Massively Parallel Processing for Dynamic Airspace Configuration

Through extensive research conducted by Mosaic ATM in the area of Dynamic Airspace Configuration (DAC), we have identified the significant benefit of the use of Dynamic Density (DD) as the DAC objective function. The use of DD as the objective function allows the DAC algorithm to directly address critical aspects of sector design beyond simple balancing of the flight counts. These sector design considerations include the alignment of sector boundaries with flow direction, proximity of conflict points to sector boundaries, and boundary alignment with respect to vertical traffic movement. By using DD as the objective function, we generate a multi-objective optimization approach that considers both efficiency and complex controller workload issues. The SectorFlow DAC algorithm has performed well in NASA's DAC algorithm comparison experiments. However, due to the additional computational complexity caused by the use of DD as the objective function, only limited application of DD as the objective function was conducted. In this proposed SBIR effort, Mosaic ATM will apply a massively parallel computing architecture to the DAC algorithm using DD as an objective function to demonstrate and evaluate both the computational advantages of massively parallel processing, and the benefits of using DD as the objective function in DAC.