and resource-sharing nature of traffic within multi-airport regions present significant challenges for air traffic management. This paper aims to develop a mesoscopic traffic model for exploring the traffic dynamics under coupled operations, and thus to conduct capacity decoupling analysis. We propose an integrated surface–airspace model. In the surface model, we utilize linear regression and random forest regression to model unimpeded taxiing time and taxiway network delays due to sparsity of ground traffic. In the airspace model, a dualized queuing network topology is constructed including a runway system, where the $G(t)/GI/s(t)$ fluid queuing model is applied, and an inter-node traffic flow transmission mechanism is introduced to simulate airspace network traffic. Based on the hybrid and efficient model, we employ a Monte Carlo approach and use a quantile regression envelope model for capacity decoupling analysis. Using the Shanghai multi-airport region as a case study, the model’s performance is validated from the perspectives of operation time and traffic throughput. The results show that our model accurately represents traffic dynamics and estimates delays within an acceptable margin of error. The capacity decoupling analysis effectively captures the interdependence in traffic flow caused by resource sharing, both within a single airport and between airports. Full article

The deployment of Advanced Air Mobility requires the continued development of technologies to ensure operational safety. One of the key aspects to consider here is the availability of robust solutions to avoid tactical conflicts between drones and other flying elements, such as other drones or birds. Bird detection is a relatively underexplored area, but due to the large number of birds, their shared airspace with drones, and the fact that they are non-cooperative elements within an air traffic management system, it is of interest to study how their detection can be improved and how collisions with them can be avoided. This work demonstrates how a LiDAR sensor mounted on a drone can detect birds of various sizes. A LiDAR simulator, previously developed by the Aerolab research group, is employed in this study. Six different collision trajectories and three different bird sizes (pigeon, falcon, and seagull) are tested. The results show that the LiDAR can detect any of these birds at about 30 m; bird detection improves when the bird gets closer and has a larger size. The detection accuracy is higher than 1 m in most of the cases under study. The errors grow with increasing drone-bird relative speed. Full article

Mycoplasma bovis is a globally significant pathogen of cattle associated with a wide range of clinical syndromes, including respiratory disease, mastitis, arthritis, otitis, and reproductive failure. Since its detection in Ireland in 1994, M. bovis has become a significant contributor to morbidity and mortality in Irish cattle. This study aimed to investigate herd-level risk factors associated with M. bovis seropositivity in replacement dairy heifers, using data from 105 Irish dairy herds. Ten heifers per herd were sampled on three occasions: spring 2018, spring 2019, and autumn 2019. Seropositivity was evaluated using two thresholds: ≥1 positive heifer (Model ≥ 1POS) and ≥3 positive heifers (Model ≥ 3POS). M. bovis seropositivity varied over time, with at least one positive heifer in 50.4% (95% confidence interval (CI): 40.5–60.3) of herds in spring 2018, 35.2% (95% CI: 26.2–45.1) in spring 2019, and 45.7% (95% CI: 36.0–55.7) in autumn 2019. Herds with three or more positive heifers increased from 31.4% (95%CI: 22.7–41.2) in spring 2018 to 42.9% (95% CI: 33.2–52.9) by autumn 2019. Risk factors for M. bovis seropositivity included the purchase of cattle, which significantly raised the odds of seropositivity across multiple visit periods (Model ≥ 1POS: Odds ratio (OR) 3.84, p = 0.02; Model ≥ 3POS: OR 3.69, p = 0.02). Managing more than three land parcels, housing heifer calves separately from bull calves, and sharing airspace between calves and older animals also increased seropositivity risks. Conversely, more colostrum feeds reduced the risk of seropositivity (Model ≥ 1POS: OR 0.81, p = 0.05), while colostrum quality assessment and feeding waste milk showed a trend toward increased risk. These findings suggest the importance of robust biosecurity measures, including limiting cattle purchases, improving calf management, and enhancing colostrum feeding practices, to control the spread of M. bovis. This study provides valuable insights into the epidemiology of M. bovis in Irish dairy herds, emphasising the need for targeted biosecurity and surveillance to safeguard herd productivity. Full article

