PRE2019 1 Group1
Autonomous systems for space traffic management
The space around Earth is becoming increasingly fuller. With the upcoming privatization and commercialization of space activities, thousands of satellites are being launched into the Earth’s orbit in the upcoming years. At the moment, governmental and non-governmental organizations monitor their satellites and maneuver their spacecraft to prevent collisions manually. In the future, the lower orbit will contain too many satellites and space debris for companies to coordinate their satellites by hand. Safety procedures will have to adapt to prevent collisions from happening. An autonomous space traffic management (ASTM) system could be a solution to this problem. Technically speaking, the development of an autonomous STM system is easily feasible. The major obstacle to the implementation of such a system is international law. Governmental and non-governmental companies would have to work together and share data to optimize the system. Clear agreements will have to be made for this to run smoothly. Future studies should focus on that part because overall, the implementation of an ASTM would benefit all parties concerned. An ASTM system increases safety in space, which benefits satellite-owning companies, scientists concerned with exploration missions, and society as a whole.
|Stijn Eeltink||Mechanical Engineering||1004290|
|Laura Külter||Psychology & Technology||0851512|
|Annelies Severens||Biomedical Engineering||1232787|
Each week will consist of two meetings. Before each meeting, the team will work individually on the tasks they have been assigned for that meeting. During the meetings, the results of these tasks will be discussed and finalized.
L = Laura, S = Stijn, A = Annelies.
|Week||Monday (morning)||Wednesday (afternoon)|
|1||ALL : choose topic||ALL : |
make the planning
define structure of the report
|2||L : introduction/problem statement
L : wiki page
A : state of the art
|ALL : PCR |
A: state of the art
S : stakeholders
L : introduction/problem statement
L : edit planning in wiki
(state of the art)
|A: state of the art on wiki |
S: edit stakeholders
L: RPC’s and update wiki
A: air traffic management
ALL: 2 questions for stakeholders (more is allowed)
|4||S: questionnaire with information
S: stakeholders in googledocs
L: autonomous mining, how does the system work?
A: Structure of the system. Would a peer-to-peer system work? Which systems does NASA or ESA use?
ALL: comment each other’s work
|All: More specific RPC, how can results be measured? |
All: Specify and categorize specific user questions
A: System architecture of third parties
L: AI systems (rule-based vs learning system)
read whole report and comment: ALL
|Contact users |
Prepare for tutor meeting Monday
||S: Roadmap/Requirements |
A+L: Ethical decision styles
L: Write out user research
L: Machine Learning
ALL: How could the system reward good behavior?
A: How would satellites be detected?
|7||A: Data collection and monitoring
L: Collision prediction and avoidance
S: Decision making approaches and communication
|DEADLINE FRIDAY |
S: System validation
A: Link requirements to system tasks
|8||ALL: Presentation and report finalized
||ALL: System validation, presentation preparation, Netlogo simulations |
ALL: Hold presentation
ALL: Finalize wiki
Space debris often gets the most attention when one talks about threats that exist to active satellites and other spacecraft (previous 0LAUK0 groups have done extensive research on that topic before: PRE2016_3_Group19, PRE2018_3_Group1, PRE2018_4_Group9). However recent developments in the space industry present a ‘new’ threat to active satellites.
Where traditionally space travel was government-driven, the privatization and commercialization of space activities have gained momentum and have developed different interests like faster and cheaper access to space. Currently, several organizations plan to launch thousands of satellites up into Earth’s orbit in the next several years. These range from governments like the UK planning to launch 2000 satellites by 2030 to large companies like SpaceX planning to launch 12000 satellites for its Starlink constellation. If we compare this to the currently 4987 satellites in orbit, of which only 1957 are still active and functional, one quickly sees how ‘full’ the currently quite ‘empty’ low orbit space around the earth will become in the near future.
This could overwhelm current space flight safety processes. However, there are encouraging signs that the government, industry, and the space community are acting to address these issues. This project will look at a possible solution for managing these many thousands of satellites by using an autonomous system for space traffic management(STM).
As stated in the introduction this project will focus on the need for an Autonomous Space Traffic Management System (henceforth called ASTM). The main reason for the need for such a system is the ever-increasing presence of active satellites in low earth orbit, which will make it no longer feasible in the near future to avoid collisions by depending on human input. There are however a lot of aspects that will need to be analyzed and discussed before a proper concept for an ASTM system can be proposed. First, the current state of the art will need to be analyzed to see how STM is handled right now and where there is room for improvement. Next, the individual stakeholders will be looked at to find the wants and needs of each stakeholder. These things will be summarized in the RPC (requirements, preferences, constraints) and work as a framework for designing a proper ASTM system.
The main reason the end goal is a concept instead of a fully-fledged system is the fact that right now STM is still quite in its infancy. Even large organizations like NASA have only started fairly recently to look into autonomous systems for STM. This means that there are many unexplored factors in regards to creating and deploying an ASTM system and so it is beyond the scope of this project to analyze all these factors in only eight weeks.
The concept will mostly be a recommendation for what type of autonomous system would be most suited to handle STM. Therefore this project will mostly ignore the technical aspects(radio communication in space, the inner workings of satellites, deploying an ASTM system on earth vs in low orbit, etc.) and instead focus on analyzing what an ASTM system could (and should) offer compared to doing STM by hand. Recommendations for architecture models, AI systems and system validation will be provided as well.
State of the art
At the moment, there are no international or even national Space Traffic Management systems. However, because of the increasing amount of non-governmental organizations executing space activities, rules are needed to ensure safety in air space. Generally speaking, Space Traffic Management can be defined by the safety insurance of: 1. Safe access to outer space, 2. The conduction of operations in outer space, and 3. The return of space objects from outer space free from interference of any form.
Currently, the Outer Space Treaty forms a basis of international space law. The treaty was opened in 1967, when the United States, the United Kingdom, and the Soviet Union signed the treaty. More countries followed in the coming years. As of 2019, 109 countries are parties of the treaty. This treaty focuses on the limitation of the use of celestial bodies and restricts nations from claiming sovereignty of outer space. It does not include any legal regulation of Space Traffic Management. At the time that the treaty was set up, the STM concept was not considered a priority. In 2015, the UNCOPUOS committee had received approval to add STM as an agenda item in 2016.
The Cosmic Study from IAA created a definition for STM. It was the first step, but too premature to implement any regulations limiting freedom.
The 2016 “Orbital Traffic Management Study – Final Report” does not contain a definition for space traffic management. Instead, it defines Space Traffic Safety. Management would imply centralized command and control, which was seen as problematic.
