A Drone Operation Plan model to support the effect of uncertainty in advanced U-Space Capacity Planning Process

Abstract

Enabling high numbers of drone operations in urban environments will require an efficient and highly automated drone traffic management system that can help balance demand against novel capacity measures. The research project DACUS designed a new, social impact-and risk-based Dynamic Capacity Management (DCM) service. As a core element, Drone Operation Plans (DOP) as the central and reliable point-of-information must include all necessary information for the DCM service to evaluate and manage the demand and the associated uncertainty of those operations at various phases of the operations planning process.This paper introduces a model to define and share DOPs that are enriched with information about technical capabilities of the drone, variations in the operating environment and the operational characteristics of each particular mission which helps facilitating the drone traffic management in capacity-constrained scenarios. The model aims to capture varying degrees and sources of uncertainty regarding the planned operations. Additionally, the model supports the integration of resolution plans to cope with a wide range of off-nominal scenarios and contingency events.For evaluation, the proposed DOP model is implemented and used in experiments embedded in Sopra Steria’s UTM or U-space Collaborative Interface System (UCIS). A social impact model and a collision risk model are used in simulations with high traffic demand and the information of the DOPs is either updated or directly applied within the DCM processes. The influence of operational uncertainty is assessed in this work using the collision risk model, which evaluates the risk of drone operations to the public and identifies potential collision risk hotspots.The simulation results show that the DOP model is suitable for the requirements of several U-space services and functions.