Metaverse-Enabled Intelligence for Open-Terrain Field Vehicle Fleets: Leveraging Parallel Intelligence and Edge Computing

Abstract

Open-terrain field vehicle (OTFV) fleets, including mining trucks, construction machinery, and agricultural machinery, often encounter significantly more intricate scenarios and unique challenges than road vehicles. Enhancing the intelligence level of OTFV fleets can significantly enhance their operational effectiveness and improve energy efficiency. This perspective paper introduces a metaverse-enabled framework to improve the intelligence levels of OTFV fleets. The metaverse-enabled framework consists of the parallel intelligence-based vehicle fleet control and edge computing-based vehicle dynamics control levels. We first delve into the framework's specifics, covering open-terrain field metaverse, parallel intelligence, edge computing, and human-vehicle cooperation. We further discuss critical issues such as artificial general intelligence (AGI) enabled large control models, vehicle teleoperation, communication privacy, and edge scenario engineering. Additionally, we provide a detailed account of edge computing and integrated domain control within the vehicle dynamics control level, illustrating the interactions among human drivers, domain controllers, vehicle systems and open-terrain field metaverse. Ultimately, the proposed framework can potentially empower intelligence to OTFV fleets and other equipment clusters with complicated system compositions and challenging missions in complex environments.