This paper proposes a new traffic flow prediction method, which combines the grey relational analysis method with the long and short term memory network, and uses Python language to build the model. Taking California expressway network PEMS data set as the research object, the speed and occupancy of target detection points, as well as the traffic flow of surrounding detection points as influencing factors, are input into the traffic flow prediction model, so as to take into account the influence of multidimensional spatiotemporal factors on the prediction model. Specifically, grey correlation analysis GRA is used as the correlation analysis method of each detection point.[1]-[4] By eliminating the traffic data with little or no correlation to the traffic flow of the target detection point, the data dimension of the input of the prediction model is reduced, and the efficiency of model training and prediction is improved. [5]-[7] Then, constructs a traffic flow prediction model based on stacked LSTM using several LSTM networks to capture the spatiotemporal characteristics of road traffic conditions that are strongly coupled in multidimensional traffic data types and massive data, thereby improving the effectiveness and accuracy of traffic state prediction.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Short-time traffic flow prediction based on GRA-SLSTM model


    Contributors:

    Conference:

    International Conference on Smart Transportation and City Engineering (STCE 2023) ; 2023 ; Chongqing, China


    Published in:

    Proc. SPIE ; 13018


    Publication date :

    2024-02-14





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Short-Time Traffic Flow Prediction with ARIMA-GARCH Model

    Chen, C. / Hu, J. / Meng, Q. et al. | British Library Conference Proceedings | 2011


    Event-Based Short-Term Traffic Flow Prediction Model

    Head, K. L. / National Research Council / Transportation Research Board | British Library Conference Proceedings | 1995


    Event-Based Short-Term Traffic Flow Prediction Model

    Head, K.Larry | Online Contents | 1995


    Short-time traffic-flow combination prediction method

    YANG CHUNXIA / FU YIQIN / WU WENLU et al. | European Patent Office | 2015

    Free access

    Short-term traffic flow prediction using time-varying Vasicek model

    Rajabzadeh, Yalda / Rezaie, Amir Hossein / Amindavar, Hamidreza | Elsevier | 2016