Implementing Autonomous Driving System in a Virtual Environment

Authors

  • Chitran Pokhrel Advanced College of Engineering and Management, Nepal
  • Aayush Khatiwada Advanced College of Engineering and Management, Nepal

DOI:

https://doi.org/10.3126/aet.v2i01.50448

Keywords:

AlexNet, ANN, Back-propagation, CNN, OpenCV, Q-learning, Reinforcement learning, ROI

Abstract

The automation in the current times has become the growing hot topic for discussion around the globe. The growth of the machine learning and the development of new techniques have made the automation one of the major topics of research among the scientist around the world. It might be too costly to observe the accuracy and precision of the algorithm in the real world; hence the virtual environments are used to test the algorithms before the real world tests with the technique are done. This work focuses on one of the various ways of developing the autonomous driving system using Convolutional Neural Networks (CNN) in a gaming environment.

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Author Biographies

Chitran Pokhrel, Advanced College of Engineering and Management, Nepal

Department of Computer Engineering

Aayush Khatiwada, Advanced College of Engineering and Management, Nepal

Department of Computer Engineering

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Published

2022-12-31

How to Cite

Pokhrel, C., & Khatiwada, A. (2022). Implementing Autonomous Driving System in a Virtual Environment. Advances in Engineering and Technology: An International Journal, 2(01), 77–85. https://doi.org/10.3126/aet.v2i01.50448

Issue

Vol. 2 No. 01 (2022)

Section

Articles

License

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