Modeling Unmanned Aerial System (UAS) Risks via Monte Carlo Simulation

Unmanned Aerial Systems (UAS) pose a variety of risks to third parties when operating over populated areas, due to the danger posed if the UAS crashes. Two commonly used metrics for assessing the risk of such crashes are the kinetic energy of the UAS at the time of impact and the probability distribution of locations where the UAS could crash. In this paper, a Monte Carlo based approach is presented for simulating UAS crashes in order to calculate these metrics. A surrogate modeling approach for UAS safety metrics is also presented, which is built using the results of the Monte Carlo simulations. The surrogate modeling approach is capable of rapidly evaluating UAS safety metrics for arbitrary UAS design and operating parameters. The proposed approach is demonstrated by modeling the kinetic energies at time of impact and crash probability distributions for UAS with dynamics models similar to that of a Cessna 182.