Abstract
This research paper aims to address the growing challenge of integrating air and space traffic within joint airspace caused by the increase in space operations. This challenge requires implementation of safety measures and global coordination between air and space traffic management. Specifically, this paper conducts a literature review on key aspects of integration, like air traffic management, spacecraft debris, global coordination, and flight path management. In these key aspects, the paper can identify current problems being faced surrounding the core challenge and then propose potential solutions to these individual problems. The research explores tools such as the space data integrator, trajectory-based operations, and machine learning as current solutions to the problems for their current ability to alleviate safety hazards. Additionally, the lack of global consensus on these problems is addressed and seen as a critical factor in solving the current issue. By alleviating this coordination barrier, leveraging advanced technologies, and realizing risks, the aviation community can establish a safer joint airspace environment for both industries.
Keywords: air traffic, space traffic, airspace integration, spacecraft debris
Air-Space Traffic Integration Safety
The rapid growth of the space industry has introduced a new challenge for the aviation community. In 2023, the United States (US) had 113 launches, which constitutes 16.7% of all activity space launch activity between 1989 and 2023. This is forecasted to continue increasing to between 195 and 338 by 2028 (FAA, 2024b). The need for an effective air-space traffic integration strategy is being realized.
Background and Context
Commercial space activity has risen and is projected to continue its rise in the coming years, especially with high-altitude platform system (HAPS) advancements. This requires increased safety parameters in areas that integrate air and space traffic. Air-space traffic integration is referencing the management of the shared airspace between traditional air traffic operations and spacecraft operations. This joint airspace is typically surrounding higher airspace operations (HAO), but includes spacecraft launches, reentries, and resulting debris.
HAO currently holds a broad definition that is not universally recognized. For example, the US has set its controlled airspace upper boundary at flight level (FL) 600, but European countries have set theirs at FL660 (Losensky & Kaltenhäuser, 2022; ICAO, 2020). Additionally, the Kármán line, where aircraft lift reduces to a point that it becomes ineffective, is set to around 100 kilometers above mean sea level (~FL327). The Kármán line is also not globally accepted (Losensky & Kaltenhäuser, 2022).
The fundamental principle of where space begins complicates the management of operations within these areas. Sovereign state issues beneath the airspaces add further complications. As sovereign countries own and operate the airspaces above their countries, but do not have clear rights to the space above that airspace, nor is there clear agreements on ownership or control (CRS, 2019). This creates the integration problem, where HAPS are controlled in state owned higher airspaces, while space operations are conducting operations in the joint environment without joint control (Pohling et al., 2023).
It is essential that aviation safety stakeholders realize the danger within joint airspace and advocate for collaboration, especially from the Federal Aviation Administration (FAA), International Civil Aviation Organization (ICAO), and space operation organizations. Additionally, stakeholders need to build tools and platforms that can assist in integration, like the spatiotemporal graph convolution network (STGCN) that predicts congestion in large airspaces (Sui et al., 2022). The FAA has also built the NextGen program to build air traffic into trajectory-based operations (TBO), which assists in managing congestion in these shared airspaces (NextGen, 2024). Tools like these are essential to continue safely conducting air and space operations together.
Air Traffic Management
Air traffic management (ATM) is half of the solution to air-space traffic integration. With space operations potentially reaching 338 by 2028 for the FAA alone (FAA, 2024b), airspace overlap, and management complexities are set to increase significantly. This increase necessitates tools, strategies, and legislation to alleviate safety concerns and accommodate HAPS.
Uncertainty management in aircraft operations, like weather deviations, performance variability, airspace changes, and spaceport activities increase unpredictability within air traffic control systems (Corver & Grote, 2016). This is exacerbated by the lack of a globally recognized higher airspace definition. ICAO has mentioned the need to account for this through amending airspace classifications, which would increase procedure and flow management (ICAO, 2020).
