Airbus UTM and MIT Paper Selected as Best Paper at 2020 ICRAT Conference
Several months ago, esteemed colleagues at MIT, alongside our Airbus UTM team, submitted a new co-authored paper to the 2020 International Conference for Research in Air Transportation (ICRAT). We’re proud to say that the paper, titled “Tradeoffs Between Efficiency and Fairness in Unmanned Aircraft Systems Traffic Management” received a Best Paper Award at the virtual conference on September 15.
Over the years, we have been diligently focused on UAS Traffic Management (UTM) initiatives that will be necessary to ensure safe and efficient operations in the airspace of the future for all users. The expected growth in unmanned and self-piloted operations is expected to make airspace resources more congested. UTM represents a digital system designed to monitor and manage this increased activity, preventing the loss of airborne separation and mitigating congestion at departure or arrival points. These functions can be achieved through airborne delays (by speed or path changes) or ground delays (delayed takeoff times) to aircraft.
Our paper evaluates the fairness implications of delay assignment while attempting to achieve more efficient operations. The tradeoff between fairness and efficiency of the UTM system as a whole is examined by modifying existing formulations of the air traffic flow management problem as an optimization. Delay assignment in UTM is analyzed using simulated scenarios where multiple warehouse delivery operators share an airspace.
The work resulted in three key findings:
- Significant improvement in fairness can be obtained in exchange for little to no decrease in system efficiency.
- Some fairness metrics may be aligned in the sense that they can be jointly optimized and improved upon. On the other hand, other fairness metrics may be conflicting, and optimizing one may worsen another.
- Dynamic demand can be incorporated in the air traffic flow management problem by using a rolling horizon framework. However, a rolling horizon framework reduces system efficiency. Interestingly, fairness of the solution may improve or worsen, depending on the fairness metric used.
We’re pleased to be able to bring this kind of research to the industry alongside researchers at MIT who are deeply committed to ensuring a sustainable and forward-looking UTM. It’s an honor to have those insights recognized at this year’s event.
To check out the paper, please visit HERE.