Purpose: Ports rely largely on trucks for hinterland transportation all over the world. With the increasing emphasis on sustainability as well as constant increase in the volume of containers transported across the globe, there is a growing focus on shift from road to rail transportation for connecting container terminals to the hinterlands. However, the existing situation at the ports is not accurately known. This study analyses the hinterland connectivity of container terminals by rail at the major seaports in the world.

Methodology: The analysis is done in two stages. In the first stage, the container terminals are classified into one of three categories based on their access to hinterland rail connectivity. This is done by examining the satellite views of the location of container terminals on OpenStreetMap, Google Maps and Baidu Maps. In stage two, several ports from Europe and USA are studied in further detail by analysing the data from the past years.

Findings: In Stage 1, 100 ports were identified and their container terminals were classified into the three categories. The study reveals that over half the total container terminals at the top 100 ports do not have access to rail. The geographical trends based on this classification is also presented. In Stage 2, the total volume throughput as well as the volumes handled by the different modes of transport are analysed for selected ports in Europe and USA. It is found that road transport still dominates the hinterland transport with only one exception. Furthermore, the destinations served by rail and their distances from the ports are studied to provide further insights into the hinterland rail connectivity of the container terminals. The minimum distance over which rail is used is much shorter than what has been previously suggested in literature.

Originality: The current situation of the container terminals worldwide with regards to their hinterland connectivity is missing from literature. This study serves as a database for various information related to the container terminals which can serve as a starting point for research with regards to terminal planning, sustainability, and hinterland transport. Additionally, a framework to quantitatively analyse the hinterland connectivity is also proposed.

Purpose: Combined transport integrates the advantages of sustainable transport modes, such as railroad or inland waterways, and flexible road transport. It aims at increasing the goods transport sustainability by covering the longest part of a transport path by train or waterway. Rail-road terminals are transshipment nodes of combined transport chains, where the Loading Units (LUs) are moved between trains and trucks. In the most cases, the LUs are also temporary stored in a storage area to decouple the fluctuations in the arrival of trains and trucks. Direct transshipments of LUs between rail and road avoid storage and improve the logistics performance of the terminals. In particular, they enable reducing storage handlings and costs as well as transshipment times of trains and trucks. In addition, they increase the maximum number of trains and trucks that can be processed per time unit (transshipment capacity).

However, the number of direct transshipments at combined transport terminals is currently very small. This is primarily due to the difficulty of synchronizing the arrival of trains and trucks. For estimating the effect of direct transshipments on the logistics objectives it is essential to assess the probability of such operations. This study therefore contributes to modeling the direct transshipments at rail-road combined transport terminals (1) by modeling the probability of such operations and (2) by modeling the effect of direct transshipments on the transshipment capacity of rail-mounted gantry cranes as main working systems of rail-road terminals.

Methodology: This study firstly analyses the requirements for direct transshipments, considering them for two main cases: train-to-truck transshipments and truck-to-train transshipments. Afterwards, it develops a quantitative model for determining the probability of direct transshipments for both cases. Further, it models the effect of direct transshipments on the transshipment capacity of the terminal. Models are evaluated using comprehensive simulation.

Findings: The models enable an analytical evaluation of the probability of direct transshipments and of their effect on the gantry crane transshipment capacity. The simulative evaluation confirms a high accuracy of the models. The probability of direct transshipments mainly depends on the synchronization of truck and train arrivals. In addition, the direct transshipments increase the transshipment capacity of a gantry crane.

Originality: There is a lack of research focusing on direct transshipments at combined transport terminals. Previously, simulation and mathematical optimization are used for their exploration. Taking into account the positive effect of these operations on the logistics objectives of the terminals, this study presents an approach for modeling the probability of direct transshipments and their effect on transshipment capacity of a gantry crane. It helps firstly to understand the cause-effect relations for their occurrence. Secondly, it supports derivation of suitable measures for increasing the number of direct transshipments and for improving logistics performance of rail-road combined transport terminals.

Due to the ever-increasing public demand for goods and services, a steady increase in global emissions can be observed, partly accounted for by the shipping industry. To reduce the ecological footprint of mentioned industry and thus increase its sustainability, this paper examines the extent to which the consumption of a ship can be reduced by path planning algorithms. The focus hereby is placed on the use case of maritime urban transportation and which adjustments to existing methods are necessary to be suited for this application. This means considering the specific requirements and restrictions that apply to the navigation of a ship in an urban environment. Therefore, an extensive study is being carried out to compare different algorithms regarding their suitability for said task. The factors that are already included in the methods and what would be needed to be added to the algorithm to complete this specific task are considered in this. Finally, an approach based on the A*-Algorithm is pursued in which the consumption along the route is to be reduced by taking environmental parameters into account. The resulting algorithms cost function can consider multiple criteria at the same time, therefore being able to solve multi objective optimization problems by applying the weighted product method and adhering to the pareto principle. To draw a comparison to the A*-Algorithm, the proposed method was applied to several use cases. Those were not only limited to urban surroundings, but also open waters. Furthermore, the effect of the environment in the form of the amount of obstacles along the route was investigated for the differing use cases. Thereby, the factors of consumption and runtime were regarded and evaluated for both methods. The use of the proposed algorithm to optimize the route planning of ships can ultimately lead to an increase in efficiency and a reduction in costs, thus increasing competitiveness and future viability.