Smart Logistics Nodes | Connect Automated Transport for Future-Proof Ports and Business Parks
Matteo Brunetti is a PhD student in the department Industrial Engineering & Business Information Systems. (Co)Promotors are prof.dr.ir. M.R.K. Mes and dr.ir. E.A. Lalla from the faculty of Behavioural Management and Social Sciences.
Global freight transport is placing increasing strain on logistics nodes such as ports, business parks, and intermodal terminals. These hubs must manage rising volumes, environmental targets, land scarcity, and operational constraints. Therefore, traditional logistics infrastructures are reaching their limits.
This dissertation was motivated by a fundamental question: “How can logistics nodes evolve to remain resilient, efficient, and sustainable in the face of these challenges?” In seeking answers, this research introduces the Smart Logistics Node, a reimagined logistics hub that integrates digitalization, automation, and collaboration. At the core of this vision is Connected Automated Transport (CAT), which combines autonomous systems with real-time connectivity and data sharing.
This dissertation has two main goals. First, to conceptualize how logistics nodes can use CAT to improve dispatching, truck arrival management, and resource utilization. Second, to develop a simulation framework for evaluating such innovations under realistic conditions. By integrating system modeling, optimization, and data-driven control methods—including reinforcement learning—the dissertation explores how CAT can be implemented in practice, the trade-offs it entails, and its potential benefits. Although grounded in Dutch case studies, the findings provide broader insights for the global shift toward smarter, more resilient logistics systems.
This dissertation is ultimately intended to support policymakers, terminal operators, and industry innovators in making informed decisions about the adoption of emerging technologies—bridging the gap between conceptual innovation and actionable change.