The 2017 German Aerospace Center (DLB) White paper on the “Implementation of a European Space Traffic Management System” defines STM as:
Over the years, there have been different definitions and approaches to STM from the United States, European Space Agency (ESA) and the International Academy of Astronautics (IAA). However, they have some similar key operations, one of which is collision avoidance. This focuses on point 2. of Space Traffic Management: the conduction of operations in outer space. Recently, the European Space Agency (ESA) has performed a collision avoidance maneuver for the first time. The satellite was moved off a potential collision course with a SpaceX satellite in the Starlink constellation. At the moment, ground operators make decisions, which might not always be optimal. The avoidance process between two satellites is largely manual and will be no longer practical if the number of satellites and other space vehicles increases. According to Holger Krag, Head of Space Safety at ESA:
The use of machine learning, artificial intelligence, is being explored to support ground operators when planning and implementing collision avoidance. This is one application that artificial intelligence can be used for. In  an initial architecture for a Space Traffic Management system is proposed, based on open Application Programming Interfaces (APIs). The use of machine learning incomplete STM systems is being explored at the moment, a great step towards complete autonomous STMs. According to  a national system will be most probably implemented before an international regime. This mainly has to do with the fact that having a good, working STM system, data must be shared between governmental and non-governmental organizations, which remains a difficult topic.
While there is a lack of proper STM in space and an autonomous system for it is still non-existent, there do however already exist similar systems in other real-world applications.
Air Traffic Control
Air traffic control includes the ground-based personnel and equipment concerned and monitoring air traffic within a particular area. Air controllers ensure safe operations of commercial and private aircraft. They, manually, keep them at safe distances from one another and direct them during takeoff and landing. An equivalent system is needed to direct satellites and other spacecraft from earth into space into their increasingly crowded flight paths. Whenever a rocket is launched into space, it must pass through the airspace where thousands of planes fly through every day, causing planes to reroute. However, an analogous system to that of Air Traffic Control is difficult for several reasons. The Federal Aviation Administration (FAA) runs the air traffic control system. Airspace is divided into zones, and each zone into sectors, segregated by national authority. When an aircraft moves through a particular sector, it is monitored by the air traffic controllers responsible for that area. Space is not separated into sections or divisions with a responsible entity monitoring and controlling that area. Nations are responsible for their spacecraft and would rather improve their system before internationalizing an STM. Also, both governmental and non-governmental organizations are unwilling to give full access to all their data regarding the position of their satellites and other spacecraft. Without widespread participation and positional information, it is difficult to create a command-and-control system that works well for STM. Data collection is, therefore, one of the main issues for any STM.
A big implementation of autonomous systems can be found in the mining industry. Fortescue Metals Group in Australia uses autonomous systems for various operations, of which their autonomous haulage system  (AHS) comes closest to a real-world example of an autonomous traffic management system. AHS is used to control the massive driverless trucks at mining sites that are responsible for transporting ores etc. from point A to B. The system is responsible for making sure the driverless trucks don’t collide with each other or other obstacles and stick to their designated routes.
According to a public news report , there has been only one reported accident involving the driverless trucks so far since the active operation started in 2012. In February 2019 one of the trucks collided at low speed with another parked truck after a wifi outage caused the truck to lose its connection with the control center. While two driverless trucks colliding with each other might not be a big deal and would mostly have a low monetary impact, such a result would not be acceptable with for instance communication satellites.
While only a single accident in 7 years is a noteworthy feat there are a few things to note here. The trucks drive in a closed environment owned by the company. This means that the system seldom has to take into account non-company owned trucks or other vehicles. The system knows everything about all the members at the mining site. However, in space, there are thousands of satellites with hundreds of different owners and not everyone is willing to share their information. Another factor is that since the mining site is owned by the company, they decide (within the boundaries of the Australian law) what happens and who can or cannot enter the site. The international space treaties however basically state that nobody is the boss in space and that everyone should have the right to shoot satellites into space. This means that while the autonomous system does work and is certainly a technological feat, it owns much of its success to the extremely limited and controlled environment it operates in.
Next to state of the art there are the stake holders. Who has a stake in STM? Four stake holders will be discussed below; Social, political, economics and scientific.
Space debris is not some far off distant problem that we need to worry about. The probability of a collision is not only continually rising, but there have been several collisions that have damaged the satellites and even the international space station. Every time we launch something into space, we generate unwanted waste. This is happening exponentially more since the privatization of space activities. Small particles like aluminum-oxide, explosive bolt fragments, and paint chips can cause serious issues. While this debris is small, it is also moving at 30.000 km/h, which means that it has enough kinetic energy to damage important satellites and the international space station.
This could be devastating to society. Satellites with critical duties we rely on every day could be struck. Global communication, GPS and navigation, and weather data could suddenly disappear. If this debris collides with such a satellite, it will be destroyed instantly. This satellite then turns into thousands of little pieces, that are capable of destroying other satellites. This could trigger an unstoppable chain reaction, which is called the Kessler syndrome. If this were to happen, the loss of our space infrastructure would set lots of technology advancements back, and limit the technological advancements made from space travel in the future.
NASA and ESA are running multiple missions  dedicated to observing the Earth, to gather information on how the planet is changing. Missions like Aqua  collect information on ocean evaporation, atmospheric water vapor, clouds, precipitation, soil moisture, sea and land ice, and snow cover. With this information, NASA wants to show the evidence for climate change, the causes, effects, and try to find solutions. NASA also observes our planet’s atmosphere, where ozone, nitrogen dioxide, and particulate matter  can be measured to indicate the air quality. Because air pollution is responsible for about 1 in 9 deaths worldwide, this data is very important.
Other missions from NASA like SMAP are valuable to agriculture. The satellite uses a radiometer that can see through the clouds to measure the soil moisture levels on earth. By measuring the moisture levels in the soil, it allows you to predict droughts, monitors floods and even predicts crop yields for a given year. The data from this program is widely available and is used by all countries for better agriculture. The technological advancements made in space travel have lots of different spinoff technologies. If space travel were to stop, the constant flow of new patents and technologies would also stop. Advancements in health, medicine, transportation, public safety, computer technology, and industrial productivity are key to the development of human society.
While space activity has democratized with many new players, the U.S. government is still the single largest actor and stakeholder in the lower earth orbit (LEO) operations environment. The U.S. government re-established the National Space Council in the summer of 2017. One of its first actions was to establish a working group to recommend a way forward on space traffic management. “National Space Traffic Management Policy” was issued on June 18, 2018, and outlines several steps changing how space traffic is managed and regulated. This paper addresses the need for improved space situational awareness (SSA), data sharing with other organizations, and space traffic management (STM).
The Department of Commerce wants to simplify the regulatory structure for licensing for commercial companies, which the industry has needed for a long time. It will also take the function of STM and SSA for the U.S. Air Force. By creating an open-architecture space data repository they will actively share information with and between operators, and encourage new technologies for SSA.
