Autonomous and collaborative trajectory planning for traffic complexity management

Abstract

To accommodate growing air traffic demand, the traffic complexity management plays a crucial role in the capacity improvement of future automated air traffic management. In this paper, an autonomous and collaborative trajectory planning (ACTP) method is presented to facilitate collaborative decision‐making and enhance flexibility of the traffic complexity management in the en route airspace. A nonlinear integer model is formulated for the conflict‐free autonomous trajectory planning by reorganizing the trajectories with the combination of speed adjustment, lateral rerouting and flight level allocation maneuvers. Within the framework of the air‐ground situation awareness sharing, the spatio‐temporal reachable space is defined to describe the feasible solution space under the constraints of aircraft performance and required time of arrival. In addition, both the system‐level and the individual‐level objectives, traffic complexity and flight efficiency, are considered in the model, which are measured through the metric based on linear dynamical systems and the deviation from the user‐preferred trajectory. To balance the optimality and computational efficiency in the multi‐aircraft trajectory planning, a multi‐aircraft clustered and collaborative optimization algorithm is proposed based on the hybrid distributed‐centralized control strategy. The experimental results of the scenario in Western China airspace is presented, which verify the effectiveness of the proposed ACTP method through the comparison of other methods. Furthermore, a multi‐criteria decision‐making problem is discussed to strike a better trade‐off between different objectives in the trajectory planning.