In intelligent transportation system (ITS), accurate and real-time prediction of short-term multi-lane traffic flow with existing traffic data is an important part of urban traffic planning, traffic management and control. The data generated in the process of vehicle driving has the cooperative characteristics of multi-source, space-time and dynamic. Combining the data with high-performance computing or cloud computing, a new space-time information framework is designed, which is of great significance for the analysis and prediction of traffic flow, as well as intelligent traffic management, service and decision-making. This paper analyzes the statistical characteristics of urban road traffic flow from the two dimensions of time and space through the spatial-temporal correlation between multi-lane short term traffic flow in single observation point and multi observation points. We constructed a data fusion powered bi-directional long short term memory (DFBD-LSTM) model for individual lane and aggregate traffic flow, then used this model to predict multi-lane short term traffic flow. By taking individual lane traffic flow and aggregate traffic flow as different variables, the model produces more accurate predictions, which can better guide people to travel, alleviate the congestion of urban road traffic network to a certain extent, and improve the utilization rate and transportation efficiency of traffic road.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Data Fusion Powered Bi-Directional Long Short Term Memory Model for Predicting Multi-Lane Short Term Traffic Flow


    Contributors:
    Xing, Lumin (author) / Liu, Wenjian (author)


    Publication date :

    2022-09-01


    Size :

    2015676 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    A Short-Term Traffic Flow Prediction Method Based on Long Short-Term Memory Network

    Ci, Yusheng / Xiu, Gaoqun / Wu, Lina | Springer Verlag | 2018


    A Short-Term Traffic Flow Prediction Method Based on Long Short-Term Memory Network

    Ci, Yusheng / Xiu, Gaoqun / Wu, Lina | British Library Conference Proceedings | 2019