Procedure for Marine Traffic Simulation with AIS Data

Miyake, Rina; Fukuto, Junji; Hasegawa, Kazuhiko

doi:10.12716/1001.09.01.07

Cited by 7 publications

(8 citation statements)

References 3 publications

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“…In this model, the course is a proportional feedback of the rate-of-turn when the course of the route is changing. The speed of the vessels are constant through the voyage, which can be dependent on vessel classification (Miyake et al, 2015;Watanabe et al, 2008), or have a specific distribution (Gucma et al, 2017), or a distribution derived from historical data (Colley et al, 1984;Davis et al, 1980;Huang et al, 2016Huang et al, , 2013Li, 2013;Xu et al, 2013). In other models, the speed of the vessels is determined by the maximum or minimum of the speed limitations (Rayo, 2013).…”

Section: Specific Rule-based Modelsmentioning

confidence: 99%

“…The behavior rule during dangerous head-on situation (starboard-to-starboard) is also defined. Li (2013) and Miyake et al (2015) trigger the collision avoidance behavior with an increase of DCPA and TCPA. Watanabe et al (2008) adopt the concept of CR by Hasegawa et al (2001) to judge the situation and calculate the timing for the vessel to turn back to the original route.…”

Section: Specific Rule-based Modelsmentioning

confidence: 99%

“…The behavior of individual vessels can hardly be modeled. Aiming to represent the details of vessel traffic, the detailed behavior of every single vessel in the area is modeled by describing the time-space state (Cheng et al, 2017;Hasegawa et al, 2001;Miyake et al, 2015). To further consider the safe passage of vessels during encounters, the evasive behavior of vessels is included (Qu and Meng, 2012;Watanabe et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Review of maritime traffic models from vessel behavior modeling perspective

Zhou

Daamen

Vellinga

et al. 2019

Transportation Research Part C: Emerging Technologies

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The importance of maritime transport keeps increasing with the trade globalization. With the growing demand for waterborne transport, vessel traffic flows are also expected to increase. This paper reviews maritime traffic models from the vessel behavior modeling perspective. The maritime traffic models include the models for vessel traffic both at sea and in confined water area. The aim of this paper is to analyze the underlying modeling paradigms and to assess the extent in which maritime traffic models can represent vessel behavior. Focusing on vessel behavior modeling, this paper provides a broad overview of the current literature on maritime traffic models of the last decades. The commercial models are not included due to the limit of information. To compare the capabilities of models in capturing the vessel behavior characteristics, the considered models are assessed from different aspects of vessel behavior representation, external impact modeling, and model applicability.The assessment shows that none of the existing models describe all dynamic kinetic information in detail for different vessels and consider the impacts from a full range of external factors, which is possibly due to the specific purpose when the models were developed. The models developed for

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Section: Specific Rule-based Modelsmentioning

confidence: 99%

Section: Specific Rule-based Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Review of maritime traffic models from vessel behavior modeling perspective

Zhou

Daamen

Vellinga

et al. 2019

Transportation Research Part C: Emerging Technologies

View full text Add to dashboard Cite

show abstract

“…The original purpose of AIS was solely collision avoidance but many other applications have since developed. In the scientific literature, the following uses have been identified: ship surveillance, tracking and security, 53,54 collision avoidance and decision support, 55,56 discovery of traffic patterns, [57][58][59][60] traffic simulation, 61,62 ship routing development, 63 risk analysis, [64][65][66][67] mission estimation, 68,69 impact on marine ecology of shipping traffic, 70 accident investigation, 71,72 maritime spatial planning, 73 and ship performance estimation. 33,74 For the present study, AIS data from the period 2007 to 2016 is used.…”

Section: Engineering Approach Reflecting Ship Performance In Icementioning

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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“…[13], Miyake et al . [14] etc. Recently, studies relating to ship navigation under extreme wind or wave have received growing interests.…”

Section: Introductionmentioning

confidence: 99%