Implementation of AIS for Ship’s Collision Analysis: Case Study

Muhammad Badrus Zaman; Dwi Priyanta; Nurhadi Siswantoro

doi:10.15866/irea.v8i6.18526

Implementation of AIS for Ship’s Collision Analysis: Case Study

Muhammad Badrus Zaman^(1*), Dwi Priyanta⁽²⁾, Nurhadi Siswantoro⁽³⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/irea.v8i6.18526

Abstract

Safety measurement is an important step to detect the causes of a ship accident. The Malacca Strait is an international shipping lane that connects various countries. The Malacca Strait is categorized as a busy strait, which has a high level of danger. In this study the traffic conditions in the Malacca Strait have been analysed in hours, days and months based on AIS data. Several factors that cause ship accidents are: ship condition factors, human error, engine, and electrical damage, navigation factors and so on. Based on the surveys, human error is the main cause of ship accidents on international shipping. In this study, the methodology of the m-SHEL model is used to analyse the interactions between ship operators, equipment, environment, regulation, management and human factors. CPA and TCPA are determined based on AIS data. Then the risk assessment is carried out using the Samson model. The results of the risk assessment are useful to avoid collision. AIS data has been used as a source of data. In this context, AIS receiver has been installed at UTM Malaysia.
Copyright © 2020 Praise Worthy Prize - All rights reserved.

Keywords

Collision; AIS Data; m-SHEL Model; Risk Assessment; Malacca Straits

Full Text:

PDF

References

Liu, C., Mao, Q., Chu, X., Xie, S. 2019. An Improved A-Star Algorithm Considering Water Current, Traffic Separation and Berthing for Vessel Path Planning. Applied Sciences. 9(6), pp.1-17, 2019.
https://doi.org/10.3390/app9061057

IMO (1972) Convention on the international regulations for preventing collisionsat sea (COLREGs), 1972.
http://www.imo.org/conventions/

Abdelaal, M., Franzle, M., Hahn, A. Nonlinear Model Predictive Control for trajectory tracking and collision avoidance of underactuated vessels with disturbances. Ocean Engineering, Elsevier,160, pp. 168–180, 2018.
https://doi.org/10.1016/j.oceaneng.2018.04.026

Yamin, H., Linying, C., Rudy, R.N., Gelder, v. P.H.A.J.M.,: A ship collision avoidance system for human-machine cooperation during collision avoidance. Ocean Engineering, Elsevier, 217, pp.1-19, 2020.
https://doi.org/10.1016/j.oceaneng.2020.107913

Zaman M B, Kobayash E, Wakabayashi E, Khanfir S, Maimun A,. Implementation of automatic identification system (AIS) for evaluation of marine traffic safety in strait of Malacca using analytic hierarcy process (AHP) J. Japan Soc Nav Archit and Ocean Engineers (JASNAOE), 16 (3), pp. 141-153, 2012.
https://doi.org/10.2534/jjasnaoe.16.141

Park, D.J.; Yim, J.B.; Yang, H.S. A Study on Collision Avoidance Action in the Situation of Encountering Multiple Ships by the Reserve Officer. J. Korean Soc. Mar. Environ. Saf. Res. Pap. 24(3), pp.346–351, 2018.
https://doi.org/10.7837/kosomes.2018.24.3.346

He, Y.; Jin, Y.; Huang, L.W.; Xiong, Y.; Chen, P.F.; Mou, J.M. Quantitative analysis of COLREG rules and seamanship for autonomous collision avoidance at open sea. Ocean Engineering, Elsevier, 140, pp. 281–291, 2017.
https://doi.org/10.1016/j.oceaneng.2017.05.029

Zhang, J.F.; Zhang, D.; Yan, X.P.; Haugen, S.; Soares, C.C. A distributed anti-collision decision support formulation in multi-ship encounter situations under COLREGs. Ocean Eng.105, pp. 336–348, 2015.
https://doi.org/10.1016/j.oceaneng.2015.06.054

Li, S., Liu, J., Cao, X., Zhang, Y. A novel method for solving collision avoidance problem in multiple ships encounter situations. In: International Conference on Computational Logistics (ICCL 2018). Vietri Sul Mare (Salerno). Italy Springer. Cham, 2018.
https://doi.org/10.1007/978-3-030-00898-7_4

Huang, Y., Van Gelder, P.H.A.J.M.,. Time-varying risk measurement for ship collision prevention. Risk Analysis, 40(1), pp. 24–42, 2020.
https://doi.org/10.1111/risa.13293

Wu, B., Cheng, T., Yip, T.L., Wang, Y. Fuzzy logic based dynamic decision-making system for intelligent navigation strategy within inland traffic separation schemes. Ocean Engineering. 197, 106909, 2020.
https://doi.org/10.1016/j.oceaneng.2019.106909

Thia-Eng C, Inggrid R L, Adrian Ross G S. The Malacca Straits Elsevier, 41 pp. 160-178, 2000.

