Building Metaverse for Vehicles and Transportation Systems: Efficiency, Fairness, and Privacy
Metaverse, envisioned as a blended reality-virtual realm, became popular in 2021. Building metaverse for vehicles and transportation systems with extended reality technologies can provide an immersive user experience for drivers and passengers. However, realizing a seamless metaverse experience in such a dynamic mobile environment faces numerous challenges, such as efficiency, privacy, and fairness. This talk will discuss several recent studies to elaborate on a collaborative transportation metaverse system toward efficient cooperative perception, privacy-preserved learning volumetric service, and fairness-guaranteed Augmented Reality service. Finally, the talk will be concluded with future directions of the vehicular metaverse.
Dr. Zhou was an EU Marie-Curie ESR and received his PhD from University of Helsinki, Finland in 2020. After working there as a PostDoc fellow for one year, he joined USTC as a research associate professor in 2021. His research interests include connected vehicles, federated learning, and metaverse. He has published first-author papers in top venues including Ubicomp, TITS, and TVT. He has served as a PC member for various top conferences such as AAAI and IJCAI, invited reviewer for TWC, TITS, IEEE Network, Springer Computing, etc., and SI editor for IEEE Network. He’s also a contributor to the top traffic open-sourced simulator, FLOW, and a core member of the mobile team in the top federated learning open-sourced community, Openmined.