Universiti Teknologi Malaysia Institutional Repository

Using AIS data for navigational risk assessment in restricted waters

Maimun, A. and Nursyirman, I. F. and Sian, A. Y. and Samad, R. and Oladokun, S. (2013) Using AIS data for navigational risk assessment in restricted waters. In: Marine Technology and Sustainable Development: Green Innovations. IGI Global, pp. 245-254. ISBN 978-146664318-5

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The Strait of Malacca is one of the most important shipping lanes in the world. It averages 150 ship passes a day and more than 50,000 ships annually. With a high concentration of vessels in a narrow path, multiple risk situations arise. Analyzing traffic density is made harder by cross traffic and an unknown traffic density at the Strait. In 2009, Universiti Teknologi Malaysia (UTM), through a collaboration with Kobe University, successfully installed an Automatic Identification System (AIS) receiver. Through the AIS receiver, data of ship movements in the Strait of Malacca and Singapore could be recorded. A program was established by UTM to retrieve the data for the purpose of marine traffic collision risk analysis. In this research, a risk assessment method using AIS data is proposed for restricted waters such as for the Strait of Malacca and Singapore. The Risk Assessment Methodology requires the estimation of collision probabilities. The collision probability of the proposed method considers the Traffic Density, directions of traffic flow (with respect to a subject vessel), and probability of navigational failure. An area in the Strait of Singapore between the latitudes of 1°13'N and 1°07'N and Longitudes of 103°4'E and 103°56'E was selected to illustrate the method. By analysing the AIS data of traffic flow, the probabilities of collision for the area were determined. The effect of vessel parameters of length and speed on the risks of collision are also shown.

Item Type:Book Section
Uncontrolled Keywords:Automation, Probability, Risk analysis, Risk perception, Risks
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Mechanical Engineering
ID Code:74674
Deposited By: Haliza Zainal
Deposited On:26 Nov 2017 08:31
Last Modified:26 Nov 2017 08:31

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