Cognitive digital twins for freight parking management in last mile delivery under smart cities paradigm

This paper examines the Freight Parking Management Problem (FPMP) of last-mile delivery within the context of Smart Cities where objects are managed by Digital Twins. Specifically, we investigate how Cognitive Digital Twins - Digital Twins with augmented semantic capabilities - can enhance real-time knowledge of parking connectivity to optimize logistics operations planning and urban resource allocation. We present a four-layer architectural framework to integrate individual logistics objects and systems into Smart Cities at a semantic level, with underlying enabling technologies and standards including Property Graph, Web Ontology Language (OWL), and Web of Things. Next, we conduct a case study of parcel delivery in Paris using a real-life Digital Twins platform called Thing in the future (Thing'in) by Orange France, coupled with an agent-based simulation model on AnyLogic, to demonstrate a real-world application of our approach. The results suggest that semantics-enabled Digital Twins connectivity can increase the comprehensive understanding of the delivery environment and enhance cooperation between heterogeneous systems, ultimately resulting in improved logistics efficiency, reduced negative externalities, and better utilization of resources. Furthermore, this work showcases potential new business services for logistics service providers and provides managerial insights for city planners and municipal policymakers. An actual mobile application prototype is presented to showcase the applicability of the work.