In the context of large cities, the growth in traffic congestion has become a major problem. Static control systems may block emergency vehicles due to traffic congestion. The goal of detecting, forecasting, and reducing traffic congestion is to improve the level of service provided by the transportation system. One of the main issues that automatic way of traffic management plan will address is the current urban traffic congestion. Due to its capability to cope with dynamic behavior over time and with vast numbers of parameters in massive data, neural networks (NN) and machine-learning (ML) techniques are being employed more and more to tackle real-world issues, surpassing analytical and statistical methods. Therefore, deep learning is becoming more relevant for these jobs as access to bigger datasets at greater resolution increases. This study focuses on a critical assessment of the state of the art for the use of Artificial Intelligence in this specific field of Intelligent Transportation Systems. The literature that is now accessible uses a variety of methods to identify and dassify traffic congestion. The conclusions obtained from a review of recent articles using two taxonomic criteria are finally presented.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Machine Learning Applications in Vehicular Traffic Prediction and Congestion Control: A Systematic Review


    Contributors:


    Publication date :

    2022-12-01


    Size :

    458860 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Machine Learning Solutions to Vehicular Traffic Congestion

    Chhatpar, Pavan / Doolani, Nimesh / Shahani, Sumeet et al. | IEEE | 2018


    Optimal Extreme Learning Machine based Traffic Congestion Control System in Vehicular Network

    Kumar Bharti, Rajendra / Suganthi, D. / Abirami, S.K et al. | IEEE | 2022



    Traffic Congestion Prediction Using Categorized Vehicular Speed Data

    Kumar, Manoj / Kumar, Kranti | Springer Verlag | 2022


    Machine learning Smart Traffic Prediction and Congestion Reduction

    Lakshna, A. / Ramesh, K. / Prabha, B. et al. | IEEE | 2021