The Federal Communications Commission has been regulating practical orbital debris for commercial companies that operate in the U.S. market. The new rules would explicitly address the issue of large constellations and post-mission disposal reliability. These new rules also contemplate active SSA data sharing, transponders, enhanced signatures, and shared maneuver plans, which would greatly decrease the amount of space debris.
Space is however fundamentally an international concern since no nation owns or controls the environment. The foundational document for international space law is the Outer Space Treaty. Though this treaty is not enough. The United Nations Committee is considering new rules for topics like space debris management and creating guidelines for the long-term sustainability of space.
While these combined actions have mitigated some of the risks in the transition, further action is recommended. The best source of innovation and solutions are the organizations that are building new systems. Industry-driven norms and standards of behavior are among the most effective methods for preventing the new activity from contributing to space debris. The government should encourage these industry-driven, voluntary approaches.
This change in space activities, especially the very large LEO constellations, represents major investments by commercial companies like SpaceX. Every U.S. operator proposing a large constellation has stated the intention of following best practices and being ‘’good citizens’’ of space. These operators have a significant vested interest in maintaining the space environment, and in protecting their investments that will run into the billions of dollars. Some of the new operators are among the strongest proponents advocating for increased regulation and scrutiny. They intend to build in high reliability for post-mission disposals, like their intent to deploy satellites at a low altitude, and then raising the orbit once checkout is complete. While there are some disadvantages to this approach, when a satellite fails, drag can bring it down much earlier.
They are building in the capability of high-precision orbit knowledge and are actively willing, even seeking, to share position and maneuver data. Also, a high level of automated collision avoidance and automated deorbit of failed systems are being developed, much like the ASTM proposed by our group. To make sure the post-mission disposal plans are successful, companies are planning to deorbit on a fixed schedule, rather than maximizing mission life as is commonly done. Also, operators are adding grappling fixtures, reflectors, and other retrieval aids, even if they have no intent for on-orbit servicing or retrieval.
As is touched upon previously, space travel is key for scientific research, technological advancements, and spinoff technologies. Originally space activities were only used for scientific research and with private companies looking to make money in this area, we need to make sure we can sustain our research in this field. More missions are researching the earth than ever before. The atmosphere, the climate, the continental drift and geodynamics, the gravity, hurricanes, the ice, the land and vegetation, the oceans, ozone, the sun and its influence on Earth, the water cycle, the weather, and wildfires are all studied by multiple missions. An STM system is mandatory to keep expanding this ever-growing research field, as well as to make sure private-owned constellations, satellites and space ships will not interfere with this research.
Space travel already requires a lot of data science, AI and cybersecurity development, and the STM system will only contribute to this. This is because a server network capable of tracking and monitoring more than 5 million objects is needed. This server system must be protected against cyber-attacks. It could form a huge threat to society if the server system falls into the wrong hands, and it is of uttermost importance to keep this from happening.
To better design an ASTM system that will fit the needs of future users attempts were made to contact several stakeholders and user groups. Several methods were used in this process and they will be listed below, ranging from sending a single message to a specific person to spreading a questionnaire on several social media platforms. Getting into contact with stakeholders proofed to be more difficult than expected and many did not reply at all. A small group of citizens did reply to the questionnaire, but due to the low response rate (22 people as of writing) and the fact that citizens are not satellite owners (while citizens benefit from satellite usage, they do not own them and so, in the end, would not have a say in the actual system integration) they will be mentioned here but will not be used much (if at all) when creating a final concept.
Organizations and Companies
Contacting actual satellite owners like NASA or SpaceX turned up no results. Getting useful contacting information of these large organizations is hard (aside from a basic HQ reception number) and the few options that did show up (email addresses, facebook, twitter) also lead to no responses. In short the following organizations received emails or social media messages; Elon Musk (SpaceX, twitter), Blue Origin, NASA(email), ESA(5 emails to different departments). Sadly none of them replied and so there is no direct input from these organizations that can be used, there is still indirect input (like articles and papers) from said organizations that can be interpreted when designing a system.
Attempts were made to get into contact with the Dutch government, specifically Jessica van Eijs and Monika Keijzer. However, both were not able or available to discuss this topic and attempts to contact other government officials also lead to no responses.
Questionnaire for the public
A questionnaire was spread on social media (facebook, twitter, family) in an attempt to find out what the public opinion is regarding STM and especially what they would think about an ASTM system. The full questionnaire can be found in SECTION-NEEDS-LISTING but the most important results will be discussed here. A total of 22 people responded to the questionnaire.
When people were asked whether an STM system should work autonomously a big majority of 69.6% said yes (see A1) while only a small minority of 17.4% said no and the final 13% can be interpreted as “it depends”. Which is an interesting result, for instance, the use of autonomous cars is always followed by heated debates whether an autonomous system can be trusted or not and yet here the majority votes to use an ASTM system. One might argue because there is a difference between asking a person whether they would entrust their life to a car or trust a satellites ‘life’ to an ASTM system, but that is not the goal of this project though could be an interesting topic of debate for another research group in the future.
Another surprising result is that 100% of the people who filled in the questionnaire voted for an international STM system. While for instance, the ISS(International Space Station) exists, most countries still focus heavily on national usage of satellites and spacecraft, which is contrary to what the people in the questionnaire would vote for.
While some of the other questions lead to inconclusive or not use-able answers there is one question that leads to some really interesting answers.
Summarizing the answers people suggested the following tasks:
- Energy supply(this would require some kind of supply station in orbit before it can be even considered possible);
- Destroy objects that present a threat;
- Navigation out of orbit, deorbiting, disintegration;
- Provide information about the satellites to the command center, fuel monitoring, etc. (this already happens);
- Prediction of collisions;
- Detecting when it is too busy. This could be interpreted in several ways, like when the system is too busy or when the space in orbit gets too busy;
- Detect space debris and save the data;
- Minimize the required amount of space satellites/attributes;
- Tracking of events;
- Alert earth if aliens pass by;
While not all the answers are useable or relevant there are several good suggestions that were not considered before. For instance, destroying objects could be very interesting in the future if machines get deployed into orbit that are responsible for cleaning up or destroying space debris, an ASTM system could monitor this to better coordinate between satellites and space debris cleaners, and even detect which space debris takes priority based on prediction models. Energy supply is also a nice future suggestion, however, right now there is no infrastructure in the orbit around the earth to actually make this feasible like supply stations.
Several other suggestions were already being considered but are here also being confirmed by participants. Like predicting collisions and deorbiting satellites when they reach end-of-life. However some suggestions are harder to interpret like ‘tracking of events’ and ‘minimize required amount of space satellites/attributes’ , the goal of the system is to manage safe space traffic and protect members its goal is not to analyze how many communication satellites, for instance, SpaceX needs, this is something the companies and users decide within their own respective organizations.
