The main motivation of this study is to take full advantage of the capabilities of neural networks techniques and dissipative system theory to design a powerful state feedback real-time controller for an over-saturated intersection. The developed controller makes a realtime decisions about whether to increase or decrease (and how much) the current green time in order to get out the over-saturation situation. First, a discrete-time model that describes the evolution of the queue lengths at signalized intersection is presented. Then, the control problem is formulated and solved by using the dissipative system theory. Moreover, the proposed intersection controller needs to be provided with a real-time input traffic flow data. To achieve this goal, we use the artificial neural networks technique as input traffic flow data predictor. The results of the simulations indicate that our control strategy guarantees a high degree of control benefit.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A note on artificial intelligence techniques and dissipativity-based approach in traffic signal control for an over-saturated intersection


    Contributors:


    Publication date :

    2011


    Size :

    6 Seiten, 7 Bilder, 2 Tabellen, 15 Quellen




    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English




    Intersection Traffic Signal Utilizing Artificial Intelligence

    LIM YOUNG HAN / KIM HAE JONG | European Patent Office | 2021

    Free access

    Intersection Traffic Signal Utilizing Artificial Intelligence

    European Patent Office | 2022

    Free access

    Intersection Traffic Signal Utilizing Artificial Intelligence

    LIM YOUNG HAN / KIM HAE JONG | European Patent Office | 2021

    Free access

    Artificial intelligence techniques for urban traffic control

    Bielli, Maurizio / Ambrosino, Giorgio / Boero, Marco et al. | Elsevier | 1991


    Intersection Traffic Jam Prediction System and Method based on Artificial Intelligence Technology

    PARK SEUNG MIN / LEE SEUNG YOUNG / SEO BU ONE et al. | European Patent Office | 2023

    Free access