Enhancing Airside Operation Efficiency through Trajectory Optimization by Computer Software

Airside operations at Taiwan Taoyuan International Airport (TPE) often encounter problems related to limited airport capacity, leading to congestion on the airport apron and taxiways, aircraft conflicts, delays, and operational inefficiencies. The pivotal role played by Air Traffic Control (ATC) in managing airport traffic in such scenarios necessitates the development of an optimization model tailored to enhance operational efficacy. The primary objective of this study was to propose an optimization model designed to streamline aircraft taxi trajectories and reduce taxi times efficiently. The model leverages the principles of shortest taxi route determination and node graph theory. The model was implemented through a user-friendly Excel program to provide air traffic controllers with a straightforward and comprehensive tool for trajectory optimization. Key functionalities of the tool included real-time calculation of the shortest aircraft trajectory, identification of potential conflict points, and estimation of taxi times. The proposed model assisted in decision-making for air traffic controllers by minimizing conflicts, mitigating air pollution, and optimizing airport operations. The model was constructed based on data derived primarily from TPE airport. In the research framework, the intricacies of TPE’s operational environment were considered to ensure the applicability and effectiveness of the proposed trajectory optimization tool. The study results contributed to the enhancement of airside operation efficiency at TPE and potentially at other congested airports facing similar challenges. The proposed optimization model offered a systematic approach to address congestion-related issues, ultimately empowering air traffic controllers with the means to make well-informed decisions promptly and benefiting both operational efficiency and environmental sustainability. Further research and practical implementation are encouraged to validate the model’s effectiveness and adaptability across various airport contexts.