Quantifying Risk of Ground Impact Fatalities for Small Unmanned Aircraft

Abstract

One of the major challenges of conducting operations of unmanned aircraft, especially operations beyond visual line-ofsight (BVLOS), is to make a realistic and sufficiently detailed risk assessment. An important part of such an assessment is to identify the risk of fatalities, preferably in a quantitative way since this allows for comparison with manned aviation to determine whether an equivalent level of safety is achievable. This work presents a method for quantifying the probability of fatalities resulting from an uncontrolled descent of an unmanned aircraft conducting a BVLOS flight. The method is based on a standard stochastic model, and employs a parameterized high fidelity ground impact distribution model that accounts for both aircraft specifications, parameter uncertainties, and wind. The method also samples the flight path to create an almost continuous quantification of the risk as a function of mission flight time. The methodology is exemplified with a 180 km flight in Danish airspace with a Penguin C aircraft.

The Value of Step-by-Step Risk Assessment for Unmanned Aircraft

“…In this work we will use previous works by the author developed specifically to conduct a quantitative risk assessment that is comparable to the SORA process. For the ground risk the model from [25] will be used, and for the air risk the model from [26] will be used.…”

“…The model for ground fatalities is a stochastic model that joins probabilities in the causal chain from drone malfunction to a potential fatality, and is based on the model in [25]. It takes the form…”

“…The four events are ballistic descent, uncontrolled glide, parachute-like descent, and flyaway. These event types, including how they are modeled, are described in more detail in [25], [27], [28].…”

“…In addition to the few variations listed in Table I, the first principles HFRM parameters used for the modeling are listed in Table V. The computational parameters for discretization and numerical integration are similar to those used in [25] and are not repeated here.…”

“…This feature is not captured in any way in the SORA, but included here to see what impact it has. It is important to note that while HFRM produces seemingly very accurate fatality rates, one should focus only on the order of magnitude of the results, since the numbers will invariably change with adjustments to any of the many parameters, some of which are purely educated guesses (see [25] for discussion of this topic).…”