Simulation of Random Events for Air Traffic Applications

Abstract

Resilience to uncertainties must be ensured in air traffic management. Unexpected events can either be disruptive, like thunderstorms or the famous volcano ash cloud resulting from the Eyjafjallajökull eruption in Iceland, or simply due to imprecise measurements or incomplete knowledge of the environment. While human operators are able to cope with such situations, it is generally not the case for automated decision support tools. Important examples originate from the numerous attempts made to design algorithms able to solve conflicts between aircraft occurring during flights. The STARGATE (STochastic AppRoach for naviGATion functions in uncertain Environment) project was initiated in order to study the feasibility of inherently robust automated planning algorithms that will not fail when submitted to random perturbations. A mandatory first step is the ability to simulate the usual stochastic phenomenons impairing the system: delays due to airport platforms or air traffic control (ATC) and uncertainties on the wind velocity. The work presented here will detail algorithms suitable for the simulation task.

Keywords

• fast time traffic simulator
• Gaussian field simulation
• air traffic management