In order to study air traffic control of UAS’s (Unmanned Aerial Systems) in very low altitudes, the UTM (UAS Traffic Management) simulator has to be as flexible and expandable as other research simulators because relevant technologies and regulations are not matured enough at this stage. Available approaches using open sources and platforms are investigated to be used in the UTM simulator. The fundamental rationale for selection is availability of necessary resources to build a UTM simulator. Integration efforts to build a UTM simulator are elaborated, using Ardupilot, MavProxi, Cesium, and VWorld, which are selected from the thorough field study. Design requirements of a UTM simulator are determined by analyzing UTM services defined by NASA (National Aeronautics and Space Administration) and Eurocontrol. The UTM simulator, named eUTM, is composed of three components: UOS (UTM Operating System), UTM, and multiple GCSs (Ground Control Stations). GCSs are responsible for generation of flight paths of various UASs. UTM component copies functions of a real UTM such as monitoring and controlling air spaces. UOS provides simulation of environment such as weather, and controls the whole UTM simulator system. UOS also generates operation scenarios of UTM, and resides on the same UTM computer as an independent process. Two GCS simulators are connected to the UTM simulator in the present configuration, but the UTM simulator can be expanded to include up to 10 GCS simulators in the present design. In order to demonstrate the flexibility and expandability of eUTM simulator, several operation scenarios are realized and typical deconfliction scenarios among them are tested with a deconfliction algorithm. During the study, some limits are identified with applied open sources and platforms, which have to be resolved in order to obtain a flexible and expandable UTM simulator supporting relevant studies. Most of them are related to interfacing individual sources and platforms which use different program languages and communication drivers.
Field study identifying barriers and delays in data-to-decision with small unmanned aerial systems
