Abstract
The growth of commercial space operations has created a new problem for the air traffic management system currently in place. Increased operations require more launches and recoveries through air traffic airspace, which may cause aircraft delays and safety concerns. This paper’s purpose is to outline the limitations of the current management systems to help realize the need for revolution in the space and air traffic management fields. This research will analyze methods used to manage airspaces, specifically to deconflict air and space traffic. A review of recent scholarly literature suggest that there is an opportunity to enhance the efficiency of aircraft operations, while simultaneously ensuring safety for aircraft and spacecraft. This is a necessary advancement in airspace management due to the projected increase in commercial space operations. It is imperative to continually research ways to integrate air traffic airspaces with the increases in spacecraft launches and recoveries to ensure a continued steady flow of operations.
Keywords: air traffic, space traffic, deconfliction, airspace management
Air and Space Traffic Deconfliction
The commercial space industry is projected to grow and cause problems for air traffic airspaces within its flight paths. Using the Polaris Market Research Report (2023) from 2023-2033, it can be seen that the commercial space industries market size was $12.69 Billion in 2021 and is expected to grow at a compound annual growth rate of 14.5%. This means that the industry is projected to be worth $42.9 Billion in 2030 (Polaris, 2023).
Increased space operations directly conflict with air traffic airspaces and flight paths, requiring proactive deconfliction. To avoid conflicts, air traffic controllers and management must deconflict operations by either time, altitude, or space. Deconflicting by moving aircraft off of their optimal flight path will lead to aircraft deviations and delays. This research paper’s objective is to find deconfliction strategies that result in increased efficiency, while maintaining safety. The definition of efficiency is the aircraft distance flown and time spent in flight.
In this research, spacecraft operations include spacecraft launches, recoveries, and any associating debris. Currently, spacecraft operations are intruding on air traffic airspaces. This has led to airspaces being closed to aircraft, disrupting aircraft flow. This study aims to identify potential strategies for deconflicting air and space traffic. In this context “air” refers to the region of space within Earth’s atmosphere that is governed by aviation laws, regulated by ICAO, and related entities. And “space” refers to the region beyond Earth’s atmosphere where regulation is by several treaties and committees, such as the COPOUS and Outer Space Treaty.
Air traffic regulations have been consistently updated by lawyers and experts in the field since the Chicago Convention of 1944 and the creation of the International Civil Aviation Organization (ICAO) (Bartsch, 2018). The current Federal Aviation Administration (2023) Order for Air Traffic Control is on 7110.65AA, making it the twenty-seventh edition to date. Unfortunately, the space operations have not been regulated as much. Only the Committee on the Peaceful Uses of Outer Space (COPOUS), the “Outer Space Treaty”, and a few other agreements up until 1979 (Howell, 2017). After that, there has been no significant space operation legislation updates. Additionally, Halunko’s (2019) research makes note of this, saying that space operations has not developed in the past 60 years.
This research paper focuses on deconflicting air and space operations, so “deconflicting” must be defined. In this context, deconfliction is the process of ensuring that aircraft and spacecraft trajectories, including debris, do not intersect. The methods used to deconflict air traffic from spacecraft operations are evaluated in this study. This includes the current method of separation, which is to issue Notice to Air Missions (NOTAMs). With the NOTAM method, airspaces are projected to be off-limits to most aircraft for an allotted time. This block of airspace is normally a circle around the launch location, then a corridor eastbound in the direction of the launch. Launches are dynamic events, so the time-frame of a launch varies significantly. This means that these NOTAM airspaces could take up significant amounts of time, even when they are not being used.
NOTAM airspaces, for this paper, are defined blocks of airspace that aircraft are required to deviate their flight paths around to avoid spacecraft operations. There are different types of NOTAMs that do not require aircraft to deviate, that is why a distinction must be made. And, NOTAM airspaces for spacecraft deconfliction can require aircraft to deviate their flight paths significantly and it can disrupt the flow of traffic for extended periods. Reducing NOTAM airspaces timeline has the potential to save money, time, and reduce aircraft emissions. Studying methods to deconflict air and space traffic will also allow for an evaluation of the current safety standards. Naturally, reducing the NOTAM size or timeline has a risk of reducing safety. In this research, the goal is to maximize air and space traffic efficiency while not reducing safety. A masters thesis research has been written on this interaction. It was found that there is theoretically room for improvement in efficiency while maintaining safety. However, the author did not have the resources to conduct simulations to prove his research theories (Lewallen, 2023).
This paper’s research does not involve simulations due to time and resource constraints. Instead, this paper will conduct a literature review to find current methods and frameworks, assess their efficiency, and then explore ways to integrate them into management systems. The research should result in a framework or a set of guidelines that can contribute to a meta-analysis to optimize deconfliction. This framework will require future research with simulation and modeling.