The advancement of Arrival MANager (AMAN) is crucial for addressing the increasing complexity and demand of modern airspace. This study evaluates the operational feasibility and effectiveness of an innovative AMAN designed for en route airspace, the so-called En Route AMAN. The En Route AMAN functions as a controller support system, facilitating the sharing of information between en route air traffic controllers (ATCos), approach controllers (current AMAN), and airport controllers (Departure Managers) in airports with multiple runways. The En Route AMAN aims to support upstream ATCos by sequencing and spacing of incoming streams via speed control and runway assignment, thereby enhancing overall air traffic efficiency. Human-In-The-Loop simulations involving rated ATCos are performed under scenarios that replicate real-world traffic and weather conditions. These simulations focus on upstream airspace to assess the impact of En Route AMAN on delay mitigation and ATCos’ performance. Unlike previous studies that solely relied on theoretical models and fast-time simulation for operational feasibility evaluation, this approach incorporates ATCos’ real-time decision-making, situational awareness, and task management, addressing critical operationalization challenges. The results demonstrated that the En Route AMAN could reduce the average flight duration by up to 25.6 s and decrease the total number of ATCo instructions by up to 20% during peak traffic volume. These findings support that the En Route AMAN is both operationally viable and effective in mitigating arrival delays, highlighting the importance of Human-In-The-Loop for practical validation. Full article

The operation of unmanned aircraft systems in shared airspace can serve as an accelerator for the global economy and a sensitive addition to the existing mix of transportation modes. For these reasons, concepts of Unmanned Traffic Management have been recently published, defining advanced rules for all potential participants in the operation of unmanned systems. Airspace primarily dedicated to automated unmanned system operations, referred to as U-space in Europe, needs to be designated with consideration for the surrounding airspace. This is especially important in cases where the airspace is controlled, and when declaring U-space airspace, it is necessary to pay particular attention to the density of surrounding air traffic. The goal of this article is to assess the suitability of establishing U-space airspace for Urban Air Mobility in terms of traffic density in a controlled area above the selected metropolis, which is Prague, Czech Republic. To achieve this goal, data on air traffic in the given area were analyzed to obtain precise information about the traffic distribution. Areas in which the establishment of U-space airspace is possible both without implementing dynamic reconfiguration and with the application of the dynamic reconfiguration concept were also selected. The result is the determination of whether it is possible to establish U-space in airspace, as in the analyzed case of the Ruzyně CTR, U-space can be introduced in 83 % of the territory. Full article

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

The safety of air traffic control (ATC) operations is an important cornerstone for the sustainable development of the civil aviation industry. In order to clarify the risk factors in the control operation process and to achieve digital representation of the safety risks of civil aviation control operations, starting from the ATC incident reports, we fully mine the safety risk information and unspoken rules of ATC operations. A risk perception model for air traffic control operations safety based on the Latent Dirichlet Allocation (LDA) topic model and the Semantic Network Based on BERT (BSN) model is suggested. First, 17 risk topics and keywords were found in the incident reports collected using the LDA topic model. These topics included those pertaining to the stage of aircraft operation, human factors in control operation, and the sector or airspace operation status and structure. The findings indicate that while most risk subjects have not changed significantly, they do show an upward tendency. Human factors and operational rules and procedures account for the highest share of all key causes, and they also have a significant impact on how risk topics evolve over time. Finally, the BSN model in the air traffic control field was built based on the keywords of each risk issue in order to highlight any potential correlations between distinct risk topics. The results show that some risk topics have interrelated risk characteristics, and there are regularities of mutual evolution between these risk topics. The relevant research results can better mine air traffic control unsafe information and lay a foundation for accurately perceiving air traffic control operations risks. Full article