Requirements, Preferences, Constraints (RPC)
With the state of the art and stakeholders taken into consideration, it is time to set down the framework by defining the requirements, preferences, and constraints. With these, it will be possible to analyze rational agent models and to begin constructing a proper concept for an ASTM system. (These requirements, preferences, and constraints will be referred to as R1, R7, P2, etc. in the report.)
The system should be able to do the following:
- The system should be able to determine the position of participating and non-participating satellites, other spacecraft and space debris.
- The system should be able to predict collisions, by predicting the position of satellites and space debris.
- The system should be able to communicate decisions to the satellites concerned.
- The system should have a low failure probability, that can support assessments of collision probabilities higher than 1.10-4, which is a common collision probability threshold. ,
- The system should be able to handle more than 5 million objects to ensure safety for the coming 10 years, as the amount of space debris is expected to grow tenfold in the next decade. Nowadays, more than 500.000 objects are tracked by NASA, meaning that the system should be able to take into account and handle large 3D flight models. 
- The system should be able to work with incomplete, inaccurate or slightly false information. Especially military organizations will be unwilling to disclose full or any information regarding strategic satellites. There is also the chance of inaccurate sensor information. In each case the system should try to use the combined data of sensors and satellites in its group to make the most accurate guess as possible;
- Fully autonomous operation. Human interference should only be needed in situations the system cannot solve, [R4] (like an approaching collision with no ‘no loss’ solution);
The following items, while not absolute requirements, would still be desired for a good ASTM system:
- Easy compatibility. To make the system as accessible to as many organizations as possible the system should be able to easily connect with different kinds of satellites, including different messaging systems and/or operating systems. This could be achieved by centralizing the system, instead of it needing to be installed on satellites it would just require to be able to listen and talk to satellites in their ‘language’;
- Ability to assist in coordinating spacecraft back to earth when end of life has been reached;
- The ability to not just react to collisions when they are about to happen but to also use 3D models and learning algorithms to predict possible collisions early on and take preventative measures if predicted collision risk reaches a certain threshold;
The constraints should never be violated, this also has mostly to do with international space treaties. So a system that can not meet one of these constraints will automatically not be an option:
- Original owners/operators (o/o) should always be able to regain control of satellites. The system is a service, not an owner;
- System should in no way violate the international space treaties (for instance nobody is the boss in space, so the system will have no influence on satellites that aren’t participating);
- The system should be impartial in its judgment and only use a cost-benefit analysis to make decisions, if no decision can be made, it should switch to manual operation from the ground.;
- Like any other form of robots or artificial intelligence the system has to follow Asimov’s three laws of robotics;
To assure proper operation there are three main tasks the system will need to perform; 1. Data collecting and monitoring 2. collision prediction and avoidance 3. Communication. A fourth task will also be discussed, compatibility with performing other tasks or assisting other services, however, this one is not crucial to the main functioning of the system and will mainly consist of 'nice to have' options for future additions to the systems main library of tasks.
The three main tasks will be discussed in their logical order. First, the system will need to collect data about space entities in low orbit(space debris, satellites, etc.). Next, it will have to monitor these entities of which participating members can have more things to monitor besides positioning data(for instance fuel levels, hardware errors, etc.). The second and most important task of the system is to use the collected data to create 3D models and predict future collisions and take action where needed. If actions need to be taken it should use an appropriate decision style to make a 'best' decision. The third and final main task is for the system to communicate with satellites or databases, communicate with mission control and send alerts when it is about to take action. In this way, the position of space debris and participating and non-participating satellites can be determined, ensuring that the system will satisfy R1.
Data collecting and monitoring
For the system to be functional, it is necessary to collect data from participating and non-participating members. A distinction will be made between participating members, non-participating members, and unknown members. From each of the three classes, a different amount of data is needed. From participating members, it is important to know the position of the satellites, the fuel levels, the function, the size, and any malfunctions that might arise. The data will already be collected by the owner of the spacecraft. It is, therefore, not necessary for the system to be able to measure these parameters. The owners should consent to share this information to the system to function properly. The second class, non-participating members, are more difficult to obtain data from. The location of these satellites can be determined because satellites do not keep track of their own position, but this is done using radar from the ground. The satellites can be followed, however, no communication can be made directly with the satellite, as the owner is not always known. Moreover, factors, such as the function of the satellite or any defects are unknown. These satellites can be communicated with if the owner of the spacecraft is known, otherwise, it should be regarded as space debris. The last class, unknown members, are satellites that have been launched into the atmosphere by governmental organizations without knowledge of the rest of the world. These include military satellites that can shield themselves from radar, and thus remain invisible.
Locating of satellites and space debris
The most important data to collect is obviously the position of the satellite. The satellites do not track their own position, instead, tracking using ground stations determine the location. The ground stations send radio signals to the satellite, the uplink, and receive data transmissions from the satellite, the downlink. Also, space debris can be located and tracked using radar. FGAN Tracking is a high-performance radar facility in Europe that is able to do so.
A requirement for an ASTM system is that is compatible with the systems used by space agencies at the moment. Space agencies like ESA and NASA are currently using distributed systems for their programs., In most of the implementations, the system consists of a central computer, the server, and a number of user computers, the clients. There are several architectures of distributed systems: peer-to-peer and client-server. Client-server is a system that is divided into servers, that carry out tasks, and clients, which require the service. A server computer can manage several clients simultaneously, and at the same time, a client can be connected to several servers, that provide different services, simultaneously. Peer-to-peer (P2P) is an architecture where all computers and devices, called peers, work together. There is no central administrator and each peer is equal to the other peers. Files can be shared directly between systems without a central server, each network can be seen as a server and a client at the same time that works towards a common goal. These computers work together to function as a single application for the client. The decentralization makes the network efficient and more tolerant of faults.
Important programs from NASA, such as NASA’s Earth Observing System Data and Information System (EOSDIS) are designed as distributed systems. For the last couple of years, NASA has been investigating Distributed System Missions (DSM). A DSM is a mission that involves spacecraft to achieve one or more common goals. However, these missions are currently focused on the use of client-server architectures. P2P architectures have yet to be investigated.
ESA uses a distributed computing environment as well, in the form of client-server architectures. The Advanced Concepts Team (ACT) is part of ESA that focuses on new technologies that could be of importance in the long term, especially on innovations in distributed computing. P2P architectures are not yet implemented in the system that ESA uses for its programs, however, the ACT department is looking in this relatively new technology.