Zaman M B, Kobayashi E, Wakabayashi N, Maimun A. Risk of navigation for marine traffic in the Malacca Strait using AIS In: Proc. Earth and Planetary Science, 14 p. 33-40, 2015.
https://doi.org/10.1016/j.proeps.2015.07.082

Siswantoro, N., Semin, S., Zaman, M., Criticality Assessment for Marine Diesel Engine Using Failure Mode and Effect Criticality Analysis (FMECA) Approach: Case Study on Lubricating Oil System, (2020) International Review of Mechanical Engineering (IREME), 14 (4), pp. 258-263.
https://doi.org/10.15866/ireme.v14i4.18060

Radam, I., Mahmud, M., Alexander, S., Factor Analysis of the Influence of River Crossing Ferry Use – A Case in Banjarmasin and Kuala Kurun, (2018) International Review of Civil Engineering (IRECE), 9 (4), pp. 154-160.
https://doi.org/10.15866/irece.v9i4.15357

Blaich, M.; Köhler, S.; Reuter, J.; Hahn, A. Probabilistic Collision Avoidance for Vessels. Elsevier, IFAC-Papers Online, 48 (16), pp.69–74, 2015.
https://doi.org/10.1016/j.ifacol.2015.10.260

Szlapczynski, R.; Krata, P.; Szlapczynska, J. Ship domain applied to determining distances for collision avoidance manoeuvres in give-way situations. Ocean Eng., 165, pp.43–54, 2018.
https://doi.org/10.1016/j.oceaneng.2018.07.041

Chai, T.; Weng, J.X.; Xiong, D.Q. Development of a quantitative risk assessment model for ship collisions in fairways. Saf. Sci., 91, pp. 71–83, 2017.
https://doi.org/10.1016/j.ssci.2016.07.018

Mousazadeh, H.; Jafarbiglu, H.; Abdolmaleki, H.; Omrani, E.; Monhaseri, F.; Abdollahzadeh, M.; Mohammadi-Aghdam, A.; Kiapei, A.; Salmani-Zakaria, Y.; Makhsoos, A. Developing a navigation, guidance and obstacle avoidance algorithm for an Unmanned Surface Vehicle (USV) by algorithms fusion. Ocean Eng. 159, pp.56–65, 2018.
https://doi.org/10.1016/j.oceaneng.2018.04.018

Grinyak V M, Devyatisilnyi A S, Ivanenko Y S. Traffic Safety Assessment in Water Area. In Proceeding of IOP Conf. Series: Earth and Environmental Science, vol.272, pp.1-5, 2019.
https://doi.org/10.1088/1755-1315/272/2/022017

Zaman M B, Kobayashi E, Wakabayashi N, Pitana T, Maimun A Fuzzy FMEA model for risk evaluation of ship collision in the Malacca Strait, Jornal of. Simulation, 8 (1), pp. 91-104, 2013.
https://doi.org/10.1057/jos.2013.9

Aouimer, Y., Boutchicha, D., Hamoudi, B., Numerical and Experimental Study of Fluid-Structure Interaction of a Marine Propeller, (2020) International Review of Mechanical Engineering (IREME), 14 (5), pp. 282-289.
https://doi.org/10.15866/ireme.v14i5.17582

Santoso, A., Semin, S., Sampurno, B., Cahyono, B., Zaman, M., New Development of Piston Crown for Dual Fuel Diesel Engine to Improve Efficiency and Reduce NOx Emissions: a Review, (2020) International Journal on Engineering Applications (IREA), 8 (1), pp. 1-7.
https://doi.org/10.15866/irea.v8i1.17449

Mujeeb-Ahmed, M.P.; Seo, J.K.; Paik, J.K. Probabilistic approach for collision risk analysis of powered vessel with offshore platforms. Ocean Eng., 151, pp. 206–221, 2018.
https://doi.org/10.1016/j.oceaneng.2018.01.008

