Date of Award
Master of Science (MS)
Mechanical & Aerospace Engineering
A geometrical point of closest approach method is used to solve air traffic conflict detection/resolution problems with a single conflict vehicle that is unaware or unable to aid in resolving the conflict. Nonlinear, three degree of freedom equations of motion for a point-mass vehicle are derived and formulated to allow commanded trajectories to steer the vehicle to a desired location. A dynamic model is developed to propagate the vehicle in three dimensions. A closed-loop model implementing a negative feedback controller using a Proportional-Integral-Derivative control scheme is used to drive the vehicle to match the commanded trajectories. A conflict detection/resolution algorithm implementing a point of closest approach method is developed to determine the point at which the simulated, target vehicle will be just on the edge of a safe sphere surrounding the conflict aircraft to simulate the Federal Aviation Administration’s requirements for proper spacing between aircraft. A velocity vector is created to steer the target vehicle to this point to avoid any conflict. MathWorks’ Simulink computational environment is used to simulate the target vehicle and conflict vehicle. Various trajectories for the target vehicle and the conflict vehicle are tested to evaluate the performance of the algorithm. The algorithm performed satisfactorily in detecting and steering the vehicle away from a conflict, always improving the relative spacing between the two vehicles. However, the algorithm was lacking in capability to precisely satisfy the separation requirement. In all cases the target vehicle mildly penetrated the safe region. Future research directions are discussed with the goal of improving the conflict detection/resolution algorithm performance so that the separation requirement can be reliably met.
Easton, Marc S.. "Detecting and Resolving Air Traffic Conflicts Using a Point of Closest Approach Method" (2016). Master of Science (MS), thesis, Mechanical & Aerospace Engineering, Old Dominion University, https://digitalcommons.odu.edu/mae_etds/13