PROJECT TITLE :

Comparison of Mixed-Integer Linear Models for Fuel-Optimal Air Conflict Resolution With Recovery

ABSTRACT:

Any significant increase in current levels of air traffic will want the support of economical decision-aid tools. One among the tasks of air traffic management is to change trajectories when necessary to take care of a sufficient separation between pairs of aircraft. Several algorithms have been developed to unravel this drawback, but the diversity in the underlying assumptions makes it tough to match their performance. In this paper, separation is maintained through changes of heading and velocity while minimizing a mixture of fuel consumption and delay. For realistic trajectories, the speed is continuous with respect to time, the acceleration and turning rate are bounded, and therefore the planned trajectories are recovered after the maneuvers. After describing the foremost modifications to existing models that are necessary to satisfy this definition of the matter, we have a tendency to compare three mixed-integer linear programs. The primary model relies on a discretization of the airspace and also the second depends on a discretization of the time horizon. The third model implements a time decomposition of the matter; it permits solely one initial maneuver and is periodically solved with a receding horizon to make an entire trajectory. The computational tests are conducted on a benchmark of artificial instances specifically designed to include advanced situations. Our analysis of the results highlights the strengths and limits of every model. The time decomposition proves to be an wonderful compromise.