Application of merging optimization to an arrival manager algorithm considering trajectory-based operations

• Published in: Transportation research. Part C, Emerging technologies Vol. 109; pp. 40 - 59
• Main Author: Toratani, Daichi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2019
• Subjects: Air traffic management; Aircraft sequencing problem; Arrival manager; Merging optimization; Trajectory optimization; Trajectory-based operations; Trajectory-based operations; Arrival manager; Trajectory optimization; Merging optimization; Air traffic management; Aircraft sequencing problem
• ISSN: 0968-090X; 1879-2359; 1879-2359
• DOI: 10.1016/j.trc.2019.09.015

•An arrival manager (AMAN) algorithm based on the merging optimization is proposed.•Optimizing arrival aircraft sequence while considering trajectory-based operations.•Actual radar data are used to evaluate the proposed algorithm.•The proposed algorithm showed better performance than the conventional algorithm. An arrival manager (AMAN) is a support system for air traffic controllers in the airspace near an airport. The AMAN assists the air traffic controller in facilitating efficient arrival sequences and arrival times to ensure smooth arrival traffic. Although the aircraft sequencing problem that optimizes the arrival sequence has already been studied for the AMAN algorithm, the AMAN algorithm must also optimize aircraft trajectories to accommodate trajectory-based operations. This study proposes a novel AMAN algorithm based on the merging optimization method. Although the merging optimization method can simultaneously optimize the arrival sequence and trajectory, it cannot be easily applied to a realistic AMAN algorithm. Thus, the receding horizon approach is employed here to apply the merging optimization method to the AMAN algorithm. To demonstrate the performance of the proposed AMAN algorithm, numerical simulations are conducted. Actual radar data are used to conduct realistic air traffic simulations and evaluate the AMAN algorithm. A conventional AMAN algorithm is also simulated for comparison. Simulation results show that the proposed AMAN algorithm reduces both the total flight time and fuel consumption of all aircraft compared with the conventional AMAN algorithm. Furthermore, the proposed AMAN algorithm reveals the trade-off relationship between the minimization of flight time and fuel consumption.