Conflict Detection Metrics for Aircraft Sense and Avoid Systems

Abstract

The task of an airborne collision avoidance system is to continuously evaluate the risk of collision and in the case of too high risk initiate an evasive action. The traditional way to assess risk is to focus on a critical point of time. A recently proposed alternative is to evaluate the cumulated risk over time. It is the purpose of this contribution to evaluate the difference between these two concepts and also to validate an approximate method for computing the cumulated risk, suitable for real-time implementations. For this purpose, random scenarios are generated from stochastic models created from observed conflicts. A realistic tracking filter, based on angle-only measurements, is used to produce uncertain state estimates which are used for risk assessment. It is shown that the cumulated risk is much more robust to estimation accuracy than the maximum of the instantaneous risk. The intended application is for unmanned aerial vehicles to be used in civilian airspace, but a real mid-air collision scenario between two traffic aircraft is studied as well.