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The gradual commercialization of entirely autonomous vehicles is expected to bring numerous benefits, such as structural transformation in the industry. Specifically, in maritime transportation, automobile terminals that import and export finished autos are seen to transform their current loading system into a CAV (connected automated vehicle)-loading system to accommodate autonomous vehicles. In this study, the impact of introducing a CAV-loading system to a roll-on, roll-off (RORO) ports was investigated. Simulation models were developed to test the performance of the terminal with the CAV-loading system. Then, a cost model was developed to determine the economic benefits of the CAV-loading system. The results in this study revealed that operating costs were reduced by 90%, while terminal operations were significantly improved. In addition, the study revealed that using the CAV-loading system resulted in a 12% reduction in CO2 emissions compared to that using the current loading system. The originality of this study lies in its transformative potential for an industry that heavily relies on human labor and has limited mechanization and automation. This study provides significant implications for incorporating autonomous vehicles in planned automobile terminal operations. [ABSTRACT FROM AUTHOR]

Despite the many advantages of containerization for goods transportation, the management of empty containers is a major disadvantage, driving costly repositioning operations. We investigate the potential for consignees to manage an inventory of empty containers at their location so as to enable direct reuse of these containers by consignors located in the surroundings. One difficulty is that the detention fees imposed by shipping companies under merchant haulage are nonlinear. Moreover, cleaning and related activities might be necessary if the consignee keeps some empties. These difficulties incentivize consignees to immediately return containers to the sea terminal. Contrary to this practice, we show that managing containers via time‐based threshold policies can save costs. Without cleaning costs, we prove that a time‐based policy with a timeout return time is optimal. We next develop a policy improvement approach to include the cleaning costs in the analysis. This results in a two‐thresholds time‐based policy where the two time thresholds control the admission into and rejection out of the inventory. We next analyze the impact of this proactive management on the level of direct container reuse. This practice enables a high level of direct reuse. It also reduces container repositioning costs. Yet, the incentive to implement our policy varies a lot from one setting to another. In particular, low cleaning costs or high repositioning costs lead to significant costs improvement when implementing our policy. Finally, we further explore if the incentive could be made stronger by modifying the structure and/or purpose of the detention costs. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a new redesigned solution on Container Terminal Production Controlling System, which goal is to correct defects existing and to rebuild business processes with lower cost, higher quality, flexible, faster and more intelligent responsiveness to whole system. The model of BPR is confirmed by the method of Logistic Object Petri Net. [Copyright &y& Elsevier]

The goal of this paper is to show that the implementation of the queuing theory could set an optimal capacity of the port container terminal, or a combination of the number of berths and cranes per berth with the minimum costs for the given traffic. The container terminal is a system composed of a specific number of mutually depending subsystems so the optimal capacity of the terminal is reduced to the calculation of the optimal number of berths, since the capacity of the berth determines the necessary capacity of the other subsystems, and thereby a throughput of the entire container terminal. The optimal solution was received by applying a model of total costs that is based on the queuing theory. This model can be used for any container terminal and for terminals in present and future conditions. The results are a basis for bringing adequate business decisions related to the operating of the terminal. The model is tested on an example of container terminal Brajdica in Port of Rijeka. [ABSTRACT FROM AUTHOR]