Free flight air traffic management optimisation using discrete particle simulations

The future of Free Flight, an air traffic control system where aircrews have the freedom and responsibility of selecting their tr'liectory and resolving it with others, is bright. The work performed by international Air Traffic Management (ATM) community is bringing Free Flight ever closer to reality. Also, due to technologies that have been accepted by the community, it has become easier to develop progressive simulations that can reasonably and logically map possible methods of evolution or progress from the post NextGen and SESAR implementation all the way to entirely Free Flight based ATM. and thus optimize the path through them. In order to ensure the accuracy of these progressive simulations it becomes necessary to analyze unique results, and by replicating them, verify how they were created in the first place. This paper describes one such analysis, where a trend in decreasing pilot preference for direct flight paths was found, replicated, and verified. It also shows the possibility to take chaotic (e.g. discrete particles simulations with Monte Carlo adjustments and large numbers of linear relationships for high fidelity) simulations and verify them to a level that would allow the propagation and harvest of emergent properties for the purposes of ATM optimization.