Deep Reinforcement Learning Based Intelligent Approach to Channel Allocation for Effective Communications in Vehicle Platoon Systems

Vehicle platoons are the applications that provide greener, safer, faster, and economical transport as part of modern intelligent transportation systems. The advent of deep learning and reinforcement learning made it possible to address standard communication problems effectively using data-driven techniques. In this short research paper, we discuss the realm of vehicular platoon where deep and reinforcement learning can be applied and requires attention. We also propose an application of deep reinforcement learning to solve the resource allocation problem intelligently, addressing the specific needs of vehicle platoons. This application should pave the way for using deep reinforcement learning implements in vehicle platoon communications per se. We also discuss the scope for improvements required to well adopt deep reinforcement learning in this regime.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/cict64037.2024.10899647
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.00
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Deep Reinforcement Learning Based Intelligent Approach to Channel Allocation for Effective Communications in Vehicle Platoon Systems

B. P Mishra, Nitin Singh Rajput, Santosh Kumar Satapathy
Traffic control and management
article

Deep Reinforcement Learning Based Intelligent Approach to Channel Allocation for Effective Communications in Vehicle Platoon Systems

B. P Mishra, Nitin Singh Rajput, Santosh Kumar Satapathy
article en

Abstract

Vehicle platoons are the applications that provide greener, safer, faster, and economical transport as part of modern intelligent transportation systems. The advent of deep learning and reinforcement learning made it possible to address standard communication problems effectively using data-driven techniques. In this short research paper, we discuss the realm of vehicular platoon where deep and reinforcement learning can be applied and requires attention. We also propose an application of deep reinforcement learning to solve the resource allocation problem intelligently, addressing the specific needs of vehicle platoons. This application should pave the way for using deep reinforcement learning implements in vehicle platoon communications per se. We also discuss the scope for improvements required to well adopt deep reinforcement learning in this regime.

Pandit Deendayal Energy University (IN)
Openalex Percentile: Top 65%
Traffic control and management
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