郑州大学学报（理学版）2025，Vol.57Issue(6)：58-64,7.DOI:10.13705/j.issn.1671-6841.2024025
基于门架数据的高速公路货车流量短时预测
Short-term Forecast of Expressway Freight Traffic Flow Based on Gantry Data
摘要
Abstract
Highway freight always occupy a large share in the freight system.Compared with other traffic sources,data collected from gantry were more accurate.But the data were difficult to obtain,so the exist-ing forecasting models rarely used gantry data to predict highway freight traffic.To address this issue,a short-term prediction model for highway freight traffic based on gantry data was proposed.Initially,the highway freight data were preprocessed.Then,an integration of attention mechanisms with AGCN was employed to excavate spatial correlations within the data,while ResNet and LSTM were utilized to uncov-er temporal dependencies.Finally,feature fusion was applied to derive the predicted highway freight traf-fic results.By comparative experiments,it was demonstrated that the proposed model exhibited higher ac-curacy in short-term highway freight traffic forecasting compared to baseline models such as LSTM and STNN.关键词
短时流量预测/门架数据/深度学习/残差神经网络/长短期记忆网络Key words
short-time flow prediction/gantry data/deep learning/residual neural network/long short-term memory network分类
信息技术与安全科学引用本文复制引用
田钊,程钰婕,李姝婕,张乾钟,邵凯凯,杨艳芳..基于门架数据的高速公路货车流量短时预测[J].郑州大学学报（理学版）,2025,57(6):58-64,7.基金项目
综合交通运输大数据应用技术交通运输行业重点实验室开放课题(2022B1201) （2022B1201）
河南省高等学校重点科研项目(24A520045) （24A520045）
