IEEE Transactions on Intelligent Vehicles · 2024 · 15 citations · 27 references
ComputingAutonomous SystemsEducational TechnologyArtificial IntelligenceAutonomous VehiclesVirtual Reality In EducationSimulation-based LearningVirtual TeamsVirtual WorldsImmersive Virtual RealityLarge Language ModelsSpectator ImmersionSpectator ModelSpectator SportsTraining SimulationsVirtual Reality PlatformsVirtual Reality Training Simulations
This letter is the third report from a series of IEEE TIV's decentralized and hybrid workshops (DHWs) on intelligent vehicles for education (IV4E). Autonomous racing serves as a vital platform for nurturing engineering talents among university students, contributing to the development of skills essential for the intelligent vehicle industry. This letter investigates how recent emerging techniques, such as large language models (LLMs) and the Metaverse, can contribute to organizing IV4E-oriented autonomous racing events. Among these DHWs, scholars from diverse fields have collectively explored the integration of LLMs and the Metaverse into autonomous racing for educational purposes. The discussions emphasize the role of Metaverse in creating dynamic and immersive training virtual reality platforms and the role of LLMs in enhancing race commentary and the spectator experience. Within this context, the Metaverse introduces complex scenarios to the racetrack, maintaining suspense about the winning team until a race's final moment. This dynamic feature excites the race and motivates the participating teams to intensify their competition efforts. LLMs facilitate personalized commentary, inspiring spectators to become future participants in these races. Our DHWs highlighted a future in which technology, autonomy, and education intersect, fostering inclusive, educational, and engaging autonomous racing events.
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A Metaverse: Taxonomy, Components, Applications, and Open Challenges
Sangmin Park, Young‐Gab Kim · IEEE Access · 2022 · 1.8K citations · Full text
A Survey on Metaverse: Fundamentals, Security, and Privacy
Yuntao Wang, Zhou Su, Ning Zhang et al. · IEEE Communications Surveys & Tutorials · 2022 · 1.2K citations · Full text