Maximum Flow Rates for Capacity Estimation in Level Flight with Convective Weather Constraints

Abstract

We study the problem of computing maximum flow rates for capacity estimation of an airspace at a constant flight level in the presence of convective weather constraints, under various operational conditions. Our problem statements are for future Air Traffic Management (ATM) operations where jetway routing is removed and aircraft routes may conform with the geometry of weather constraints. We consider several ATM flow organizations: All Altitudes (aircraft flying in any direction), Alternating Altitude Rule (aircraft flying with headings from 0° to 180°, versus 180° to 360°), Monotonic Rule (aircraft flying in from the west), and Unidirectional (aircraft flying from west to east). We investigate both decentralized Free Flight scenarios and centralized Packed scenarios under each flow organization. For each flow organization, we compute the maximum flow rates for the airspace through experimental analysis based on simulated demand for travel through the airspace and routes computed using an algorithmic solution. We compare the throughput, observed in simulations, to the theoretical upper bounds we compute using network flow theory adapted to the geometric problem domain. We also compute a complexity metric to evaluate the solutions computed under each flow organization. Experiments are based on both real and synthesized weather data.