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Open Access Journal Article

Deep Reinforcement Learning for Autonomous Vehicle Navigation

by John Smith 1,*
1
John Smith
*
Author to whom correspondence should be addressed.
ISTI  2021, 22; 3(2), 22; https://doi.org/10.69610/j.isti.20210921
Received: 16 July 2021 / Accepted: 13 August 2021 / Published Online: 21 September 2021
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Abstract

This paper explores the advancements in deep reinforcement learning (DRL) techniques for enhancing the navigation capabilities of autonomous vehicles. With the rapid progress in the field of autonomous driving, there is an increased demand for intelligent navigation systems that can adapt to various road conditions and traffic scenarios. Deep reinforcement learning, which combines the principles of reinforcement learning with deep neural networks, has emerged as a promising approach to address these challenges. The paper presents a comprehensive review of the latest DRL algorithms and their application in autonomous vehicle navigation. It discusses the benefits and limitations of DRL-based navigation systems, highlighting the need for robustness, safety, and efficiency. Furthermore, the paper examines the impact of real-world data integration, sensor fusion, and multi-agent systems on the performance of DRL-based navigation algorithms. Through an extensive analysis of existing literature and case studies, the paper concludes with a set of recommendations for future research directions in the field of DRL for autonomous vehicle navigation.

Keywords: Deep Reinforcement Learning, Autonomous Vehicles, Navigation, Algorithmic Efficiency, Sensor Fusion, Multi-Agent Systems.;
Copyright: © 2021 by Smith. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Smith, J. Deep Reinforcement Learning for Autonomous Vehicle Navigation. Information Sciences and Technological Innovations, 2021, 3, 22. https://doi.org/10.69610/j.isti.20210921
AMA Style
Smith J. Deep Reinforcement Learning for Autonomous Vehicle Navigation. Information Sciences and Technological Innovations; 2021, 3(2):22. https://doi.org/10.69610/j.isti.20210921
Chicago/Turabian Style
Smith, John 2021. "Deep Reinforcement Learning for Autonomous Vehicle Navigation" Information Sciences and Technological Innovations 3, no.2:22. https://doi.org/10.69610/j.isti.20210921
APA style
Smith, J. (2021). Deep Reinforcement Learning for Autonomous Vehicle Navigation. Information Sciences and Technological Innovations, 3(2), 22. https://doi.org/10.69610/j.isti.20210921

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