Arctic sea route path planning based on an uncertain ice prediction model

Choi, Minjoo; Chung, Habong; Yamaguchi, Hideyo; Nagakawa, Keisuke

doi:10.1016/j.coldregions.2014.10.001

Cited by 49 publications

(23 citation statements)

References 18 publications

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“…Such model would also allow better choices in route selection process using route optimization tools. 14,16,21,37,39,[46][47][48]49 The engineering and datadriven approaches leading to the development of two sub-models A and B of the HM are presented in the following sections.…”

Section: The Idea Of Hybrid Modelingmentioning

confidence: 99%

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Montewka

Goerlandt

Lensu

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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Practical knowledge about the performance of a ship while navigating in ice is crucial for the selection of safe and efficient route for a ship. Existing route finding tools estimate ship performance in ice adopting numerous approaches, ranging from model tests and engineering models to experts-based guidelines. Therein ship performance is usually understood as attainable ship speed or the average speed in given ice conditions; rarely the probability of besetting in ice is taken into account. Those models despite being fairly accurate in the theory share the same shortcoming in practice. The latter encompasses three main issues: (1) inaccurate information about prevailing ice conditions, (2) presence of ice conditions that goes beyond the scope of the models, and (3) the effect of operational patterns and traffic organization on the performance of an individual ship. To approach those issues, we propose a hybrid model of ship performance in ice-covered waters. The hybrid model combines two other sub-models: engineering and data-driven. The former determines ship speed and besetting probability in ridged ice field with ice concentration close to 100%. The latter sub-model provides information on ship's speed in the actual ice conditions, where the speed is affected also by operational restrictions and icebreaker assistance. It is based on an extensive dataset combining ship data from automatic identification system and ice data from ice charts and ice forecast models. The presented hybrid model is valid for a specific ship type, which is ice going bulk carrier (IA Super ice class), operating within the Northern Baltic Sea winter navigation system. The obtained results reveal that the hybrid model in principle is capable of providing reliable information about the performance of a ship in a wide range of conditions accounting for environmental variability and existing operational conditions. The model is suitable for the purpose of safe route planning in ice for a single ship or group of similar ships, accounting for the economy and safety of a voyage.

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Section: The Idea Of Hybrid Modelingmentioning

confidence: 99%

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Montewka

Goerlandt

Lensu

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…With the development of computer technology, mapping technology and information technology, the current marine data can accurately and completely describe the navigation environmental information. In this case, the researchers began to use heuristic algorithms to automatically generate ship route and many methods and procedures have been developed to determine the best route available (Dijkstra 1959, E. Kobayashi 2011, Choi et al 2015. However, in complex situations, it is difficult to realize in the actual navigation environment, and it is difficult to accurately and completely represent the obstacles in the complex environment with many obstacles.…”

Section: Introductionmentioning

confidence: 99%

Ship Route Planning Using Historical Trajectories Derived from AIS Data

He¹,

Zhang²,

Zhang³

et al. 2019

TransNav

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Ship route planning is one of the key issues in enhancing traffic safety and efficiency. Many route planning methods have been developed, but most of them are based on the information from charts. This paper proposes a method to generate shipping routes based on historical ship tracks. The ship's historical route information was obtained by processing the AIS data. From which the ship turning point was extracted and clustered as nodes. The ant colony algorithm was used to generate the optimize route. The ship AIS data of the Three Gorges dam area was selected as a case study. The ships' optimized route was generated, and further compared with the actual ship's navigation trajectory. The results indicate that there is space of improvement for some of the trajectories, especially near the turning areas.

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“…The system employed a modified transit model devised by [9], which integrated various parameters such as ice-breaking fee, port charge, capital cost, etc. Reference [10] developed another ice navigation system where the uncertainty of sea ice prediction and the extremely severe conditions were taken into consideration. The route optimization problem in ice-covered water was regarded as a dynamic stochastic path planning problem, and a heuristic route optimization model was proposed to solve it.…”

Section: Introductionmentioning

confidence: 99%

An Improved A* Algorithm Based on Hesitant Fuzzy Set Theory for Multi-Criteria Arctic Route Planning

2018

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This paper presents a new route planning system for the purpose of evaluating the strategic prospects for future Arctic routes. The route planning problem can be regarded as a multi criteria decision making problem with large uncertainties originating from multi-climate models and experts’ knowledge and can be solved by a modified A* algorithm where the hesitant fuzzy set theory is incorporated. Compared to the traditional A* algorithm, the navigability of the Arctic route is firstly analyzed as a measure to determine the obstacle nodes and three key factors to the vessel navigation including sailing time, economic cost and risk are overall considered in the HFS-A* algorithm. A numerical experiment is presented to test the performance of the proposed algorithm.

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Arctic sea route path planning based on an uncertain ice prediction model

Cited by 49 publications

References 18 publications

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Ship Route Planning Using Historical Trajectories Derived from AIS Data

An Improved A* Algorithm Based on Hesitant Fuzzy Set Theory for Multi-Criteria Arctic Route Planning

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