An innovative approach, IRTPML, aims to enhance both routing efficiency and road safety in vehicular networks. The proposed model integrates geometric particle swarm optimization for routing and convolutional neural networks (CNNs) for traffic accident prediction, leveraging vehicle-to-vehicle communication. By dynamically adapting routing paths based on network conditions and issuing early warnings for potential traffic accidents, the IRTPML model demonstrates significant improvements in energy efficiency, energy consumption, average delay, network throughput, and data delivery ratio compared to existing protocols. Extensive simulations and comparative performance analysis validate the efficacy of the proposed model, suggesting its promising potential for optimizing VANETs and enhancing transportation safety.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Improved Routing Model with Traffic Accident Prediction Using Machine Learning in Vehicular Communication


    Beteiligte:
    Kalpana, D.Divya (Autor:in) / Thenmozhi, P. (Autor:in) / Jaber, Ala H. (Autor:in) / Babu, SK.Anjaneyulu (Autor:in) / Chadge, Rajkumar (Autor:in) / Sundaram, Siva (Autor:in)


    Erscheinungsdatum :

    27.03.2025


    Format / Umfang :

    817272 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Traffic Accident Risk Prediction Using Machine Learning

    Banerjee, Kakoli / Bali, Vikram / Sharma, Aanchal et al. | IEEE | 2022



    Traffic prediction with deep learning for vehicular communication network

    Wang, Jin / Liu, Peixin | British Library Conference Proceedings | 2022


    Traffic Accident Detection Using Machine Learning Algorithms

    Sharma, Swati / Harit, Sandeep / Kaur, Jasleen | Springer Verlag | 2022


    Traffic accident analysis using machine learning paradigms

    Chong, M. / Abraham, A. / Paprzycki, M. | Tema Archiv | 2005