A fuel optimal and reduced controller workload optimization model for conflict resolution

Despite the existence of several automated air traffic conflict resolution algorithms, there is a need for formulations that account for air traffic controller workload. This paper presents such an algorithm with controller workload constraints modeled parametrically. To this end, we first develop an integer programming model for general conflict resolution, which emphasizes the minimization of fuel costs, and runs in near real-time. A parametric procedure based on this model is then developed to consider controller workload limitations. Two versions of the parametric approach are described, along with computational results. It is demonstrated that both formulations can be used to capture a broad range of possible controller actions.

Introduction

The projected growth in air transportation demand over the next twenty years is likely to exceed the capacity of the unaided air traffic controller. Consenquently the past two decades have seen significant investment in the development of advanced air conflict detection and resolution algorithms. The aim of these algorithms is twofold: to increase capacity and to improve safety. Both the United States Federal Aviation Administration (FAA), and EUROCONTROL, recognize the need to develop support systems for both the tactical (radar controller) and strategic (traffic flow management) controller positions. At the tactical level these systems are particularly important for deconflicting air traffic [1], [2].