Maritime Transport Research最新文献

The circular economy (CE) brings many opportunities, but also many challenges for ports, cities, and their hinterland. The goal of this paper is twofold. First, we embrace the inherent uncertainty of the spatial impact of the CE on ports and cities. We employ scenario methodology to guide us in steering this uncertainty by developing four scenarios. To explore the complexity of these four scenarios, we focus on the Dutch province of South-Holland. This region hosts the port of Rotterdam, the largest port in Europe, and its direct hinterland consists of a dense urbanised region. As such, the four scenarios cannot only shed a light on the future of the port, but also how its relations with its direct urbanized hinterland can potentially change. In two scenarios deglobalisation occurs. The consequences are, on the one hand, that the port's focus changes more to its direct hinterland instead of a global oriented focus. On the other hand, the existing water bound industrial areas in, or nearby cities increase in importance, in contrast to the contemporary pressure to redevelop these into waterfront residential and commercial areas. In other words, port and city/region grow towards each other. The second goal of the paper is to dive into the specific consequences of these scenarios for day-to-day planning practices. By combining micro-economic and AIS shipping data, we discovered the most important terminals and industrial areas for the transition towards a CE in port, city, and hinterland.

This paper contributes to the literature by deriving upper and lower bounds on the fuel consumption in container shipping. The bounds are derived from sailing distances, port times, and the possible arrival times at ports/ the berth windows negotiated between the ocean carrier and the port operators. Crucially, the derived bounds can be used in conjunction with any of the common fuel consumption functions proposed in the literature. This latter is especially important since currently there is no consensus on a specific functional form for the fuel consumption function. The behavior of the bounds will be illustrated with numerical examples.

This study addresses the pressing need for the Norwegian fishery sector to align with national reduction targets and mitigate its environmental impact. Norway has committed to reducing GHG emissions from the fishery sector by at least 40% by 2030 and 95% by 2050. We propose a mathematical model designed for the strategic renewal of the Norwegian fishing fleet by introducing low- and zero-emission propulsion systems. This model generates fleet renewal schedules that minimize the total operational and renewal costs while ensuring compliance with emission targets. We apply our model to a case study based on the Norwegian fishing fleet and determine the optimal decarbonization strategy. We then analyze the impact of changes in energy costs and emission taxes on this strategy through a sensitivity analysis Our results indicate that (1) fleet renewal is mainly driven by the emission reduction targets, rather than economic benefits, and (2) zero-emission propulsion systems are preferable to low-emission propulsion systems when decarbonizing the fleet.

In a container terminal, the length of time that containers remain in the yard, known as Container Dwell Time (CDT), is considered one of the significant operational indicators due to its direct correlation with terminal productivity and efficiency. However, due to complex processing procedure and the involvement of various logistics stakeholders, CDT is subject to high uncertainty, making it more difficult for the terminal to manage. To address this issue, this paper presents a comprehensive framework to identify the Key Factors (KFs) influencing prolongation of CDT for import containers. In order to elucidate abnormal cases from dataset which contains yard loading information, the Process Mining (PM) method is utilized. Subsequently, XAI has been utilized to identify the KFs of import CDT. To reflect reality as closely as possible, we collected event data from a container terminal in Busan, Korea. Based on experiments, the KFs thus identified were: 1) Temperature, 2) Weight of container, 3) Voyage number of container 4) Block, 5) Shipping company, and 6) Month of discharging. To conclude, we formulated domain knowledge-based interpretations of the six most influential KFs.

We study the potential effects of introducing autonomous ferries in a transportation system of water buses. We develop two integer linear programming models and a heuristic to find weekly passenger transportation plans. One model is tailored for a fleet of autonomous ferries and the other one for manually operated ferries. The objective of the models is to minimize a penalty function for unmet demand, adding up penalties on time delays with respect to the wished time of arrivals of the passengers and penalties on the assignment of passengers to alternative transportation modes. The models differ because working laws affect the crews’ working capacities, and we study the changes when these requirements are absent with autonomous ferries. Our work is motivated by the case of Bergen, a coastal city in Norway. In this case, the use of autonomous ferries has the potential to improve passengers’ utility significantly. However, we suggest that it may be beneficial to consider autonomous ferries as a complementary alternative that can operate especially in low-demand hours—a recommendation that may be particularly relevant if there are few autonomous ferries available or the ferries can only be operative for a limited number of hours of the day.

Maritime transport serves as a critical component of global trade and logistics, enabling the movement of goods and resources across oceans and waterways. Especially in busy waterways and ports, effective and accurate communication is essential, as it ensures the seamless exchange of information and the coordinated execution of port activities. However, comprehensibility is often hindered by factors such as poor audio quality, background noise, and diverse languages and accents. Automatic Speech Recognition (ASR) systems can mitigate these issues by providing real-time transcription and enabling the implementation of automated, value-adding services to enhance situational awareness. While pre-trained ASR models excel on general speech, maritime ASR faces unique challenges due to a lack of annotated data, diverse accents, and specialized terminology.

