Self-driving vehicles have the potential to revolutionise society and ease daily lives a little bit. When it comes to designing self-driving cars computer simulation is an essential process. However it can be challenging and time-consuming to create any such simulation programme. This paper makes a proposal about a technique to simulate a vehicle using an online game that is, GTA 5. GTA 5 is a good simulation tool as it already includes a variety of roads, people, and vehicles. OPENCV is used to take the GTA 5 game screen, and Tensorflow was used to analyse each captured image. Hence algorithms for lane recognition, object detection, and collision detection can be written. After these algorithms are developed, vehicles in GTA 5 can be driven using a number of fundamental autonomous driving features, including lane recognition, object detection, and collision avoidance.


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    Titel :

    Lane, Car, Traffic Sign and Collision Detection in Simulated Environment Using GTA-V


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Raj, Jennifer S. (Herausgeber:in) / Perikos, Isidoros (Herausgeber:in) / Balas, Valentina Emilia (Herausgeber:in) / Bharadwaj, Rakhi (Autor:in) / Gajbhiye, Pratham (Autor:in) / Rathi, Atharva (Autor:in) / Sonawane, Atharva (Autor:in) / Uplenchwar, Rucha (Autor:in)

    Kongress:

    International Conference on Intelligent Sustainable Systems ; 2023 ; Tirunelveli, India February 02, 2023 - February 03, 2023



    Erscheinungsdatum :

    2023-06-16


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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