The emergence of metaverse applications and services heralds a new era of immersive driving experiences in future vehicular ad hoc networks (VANETs). This unprecedented metaverse-infused driving experience, however, requires high-throughput transmissions for real-time high-quality 360° video streaming, which challenges today's limited bandwidth resources provisioned by wireless communication infrastructure. To this end, this article introduces virtual road, real connection (VRRC), a novel framework for enhancing the metaverse-infused driving experience in VANET through the Internet of Robotic Things (IoRT). In the face of limited bandwidth resources, VRRC effectively addresses the challenge of high-throughput demand from two key perspectives. First, VRRC reduces redundant transmission by implementing a graph neural network (GNN)-based vehicle clustering method for dynamic multicast group formation, taking into account both the geographical status of vehicles and their communication patterns. Second, VRRC aggregates bandwidth resources across various channels by employing a multiagent reinforcement learning (MARL)–based multipath packet scheduling policy to adapt to heterogeneous channel conditions and dynamic vehicular mobility. Extensive experiments with real-world vehicular traces validate the effectiveness of VRRC and demonstrate its outperformance in reducing redundant traffic by 54% and improving overall throughput by 28%. VRRC represents a substantial leap forward in the integration of the metaverse experience into VANET.
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Luan et al. (2024) studied this question.
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