Currently, innovations are being made to begin addressing these challenges, like the Space Data Integrator (SDI). This tracks spacecraft launches and reentries in real-time and integrates it into the ATM system (CRS, 2019). Also, the FAA, ICAO, and other leading aviation organizations have begun transitioning to satellite-based navigation systems to increase awareness of where aircraft are (Landry, 2018). Traditionally, ground-based systems were used and had the vulnerability of losing aircraft data if outside of its range. Additionally, systems are being built to increase air traffic controllers (ATC) cognitive availability, like the Air Traffic Flow Management (ATFM) system and the STGCN, both allowing ATM to dynamically manage large airspaces (NextGen, 2024; Sui et al., 2022). Furthermore, the German Aerospace Center (DLR) has begun developing the Launch Coordination Center (LCC), promising to be a hub for space operations to disseminate information to appropriate locations. Providing real-time data adds to ATM situational awareness, which could prompt appropriate air traffic changes to avoid safety concerns (Hampe & Stahnke, 2024).
The ATM system requires tools like SDI, ATFM, NextGen, and LCC to mitigate uncertainty in joint airspaces. Additional resources will be needed to allow for safer operations, but this requires global cooperation and universally defined airspaces. Regulatory guidance is needed to ensure consistency and structure across all ATM cells.
Spacecraft Debris Management
In addition to the conflicts arising from air and space traffic conducting HAO, there are also threats from spacecraft debris generated during launches, reentries, and accidents. This consideration poses an additional challenge to ATM and Space Traffic Management (STM). This is different from orbital space debris, as it rarely descends into controlled airspace. Spacecraft debris often creates hazards by falling through air traffic airspaces (Chen et al., 2023).
The most abundant unexpected spacecraft debris is generated from uncontrolled reentries and suborbital vehicle disintegration. Uncontrolled reentries of the vehicle or its stages can be unpredictable due to the fact the velocity and direction of the debris is unknown. For example, Stefanescu et al. (2024) says the Long March 5B booster reentry in 2022 was unexpected, so airspaces were closed as a precaution, resulting in 300 flights across Europe being diverted. Like this, suborbital vehicles accidents can cause the same unknown hazard and close airspace as a safety measure (Chen et al., 2023). Chen et al. (2023) notes the SpaceX Starship’s 2023 mid-air explosion as an example that caused airspace closures due to its unexpected debris hazards. A precaution has been established to establish temporary flight restrictions (TFR) for launches and known reentries to allow for air traffic preparations. However, there are currently no structures in place to expedite information exchanges for unexpected spacecraft debris.
Gao et al. (2024) used machine learning to build an algorithm using support vector regression (SVR), decision tree regression (DTR), and multilayer perceptron (MLP) together to predict landing points for these events. The model is reported to have +/- 0.96 degrees of longitude error and +/- 0.53 degrees of latitude error. Using this algorithm and the known origin, you could predict the path of the debris and reduce closures safely. Additionally, Chen et al. (2023) simulated the use of the improved Lazy Theta algorithm to provide shorter flight path lengths and flight time to avoid debris hazard zones. Research on machine learning uses in spacecraft debris avoidance is increasing accuracy of predictions by incorporating real time data like winds and atmospheric drag, improving collision avoidance.
Spacecraft debris data needs to be coordinated efficiently with ATM for it to have any use in conflict resolution. The SDI aims to do that by providing real-time spacecraft data to ATM systems, specifically during known launches and reentries (CRS, 2019). This allows for the activation of dynamic hazard zones so ATC can efficiently evacuate aircraft from realized hazards from debris. The STGCN model also assists in predicting congested areas for ATM and STM and it can be used to increase coordination efficiency in high-risk situations (Sui et al., 2022). Still there remains a need for global coordination on these efforts as STM and ATM entities often don’t share local procedures. ICAO and the United Nations (UN) Committee on the Peaceful Uses of Outer Space (COPUOS) have expressed the need to standardize data sharing and hazard management globally (Ailor, 2022).
Communication and Coordination
Air-Space traffic integration is a global requirement with stakeholders from air and space communities. Some of the main stakeholders are the FAA, ATC, ICAO, EUROCONTROL, national and international spaceports, private organizations like SpaceX and Blue Origin, and international organizations like ICAO and UN COPUOS. Many of these agencies do not require normal coordination with the others to conduct normal operations. However, to integrate air and space traffic, at a minimum there must be established collaboration during spacecraft pre-mission, execution, and post-mission phases.
