交通运输研究2026，Vol.12Issue(1)：70-79,10.DOI:10.16503/j.cnki.2095-9931.2026.01.007
基于GAN-LSTM的通用机场冲突探测与智能解脱方法
Conflict Detection and Intelligent Resolution Method for General Aviation Airports Based on GAN-LSTM
摘要
Abstract
To enhance the conflict detection and resolution capability in dynamic environments of Category A general aviation terminal areas,this paper proposes an end-to-end conflict detection and intelligent resolution method based on the deep integration of Generative Adversarial Networks(GAN)and Long Short-Term Memory(LSTM).The core innovations of the method are:①constructing a dual-task discriminator architecture that performs both trajectory authenticity discrimination and conflict probability prediction through shared feature representation;②designing a physics-constrained generator that produces diverse resolution trajectories under flight performance constraints and selects the optimal solution via a multi-criteria screening mechanism;③proposing an adaptive loss weight adjustment strategy to dynamically balance multiple objectives such as trajectory reconstruction accuracy,adversarial training stability,and conflict avoidance.Comprehensive experiments based on the TrajAir dataset show that the proposed method achieves a conflict detection accuracy of 93.4%and a resolution success rate of 88%,significantly outperforming conventional geometric rule-based methods.The generated trajectories exhibit small errors,comply with flight performance constraints,demonstrating the real-time capability,accuracy,and decision-making flexibility of the method.This study provides a feasible technical solution for intelligent air traffic management in general aviation,contributing to safer and more efficient low-altitude airspace operations.关键词
通用航空/冲突探测/轨迹生成/生成对抗网络/深度学习Key words
general aviation/conflict detection/trajectory generation/Generative Adversarial Net-works(GAN)/deep learning分类
交通工程引用本文复制引用
陈博,李梓明,徐松涛,叶一龙,柯颖,高峰,王东..基于GAN-LSTM的通用机场冲突探测与智能解脱方法[J].交通运输研究,2026,12(1):70-79,10.基金项目
海南省重大科技计划项目(ZDKJ2021050) （ZDKJ2021050）
