In this paper, we study the impact of using a new intelligent vehicle technology on the performance and total cost of a European port, in comparison with existing vehicle systems like trucks. Intelligent autonomous vehicles (IAVs) are a new type of automated guided vehicles (AGVs) with better maneuverability and a special ability to pick up/drop o containers by themselves. To identify the most economical eet size for each type of vehicle to satisfy the port's performance target, and also to compare their impact on the performance/cost of container terminals, we developed a discrete-event simulation model to simulate all port activities in micro-level (low-level) details. We also developed a cost model to investigate the present values of using two types of vehicle, given the identi ed eet size. Results of using the di erent types of vehicles * Co-rst authors. These authors contributed equally to this work. Given the best con guration and eet size as identi ed by the simulation, we use the developed cost model to estimate the total cost needed for each type of vehicle to meet the performance target. Finally, we study the performance of the case study port with advanced real-time vehicle dispatching/scheduling and container placement strategies. This study reveals that the case study port can greatly bene t from upgrading its current vehicle dispatching/scheduling strategy to a more advanced one.

A new class of Intelligent and Autonomous Vehicles (IAVs) has been designed in the framework of Intelligent Transportation for Dynamic Environment (InTraDe) project funded by European Commission. These vehicles which are technologically superior to the existing Automated Guided Vehicles (AGV) in different technical aspects offer more flexibility and intelligence in manoeuver in the area where the logistics operations take place. This includes the ability of pairing/unpairing enabling a pair of 1-TEU (Twenty-foot Equivalent Unit) IAVs join and transport any size between a 1-TEU and a 1-FFE (Forty-foot Equivalent) containers. To accommodate this feature, in this article, we extend the classical mixed integer programming model of AGV scheduling in order to minimize the makespan of operations to transport a set of containers of different size between quay cranes and yard cranes. In particular, a case study on Dublin Ferryport Terminal is carried out. In order to cope with the complexity of the scheduling model, we design a Lagrangian decomposition approach utilized with variable fixing procedure and a primal solution heuristics to obtain high quality solution of instances of the problem.

Governments and legislators all over the world view ports and terminals as vital infrastructure assets as they play a critical role in economic growth by attracting and generating trade. A port that does not have the ability to cope with rapidly advancing technologies will not be in a position to foster the development of the trade sector. Their ability to 'go green' by reducing their carbon footprint and by being more sensitive to environmental considerations is vital to their success.The future is bringing increased demands for greater efficiency and for more sustainable designs in cargo handling technologies. Moreover, the scarcity of land is forcing port companies to realise higher area utilizations.With the arrival of the next generation ultra-large Triple-E vessels carrying 18,000 TEU (twenty foot equivalent unit), it is important to investigate the opportunities to introduce innovation in the development of terminal operations and the logistics chain. The crucial terminal management problem is how to balance the integration of the current technology with the new state of the art technology such as the Intelligent Autonomous Vehicle (IAV). Although the IAV is not exactly new, what makes it different is that it does not require a guidance system such as rails or transponders set into the ground, to reach its destination. Traffic management and space optimization is a problem with the future development of container terminals. The problem can be solved by having a remote 'traffic control centre' directing vehicles to marshalling areas where the containers are handled by IAV's. The challenge is to find innovative solutions to balance service requirements while integrating automated and non-automated cargo handling equipment in container terminals to ensure sustainability, safety and security.

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