To this end, we focus on improving the transcription quality of pre-trained ASR models for maritime communication with a particular focus on accurately recognizing maritime-specific terminology such as vessel and location names. Due to the scarcity of transcribed maritime communication, we create a synthetic training dataset tailored to regional maritime terminology. The synthetic audio is augmented with general human speech and used to fine-tune an end-to-end ASR model under various settings. The evaluation of the models employs a proprietary dataset of regional maritime radio communication from the port of Hamburg.

The experimental results demonstrate a notable enhancement in ASR performance. Specifically, our approach yields an absolute improvement over the pre-trained baseline of 13.46% Word-Error-Rate and an increase of 41.57% recall for vessel names and 38.65% recall for locations. Our findings underscore the efficacy of integrating synthetic training data to address the challenges encountered in maritime ASR, paving the way for more robust and accurate speech recognition systems tailored to maritime applications.

A maritime transportation system is a network of ports and commercial terminals connected by navigation channels and navigable inland rivers that enables international trade and the global supply chain. The channels and rivers are subject to recurring sedimentation, which reduces available depths, sailing drafts, and volumes of cargo that vessels can transport between ports. To maintain this network at sufficient depths and enable cost-effective maritime transportation, a specialized fleet of dredging vessels, or dredges, periodically remove accumulated sediment and restore capacity. Scheduling dredges to perform work requires simultaneous consideration of factors specific to the location, dredge, and underlying maritime network and, in practice, often results in significant inefficiencies and delays. Previous models proposed in the literature to optimize dredge scheduling are either intractable or consider only limited aspects of the problem. This paper defines the problem of tactical dredging portfolio scheduling, introduces the General Dredge Scheduling Model (GDSM) as a constraint programming model to solve this problem, and applies GDSM to a realistic problem composed of a portfolio of dredging jobs, fleet of dredges, and sets of seasonal and environmental restrictions.

The International Maritime Organization (IMO) has stated an ambition to achieve net-zero GHG emissions by 2050 and new regulations are under development to achieve this. To inform decisions on GHG regulations, this study has modeled the CO₂ emission abatement potentials and costs towards 2050 for all ships above 400 gross tons. We explore CO₂ reduction pathways based on marginal abatement cost curves (MACC) for 2030, 2040 and 2050. MACC is an important tool to assess the potential impact of regulations and can inform current policy debates as well as ship owners that need to develop their decarbonization strategies. Compared to previous work, we provide global MACCs taking into account the latest technologies and cost development, including alternative fuels. The updated MACC is based on more than 50 state-of-the-art abatement measures, 10 fuel systems and 8 fuels. The results indicate that the revised IMO GHG strategy ambition of 20–30 % GHG emission reduction in 2030, relative to 2008, can be reached at a marginal cost of 50–100 USD/tCO₂; 70–80 % emission reduction in 2040 can be achieved at 230–240 USD/tCO₂ and net-zero emissions in 2050 at a marginal cost of 300 USD/tCO₂. The two inputs which have the highest impact on the results are the future cost of carbon-neutral fuels and growth in seaborne trade.

Port safety plays an important role in port operations. Ship size has become larger and the port environment has rapidly changed in recent years. Ship accidents occur in the port area due to the complex environment in the port area. To improve past decision analysis methods on port operation safety fields and reduce fatalities and financial loss for potential accidents, the novelty of this study is to construct a safety index of ports with the application of the Best Worst Method (BWM). Four dimensions and 14 indicators were summarized based on an intensive literature review. The BWM was implemented to prioritize the weights of dimensions and indicators. Based on 21 expert questionnaires, the results indicate that the ranking of dimensions is ‘human’, ‘ship facilities’, ‘port facilities’, and ‘documentation check’. Regarding the ranking of indicators, the top three are ‘fire-fighting and life-saving equipment’, ‘captain’, and ‘pilot’. Safety improvement strategies (e.g. revising inappropriate operational rules and strengthening human safety education and training) based on these research findings are provided. The merits of this paper are presenting a simpler questionnaire-filling method and overcoming the traditional complicated questionnaire survey process and research limitations (e.g. indicator independence problems in the Analytic Hierarchy Process, and the complexation of filling out a questionnaire in the Analytic Network Process). In addition, the findings can help decision-making for port management authorities, port practitioners, and shipping operators (shipowners) regarding policy implementations of port safety.

Many advancements are being made within the domain of autonomous shipping, motivating discussions of corresponding amendments to international safety regulations within the International Maritime Organization. Near-coastal passenger ferries are a form of sea traffic that has been the target of automation trials due to their short voyages and relatively protected waters of operation. This study investigated emergency evacuation from a range of such ships, covering both the current situation (focused on crew tasks, external rescue actors and interactions) and safety aspects that should be considered when automation brings about new work patterns, such as remote supervision and control. The study employed qualitative methods – interviews, field visits and a stakeholder workshop. Results give insight into ferry evacuation processes and challenges in their current form. In addition, results from the application of different automated evacuation scenarios suggest that more detailed studies are needed within the areas of remote operation situation awareness, remote operator and onboard personnel competencies, passenger safety information and communication, simple and robust evacuation equipment, technical means allowing assistance between autonomous and regular ships, and lastly, both procedures and interfaces for collaboration in a changing rescue network.