Today, Artificial intelligence has brought in major developments in the field of technology. The evolution of technology has made it possible to build a fully autonomous driverless vehicle. According to the recent data, a vast majority of road accidents occur due to human errors or spontaneous traffic resulting in a lack of response time. The problem can be solved with the help of automated systems. This paper proposes a working prototype of a self-driving car that is capable of driving in indigenous tracks like curved tracks, straight tracks, or curvilinear tracks. The proposed system uses image processing as well as neural networks for the path planning and identification of road signs according to the regulations; to ease the lives of the drivers and automate the driving process.


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    Titel :

    Self Driving Car using Neural Networks


    Beteiligte:
    Kalathil, Divit (Autor:in) / Mandal, Vivek Kumar (Autor:in) / Gune, Archis (Autor:in) / Talele, Kiran (Autor:in) / Chimurkar, Priya (Autor:in) / Bansode, Manisha (Autor:in)


    Erscheinungsdatum :

    2022-05-09


    Format / Umfang :

    1127156 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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