Right of Way Rules based Collision Avoidance Approach Using Model Predictive Control

This paper presents a Model Predictive Control (MPC) based collision avoidance scheme for unmanned aerial vehicles (UAVs) in civilian airspace consisting of manned and unmanned aerial vehicles. The MPC formulation takes the Federal Aviation Regulations for collision avoidance mid-air collision scenarios into account. The optimal control inputs to the UAV in the form of angular velocities are computed by optimizing the MPC cost function for a finite prediction horizon. The algorithm is evaluated for pairwise and multi-UAV conflict scenarios and compared against inverse proportional navigation (IPN) collision avoidance approach. The results show that MPC has lower control effort than the IPN while achieving similar performance of IPN.