铁道运输与经济2026，Vol.48Issue(3)：59-67,9.DOI:10.16668/j.cnki.issn.1003-1421.20251021002
基于时空注意力机制的GCN-LSTM地铁短时OD客流预测方法
Short-Term OD Passenger Flow Prediction Method for Subway Systems Based on Spatio-Temporal Attention Mechanism and GCN-LSTM
摘要
Abstract
Under subway network operation conditions,passenger flow exhibits highly complex spatio-temporal dynamics.Accurate short-term origin-destination(OD)passenger flow prediction is a fundamental requirement for transportation organization optimization and congestion mitigation.However,existing prediction methods still show limited capability in joint spatio-temporal dependency modeling of passenger flow.To address this issue,this paper proposed a novel short-term OD passenger flow prediction model.It introduced a spatio-temporal attention mechanism,and deeply integrated graph convolutional networks(GCN)-long short-term memory networks(LSTM)modeling advantages.The model adaptively assigned historical time-step importance and dynamically identified key stations or regions influencing target OD pairs.This allowed for a more precise capture of the nonlinear spatio-temporal passenger flow propagation in complex subway networks.Validation was performed using real subway network data.The results show that the proposed spatio-temporal attention GCN-LSTM model significantly improves prediction accuracy compared with baseline models.Spatio-temporal passenger flow fluctuations are captured more accurately.This provides reliable data support and a decision-making basis for subsequent fine-grained passenger flow control,capacity allocation,and collaborative optimization in subway network systems.关键词
网络化/地铁/短时OD客流预测/时空注意力机制/GCN-LSTM模型Key words
Network/Subway/Short-Term OD Passenger Flow Prediction/Spatio-Temporal Attention Mechanism/GCN-LSTM Model分类
交通工程引用本文复制引用
蔡梦影,张淼,丁怡,王兵,陈钉均,卢广志..基于时空注意力机制的GCN-LSTM地铁短时OD客流预测方法[J].铁道运输与经济,2026,48(3):59-67,9.基金项目
国家重点研发计划课题(2022YFB4300502) （2022YFB4300502）
四川省科技创新人才项目(2024JDRC0020) （2024JDRC0020）
四川省科技计划项目(2025YFHZ0328) （2025YFHZ0328）
广州市重点研发计划项目(202206030007) （202206030007）
中国铁路上海局集团有限公司科研计划课题(20.25037) （20.25037）
