电子学报2025，Vol.53Issue(1)：141-150,10.DOI:10.12263/DZXB.20221308
基于双图卷积机制的数字孪生交通流预测
Traffic Flow Prediction of Digital Twin Based on Two-Graph Convolution Mechanism
摘要
Abstract
The improvement of urban digitalization has generated a large amount of data.Through the integrated anal-ysis of traffic flow data and weather data,urban traffic congestion caused by various weather conditions can be effectively alleviated.However,in the existing traffic flow prediction algorithms,the potential spatial relationship in the traffic flow has not been fully considered,and the prediction errors caused by external factors such as weather are ignored,which great-ly affects the accuracy of the prediction.In response to the above problems,this paper proposes a digital twin traffic flow prediction method TCM-DTFP(Two-graph Convolution Mechanism-based Digital twin flow Prediction)based on the dou-ble-graph convolution mechanism.The algorithm builds an augmented matrix that integrates traffic flow features and weath-er features,adds weather features to traffic flow data,avoids the impact of complex weather conditions on traffic flow pre-diction,and improves the robustness of the algorithm;at the same time in order to improve the algorithm's ability to capture the spatial correlation of traffic flow,a two-graph convolution mechanism based on TCN(Temporal Convolutional Net-works)is proposed to comprehensively consider the dynamic interaction between temporal correlation,spatial correlation and regional flow in traffic influence of flow.Finally,extensive experiments on two real datasets,TaxiBJ and PeMSD4,demonstrate the effectiveness of our method.关键词
交通数字孪生体/时空相关性/时间卷积网络/双图卷积机制/交通流预测Key words
traffic digital twin/spatio-temporal correlation/temporal convolutional networks/two-graph convolu-tion mechanism/traffic flow prediction分类
信息技术与安全科学引用本文复制引用
胡春华,曾萼岚,荣辉桂..基于双图卷积机制的数字孪生交通流预测[J].电子学报,2025,53(1):141-150,10.基金项目
国家自然科学基金(No.72072053,No.91846301) （No.72072053,No.91846301）
国家重点研发计划(No.2021YFC3340403) National Natural Science Foundation of China(No.72072053,No.91846301) （No.2021YFC3340403）
National Key Research and Development Program of China(No.2021YFC3340403) （No.2021YFC3340403）