Literature Review
The literature was gathered from online database searches for peer-reviewed, scholarly works with the keywords “air traffic control” (ATC), “spacecraft operations”, “aerospace technology”, and “airspace management” to identify potential strategies for deconfliction. A portion of the literature focused on predicting the re-entry of space debris to manage it and to minimize potential conflicts with air traffic. Bernelli-Zazzera et al. (2023) proposed a strategy for managing re-entries. This was by gathering data on debris spread from spacecraft operations in simulations and then incorporating it into the separation standards. Additionally, Gao et al. (2024) used machine learning to assess spacecraft debris risk and adding it to predictive models in real-time risk assessment.
Research has also looked into the use of machine learning to enhance air traffic flow and to predict aircraft rerouting. Research by Dalmau (2022) used machine learning algorithms to predict air traffic rerouting. This demonstrated that ability for machine learning to be used to reduce air traffic delays in rerouting. Sui et al. (2022) also developed a prediction method for large-scale airspaces. Their prediction method was over 90% accurate on air traffic situations within one hour. This allows ATMs to predict aircraft movement and adjust air traffic flow accordingly. However, the research still needs to be evaluated through real-world conditions instead of just simulation. Continuing with this, artificial intelligence (AI) and automation systems may also be used to improve ATM. Ortner et al. (2022) proposed an augmented ATC system that uses AI to predict air traffic conflicts. Their research concluded that AI was able to enhance ATCs situational awareness and reduced human error. The study noted the limitation that the sample size of air traffic situations was not diverse or complex enough to determine real-world viability.
Research by Pohling et al. (2023) identified that higher airspace operations (HAO) is an additional location where air traffic efficiency and safety are being affected. HAO is defined as operations above 60,000 feet. Pohling et al. (2023) also evaluated the impact of HAO on air traffic in Europe. The results showed an increase in airspace congestion and a need for adaptive management strategies. However, the research also showed varying results based on the type and time of operations.
Robson et al. (2024) researched the impacts of space launches on ATM, as well. Their research was able to show the complexities involved with integrating space operations into existing air traffic systems.
Methodology
First, a literature review was conducted of relevant scholarly works on ATM, ATC, space traffic management, and related topics within the last three years. This involved searching across various online databases such as PubMed, Google Scholar, IEEE Xplore, and pertinent aerospace journals with the keywords; "air traffic management," "air traffic control," "space traffic management," and "deconfliction strategies”.
Then, the selected literature was reviewed to find strategies and methods to deconflict air traffic and space operations. Each paper was given an abstract with the purpose of the study, research design, setting, number of participants, types of samples, data collection methods, data analysis procedures, key findings, limitations, and recommendations for future research. The data from this was based on recurring themes, trends, and gaps in research. Comparisons were then drawn between the literature to evaluate the strengths and limitations of the approaches to deconfliction.
Limitations exist in the methodology due to available resources, such as time. The depth of the analysis has suffered from the time constraints to produce the research paper. The 30 literature-reviewed documents could not be thoroughly reviewed and synthesized in the six-week time-frame.
Results and Discussion
This section analyzes and discusses various studies, strategies, and advancements in air and space traffic deconfliction. The research ranges from minimizing the impact of space operations re-entries to enhancing ATC efficiency by using predictive analytics and machine learning. Each portion of this research is meant to help understand challenges and opportunities in managing aircraft and spacecraft.
ATM Solutions for Deconfliction
The first topic focuses on using ATM as a solution for deconflicting. It focuses on two main areas of ATM, which are managing airspaces and mitigating space operation’s impact on airspaces. There is a strategy presented by Bernelli-Zazzera et al. (2023) for a more efficient airspace management technique for uncontrolled rocket re-entries. Their research used a simulation of 1,000 rocket re-entries and then they took the data from their simulation and integrated it with the FAAs NextGen system to create a procedure to avoid collisions. This research paper contributes to the creation of new standards in deconfliction that can reduce the time needed for air traffic to evacuate hazardous areas.
ATM is also affected by the space HAO, therefore Losensky & Kaltenhäuser (2022) proposed key principles to guide ATM within this portion of airspace. Additionally, Pohling et al. (2023) assessed the impact of HAO on air traffic in Europe and was able to show influences that were based on the type and timing of HAO. They compared flight efficiency during HAO and outside of HAO. Their analysis highlights the need for a better understanding of the relationship between air and space traffic.
There is also a need to understand the strategic planning and economic consequences of space launches with ATM strategies. There was research conducted by Robson et al. (2024) on this, showing how space launches add complexity and have vast economic impacts by evaluating case studies, simulations, and models. The results from Robson et al. (2024) show the impact of space launches on aircraft efficiency and the necessity for strategic planning in ATM systems.
