Efficient traffic management plays a crucial role in ensuring smooth and uninterrupted movement of vehicles, reducing traffic congestion, and improving transportation systems. One significant aspect of traffic management is traffic signal optimization. Rather than traditional fixed-time signal light systems, dynamic adaptive systems can be employed to continuously monitor traffic patterns in real-time and adjust signal light timings accordingly. To address traffic congestion problems, this paper proposes a traffic management system that leverages existing V2V (vehicle to vehicle) and V2I (vehicle to infrastructure) communication. The proposed system is an IPC (Inter Process Communication)-based system with multiple clients, servers, and proxies that can achieve data collection and processing on a global scale. Unlike other intelligent traffic systems that predict traffic, the proposed system takes a more straightforward and effective approach, dynamically adapting based on real-time traffic conditions. The green and red light times are determined based on the number of vehicles crossing or waiting at the junction.


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    Titel :

    Adaptive Traffic Management System Based on Real-Time Traffic Conditions


    Weitere Titelangaben:

    Lect.Notes Computer


    Beteiligte:
    Nguyen, Ngoc Thanh (Herausgeber:in) / Chbeir, Richard (Herausgeber:in) / Manolopoulos, Yannis (Herausgeber:in) / Fujita, Hamido (Herausgeber:in) / Hong, Tzung-Pei (Herausgeber:in) / Nguyen, Le Minh (Herausgeber:in) / Wojtkiewicz, Krystian (Herausgeber:in) / Gherghinescu, Mihai (Autor:in) / Ivașcu, Todor (Autor:in) / Ștefănigă, Sebastian (Autor:in)

    Kongress:

    Asian Conference on Intelligent Information and Database Systems ; 2024 ; Ras Al Khaimah, United Arab Emirates April 15, 2024 - April 18, 2024



    Erscheinungsdatum :

    16.07.2024


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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