Low-level collision risk modelling for unmanned aircraft integration and management

This paper considers the problem of robustly quantifying the collision risk associated with unmanned aircraft operations in non-segregated airspace. The work leverages real surveillance data and statistical analysis to produce a new quantitative collision risk methodology that can be scaled to support nationwide determination of air risk. Specifically, spatial and temporal manned traffic attributes are extracted from the surveillance data and uniquely combined with well-established collision modelling concepts to numerically estimate collision risk, conditioned on unmanned mission location and exposure time. The collision risk approach is then applied to a set of low level unmanned operations to illustrate its utility.