Multiobjective Four-Dimensional Trajectory Synergetic Optimization Based on Congestion Prediction and NSGA3-SA

Abstract

Synergetic trajectory planning of flights is one of the important goals of trajectory-based operation (TBO), and it is also a method to further improve the utilization of airspace resources with the increasing number of flights in recent years. In order to plan the four-dimensional trajectory (4DT) pretactically and comprehensively, match the flight traffic with airspace capacity, reduce congestion, potential conflicts, and fuel consumption thus improving the efficiency of flights, this paper conducts a method for synergetic trajectory planning in the en-route phase from the perspective of airlines. Firstly, the aircraft performance model, aircraft fuel consumption model, and atmospheric model are constructed according to the base of aircraft data (BADA3.11), and an airspace congestion prediction model is constructed based on the historical flow data of airspace. Secondly, a multi-objective synergetic trajectory planning model is established, and a solution method based on the non-dominated sorting genetic algorithm and simulated annealing algorithm (NSGA3-SA) for the problem of synergetic trajectory planning is designed. The simulation shows that the optimization model and the solution algorithm of NSGA3-SA can reduce fuel consumption by about 4.5% compared to the original flight plans and has a good effect on reducing congestion and avoiding conflicts. The running time of the NSGA3-SA can meet the operational requirements of the pre-tactical trajectory planning. The multi-objective optimization model and the solution algorithm proposed in this paper have great value for the research of flight plan optimization.

Four-Dimensional Trajectory Planning Algorithm for Fixed-Wing Aircraft Formation Based on Improved Hunter—Prey Optimization

“…Many researchers have performed a great deal of work on four-dimensional trajectory planning for aircraft. By investigating the historical trajectory data of civil aircraft and comprehensively considering constraints such as aircraft flight performance, fuel consumption and atmospheric conditions, a multi-objective four-dimensional trajectory collaborative optimization algorithm based on the non-dominated sorting genetic algorithm and simulated annealing algorithm was proposed [4]. Comparing the trajectory obtained by this algorithm with the historical trajectory data, the fuel consumption is reduced by 4.5%.…”