In this paper, one solution for driver behavioral cloning using deep learning is presented. The aim of this paper is to achieve autonomous driving in simulated conditions. In the simulator, images obtained from a camera mounted in the vehicle mimics the driver's vision, and then the reaction, control of the vehicle. Based on the images from the cameras gained in the manual mode, the neural network is trained using deep learning. Using this trained deep neural network leads to autonomous driving. The driver behavioral cloning algorithm, developed and described in this paper, is based on the NVIDIA convolutional neural network model.


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    Title :

    Driver behavioral cloning using deep learning


    Contributors:


    Publication date :

    2018-03-01


    Size :

    823800 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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