A quantitative approach for risk assessment of a ship stuck in ice in Arctic waters

International audienc

On risk management of shipping system in ice-covered waters : Review, analysis and toolbox based on an eight-year polar project

Publisher Copyright: © 2022 The AuthorsWith the climate change, polar sea ice is diminishing. This, on one hand, enables the possibility for e.g., Arctic shipping and relevant resource exploitation activities, but on the other hand brings additional risks induced by these activities. Increasing research focuses have been observed on the relevant topics in the complex and harsh polar environment and its fragile ecosystem. However, from risk management perspective, there is still a lack of holistic analysis and understanding towards safe shipping in the ice-covered waters and its available models applicable for managing risks in the system. Therefore, this paper aims to establish a framework and analysis for better understanding of this gap. The paper targets a comprehensive and long-term project specifically focusing on holistic safe shipping in ice-covered waters as the analysis basis. It firstly creates a holistic framework for the shipping system in ice-covered waters and then implements review and analysis of project publications on their overall features. Quantitative prediction models are selected for a structured applicability analysis. Furthermore, an extensive review outside the project following the elements established for the holistic shipping system is conducted so that this paper provides an overview of models for the shipping system in ice-covered waters, addressing the status of the current toolbox. Moreover, it helps to identify the next scientific steps on risk management of shipping in ice-covered waters.Peer reviewe

Multi-objective route selection for ice-class vessels using reinforcement learning and graph-based approaches

Route selection for ships in ice is a complicated problem in marine navigation. The navigators have to optimize many economic and environmental factors of the routes while adhering to all maritime regulations to ensure safety. The International Maritime Organization has introduced the Polar Operational Limit Assessment Risk Indexing System (POLARIS) as guidelines for all vessels operating in the Arctic Ocean. This research investigates a framework for finding an optimal route for different ice-class vessels using two methods: graph-based approaches and reinforcement learning. The system uses ice charts from the Canadian Ice Service to explore possible routes in a grid world. Reward and cost functions are formulated to achieve operational objectives, such as optimizing the distance travelled, voyage time, and fuel consumption while complying with POLARIS regulation. The graph-based method surpasses the Q-learning in deterministic cases. Despite the shortcoming of not handling the non-deterministic environment, it also shows similar routes compared to Q-learning in a stochastic context. The trial results show that the framework provides a means to identify an optimal route for vessels navigating through ice-covered waters

Towards an Automatic Ice Navigation Support System in the Arctic Sea

Conventional ice navigation in the sea is manually operated by well-trained navigators, whose experiences are heavily relied upon to guarantee the ship’s safety. Despite the increasingly available ice data and information, little has been done to develop an automatic ice navigation support system to better guide ships in the sea. In this study, using the vector-formatted ice data and navigation codes in northern regions, we calculate ice numeral and divide sea area into two parts: continuous navigable area and the counterpart numerous separate unnavigable area. We generate Voronoi Diagrams for the obstacle areas and build a road network-like graph for connections in the sea. Based on such a network, we design and develop a geographic information system (GIS) package to automatically compute the safest-and-shortest routes for different types of ships between origin and destination (OD) pairs. A visibility tool, Isovist, is also implemented to help automatically identify safe navigable areas in emergency situations. The developed GIS package is shared online as an open source project called NavSpace, available for validation and extension, e.g., indoor navigation service. This work would promote the development of ice navigation support system and potentially enhance the safety of ice navigation in the Arctic sea

Fuzzy Techniques for Decision Making 2018

Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches