Davin Oyelaran
Systems & Simulation Correspondent
Davin translates the work of the simulation team into plain language, covering deconfliction, risk frameworks and the architecture of a modern UTM stack.
Reading the Sky: How Simulation Shapes Safer Drone Corridors
Before a single corridor opens over a real city, it has already flown hundreds of thousands of times inside our simulation environment.
Autonomous Conflict Avoidance Systems for the Airspace of the Future
In our last memo, we presented the idea of using mathematical models like the Markov Decision Process (MDP) to enable better decision making when faced with complex and uncertain environments, like the increasingly populated airspace.
Solving for Uncertainty: Exploring the Markov Decision Process in Dense Airspace
As humans, when we're faced with a difficult decision, we try to evaluate the most likely outcomes without introducing an internal bias into the process.
Encounter Aware Flight Planning in the Unmanned Airspace
To our knowledge, this is the first ever quantitative analysis of flight planning in the context of centralized and federated UTM architectures.
Centralization v Federation
In preparation for the release of our technical paper, Encounter Aware Flight Planning in the Unmanned Airspace, we use this memo to provide an overview of centralized and federated architectural approaches.
How Does Risk Influence Airspace Capacity?
To ensure that our Open Risk Framework can effectively anticipate and respond to changes in capacity, we're conducting a range of studies in our UTM prototype simulator.
What are the Biggest Factors that Contribute to Risk?
From the sensitivity analysis of our fault trees for a UAV crash or collision, we learned that four broad categories of factors have a strong influence on the probability of a loss of control that results in a crash.
How Do We Calculate Risk?
Our second risk briefing focuses on how we developed our flexible open risk framework.
The Role of Risk Assessment in UTM
Successful safety risk management for autonomous vehicles in our airspace will require that we extend and evolve our current frameworks, many of which are qualitative and subjective.
How Many Drones Will a UTM Need to Support?
In this memo, we're sharing a sneak preview of The Blueprint's projections in the context of last week's memo highlighting the need for an air traffic management architecture built to be scalable and flexible.
Architecture of a UTM
The memo debut of our design for a modular and scalable UTM service stack.
Volume Estimation Tool
We built a tool to streamline the calculations for estimating the volume of drones coming to our skies and shared it with all our subscribers along with instructions for different ways the tool can be used.
Airspace Bands by Heading
We set up this study to measure the effect on collision rates when autonomous vehicles are assigned altitude based on their direction of flight - easterly moving aircraft at one altitude, westerly moving aircraft at a second altitude.
When Drones Fly at Different Speeds and Altitudes
In this study we tested the effect of airspace configuration on safety, specifically on what happens when varying both speed and altitude.
How Many Drones until Big Sky isn't Big Enough? Part II
Once again using our simulation tool we explored traffic over major cities and found that, for a city like Paris, at a rate of 1,000 short urban mobility flights per hour, a collision will occur about 800 times per million flight hours.
Metrics for Near-Miss Events
There is no publicly available global metric for comparing air traffic safety events in which two aircraft get close enough to one another that a collision was barely avoided.
How Many Drones until Big Sky isn't Big Enough? Part I
Using our proprietary air traffic simulation tool, we began to model what the airspace would look like with varying traffic types, traffic densities, rules of the road, and conflict avoidance methods.