Multi-objective four-dimensional trajectory planning for free-route operations considering weather forecast uncertainty

Abstract

Free-route Operations (FRO) represent a significant shift in the future air traffic management, offering enhanced system capacity and operational efficiency. However, there remains a lack of trajectory management methods tailored to FRO that can effectively address the challenges of unstructured traffic flows, high traffic complexity, and uncertain weather conditions. This paper proposes a novel multi-module framework for 4D free-routing trajectory management, including trajectory prediction, airspace configuration, and strategic and tactical trajectory planning. Trajectory prediction incorporates ensemble-based weather forecasts to address uncertainty. A routing method tailored to FRO is adopted, combining a two-layer network with a K-shortest path algorithm to generate alternative routes. The core of this framework is a strategic trajectory planning method, integrating flow management and conflict management to optimize safety, efficiency, and flexibility. A complexity metric based on the linear dynamical system is adopted for safety evaluation. A distributed multi-objective optimization method is designed based on the decomposition mechanism, solving subproblems in parallel. The proposed framework is validated through a simulation scenario based on historical data from the western China airspace. Results demonstrate that the proposed method reduces operational risk by 88.52 % and increases flexibility by 51.66 %, with only a 6.84 % increase in cost. Additionally, trade-offs among three objectives are identified from non-dominated solutions, and a multi-criteria decision-making method guides the selection of the ideal solution and maneuver type. The proposed method also demonstrates high computational efficiency, making it a practical decision-support tool for future free-route operations.