DLR has begun operating and testing the LCC as a potential solution to coordinating between the two sectors. Specifically, LCC offers the SpaceTracks Suite (STS) as a microservice architecture. STS is a software solution that incorporates air and spacecraft flight characteristics and air traffic systems with variables like security, scalability, flexibility, and expandability to ensure mass distribution for other air and space uses (Hampe & Stahnke, 2024). It potentially serves as the solution to each phase, for pre-mission it allows support, risk analysis, and stakeholder engagement. It can give real-time trajectory of spacecraft and notify ATM of any hazards during execution. And, post-mission, it can provide feedback, lessons learned and organize this data for future uses (Hampe & Stahnke, 2024). In all, STS allows for potential global integration and real-time data sharing between ATM and STM functions.
No matter how promising DLR’s LCC is, there are still challenges to its global implementation. Higher airspace is not globally defined, and high level national and international organizations use different variables to distinguish what constitutes their air traffic airspace. There must also be consideration given to the fact that nations would want to protect their sensitive data. For example, a US operated secret spacecraft mission operating over Europe may not want to share their real time data with national air traffic organizations.
Global collaboration efforts must be led by organizations like ICAO and UN COPUOS to standardize air-space traffic integration. ICAO has advocated for a global definition for higher airspace through a Procedures for Air Navigation Services publication but has failed to conclude a final verdict (Kaul, 2021). Additionally, UN COPUOS has emphasized the need for data-sharing agreements for air-space integration (Ailor, 2022). However, neither ICAO or UN COPUOS have binding agreements internationally and cannot force the changes needed, only advocate.
Navigation and Flight Path Management
To alleviate the pressure of the joint environment, advanced trajectory planning, real-time rerouting, and segregated airspaces will be required. TBO has been made the main objective of the FAA and its NextGen program and modern ATM. In the FAA’s (2024a) Commercial Space Integration into the National Airspace System (CSINAS) concept of operation, it outlines TBO principles to be used in integrating space operations within the NAS. One concept is that aircraft and spacecraft trajectories information of latitude, longitude, altitude, and time be shared real-time between ATM and STM systems (FAA, 2024a).
Space transition corridors have also been theorized as designated pathways for spacecraft launches and reentries to avoid air traffic altogether. Bilimoria and Jastrzebski (2013) defines the corridors to be flown and standardizes its procedures for being operated. The STC would be dynamically activated based on spacecraft missions with real-time considerations. This report was established in 2013, however global challenges prevent implementation. Establishing STC would require standardization of airspace structures and international collaboration.
Currently, tools are being developed that can be used locally, without international collaboration. ATFM is a current NextGen (2024) tool that dynamically manages flight paths to optimize airspace and safety. This can be further developed with satellite navigation to provide real-time positioning for flight path analysis and accurate deconfliction, if necessary. Also, there are machine learning applications, like Sui et al.’s (2022) STGCN and Chen et al.’s (2023) Lazy Theta, that can increase safety by amending flight paths. These can continue to be developed into artificial intelligence (AI) support tools to analyze and integrate large datasets from ATM and STM systems. Ruan et al. (2024) describes a hybrid AI that combines satellite-based positioning data with atmospheric conditions to increase prediction accuracy for flights.
Conclusion
Air-space traffic integration is a near future challenge that demands attention immediately to ensure safety for operations. This challenge has presented itself on multiple fronts, first from the ATM and STM standpoint and its need for tools to manage the complexities with joint airspace. The SDI, TBO concept, LCC, and other tools are starting to solve the problem, but further investment is needed. Stakeholders also need to be looking outside of the immediate conflict and into managing unexpected spacecraft debris. Predictive models have been established, like DTR and Lazy Theta, to mitigate the risk of these events. Also, since this is an international challenge, collaboration between air and space organizations is mandatory. DLR’s STS can facilitate the real-time data sharing that is needed, but it can only do it if all parties are working together to allow it to happen. Finally, there are technologies in place that allow increased safety for integration now. Satellite positioning, predictive machine learning, and TBO are examples of these technologies actively improving navigation and flight paths. These can be built on to pave the way to a safer joint airspace environment.
References
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