All considered a distributed client-server architecture would work best for the system. If organizations would switch to peer-to-peer systems, the ASTM system could be developed in such a way as well. However, currently, there has been too little research on the effects of the implementation of p2p systems to say with certainty that such a system would work effectively.
Collision prediction and avoidance
The second and most important task of the system after data collection is collision prediction and avoidance. Currently, to protect the ISS against possible collisions, a “warning box” is defined. This perimeter set around the spacecraft is a box of approximately 25 km along the track of the orbit, 5 km across the track of the orbit, and 5 km out of the plane of the orbit. When an object passes through this “warning box”, a more accurate algorithm is applied to evaluate whether the object is predicted to pass through a smaller box. This, so-called “maneuver box”, is a box of 5 km along the track, 2 km across the track, and 2 km in the radial direction. If an object is predicted to come within this second box, a maneuver is initiated. In this manner, the system satisfies R2; able to predict collision.
For the system conceptualized in this study, the same approach will be used. Because satellites are somewhat smaller than the ISS, it can be decided to make the maneuver box smaller. These parameters can be adjusted based on the size of the spacecraft. Since the goal is to automize collision avoidance an artificial intelligence (AI) will be used to handle this task. Next, when the system detects a possible collision it will have to take action, either automatically or by informing mission control. Again the goal is for the system to handle these tasks autonomously but there might be special cases where human interference might be needed. If the predicted collision is between one or more entities that the system has authority over and that can be handled without human interference it will do so using a decision structure to determine the best course of action.
First, the types of AI systems will be discussed and a recommendation will be made which would best suit this system. Next the decision structure will be discussed, again including recommendations, and lastly, some special cases will be mentioned as well.
AI systems: Rule-Based Systems vs Machine Learning Systems
AI systems can mainly be split into two groups; rule-based systems (RBS) and machine learning systems (MLS), with each their own benefits and drawbacks. Choosing between these systems is important because they form the foundation for which methods the system will use to detect and avoid collisions. First, a basic explanation of both systems will be given with each their pros and cons followed by a recommendation on which system would be best suited to handle collision detection and avoidance. The ongoing discussions in the field of AI about whether an RBS system is actually intelligent or not, will not be discussed here.
In principle, Rule-Based Systems (RBS) use coding in the form of if-then-else statements using the knowledge of a human expert. This means that the system uses a (large) set of predetermined rules and facts to make decisions and take actions. A key benefit being that these rule sets can be easy to write, especially in limited environments.
In most closed systems (like a robot arm in a car manufacturing plant) this is fine, but in more complex and changing environments this system can lead to major drawbacks in the long run. For instance, if the system encounters a new situation it will freeze or get stuck in a loop it cannot solve. In the long run, the biggest drawback of the system will be that adding rules later on without accidentally creating contradictions with earlier rules is tough. Basically the entire system needs to be checked when rules are added making maintenance time consuming and expensive.
Using a Rule-Based ASTM system
There are several pros and cons to using a rule-based ASTM system. A major advantage is that everything the system does is clear from start to finish, if anything ever goes wrong it can be easily traced back to what caused it. From a legal and ethical standpoint, this can be very desirable, it might also help with attracting users. A lot of users might not like the idea that the fate of their million-dollar investments gets decided by what an AI considers to be the ‘best’ decision. In an RBS, users can be informed beforehand what actions the system will take, allowing the users to take a better-informed decision about what their risks are. Another advantage is that RBS does not need to ‘learn’ and if programmers are able to program in every possible situation it should work without ever creating an error. This tends to allow for easy and safe implementation.
On the other hand, an RBS has major drawbacks, especially when handling STM. As explained before a lot is going to change regarding satellite usage and the space around earth is going to get a lot busier in the coming decennia. RBS works best (if only) when all possible situations are known, however, due to the changing nature of space usage in the coming decennia it will be hard or near impossible to predict all possible situations the system may encounter. If an RBS encounters an unknown situation it will freeze since RBS cannot update its own rules.
Which is where the second major drawback comes in. Rule-based systems can be cheap and easy to implement in simple environments (like a robot arm in a factory that needs to always place the same part in the same place) at first, but in complex changing environments they tend to get unwieldy and extremely expensive in the long run. So in regards to STM, the system might work fine at first but will require frequent updates in the long run and might eventually become error-prone, especially when the environment changes faster than the speed at which the system can get updated.
Machine learning Systems
Machine learning systems (MLS), on the other hand, can adapt to situations more easily and often on their own without human interference. When a learning system encounters new information it is able to change or discard existing models in favor of (hopefully) better models. This means that a learning system is not limited to its initial knowledge or a static rules set. However proper training data is needed so the system can build ‘good’ models and in some application areas that can be an issue, as there might be no available prior knowledge. In that case, a system builder could let a learning system take several shots at creating a model based on input/output but in sensitive areas, like STM, using a badly or untrained system would not be wise. Luckily with STM, there is already a lot of prior data to use which can help in creating ‘good’ models for the system to start from. However, the adaptability of this system is also its major drawback if the system creates a wrong model it can lead to a lot of damage depending on how late or early the faulty model is discovered.
Using Machine Learning for an ASTM system
Considering the complex and changing environment of STM there are several obvious advantages for choosing MLS over RBS. First off MLS is actually able to update itself and can almost instantly react to new situations. This decreases maintenance and also lowers the chance of errors due to changing situations. Though a side note should be made, it can decrease the chances or errors due to changing situations, something RBS struggles with, but this does not mean that it is less error-prone necessarily in general. For instance, MLS depends a lot on the training data they are provided to construct their models. While RBS would force a programmer to make a system that takes into account all possible situations with MLS good quality control might be overlooked in favor of quicker implementation and cost savings. However, a badly trained MLS will also behave badly leading to costly errors.
Another side of MLS is its ability to make ‘best’ decisions and to create predictive models. Both are features that would be highly desirable for ASTM from a technical standpoint, especially when such a system might need to control tens of thousands of spacecraft in the future at which point things like efficiency and good prediction models can have big impacts on cost savings. However, from a legal standpoint, there might be a big downside to this as well. As discussed earlier MLS is a black box, while a programmer can feed it training data and set some requirements, In the end, there is no way to know exactly why the system made a certain decision. While in closed environments where only one or two parties are involved this might be less of an issue, it can be a bigger issue when the system is responsible for taking care of thousands of satellites from hundreds of owners. Why did satellite A move to avoid B? Why was B not forced to move? Why did satellite C get sacrificed in an unavoidable collision instead of satellite D? And who would pay for the costs involved, who is even responsible? While some of these questions are general legal issues other systems also run into like autonomous cars, it is still something that can be a consideration for choosing one system over the other depending on future legislation.
Best system for collision prediction and avoidance?
