Trajectory prediction in North Atlantic oceanic airspace by wind networking

Aircraft in the North Atlantic oceanic airspace are subjected to strong winds caused by the Jet Stream. The flight progress prediction is based on meteorological data forecast. The roughness in wind forecast often results in large differences between the predicted and the actual cruising times. This increases the uncertainty in conflict detection. All aircraft are able to perform instant meteorological measurements. Implementing new technologies enables exchanging these measured data directly between aircraft. Thus, an aircraft can obtain information about winds on its route from preceding aircraft and adjust its time predictions. This process is called Wind Networking. As the data obtained with wind networking is much more accurate than the initial forecast, the adjusted predictions are much closer to the reality. In this work, we perform simulations of the wind networking process. We compare the results of applying this approach and the results obtained using the meteorological forecast in terms of cruising time prediction and conflict prediction. We observe a remarkable improvement in the predictions by the wind networking and we quantify the benefits of using such an approach.