Urban areas worldwide grapple with the persistent issue of traffic management. Various intelligent techniques has emerged to tackle this problem, but they often rely on costly traffic lights and struggle with emergency situations. This research introduces three innovative: (i) Deep Mutual Exclusion Algorithm based on Single Instruction (D-MEASIR), (ii) D-Mutual Exclusion Algorithm based on optimal path (D-MEAPRI), and (iii) Deep Mutual Exclusion Algorithm based on Multi-Agent Systems (D-MEAMAS). These algorithms facilitate management within a group through a queue structure using traffic prediction dataset, employing external elements like routers for internal communication. Beyond presenting experimental and simulation outcomes, the article conducts a comprehensive statistical analysis, comparing the efficiency of D-MEASIR, D-MEAPRI, and D-MEAMAS with existing alternatives. Finally, these algorithms demonstrate remarkable efficiency while maintaining a CC of O(n) for accessing critical sections.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Revolutionizing Urban Traffic Management: IoT-Driven Algorithms for Intelligent Transportation Systems


    Weitere Titelangaben:

    Int. J. ITS Res.


    Beteiligte:


    Erscheinungsdatum :

    01.08.2025


    Format / Umfang :

    28 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    REVOLUTIONIZING SPACE TRAFFIC MANAGEMENT

    Wilhelm, Claire | TIBKAT | 2021




    Revolutionizing Urban Mobility: YOLO D-NET-Based AIoT Solutions for Sustainable Traffic Management

    Islam, Md. Ashraful / Islam, Md. Atiqul / Sujana, Faiza Mollic et al. | Springer Verlag | 2024