An algorithm for conflict detection in dense traffic using ADS-B

In this paper, we propose a novel algorithm for traffic situation awareness and alerting using ADS-B. The objective of the system is to alert pilots of incoming potential collisions or hazardous situations. The system, intended for all aircraft types, particularly targets General Aviation aircraft, as it should demonstrate high performance such as an early detection time and a low nuisance alert rate, in dense traffic conditions such as airport traffic patterns. The algorithm takes a deterministic approach to the collision avoidance problem. We define two buffer zones surrounding the target, or intruder, aircraft. The first, the Collision Airspace Zone (CAZ), has a constant size, which is based on uncertainties in position measurement for the ownship and the intruder. The second, the Protected Airspace Zone, is dynamic and is intended to reflect the distance pilots feel comfortable flying from other aircraft based on closure rate. We define two levels of alert based on the prediction of the buffer zones. A high level alert, based on CAZ penetration, indicates the potential of a mid-air collision. A medium level alert, based on PAZ penetration, warns the pilot that his aircraft may come in close proximity to another aircraft. Trajectory prediction is based on propagating constant turn rate, velocity and vertical velocity for both the target and ownship. Using an encounter model to evaluate the performance of the algorithm on representative traffic, we show that the trajectory propagation method outperforms the linear velocity propagation currently used by TCAS.