Fundamental diagram of ship traffic in the Singapore Strait

Kang, Liujiang; Meng, Qiang; Liu, Qiang

doi:10.1016/j.oceaneng.2017.10.051

Cited by 73 publications

(32 citation statements)

References 33 publications

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“…The 12 works on big data applied to shipping can be summarized as follows: Seven are applications on navigation [ 66 , 67 , 68 , 69 , 70 , 71 , 72 ]. Four are works on maritime economics [ 73 , 74 , 75 , 76 ].…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…Regarding navigation and big data, in 2017 Isenor et al [ 66 ] used open-sourced technologies for the design and implementation of a maritime data management infrastructure capable of coping with vessel positional data and supporting vessel metadata. In 2018, Kang et al [ 67 ] made use of big data techniques to manage automatic identification systems (AIS) and extract conclusions on maritime transport management in the Singapore Strait. They concluded that ship speed generally decreases with the increase of ship density; the four classic traffic flow models for the fifteen legs in the Singapore Strait are estimated by the weighted and non-weighted least square approaches, respectively.…”

Section: Digitalization On Maritime Transport: the Situation At Thmentioning

confidence: 99%

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Toward Digitalization of Maritime Transport?

Sanchez-Gonzalez

Díaz-Gutiérrez

Leo

et al. 2019

Sensors

123

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Although maritime transport is the backbone of world commerce, its digitalization lags significantly behind when we consider some basic facts. This work verifies the state-of-the-art as it currently applies to eight digital domains: Autonomous vehicles and robotics; artificial intelligence; big data; virtual reality, augmented and mixed reality; internet of things; the cloud and edge computing; digital security; and 3D printing and additive engineering. It also provides insight into each of the three sectors into which this industry has been divided: Ship design and shipbuilding; shipping; and ports. The work, based on a systematic literature review, demonstrates that there are domains on which almost no formal study has been done thus far and concludes that there are major areas that require attention in terms of research. It also illustrates the increasing interest on the subject, arising from the necessity of raising the maritime transport industry to the same level of digitalization as other industries.

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Section: Analysis and Discussionmentioning

confidence: 99%

Section: Digitalization On Maritime Transport: the Situation At Thmentioning

confidence: 99%

Toward Digitalization of Maritime Transport?

Sanchez-Gonzalez

Díaz-Gutiérrez

Leo

et al. 2019

Sensors

123

View full text Add to dashboard Cite

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“…While one vessel is close to the hydrophone, other vessels are assumed distributed in the surrounding well-defined ocean area on the sea surface [36]. The ship traffic noise (SL 3 ) accounts for the cumulative radiating effect of a number of vessels and corresponds to the distribution of these vessels.…”

Section: Ship Traffic Noisementioning

confidence: 99%

“…In underwater environments, ship noise is another significant contributor, which can cause substantial elevation of ambient noise [17], and affect the ability to detect and quantify leaks. The ship noise, including transit noise and traffic noise [36], can be a dominant noise source, especially the transit noise, i.e., noise from a vessel travels in the vicinity of acoustic receiver, where there is little propagation loss in the acoustic channel [29]. To assess the impact of nearby shipping, we compute the distance at which a vessel is likely to hinder detection of a leak.…”

Section: Introductionmentioning

confidence: 99%

A noise impact assessment model for passive acoustic measurements of seabed gas fluxes

White

Bull

et al. 2019

Ocean Engineering

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Accurate determination of seabed gas flux is important for understanding natural processes as well as giving confidence that the size of any leaks from marine infrastructure can be properly assessed. Acoustic methods for flux determination require a relatively quiet underwater environment, and can fail when there is too much noise from other natural or anthropogenic sources. This study applies an acoustic monitoring example of seabed gas leakage in terms of sound level intensity, to statistically assess and minimize the impact from oceanic noise on seabed acoustic experiments which require relative quiet environment. It addresses the question: how far from a source of radiated ambient noise does a recording hydrophone and location of seabed gas need to be so that acoustic methods for remotely determining gas flux are successful. We develop a model to assess impacts of ambient noise under various conditions, incorporating sound/noise sources (seabed gas leaks, sea surface agitation and shipping) and underwater acoustic propagation. The reliability of the model is tested by comparing measured seabed ambient noise in the central North Sea, and the robustness of it is verified by presenting statistical outliers and a receiver operating characteristic (ROC) curve. A range of scenarios are presented for several gas flow rates, which show the threshold of detection when the recording hydrophone is at different distances from the location of seabed gas escape, and competing noise sources (including shipping and surface waves).

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“…In a brief explanation, the Automatic Identification System (AIS) technology is a system that enables a vessel to obtain about the encountered vessels, such as their position (Zaman et al, 2015), course, speed, and other parameters automatically by very high frequency (VHF) radio transmission (Kundakci et al, 2018). Using AIS (Wu et al, 2017;Kang et al, 2018) will improve and remedy the traffic congestion on open water as it gives required data for traffic analysis (Xiao et al, 2015;Zhang et al, 2019;Fiorini et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Marine Traffic Density Using Different Time Series Model From AIS data of Port Klang and Straits of Malacca

Ramin¹,

Mustaffa²,

Ahmad³

2020

Trans. Marit. Sci.

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In the study of ocean engineering, marine traffic is referring to the study of the pattern of the density of ships within the particular boundaries at certain periods. The Port Klang and Straits of Malacca are known for one of the heaviest traffics in Malaysia and the world. The study of traffic within this area is important, because it enables ships to avoid traffic congestion that might happen. Thus, this study is mainly aimed at predicting or forecasting the density of the ships using the route through this waterway by using quantitative methods which are time-series models and the associative models from the Automatic Identification System (AIS) data. The moving averages, weight moving average, and exponential smoothing for the time series model and associative model have used multiple regression. The results show an exponential smoothing alpha 0.8 and give the lowest MAPE as 20.701%, thereby making this method to be the best in forecasting the future traffic density among the method categories.

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Fundamental diagram of ship traffic in the Singapore Strait

Cited by 73 publications

References 33 publications

Toward Digitalization of Maritime Transport?

Toward Digitalization of Maritime Transport?

A noise impact assessment model for passive acoustic measurements of seabed gas fluxes

Prediction of Marine Traffic Density Using Different Time Series Model From AIS data of Port Klang and Straits of Malacca

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