Advanced air mobility (AAM) is an emerging sector in aviation aiming to offer secure, efficient, and eco-friendly transportation utilizing electric vertical takeoff and landing (eVTOL) aircraft. These vehicles are designed for short-haul flights, transporting passengers and cargo between urban centers, suburbs, and remote areas. As the number of flights is expected to rise significantly in congested metropolitan areas, there is a need for a digital ecosystem to support the AAM platform. This ecosystem requires seamless integration of air traffic management systems, ground control systems, and communication networks, enabling effective communication between AAM vehicles and ground systems to ensure safe and efficient operations. Consequently, the aviation industry is seeking to develop a new aerospace framework that promotes shared aerospace practices, ensuring the safety, sustainability, and efficiency of air traffic operations. However, the lack of adequate wireless coverage in congested cities and disconnected rural communities poses challenges for large-scale AAM deployments. In the immediate recovery phase, incorporating AAM with new air-to-ground connectivity presents difficulties such as overwhelming the terrestrial network with data requests, maintaining link reliability, and managing handover occurrences. Furthermore, managing eVTOL traffic in urban areas with congested airspace necessitates high levels of connectivity to support air routing information for eVTOL vehicles. This paper introduces a novel concept addressing future flight challenges and proposes a framework for integrating operations, infrastructure, connectivity, and ecosystems in future air mobility. Specifically, it includes a performance analysis to illustrate the impact of extensive AAM vehicle mobility on ground base station network infrastructure in urban environments. This work aims to pave the way for future air mobility by introducing a new vision for backbone infrastructure that supports safe and sustainable aviation through advanced communication technology. Full article

For skywave over-the-horizon radar, beamforming techniques are often used to suppress airspace radio frequency interference because the high-frequency band is shared by many devices. To address the problems that the traditional beamforming method is not capable of recognizing the electromagnetic environment and that its performance is greatly affected by the accuracy of signal feature estimation, a cognitive beamforming method using range-Doppler (RD) map features for skywave radar is proposed. First, the RD map is weighted by a local attention model, and then, texture features are extracted as the inputs to a support vector machine. Finally, the support vector machine is used to predict the optimal diagonal loading factor. Simulation results show that the output signal-to-interference-plus-noise ratio is improved compared with previous methods. The proposed method is suitable for many kinds of common unsatisfactory scenarios, making it beneficial for engineering implementation. Full article

In the context of the future urban mobility airspaces, U-space lays the foundation for unmanned aircrafts to be integrated with conventionally manned traffic to offer a multitude of services to citizens and businesses, such as urban public transport, goods movement, parcel delivery, etc. Given these extensive possibilities, it is estimated that thousands of aircrafts (or even more) from different owners will share common airspace volumes, and the probability that all of them will travel without colliding is extremely low if no means are put in place to prevent it. This paper aims to introduce the reader to the conflict management policy proposed in U-space and proposes a new version of the PCAN (Prediction-based Conflict-free Adaptive Navigation) algorithm to adapt to this policy. In particular, the new implementation of PCAN takes into account a more than likely classification of flights according to their priority. The evaluation of this priority-aware algorithm shows that it is still possible to avoid any conflict between the set of aircraft in flight, with an insignificant detriment to higher priority flights, while maintaining minimal detriment on average. Full article

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

While the potential risks of unmanned aircraft have received significant attention, there is little in the academic literature that examines how operational risks are mitigated by users. This study examines the prevalence of key operational risk mitigations amongst a sample of 812 unmanned aircraft users in New Zealand, their confidence levels in identifying and complying with airspace requirements, and their ability to read visual navigation charts (VNCs) and use AirShare (a local tool that shows airspace requirements). Significant differences exist between the number and type of mitigations applied, users’ confidence levels in identifying and complying with airspace requirements, and users’ ability to read VNCs and use AirShare based upon user characteristics. Education, practical assessment, membership of a professional body, professional/semi-professional use, and operating for a certificated organisation all improve risk mitigation (greater number and variety of risk mitigations applied). The only risk mitigation employed by almost all users was conducting a pre-flight check of their aircraft, identifying the need for users to view risk mitigation more holistically. The findings support policy directions related to educational requirements, the ability for member-based organisations and professional bodies to self-regulate, and the fitness of the current regulatory system in New Zealand. Full article