A Cooperative Distributed Approach to Multi-Agent Eulerian Network Control: Application to Air Traffic Management

Abstract

Based on an Eulerian network model, air traffic flow in the National Airspace System is optimized using second order adjoint methods for hyperbolic PDEs. Multiple airlines with independent cost structures are added to previous work on air traffic flow modeling and optimization. A cooperative, distributed solution methodology is proposed that allows airlines to keep cost information private by distributing the computational workload between the airlines while ensuring efficient outcomes. The Nash Bargaining Solution is presented as a possible solution concept, and a distributed method for its calculation is presented. I. Introduction Management of today’s National Airspace System (NAS) has become an extremely complicated task. Pilots and controllers must continuously manage numerous complex subsystems and adapt to frequent changes in traffic flow, spacing and routing caused by variable weather conditions and other network delays. Specifically, the national Air Traffic Control System Command Center (ATCSCC) is responsible for continuously updating decisions concerning traffic flow to maximize network throughput. The current methodology is based on a sophisticated set of rules described in playbooks that have been developed through years of controller experience. This procedure is neither automated nor optimal, and requires constant human intervention to allow the system to operate. Airlines are an integral element of the NAS and are developing more and more advanced methods of aircraft management, as supervised by Airline Operations Centers (AOCs). Their stake in aircraft flow decisions is quite high, as their profitability is directly tied to on-time performance, and significant costs are incurred by flight delays, cancellations and rerouting. Furthermore, their preferences change dynamically, based on highly variable parameters such as aircraft load factor and percentage of connecting passengers per flight. Unfortunately, airlines are currently only able to affect decisions over a small part of the network flow problem, by swapping slots with their own aircraft and deciding which flights to delay when required. For smooth flow of their aircraft over the NAS network, the airlines must rely on the savvy and equity of the ATCSCC controllers who attempt to minimize schedule disruption while not necessarily minimizing incurred costs. This need not be the case. Consider a futuristic scenario for the NAS, where airlines cooperate with each other in a distributed manner, supervised by the FAA, to dynamically reroute and reschedule flights based on restrictions imposed by weather conditions and network delays in such a manner that their individual profits are maximized, while all safety requirements are met and the airspace is used efficiently. In sucha scenario, real-time collaboration amongst the airlines will drive the efficient use of resources by incorporating airline specific preferences between routes into the flow optimization and ultimately, the passenger will be better served.