Traditional traffic signal controls at intersections are ineffective that causes traffic congestion, time wasting, and environmental problems. This paper proposes an intersection traffic light management system that incorporates machine learning technique with the traditional traffic light management system to solve the above challenges. To tackle traffic congestion and waiting time problems, Q learning algorithm is used as the reinforcement learning to choose new action. Action states include various traffic signal phases that are important in generating in realistic control mechanism. In this work, SUMO open source traffic simulator is used to construct realistic traffic intersection settings and the intersection Discretized Representation method is applied to get environment state and to calculate reward. Then, experience replay technique is used to enable reinforcement learning agent to memorize and reuse past experience. The results show that the proposed traffic system outperforms traditional traffic system in Mandalay city. The waiting time reduced 3 times compared with the traditional traffic control.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Analysis of Intersection Traffic Light Management System in Mandalay City


    Contributors:


    Publication date :

    2020-11-04


    Size :

    2727231 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Electric tramway in Mandalay

    Engineering Index Backfile | 1904


    The Mandalay-Kunlon railway

    Wagstaff, Wynan E. | Engineering Index Backfile | 1899


    Electric tramways in Mandalay

    Engineering Index Backfile | 1904


    Air Mandalay: The ATR72 in the land of pagodas

    Bloch, André | Online Contents | 1997


    Mandalay Bay People Mover: Safe Operations for 10+ Years

    Mori, J. David / Sandoval, Jose | ASCE | 2011