This article investigates the use of artificial intelligence, particularly artificial neural networks (ANNs), to enhance road safety by refining lateral stability and trajectory tracking in autonomous driving systems. ANNs are utilized as control models to optimize the performance of these safety systems. The study employs rigorous methodologies for data collection, neural network training, and thorough testing and validation to evaluate the efficacy of these controllers. The primary goal is to compare the performance of ANN-based controllers with that of established automotive simulation software like Carsim, focusing specifically on metrics related to stability and efficiency. Numerical simulations confirm the validity and effectiveness of the proposed methods, showcasing how AI-driven control systems can significantly improve road safety in autonomous driving scenarios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Lateral Control for Autonomous Vehicles Utilizing an ANN-Based Controller


    Beteiligte:


    Erscheinungsdatum :

    17.10.2024


    Format / Umfang :

    1120745 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    LATERAL CONTROLLER FOR AUTONOMOUS VEHICLES

    WENGERT NICOLAI / KUEHNLE FLORIAN | Europäisches Patentamt | 2025

    Freier Zugriff

    Lateral control of autonomous vehicles based on fuzzy logic

    Wang, Xinyu / Fu, Mengyin / Ma, Hongbin et al. | Tema Archiv | 2015


    Sliding Mode Based Robust Lateral Control for Autonomous Vehicles

    Bhoi, Shiv Charan / Swain, Subrat Kumar | IEEE | 2021



    Cascade Architecture for Lateral Control in Autonomous Vehicles

    Pérez, J / Milanés, V / Onieva, E | IEEE | 2011