Digital Twins in Freight and Supply Chains

This chapter examines how digital twins improve freight and supply chain performance by linking real-time operational data with adaptive models for planning and control. It traces the shift from static simulations to continuously synchronized twins and presents a practical framework that covers data acquisition, integration platforms, analytics engines, and visualization tools. Applications span urban delivery, ports, intermodal corridors, and warehousing, with attention to disruption response, scenario testing, and emissions management. The chapter explains integration with Intelligent Transport Systems (ITS), including artificial intelligence (AI)-driven routing, blockchain, big data analytics, Internet of Things (IoT) sensors, fifth generation and edge computing, Geographic Information Systems (GIS), autonomous systems, and cloud-based collaboration. Case examples and a conceptual predictive freight flow framework illustrate pathways from pilots to scalable operations. Implementation challenges and future directions are outlined, positioning digital twins as a core enabler of resilient and low emission freight logistics.