Collision Risk Modeling and Analysis for Lateral Separation to Support Unmanned Traffic Management

This article investigates the utility and extension of well-established collision risk modeling approaches for lateral separation standard development for unmanned traffic management and network design. The applicability of standard assumptions and simplifications made in the manned environment to a scaled-down unmanned aerial systems (UAS) environment is first investigated. The results are used to derive an iso-risk surface that shows the tradeoff between separation distance and navigation performance for a given risk level or target level of safety. The model is then extended to consider collision risk from one to $$ tracks, and finally to determine the total collision risk and the related iso-risk surfaces for systems of $$ parallel tracks with additions to account for the effects of more than two parallel tracks. The extended model is applied to a case study where airspace design for an urban area is conducted via maximization of the number of same-direction parallel tracks while meeting the target level of safety. The results suggest that lateral separation distances less than 100 m are achievable for small UAS, and that the separation standards are mostly affected by the proportion of poorly navigating aircraft.