Autonomous Vehicles: Applications of Deep Reinforcement Learning

Author(s)	Chinmay Kale
Country	India
Abstract	This research paper offers a concise exploration into the pivotal role played by deep reinforcement learning in propelling advancements in both perception and decision-making aspects of autonomous vehicles. Through the fusion of deep learning and reinforcement learning techniques, we delve into how these methodologies synergistically contribute to augmenting the navigational proficiency of autonomous vehicles amidst intricate and dynamically changing environments. With a focus on a streamlined presentation, this paper provides a succinct yet insightful overview of various perception algorithms utilized by autonomous vehicles, emphasizing object detection, semantic segmentation, and LiDAR-based techniques.
Keywords	deep reinforcement learning, autonomous vehicles, perception algorithms, decision-making, navigation, real-time processing, deep learning, reinforcement learning, ethical considerations, case studies.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 1, January-February 2024
Published On	2024-02-28
Cite This	Autonomous Vehicles: Applications of Deep Reinforcement Learning - Chinmay Kale - IJFMR Volume 6, Issue 1, January-February 2024. DOI 10.36948/ijfmr.2024.v06i01.13792
DOI	https://doi.org/10.36948/ijfmr.2024.v06i01.13792
Short DOI	https://doi.org/gtktjc

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