Short-term traffic flow prediction is one of the most significant research topics in traffic engineering. It is instrumental in designing a more modern transport network to manage traffic signals and reduce congestion. Short-term traffic flow is a challenge that a third-world country like Bangladesh is all too familiar with. Like the other cities of Bangladesh, Khulna Metropolitan City is gradually becoming more aware of this situation. The Khulna-Jashore National Highway (N-7), which runs through the city and provides a linear shape, serves as the backbone of the Khulna Metropolitan City traffic flow. This study developed an Artificial Neural Network (ANN) model for the short-term Traffic Flow Prediction on Two-Lane Highway in Khulna Metropolitan City, Bangladesh. Data was collected from March 1, 2021, through June 30, 2021, during 600–900 hours and 1200–1500 hours. Good-quality electronic cameras recorded the vehicles at the full designated length. The regression graphs displayed the network outputs with targets for the training, validation, and test sets. The various speed level parameters for which the fit is reasonable for all data sets, with R values of 0.98426 in each case. The various traffic volume parameters for which the fit is reasonable for all data sets, with R values of 0.96758 in each case. The model's superiority is indicated by its low mean squared error values. This study demonstrated that the neural network has a good prediction effect on specific road traffic flow, which can achieve the goal of short-term prediction and has improved practicability through testing on real traffic data. This study provides an opportunity to provide a suitable alternative for short-term traffic flow forecasting in Khulna Metropolitan City with traffic flow conditions for two-lane undivided highways.


    Access

    Download


    Export, share and cite



    Title :

    An Artificial Neural Network Model for Short-Term Traffic Flow Prediction in Two Lane Highway in Khulna Metropolitan City, Bangladesh


    Contributors:


    Publication date :

    2024




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    The impact of urban street median in pedestrian behavior and traffic flow: Experience from a growing city Khulna, Bangladesh

    Md. Abdul Fattah / Syed Riad Morshed / Syed Yad Morshed et al. | DOAJ | 2021

    Free access


    Assessment of traffic congestion scenario at the CBD areas in a developing city: In the context of Khulna City, Bangladesh

    Md. Asaduzzaman Noor / Sultana Ashrafi / Md. Abdul Fattah et al. | DOAJ | 2021

    Free access

    Short term traffic flow prediction in heterogeneous condition using artificial neural network

    Kumar, Kranti / Parida, Manoranjan / Katiyar, Vinod Kumar | British Library Online Contents | 2015


    Short-Term Traffic Flow Prediction Based on EMD and Artificial Neural Network

    Luo, X. / Niu, G. / Wu, Q. | British Library Conference Proceedings | 2009