Traffic Message Channel Prediction Based on Graph Convolutional Network

被引:2
|
作者
Li, Ning [1 ]
Jia, Shuangcheng [1 ]
Li, Qian [1 ]
机构
[1] Mogo Auto Intelligence & Telemat Informat Technol, Beijing 100009, Peoples R China
关键词
Roads; Correlation; Predictive models; Principal component analysis; Convolution; Task analysis; Covariance matrices; Traffic prediction; PCA; LSTM; PST-GCN; GCN; spatio-temporal correlation; FLOW PREDICTION; GAME; GO;
D O I
10.1109/ACCESS.2021.3114691
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the development of big data, large-scale traffic flow forecasting which is a part of smart transportation has become an increasingly important research direction. Accurate and real-time traffic flow prediction is the key and difficult part of the traffic. The complex spatial topological structure and dynamic traffic flow information in urban roads constitute a changeable spatial correlation, and the daily traffic flow cycle and weekly traffic flow cycle constitute a complex time correlation. For the current mainstream model, there are two main limitations: 1. Most of the existing models only focus on time correlation and ignore spatial correlation. 2. Even if the spatial correlation is concerned, the topological relationship between spaces is not fully considered. This paper proposes a new traffic-flow prediction model, which named Principal Spatio-Temporal Graph Convolution Network (PST-GCN) model, which uses a combination of Principal Component Analysis (PCA), Graph Convolution Network (GCN), and Long Short-Term Memory model (LSTM). Specifically, PCA is used to reduce the dimension of data, GCN is used to learn the network topology of urban roads, LSTM is used to capture the time correlation of traffic flow. By comparing the results of different models, the proposed model is better than the current mainstream models.
引用
收藏
页码:135423 / 135431
页数:9
相关论文
共 50 条
  • [1] Bayesian graph convolutional network for traffic prediction
    Fu, Jun
    Zhou, Wei
    Chen, Zhibo
    [J]. NEUROCOMPUTING, 2024, 582
  • [2] Heterogeneous Modular Traffic Prediction Based on Multilayer Graph Convolutional Network
    Chang, Mengmeng
    Ding, Zhiming
    Zhao, Zilin
    Cai, Zhi
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 25 (07) : 7805 - 7817
  • [3] Optical Network Traffic Prediction Based on Graph Convolutional Neural Networks
    Gui, Yihan
    Wang, Danshi
    Guan, Luyao
    Zhang, Min
    [J]. 2020 OPTO-ELECTRONICS AND COMMUNICATIONS CONFERENCE (OECC 2020), 2020,
  • [4] Prediction of Cellular Network Channel Utilization Based on Graph Convolutional Networks
    Zhu, Rui
    Luo, Xingshuang
    Yao, Jiayi
    Zhu, Xinning
    Zhang, Chunhong
    [J]. 2022 IEEE 33RD ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (IEEE PIMRC), 2022, : 1233 - 1238
  • [5] Network Traffic Prediction Method Based on Multi-Channel Spatial-Temporal Graph Convolutional Networks
    He, Yechen
    Yang, Yang
    Zhao, Binnan
    Gao, Zhipeng
    Rui, Lanlan
    [J]. 2022 IEEE 14TH INTERNATIONAL CONFERENCE ON ADVANCED INFOCOMM TECHNOLOGY (ICAIT 2022), 2022, : 25 - 30
  • [6] Traffic Flow Prediction Model Based on Attention Spatiotemporal Graph Convolutional Network
    Sun, HongXian
    [J]. 2023 3rd International Symposium on Computer Technology and Information Science, ISCTIS 2023, 2023, : 148 - 153
  • [7] Graph Pruning Based Spatial and Temporal Graph Convolutional Network with Transfer Learning for Traffic Prediction
    Jing, Zihao
    [J]. arXiv,
  • [8] Traffic Demand Prediction Based on Multi-dimensional Graph Convolutional Network
    Zeng, Peiying
    Jiang, Liying
    Lai, Yongxuan
    Yang, Fan
    [J]. Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023, 2023, : 996 - 1004
  • [9] Short-term Network-wide Traffic Prediction Based on Graph Convolutional Network
    Chen, Xi-Qun
    Zhou, Ling-Xiao
    Cao, Zhen
    [J]. Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2020, 20 (04): : 49 - 55
  • [10] A Graph Convolutional Method for Traffic Flow Prediction in Highway Network
    Zhang, Tianpu
    Ding, Weilong
    Chen, Tao
    Wang, Zhe
    Chen, Jun
    [J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2021, 2021