Understanding U-AGREE: DLR Insights on UAS Mid Air Collision

Dr. Miguel Ángel Fas works in the Unmanned Aircraft Systems Department of the Institute of Flight Guidance at the German Aerospace Center (DLR). In U-AGREE, DLR contributes by developing an air risk model to more precisely estimate the severity of a possible air encounter involving uncrewed aircraft or Vertical Take-Off and Landing (eVTOL) vehicles. The model also reflects how serious a collision would be with different types of birds. 

In this interview, he shares his insights on how air risks are defined, assessed, and integrated within the U-AGREE framework.

How is “mid-air collision risk” defined within the context of UAS operations?
A mid-air collision (MAC) is defined by ICAO as an accident where two aircraft come into contact with each other while both are airborne. But in the evaluation of the air risk an aircraft is represented with a cylindrical volume containing it and a MAC is assumed if other aircraft enters into it. The size of the volume is based on the predicted time to conflict and relative motion of the other aircraft.

What is the current state of the art in assessing mid-air collision risk?
The European regulation requires the use of the Specific Operations Risk Assessment (SORA) methodology to evaluate the risk of the operations in the specific category (which encompasses the majority of the expected operations over urban areas). Following the criteria of SORA, it must be expected less than one mid-air collision per 10 million flight hours. In U-AGREE we suggest refinements to SORA so that it can better adjust to the reality of the drone operations.

Which factors or variables are considered most critical in evaluating mid-air collision risk (e.g. traffic density, airspace structure, detect-and-avoid capabilities)?
For severity, the size of the traffic or bird involved, and for the probability, the historical data of presence in each of the cells into which the airspace is divided for analysis. Also, the presence in the surrounding cells, to guarantee a minimum separation of the traffic of a cell side distance.

How does the U-AGREE project approach and implement the air risk (mid-air collision) model?
In the air risk model proposed in U-AGREE the probability of encounter is estimated based on historical data. The airspace is divided into cells that receive a risk probability proportional to the accumulated presence of traffic during a relevant period of time that could be, for instance, the last few years. Apart from the probability it is estimated also the severity that will be in function of the category of size of the traffic involved. This categorization includes also different categories of birds, for which data on their presence is also taken into account.

What results or preliminary findings have U-AGREE achieved so far regarding mid-air collision risk?
EASA’s Easy Access Rules (EAR) for UAS, the SORA air-risk model, only addresses the hazard to conventional manned traffic due to UAS operations. Then the current version just addresses UAS-manned aircraft MAC. U-AGREE’s air risk model distinguishes more combinations of airspace encounters, like UAS-UAS MAC (with or without people on board), or bird strikes.
The SORA 2.0 air risk model considers that any collision between any UAS and a manned aircraft will provoke the latter to fall to the ground with lethal consequences for all people on board. The U-AGREE air risk model allows to weigh the consequences of a MAC for the aircraft involved, since depending on the participants a loss of control will not necessarily be the case.