Quantum Long Short-Term Memory-Assisted Optimization for Efficient Vehicle Platooning in Connected and Autonomous Systems

Vehicle platooning, especially when dedicated to carrying goods, represents a forward-looking approach to optimizing logistics and freight transportation using autonomous vehicles. In this study, we propose to employ Quantum Long Short Term Memory (QLSTM) models to predict the vehicle dynamics of a...

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Bibliographic Details
Main Authors: Mahzabeen Emu, Taufiq Rahman, Salimur Choudhury, Kai Salomaa
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of the Computer Society
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10783047/
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