Real-time trajectory optimization and air traffic control simulation for noise abatement approach procedures

Abstract

Aircraft noise is a major obstacle to the growth of aviation. This thesis presents an adaptive onboard real-time optimization algorithm and an Air Traffic Control simulation model that can minimize the aircraft approach noise and meet air traffic control targets and restrictions. The adaptive real-time optimization algorithm uses dynamic programming, nonlinear optimization, and receding horizon control to generate approach procedures. The resulting noise abatement trajectories compensate for environmental uncertainties, provide more flexibility to air traffic controllers and pilots, and improve airport efficiency while lowering community noise. The Air Traffic Control simulation model simulates a fleet approach with noise abatement approaches. Three different status displays are tested and compared in the simulation, and the optimal displays for controller are explored in the thesis.