Close proximity and collision risk assessment of drones and urban air mobility

Abstract

For quantitative assessment of close proximity and collision risks of drones and urban air mobility there is a need for simulation approaches that can represent a variety of operations and types of uncertainty and hazards that can affect them. This paper shows that agent-based modelling in combination with Interacting Particle System (IPS) Monte Carlo (MC) simulation and risk decomposition for global failure conditions can be effectively used for assessment of small probabilities of close proximity and collision events. It is demonstrated for a use case with drone and air taxi traffic simulations in an urban area south of Paris.