Making autonomous driving a safe, feasible, and better alternative is one of the core problems for researchers from academia and industry. The development of autonomous cars in a real-world setting poses many challenges. This paper presents a low-cost, small-scale self-driving automobile model called ‘Zumee’, powered by a deep convolutional neural network. Zumee offers synchronised image data collection using a camera for deep learning models. The proposed model is experimentally validated using an Nvidia Jetson TX2 board as the onboard computer. Data augmentation, transfer learning, and neural networks are used to train the prototype model. Specifically, a convolutional neural network (CNN) model is trained using data from various scenarios. A robust dataset is generated by augmenting the images obtained using a camera to accommodate multiple environments. The prototype model is trained to imitate the policies used by a human supervisor to drive a robot car autonomously in a closed environment. The proposed prototype could be used as a base for more advanced driverless autonomous vehicles or for educational purposes as an economical prototype model.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An Autonomous Vehicle Prototype for Off-Road Applications based on Deep Convolutional Neural Network


    Beteiligte:
    Ullah, Rahmat (Autor:in) / Asghar, Ikram (Autor:in) / Griffiths, Mark G (Autor:in) / Evans, Gareth (Autor:in) / Dennis, Rory (Autor:in)


    Erscheinungsdatum :

    27.10.2022


    Format / Umfang :

    971246 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Road Identification using Convolutional Neural Network on Autonomous Electric Vehicle

    Hermawan, Markus / Husin, Zaenal / Hikmarika, Hera et al. | IEEE | 2021


    Deep convolutional neural network based autonomous drone navigation

    Amer, Karim / Samy, Mohamed / Shaker, Mahmoud et al. | SPIE | 2021


    Traffic Sign Detection for Navigation of Autonomous Car Prototype using Convolutional Neural Network

    Ikhlayel, Mohammed / Iswara, Adre Johan / Kurniawan, Arief et al. | IEEE | 2020


    Convolutional Neural Network Based on Self-Driving Autonomous Vehicle (CNN)

    Babu Naik, G. / Ameta, Prerit / Baba Shayeer, N. et al. | Springer Verlag | 2022


    Road traffic target tracking method based on deep convolutional neural network

    LI DECHENG / DONG DONG / WU XIAOFENG et al. | Europäisches Patentamt | 2022

    Freier Zugriff