Enhancing ATC Efficiency
ATC efficiency is essential to safe and effective control within complex airspaces. It has been shown that efficiency can be enhanced through training and simulation. Fürstenau & Radüntz (2022) developed a study focusing on the controllers mental workload. They were able to establish a relationship between task load and perceived workload. Their study quantified the impact of air traffic workload on controllers. This relationship can develop workload models that can help predict periods of high stress and potential controller overload. This data allows for better planning and distribution of tasks among controllers.
A study by Trapsilawati et al. (2022) goes into the decision-making processes involved in ATC. Their research shows the preferences that controllers have for traffic deconfliction and the cognitive loads associated with each action. The data from this research suggests training programs that prepare controllers for the scenarios they might face, focusing on minimizing cognitive load without compromising the safety and efficiency of conflict resolution. These training programs allow ATC to work more aircraft without compromising the aircrafts safety.
ATC can also use training and simulation to obtain the skills needed to control complex airspaces and high levels of traffic. A research study conducted by Rangrazjeddi et al. (2023) uses a theory to enhance ATM by developing ATC decision-making skills. Enhancing these skills was shown to enable controllers to better predict and mitigate conflicts.
Predictive Methods, Machine Learning, Technology Integration
Integrating machine learning technology into ATM represents a significant advancement in the modernization of ATM. By addressing traffic flow disruptions and safety concerns, these technologies are another layer of efficiency to air traffic. A study by Dalmau (2022) shows how a predictive methods approach can reduce ATM delays. He does it by inputting historical ATM data into a machine learning algorithm that calculates rerouting actions for traffic flow. Additionally, Stover & Mahadevan (2022) was able to contribute to this concept with their research on preventing midair separation violations. Their research shows that there is potential to integrate data into predictive models to enhance risk assessment and provide an early warning for deconfliction. These innovations are critical for maintaining safe aircraft distances in congested airspace.
Gao et al. (2024) also uses machine learning is their study to assess the risks and ensure safety with re-entry operations. Their research uses an algorithm to predict risks with spacecraft debris. Also, Sui et al. (2022) uses a data-driven prediction model that is able to anticipate ATC situations in a large-scale airspace setting. Their research proved to be over 90% accurate in forecasting ATC conditions within one hour.
Policy and Regulation Considerations
The history of air and space traffic legislation has lacked in producing regulations that govern the cross-section of the air and space domains. With this, Stefanescu et al. (2024) was able to show the significance of understanding the risks of uncontrolled space debris re-entry. Stefanescu et al. (2024) risk assessments highlight areas where current legislation is not enough to protect air traffic from such events. As space operations continue to grow and increase, the potential for these events also increases (Polaris, 2023). This shows the need for regulatory bodies to force the incorporation of risk models into ATM policies.
Research from Zhu and Kan (2022) provided an approach to managing airspace under rough set theory, a method that may be particularly beneficial for regions experiencing rapid growth in civil aviation. The findings of their research were that current airspace classifications and regulations need to be redefined to accommodate the complexity of the modern air traffic situation.
Simulation Technologies for ATM Research
Simulation technologies were key in ATM research, where Rojano-Padrón et al. (2023) illustrate the capabilities of Multi-Agent Transport Simulation (MATSim) in their examination of electromobility infrastructure planning. Although this study focuses on the placement of electric vehicle charging stations, the application could apply to ATC research. The MATSim tool is able to simulate the movements and interactions of numerous vehicles. It can also be used to model the flow of air traffic and the effects of infrastructural changes within airspaces. By adapting MATSim to air traffic situations, researchers can simulate various scenarios, including methods of deconflicting air and space traffic.
Research conducted by Dönmez et al. (2023) uses a different simulation called Airport and Airspace Simulation Model (SIMMOD). SIMMOD is used to evaluate the impact of taxiway system development on runway capacity. The key portions of the SIMMOD tool allows for the detailed modeling of airport operations, enabling researchers to assess how changes to taxiway configurations can affect overall airport efficiency. This could potentially be used to model airway operations and configure them for optimal efficiency of air traffic flow.
Conclusion
Air traffic airspaces are currently being encroached on by commercial space operations. This is necessitating a proactive look into how to deconflict the two operations. This is only exacerbated by the fact that the commercial space industry is projected growth for the future.
The current frameworks for air traffic and space operations are lacking and need to be updated. This includes an update in legislation, regulations, and guidelines for the challenges that are projected from space activities. These challenges of air and space deconfliction need to be resolved to ensure safety, efficiency, and sustainability of aviation.
The research in this paper shows the potential for machine learning, predictive models, and other advanced technologies to be a part of the answer. These integrating into ATM systems have been shown to enhance efficiency and safety. Additionally, developing controllers through training and simulation could allow for more complex airspaces and more air traffic.
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