BEIJING, June 20,
2024 /PRNewswire/ -- Imagine a world where augmented
reality systems project a digital avatar onto your vehicle's
dashboard, guiding you in real time. This integration of vehicular
navigation within the Metaverse combines the digital and physical
worlds in ways that were previously not possible, creating
opportunities for richer, more interactive experiences for drivers
and passengers.
To ensure seamless communication between the servers and the
vehicles, researchers from Nanyang
Technological University, Singapore
University of Technology and Design, Guangdong University of Technology, Army
Engineering University of PLA, and the National Natural Science
Foundation of China have proposed
a task migration system that intelligently determines the optimal
time to move tasks between the vehicle and external servers. Their
paper was published in the 2024 Issue 2 of the IEEE/CAA Journal
of Automatica Sinica.
"The mobility of vehicles poses a significant challenge for
unmanned aerial vehicle-assisted vehicular Metaverses to ensure the
continuity of avatar services, especially when the vehicles leave
coverage of their host edge servers. We propose a framework to
address this issue. By using advanced computer algorithms, we can
quickly and reliably determine the best server to handle each task,
much like how a smart assistant would choose the best route based
on current traffic conditions," says Zehui Xiong, the corresponding author of the
study and an Assistant Professor at Singapore
University of Technology and Design.
The researchers integrated transformers into a multi-agent
proximal policy optimization (MAPPO) algorithm. In this process,
the digital avatar or the agent migrates a task, based on its
observations, such as its location, speed, traffic conditions, and
available servers. To further optimize the decision-making, the
transformer converts the actions and observations of multiple
agents into sequences.
"This approach allows each vehicle to dynamically decide
whether to perform an avatar task pre-migration, thereby reducing
the average latency of all vehicles and improving the quality of
avatar services," says Dr. Xiong. To ensure the security
of communications, the transactions between the vehicle and the
external server are recorded using Smart Contracts deployed on
blockchains.
The researchers found that the method outperforms traditional
reinforcement learning approaches by approximately 2% and reduces
avatar task execution latency by around 20%. Thus, the proposed
method paves the way for vehicular services in the Metaverse, with
broad potential applications.
"This research could lead to widespread adoption of highly
interactive and immersive vehicular services, improve road safety
through better navigation aids and real-time updates, and pave the
way for more sustainable and scalable smart city
infrastructures," says Dr. Xiong.
You can hear directly from the researchers in this podcast.
Reference
Authors: Jiawen Kang1,
Junlong Chen1, Minrui
Xu2, Zehui
Xiong3, Yutao Jiao4, Luchao
Han5, Dusit Niyato2, Yongju Tong1, and Shengli Xie1
Title of original paper: UAV-Assisted Dynamic Avatar Task
Migration for Vehicular Metaverse Services: A Multi-Agent Deep
Reinforcement Learning Approach
Journal: IEEE/CAA Journal of Automatica Sinica
DOI: https://doi.org/10.1109/JAS.2023.123993
Contact:
Yan Ou
+86 10 82544459
379386@email4pr.com
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SOURCE IEEE/CAA Journal of Automatica Sinica