There are many diverse concepts for autonomous drone operations. One of these concepts is the delivery of packages in urban areas. Transportation companies are already testing vehicles capable of performing such operations, and many studies indicate that this concept is both tech
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There are many diverse concepts for autonomous drone operations. One of these concepts is the delivery of packages in urban areas. Transportation companies are already testing vehicles capable of performing such operations, and many studies indicate that this concept is both technically feasible and financially attractive. However, how much risk do civilians living in cities (also called third-party-risk, or TPR) face following these drone operations? Moreover, what measures can be employed to mitigate this risk? Regulators demand answers to these questions before allowing autonomous Unmanned Aircraft Systems (UAS) operations to take off. Recent research has focused on developing methods of calculating the TPR, or on creating models that accurately resemble drone operations in urban cities. The model proposed in this work bridges the gap between these categories using an agent-based safety risk analysis. In this analysis, we study the TPR of UAS package delivery operations in Delft, New York and Paris. This model leads to two main contributions. The first considers observations regarding the influence of the environment on the TPR. In particular, our model suggests that if the low-risk areas are clustered in a city, this leads to higher TPR. The second contribution is derived from the interaction of the risk computation with our model of the environment. Global- and local sensitivity analyses led to a few interesting observations. For example, our model suggests that it is more important to understand the vehicle's failure rate in the cruise-phase, than in the takeoff- and landing-phase. It is also suggested that it is more important to understand how buildings protect people from impact than to understand the effects of an impact directly on a human. Another finding is that modelling the impact speed with the terminal speed, as is common in literature, leads to a TPR that is 15% - 26% higher than when the impact speed is modelled based on the drone's dynamics.