TRACE: a Reference Architecture for Intelligent Logistics Operations in B5G Networks

As supply chains grow increasingly complex and demand for autonomous delivery solutions rises, traditional logistics systems struggle with real-time coordination requirements across multiple transportation modes. The TRACE Reference Architecture (RA) addresses these challenges through a telecommunications-aware design that integrates multimodal transportation systems with advanced network capabilities. Following a layered structure, the proposed RA incorporates user interfaces, application services, data management mod-ules, and physical infra-structure components, fostering real-time decision-making and coordination across lo-gistics stakeholders. The architecture also leverages edge computing, distributed intelligence, and blockchain technologies to ensure secure data exchange while supporting autonomous vehicles (e.g., ground vehicles, drones) as part of multi-modal logistics operations. We demonstrate the architecture's versatility through three distinct implementation scenarios in Italy, Slovenia, and Greece, showcasing different network configurations including 5G Stand-Alone, Non-Stand-Alone, and Vehicle-to-Vehicle communications that sup-port autono-mous delivery, platooning, and multimodal transport coordination. This paper illustrates how the TRACE RA provides a scalable foundation for next-generation logistics that balances operational efficiency with security and privacy requirements in the emerging B5G ecosystem.