The Prototype Introduction
Learn about the Airbus Simulation Tool Shaping the UTM Systems of the Future
As part of the Airbus organization, it is in our DNA to ensure that the UTM system we develop and deploy is designed to serve a broad spectrum of stakeholders for both today's airspace, and the increasingly complex and crowded airspace of tomorrow. Solving problems in an airspace that doesn’t yet exist is challenging - but visualizing those conditions in a simulation environment is one way to understand what that future airspace will look like. At Airbus UTM, we use our unique simulation tool to explore and evaluate concepts, services, and architectures that will serve as critical foundation pieces of a robust and future proof UTM framework.
One of the first efforts kicked-off within Altiscope, the Acubed project that became Airbus UTM, was the development of a dynamic simulation tool the team called “The Prototype.” In those early stages, the Prototype was designed to explore ideas about the basic requirements of UTM: concepts like fairness and deconfliction, which the UTM community was still defining at the time. Since then, the tool has gone through many evolutions to become the powerful system we use to answer critical questions about how UTM solutions will function in increasingly autonomous and digitized airspace.
Today, the Prototype is a distributed, service-based system that can simulate everything from the physics of an aircraft to the wide variety of factors that impact flight: like weather, infrastructure, and other nearby vehicles. Layered over this is a component that simulates the UTM system itself: allowing configuration for an almost infinite variety of operator and mission scenarios along with the UTM services that enable those operators to take to the skies.
This simulation framework allows us to get a big picture view of the airspace from the perspective of many different stakeholders: small drone operators, urban air mobility vehicles, commercial air traffic, and air traffic control. The environment provides data at scale: running thousands of test flights representing those stakeholders in the real world is impractical. The Prototype, using the Airbus UTM cloud platform, can simulate hundreds of thousands of flight hours in under a day, identifying anomalies and providing reliable and reproducible results.
More specifically, we use the Prototype to develop a set of sustainable and forward-looking safety critical tools and services to support advanced concepts like urban air mobility, wide scale drone delivery in urban areas, or automated flight beyond visual line of sight (BVLOS). The simulation environment allows researchers to explore these advanced concepts in an astoundingly complex future environment: one that may include not only high volumes of traffic, but also new regulatory requirements and policies that have yet to be enacted.
UTM concepts like deconfliction, for example, are complex problems that become even more critical in dense airspace. Simulation can allow researchers to develop and test deconfliction strategies that move beyond pairwise deconfliction and consider the problem of maintaining efficient flight paths while avoiding conflicts from multiple directions at once.
We also use simulation to explore interoperability, by considering the effects of having many operators and USS stakeholders in the system, each with their own business interests and each attempting to optimize their operations in shared airspace. Through this understanding, we explore concepts of fairness: What happens when one operator reserves a disproportionately large amount of airspace? How is priority negotiated?
The safety impact of strategic deconfliction on a simulated many-vehicle scenario
The Airbus UTM tools and simulation environment are at work for the entire aerospace industry, providing valuable data to inform industry standards and gain a global consensus on what the airspace of the future will look like. Our publicly-available Drone Volume Estimation tool, which provides an estimate on the number of drones a region might see in a particular area given economics and other factors, have been used worldwide to inform regulators. Data from the drone volume estimation can be used in the simulator to see exactly how that estimated scenario functions. Tools like the volume estimator describe the “what”: the simulation environment leads to the discovery of “how.”
We're developing ideas and models that have been vigorously stress-tested and capture not only the data points we find, but the uncertainty uncovered in a dynamic airspace. At Airbus UTM, we are committed to making our research and algorithms available to the community, to enable the development of traffic management systems that will support the whole airspace ecosystem. Additionally, here is a list of our recent research papers that have been shaped, tested, or verified by the Prototype:
Have you considered and embraced the idea of collaborative simulation as part of your UTM toolset?
Have you considered and embraced the idea of collaborative simulation as part of your UTM toolset? Let’s come together as a community to design an interoperable simulation framework where our systems could coexist and be tested against one another. There’s no doubt about it - simulation is a key enabler of the evolution of UTM.
The future evolution and the growing complexity of simulated airspace over Auckland
Technical Papers
Encounter Aware Flight Planning in the Unmanned Airspace
This paper proposes and evaluates a novel algorithm that combines strategic demand-capacity balancing with 4D trajectory planning for UTM operations. We apply the algorithm as an automated strategic deconfliction UTM service available to simulated operators. The performance of the algorithm is evaluated using the prototype, and is shown to significantly outperform naive strategic deconfliction approaches, particularly when the airspace is dense.
Optimizing Collision Avoidance in Dense Airspace using Deep Reinforcement Learning
(ATM R&D Seminar 2019 with Stanford University): This work studies the limits of collision avoidance in increasingly dense airspace. Simulation is used to both evaluate and train neural network collision avoidance policies that are optimized to resolve many vehicle encounters that could be present in a dense airspace. The work both proposes a novel methodology for developing collision avoidance technologies and a density upper bound on their performance.
Fairness In Decentralized Strategic Deconfliction in UTM
(SciTech 2020): In this work we explore fairness implications of first-come first-served allocation in strategic deconfliction using the prototype. We use simulation to quantify the fairness disparities that result from certain operators filing ahead of others for package delivery and air taxi use cases.
Unlicensed Technology Assessment for UAS Communications
(ICNS 2020): This work evaluates the feasibility of proposed unlicensed technologies for UAS communication. The prototype is used to simulate air traffic, bandwidth, and saturation characteristics of communications technologies in a dense airspace.
Tradeoffs between Efficiency and Fairness in Unmanned Aircraft Systems Traffic Management
(submitted to ICRAT 2020 with MIT): In this work, the balance between fairness and efficiency of the UTM system as a whole is examined. Specifically, delay assignment in UTM is analyzed using simulated scenarios where multiple warehouse delivery operators share an airspace. The work shows that optimizing certain fairness metrics can lead to significant improvements in the fairness of the system while leading to little decrease in system efficiency.