The three things that are most desirable from the system are; easily adaptable, highly scalable, legally sound. Considering the complexity and currently changing nature of the STM environment MLS obviously wins from RBS when it comes to adaptability. Next, there is scalability. To put this into perspective a 3D body has six degrees of movement (x, y, and z-axis). If two satellites are on a collision course with each other this would mean there are two 3D bodies with six degrees of movement, so 6x5=30 movement solutions. Now obviously this is something a programmer could still easily program in RBS, but remember the system should in the future control multiple constellations which will consist of thousands of satellites each. If two constellations cross each other’s flight paths there might be thousands of satellites that will enter each other’s “warning boxes” resulting in perhaps a hundred bodies needing to move in one of the six degrees. Obviously asking a human programmer to predict the movement of hundreds if not thousands of satellites with six degrees of movement is a nearly impossible task. One might propose to use very basic solutions like “always move the satellite with the highest orbit further up to avoid a collision.”, but such rules could result in extreme situations where satellites end up being pushed away from earth or in the opposite direction get forced down into the atmosphere. So also here MLS wins because the system is better able to use 3D models to analyze and predict what future results of orbit adjustments will be and therefore the system can use a ‘best’ result each time instead of getting stuck in a loop of shooting satellites away.
Already MLS has a two to zero advantage over RBS but the last point is also the most difficult one. Regardless of how wonderful technology or a system is, it can only be used if legislation allows it. While there is no legislation against MLS, there are still many legal issues the system could run into. As mentioned earlier RBS has the advantage that all actions can be traced back and explained. However with MLS, there is input, output, and boundary conditions, but other than that the decisions MLS takes are complete black boxes. Right now there is no legislation to handle MLS, a result of this could be that if something does go wrong that the company that owns the system gets sued out of business by parties that endured loss due to the system.
At the end from an engineering standpoint, there is no reason to pick RBS over MLS, however, MLS suffers from the same problem as many other STM issues, legislation is key and can make or break it.
Decision style when a possible collision is predicted
Once an ASTM has predicted a possible collision, it should make “the best” decision. This is a vague term that needs to be specified. When a satellite encounters a piece of space debris, there is no debate about who will adjust their path, simply because space debris is not able to change direction. When two satellites are about to collide, and both have the ability to make a maneuver, decision making becomes much more complex. Satellites have the ability to move in four directions, up/down/left/right, from a certain perspective. For some satellites, it is important to return back to their particular place in the orbit. For others, it might be favorable to change their height in orbit. Every satellite diverges a little bit from its course over time and has to adjust their position eventually. In addition, “the best” decision can be quite different when based on different aspects of the problem. Four relevant approaches are listed below that will be discussed. Each one has its advantages and disadvantages when chosen as the decision-making approach for the ASTM system.
- Monetary value
- Randomness, nobody responsible
First off, a decision can be made based on the monetary value of the spacecraft. For some satellites, it is more expensive to make a maneuver than for another. The one with the lowest costs should be chosen to make the maneuver. A downside of this approach could be that some users might not disclose the costs of their satellites, however, such behavior could be ‘punished’ by telling the system that satellites with no known cost always have a lower value than satellites have a disclosed cost. Another issue of this approach could be that always the same satellites will have to move, which could mean the same user always has to swallow the cost.
In addition, there is always a chance that there is no possibility to avoid a collision. This can be for a number of reasons. If the system is in charge of making the final decision and if it is possible to save a satellite, the satellite with the most monetary value should be the priority. The downside to this form of decision-making is that the functional loss of a relatively cheaper GPS satellite might be higher than the functional loss of a very expensive space research satellite.
Another aspect to base the decision on is the function of the satellites. Several functions of satellites can be the collection of weather data, space research, or civilian GPS (Global Positioning System). When a satellite changes its course, this can affect the accuracy of the data, as the instruments are calibrated at a certain height. For some functions, this is not as big of a deal, such as weather data collecting satellites. For other functions, however, such as GPS, it can disrupt the communication and degrade positioning performance. At the moment, GPS satellites maneuver for station keeping. When a maneuver is about to happen, the Notice Advisory to Navstar Users (NANU) is issued to inform users depending on the system concerned. If a decision were made based on the function of the satellite, a weather satellite would have to move before a GPS satellite, for example. This form of decision-making solves the problem that was encountered when only looking at a monetary value. However, a new problem arises. When there are two satellites with the same function that are on the verge of a collision, there are no clear rules which of the two should move.
Utility is the result of the previously mentioned ways of decision-making combined. This approach is based on the philosophical direction called utilitarianism. The decision of whether actions are right is dependent on the effect of that action. More specifically, according to utility the action that results in most happiness can be considered as the best decision. The happiness of the owners of the satellite and the clients of the servers of the satellite are both taken into account and balanced for optimal happiness. A disadvantage is that happiness cannot be measured with a universal system that everyone agrees on.
From a system, perspective utility could be used to determine which action has the best result in the long run. For instance, making satellite A move instead of satellite B might not be desirable if moving satellite A just triggers a new collision course with satellite C while moving satellite B would not trigger a new collision course.
A totally different approach is randomness. This approach can especially be handy when one or more satellites will be lost regardless of which action the system takes. There is no party responsible, and it can be seen as each participating party taking its turn.
Decision style recommendation
Since not all possible decision styles are considered here (mostly the most relevant ones) and all the options mentioned have their pros and cons it might be better to actually combine them. For instance, with function, an issue arose where multiple satellites might have the same function, who moves then? Well in such a situation the system could move on to another decision style, like monetary value. A priority hierarchy could be used where the system first looks at function, followed by monetary and eventually if no decision style offers a ‘best’ decision then it can use randomness as a last resort. Another option is to assign rankings or values to the results of each decision style. For instance satellite A scores 15 points based on function and monetary value, while satellite B only scores 10 points. The system would then make satellite B move instead of the overall more valuable satellite A, again if the points end up being equal randomness could be applied.
There is always a possibility that the system will encounter a possible collision with no solution or where the solution might require another party to take action. Since not every active satellite will be participating in the same or any ASTM system it could happen that a satellite that cannot maneuver reaches a collision course with an active satellite that can maneuver but is not under the control of the ASTM system. In this situation, the ASTM system would have to either alert mission control or contact the owner of the other satellite. In an ideal future if both satellites are controlled by an ASTM system they could automatically contact each other like; “Satellite A of ASTM C will collide with satellite B of ASTM D…..Satellite A cannot maneuver, Satellite B can maneuver….ASTM C requesting ASTM D to move Satellite B”. However, especially in the early years of system implementation, there will be many satellites that are not part of an ASTM system and so the system would need to inform mission control to contact the other party.
