A flight slots allocation method for single airport based on Q-learning algorithm

Xinyi Fang; Haiyan Chen; Yuhang Qian; Lei Yang

doi:10.1117/12.3050724

20 January 2025 A flight slots allocation method for single airport based on Q-learning algorithm

Xinyi Fang, Haiyan Chen, Yuhang Qian, Lei Yang

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 1342225 (2025) https://doi.org/10.1117/12.3050724
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

The air traffic demand surpasses the capacity of most of the busiest airports worldwide. The mismatch between airport capacity and air traffic demand leads to serious congestion and delay problems. Since airport capacity is difficult to expand in a short time, in order to reduce flight delays, we need to adjust and optimize flight slots for flight applications, and allocate flight time resources scientifically and efficiently under the premise of meeting airspace resource constraints such as airport capacity. In this paper, we proposed an airport flight slots allocation method based on the Q-Learning algorithm in reinforcement learning. Firstly, we preprocess the original data set. Data cleaning processes data with missing attribute values and removes irrelevant attributes. Through data transformation, the data of string attribute is transformed into discrete numbers, and the time attribute is processed. After that, we construct a mathematical model of single-airport flight time allocation, which is a combinatorial optimization problem and determines the optimization objectives and constraints. Then we apply the reinforcement learning algorithm Q-Learning to solve this optimization problem, and the algorithm updates the strategy through interaction with the environment to get a better solution. Finally, we take Guangzhou Baiyun International Airport as a study case to train and verify the proposed single-airport flight time allocation model. The experimental results show that, the optimized flight slots satisfy the airport capacity constraints while minimizing the adjustment of flight schedules as much as possible, and adjust the flights at some times to alleviate the congestion.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinyi Fang, Haiyan Chen, Yuhang Qian, and Lei Yang "A flight slots allocation method for single airport based on Q-learning algorithm", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 1342225 (20 January 2025); https://doi.org/10.1117/12.3050724

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KEYWORDS

Mathematical optimization

Particle swarm optimization

Data modeling

Particles

Process modeling

Performance modeling

Data processing

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