A Sector-Specific Probabilistic Approach for 4D Aircraft Trajectory Generation

Abstract

Generating realistic four-dimensional trajectories is a fundamental challenge in air traffic control (ATC) that is relevant to both operational tasks and to effective simulation of airspace for the purposes of training controllers and designing new airspaces and/or procedures. Traditional trajectory generation methods are deterministic and use physics-based models with well-calibrated physical parameters and speed schedules. However, these models require knowledge of the clearances issued to aircraft in order to produce a full trajectory. Tools which can marginalise over these clearances to generate a four-dimensional trajectory are valuable in simulations as they emulate the behaviour of human controllers in background sectors, while also reflecting the level of uncertainty present in the system. Consequentially, this work proposes a probabilistic method for generating 4D aircraft trajectories that are specific to a sector of airspace, incorporating multiple routes and allowing local procedures such as co-ordinated entry and exit points to be modelled. The proposed model couples a model for generating plausible aircraft ground tracks with data-driven climb and descent models specific to an aircraft's (ICAO) wake turbulence category. A simple algorithm combines the lateral and vertical trajectories together to produce a four-dimensional (4D) trajectory. A busy sector in the United Kingdom's upper airspace was the focus of the study, which used a dataset comprising one month of aircraft surveillance data. It was found that the proposed model offered improved modelling of aircraft performance and the lateral path followed by aircraft compared to existing, deterministic methods of trajectory generation.