Another special case is where the system reaches an unavoidable collision, more specifically speaking a collision where there is no ‘no loss’ solution, meaning 1 or more satellites will be damaged or destroyed regardless of which action the system takes. This is different from a situation where the system can literally not do anything to influence the outcome, for example, two satellites that both cannot maneuver on a collision course with each other. While such a thing would be very rare, it can still happen and should be taken into consideration when designing the system. In such a situation the system should alert mission control about the impending collision, that way mission control can inform the involved users, present possible actions the system can take and what the costs will be of each outcome for each user. It would then be up to the users to reach an agreement about who takes which loss.
The system needs satellite position data to calculate these collisions. This data is widely available as NASA and ESA have data and information sharing policies that state :
“NASA promotes the full and open sharing of all data with the research and applications communities, private industry, academia, and the general public.”
Because the system needs real-time data, an agreement has to be made with these organizations to share this with the server of the system. When a collision is predicted and the chance of that collision is higher than a certain value, a report of this event will be sent to the mission control of the participating satellite. This way the participating members always know what is going on with their satellites and if desired, the member can react to the upcoming event. When a satellite from a non-participating member is involved in the collision and has to be maneuvered, the report has to be sent manually in order to inform the mission control. Even though the system cannot maneuver that specific satellite, it is still necessary to inform the owner. The system communicates data to the satellites this way, satisfying R3. When the system has chosen how to react to the upcoming predicted collision, mission control will be informed of this maneuver in order to make sure the action is agreed upon. If the action is denied by mission control, the system will take a look at different solutions to solve the issue. It is important to keep the mission control of that specific satellite updated on the planned maneuvers, not only to keep them informed for their missions but also to hold them responsible for its actions.
To assure that the ASTM system meets the user’s demands, the system has to be validated through simulation models. Normally, a system can be validated with experiments. This, however, is not possible with an STM system for obvious reasons. Verifying an STM system experimentally would be costly, not to mention the consequences when the model fails.
To validate the system, a computer model has to be made that simulates a great number of objects in orbit around earth. First, a model has to be made of how the situation will be in the future, with multiple satellite constellations, active and non-active satellites, and space debris. This model has to be made in order to have a reference model to compare the STM system to. Because it is impossible to know how many collisions would occur with human intervention, this model has to calculate how many collisions would take place without external input.
After a base model has been simulated, the STM system has to be implemented in the model. To make sure this model is as close to reality as possible, some data has to be incomplete or unknown to the system. To validate a model, a three-step approach has been formulated by Naylor and Finger  that has been widely followed:
- Step 1: Build a model that has high face validity, meaning that the model is a reasonable imitation of a real-world system.
- Step 2: Validate model assumptions, which can be divided into structural and data assumptions. Structural assumptions are assumptions about how the system operates and how it is arranged. There should be a sufficient amount of appropriate data available to build a conceptual model.
- Step 3: Compare the model input-output transformations to corresponding input-output transformations for the real system.
Because this model is a representation of a future system, it is not possible to compare it to a real-world system. However, a lot of knowledgeable people on space traffic could decide on the face validity of this model.
The structural assumptions of this model are validated when all operations of the system have been stated clearly and are agreed upon.
Data assumptions are the most difficult part to validate because a lot of assumptions and predictions on what the future will be like have to be made in order to simulate this model. In order to validate the model, data from reliable sources has to be used.
Because it is impossible to validate a future model concept, other options have to be explored. Validating input-output transformations could be done by making a simulation of the current state and validating it to the collisions that have been recorded. However, this is not reliable, as there have only been a couple of incidents in the past.
System simulations using NetLogo
To demonstrate the capabilities of an ASTM system and to show an example of what a system validation might look like, simulations were done using the NetLogo simulation program. Version 6.1.1 was used of NetLogo 2D, this wasn't however without complications mostly due to software limitations as will be discussed below. Some snippets of the models will be provided as well as the full programs in a .zip file down below.
Model simulations and limitations
In the end, 2 models were created, a scaled version and a non-scaled version, there are several reasons for doing this. The main reason being software limitations(NetLogo version 6.1.1). Satellites can be around 5 meters wide or even more, however, their speed in low earth orbit(LEO) is around 7.1 km/s to sustain orbit. This creates a difference of around 1 to 1400. The same issue arises with the collision boxes, 25 km forward means 1 to 5000 and 5 km in all other directions is 1 to 1000. This meant that if in the program a satellite is 1 pixel (or patch since the patches are scaled at 1 to 1 for this model), it would take another 5000 pixels to simulate just the width of the forward collision box(available screens were limited to 1920*1080 or 2560*1080).
This is why in the scaled version there is nothing 'visible' since the objects are too small, the window is 1600*800 where every pixel is 62.5 meter(so a satellite in this model is less than 1/12th of a pixel) and so the window represents an area in space of 100 km * 50 km. However regardless of hardware used (SSD's , 12gb or 16gb RAM, 4th gen I5 or 5th gen I7 processor) the program became extremely slow, using only between 20% to 40% of processing power, processing at almost 1 tick per second where each tick a satellite moves 7.1 km so the simulation actually slowed down so much that it became a 1 to 1 simulation in time.
To be able to actually show what happens in the simulation and to be able to actually run the program at a normal speed again a non-scaled version was created. When it comes to scale and realism this model is not an accurate simulation of reality. It is, however, good enough (in lack of other available hardware or software) to visually show the basic principles.
In this model, the simulation window is 200*80 patches where every patch is 10 pixels large (so 2000*800). Considering a satellite should be 5 meters large this window would only represent an area of 1000 meters by 400 meters. The number of objects in such a small area, especially satellites, is not representative of the real world and this simulation should only be used for showing off the basic principles. Of course with more advanced software and using supercomputers such simulations could not only be more accurate to reality but also be done way faster. For instance to validate the system it might be desirable to simulate one year of system usage. With NetLogo, this would result in needing to let a consumer pc run a scaled simulation for a whole year, while organizations like NASA and ESA should have the resources to do this in a fraction of the time.
Provided below are the source files of both the scaled model and the non-scaled model.
The next step in the development of the ASTM system is the testing of the automated parts. The types of validation models have been described in the body of this study. What remains is the set-up of these experiments to test whether the proposed STM architecture will suffice w.r.t. the requirements. Collaboration from STM stakeholders in the development of the testing is encouraged, to ensure the best validation.
In this study, the focus was put on the conceptualization of an ASTM, with as main tasks tracking, monitoring, and collision avoidance. Through a survey, input has been given by public users that could take this concept a step further. The most relevant feedback given is the proposal of letting the ASTM system cooperate with other important space systems. These include assisting space debris cleaning operations and assisting satellites with end-of-life removal. Space debris mitigation systems are critical to preventing many of the problems of concern. Next to the launching of increasingly more satellites in space, space debris is the number one reason that a space traffic system is needed. Even if from now on all satellites that would be launched would deorbit after they have come to the end of their life, then there still remains a lot of space debris in LEO. A vast amount of the satellites that are currently up will end up as space debris. Therefore, the cooperation with space debris mitigation systems might be a very important feature to add to an ASTM system. Not only will it prevent satellite loss, but it will also prevent collision avoidance and tracking systems to overload. A way to minimize space debris is by deorbiting spacecraft as soon as possible after the end of their lives. Preventing the problem is often better than trying to clean up afterward. To accomplish this, international legislation should be adjusted to provide rules and guidelines for existing debris mitigation.
Rules and legislation
At the moment, technology is ready to develop an ASTM. No new technological advances have to be made to fulfill the requirements set for such a system. The field that has to develop is the field of rules and legislation. Data-sharing protocols, standards, and norms for operating in low orbit need to be created and agreed to internationally for the system to work properly. As already stated, international legislation lacks rules and standards for a system to be implemented this instant. A global consensus must be reached concerning the handling of sensitive information, authority over this data and the potential liability of an autonomous system.
One way to ensure safety in space concerning international law could be to extend the analogy to aircraft a bit further. Low orbit space could be divided into specific areas under control of certain stations on the ground. As with air control, there are different rules for operations in the vicinity of airports than there are in the open sky. Near space stations, assuming in the future more will come, different rules could apply. However, every solution comes with many questions. Should we divide space and consider it as an extension of the Earth? Who would monitor and control these divided areas? Who would have the authority?
Before any decisions can be made, international law needs to be updated. Next week, October 2019, the International Astronautical Congress (IAC) meeting in Washington will take place, a key opportunity to debate these points of discussion.
This project was done for the course 0LAUK0 and over a period of eight weeks. Over the course of this project, the group learned more about the importance of the user but also how hard it can be to contact users, especially in a time-constrained project. It is easy for engineers to make something that is technically and functionally sound, but if it does not fulfill the wants and needs of the user, it is doomed to fail regardless. On the flip side one might argue that the user also has a responsibility to the engineer, if engineers try to inquire users about what they want, but they do not answer the engineer cannot be blamed in the end for trying to make a ‘best’ guess of what the user might want.
A big learning point in the project came from probably the biggest obstacle this project faced, legislation. The world is ruled by laws and everyone has to follow them, not just humans but also the machines we design. Especially when it comes to the usage of space and STM the current international laws are a big hindrance. In this report, recommendations have been made regarding the need to update the old international space treaties to account for modernization. However, we are not technocrats and so it is not up to us to change or determine the laws. We as engineers have a duty to properly inform legislators, but we should never decide for them.
Another noteworthy learning point came from the conversations during the weekly meetings. When we were presented with a problem, oftentimes we got pretty headstrong. This could be because of our knowledge of the subject or because of our education. When this happens it is important to keep listening to the other person. Sometimes we were communicating the exact same idea or truth but from two different perspectives, and because we weren't saying it exactly the same way, we misinterpreted that to mean that one of us had to be wrong. When we disagree, it is imperative to stop, listen, and completely understand the other person's perspective.
There is also something to be said about finding the ‘best’ solution. Especially in education, we are often thought that everything has a single or best solution, however, in practice, this is often far from the truth. Especially when one has to design a system in a complex environment for many users there will often not be a single solution. And this is also something we acknowledge about our recommendations, they are not the end all be all, they are not perfect and they are definitely not the only possible solution. But as a group we made these recommendations based on literature studies, user inquiries (although few) and the knowledge we currently possess as engineers. But whether or not our concept will form the stepping stone for future intergalactic STM or whether it will be overshadowed and forgotten in favor of a ‘better’ solution, the skills and knowledge we gained will always be valuable to us.
The questionnaire can be found at the following link:
The full data set with all the answers is available through the following pdf: File:Space Traffic Management Survey Answers.pdf
A copy of the questionnaire is provided below.
Space debris often gets the most attention when one talks about threats that exist to active satellites and other spacecraft. However recent developments in the space industry present a ‘new’ threat to active satellites.
Where traditionally space travel was government-driven, the privatization and commercialization of space activities have gained momentum and have developed different interests like faster and cheaper access to space. Currently, there are several organizations that plan to launch thousands of satellites up into the earth’s orbit in the next several years. These range from governments like the UK planning to launch 2000 satellites by 2030 to large companies like SpaceX planning to launch 12000 satellites for its Starlink constellation. If we compare this to the currently 4987 satellites in orbit, of which only 1957 are still active and functional, one quickly sees how ‘full’ the currently quite ‘empty’ low orbit space around the earth will become in the near future.
This could overwhelm current space flight safety processes. However, there are encouraging signs that the government, industry, and the space community are acting to address these issues. This project will look at a possible solution for managing these many thousands of satellites by using an autonomous system for space traffic management (STM).
If you don't know why space debris forms a problem in the first place, we suggest you watch the video below to bring you up to speed!
We would first like to get to know you a little more!
How old are you?
What is your gender?
- Prefer not to say
What is your highest level of education?
Some first thoughts on the topic.
Did you know what space debris was, and why it is a problem?
- Yes, I did and I knew it was a problem.
- Yes, but I didn’t think it was such a big deal.
- No, I had never heard of it.
Do you think there is a need for an autonomous Space Traffic Management system when you look at the current situation? Yes/no, why?
Do you think such a system should work autonomously? (example: satellites avoiding collisions without human input)
What do you think an autonomous STM system should be able to do?
Do you think an STM system should be completely autonomous?
Do you think an autonomous system could be able to make “right” decisions? If two satellites would run into each other, for example, do you think it could be programmed to make the best decision?
Do you think a system should be allowed to make such decisions?
Aside from collision avoidance, what other tasks do you believe an autonomous STM system should be able to handle?
How do you see such a system implemented in modern-day society?
Do you think there should be an overall body responsible for an STM system?
Do you think a system should be run by a governmental or non-governmental organization?
If you answered government-driven on the previous question, do you think an STM system should be implemented on a national or international level?
Would an STM system lead to international collaboration or conflicts?
Do you think all parties involved in space traffic should participate?
Do you believe the main world powers (US, Russia, China, Europe) would be willing to participate together?
Do you think a system could be implemented, even though not all parties agree to share their positional data?
How long do you think it will take before an STM system will be implemented?
- 1 year
- 5 years
- 10 years
- More than 10 years
Are you afraid that an STM system could be a target for terrorism in the future?
End of the survey
Thank you so much for taking the time out of your day to complete our survey!
If you have any other comments or thoughts we haven't discussed yet, feel free to leave them here!