Husni, E., Design of Automatic Identification System (AIS) Receiver for Low Earth Orbit (LEO) Satellite, (2016) International Review on Modelling and Simulations (IREMOS), 9 (6), pp. 435-441.
https://doi.org/10.15866/iremos.v9i6.10958

P. Lessing, L. Bernard, B. Tetreault, and J. Chaffin, Use of the Automatic Identification System (AIS) on Autonomous Weather Buoys for Maritime Domain Awareness Applications, OCEANS Conference, pp. 1-6, Singapore, May 2016.
https://doi.org/10.1109/oceans.2006.307023

Rao, S.N.; Balakrishnan, A. Harnessing Low-Cost Marine Internet for Collision Avoidance of Vessels at Sea. In Proceedings of the IEEE WiSPNET 2017 Conference, Chennai, India, 22–24 March 2017; pp. 2147–2152, 2017.
https://doi.org/10.1109/wispnet.2017.8300140

Lyu, H., Yin, Y., COLREGS-Constrained Real-time PathPlanning for Autonomous Ships UsingModified Artificial Potential Fields, Journal of Navigation, The Royal Institute of Navigation 2018, pp. 1-21, 2018.
https://doi.org/10.1017/s0373463318000796

Hexeberg, S.; Flåten, A.L.; Eriksen, B.H.; Brekke, E.F. AIS-based Vessel Trajectory Prediction. In Proceedings of the 20th International Conference on Information Fusion, Xi’an, China, 10–13 July 2017; pp. 1–8, 2017.
https://doi.org/10.23919/icif.2017.8009762

Tu, E.M.; Zhang, G.H.; Rachmawati, L.; Rajabally, E.; Huang, G.B. Exploiting AIS Data for IntelligentMaritime Navigation: A Comprehensive Survey From Data to Methodology. IEEE Trans. Intell. Transp. Syst.19, pp.1559–1582, 2018.
https://doi.org/10.1109/tits.2017.2724551

Schiaretti, M., Chen, L., Negenborn, R.R.,. Survey on autonomous surface vessels: Part II - categorization of 60 prototypes and future applications. Comput. Logist, vo.10572, pp. 234–252, 2017.
https://doi.org/10.1007/978-3-319-68496-3_16

E. Akyuz and E. Celik, A Quantitative Risk Analysis by Using Interval Type-2 Fuzzy FMEA Approach: The Case of Oil Spill, Maritime Policy & Management, Vol. 45, n. 8, pp. 979-994, 2018.
https://doi.org/10.1080/03088839.2018.1520401

Semin, S., Zaman, M., Santoso, A., Effect of Compression Ratio Improvement on the Performance of Dual Fuel Engine, (2019) International Review of Mechanical Engineering (IREME), 13 (3), pp. 142-147.
https://doi.org/10.15866/ireme.v13i3.15854

Valdez Banda, O.A., Kannos, S., Goerlandt, F., van Gelder, P.H.A.J.M., Bergstr ̈om, M., Kujala, P.,. A systemic hazard analysis and management process for the concept design phase of an autonomous vessel. Reliab. Eng. Syst. Saf. 191, pp.1-16, 2019.
https://doi.org/10.1016/j.ress.2019.106584

Jalil, A.S.; Dawal, S.Z.; and Zakwan, N.M., Human performance in transportation a comparative study of human performance models. Journal of Engineering and Technology, pp. 111-115, 2012.
https://doi.org/10.7763/ijet.2012.v4.329

Yang, X., Utne, I.B., Holmen, I.M.,. Methodology for hazard identification in aquaculture operations (MHIAO). Saf. Sci. 121, pp. 430–450, 2020.
https://doi.org/10.1016/j.ssci.2019.09.021

Fang, M.-C., Tsai, K.-Y., Fang, C.-C.,. A simplified simulation model of ship navigation for safety and collision avoidance in heavy traffic areas. J. Navig. 71(4), pp.837–860, 2017.
https://doi.org/10.1017/s0373463317000923

Itoh, H.; Mitomo, N; Matsuoka, T.; and Murohara, Y., An extension of m-SHEL model for analysis of human factors at ship operation.In. Proc of International Conference on Collision and Groundings of Ships (ICCGS), pp.118-112, 2004.

Nguyen, M.; Zhang, S.; Wang, X. A Novel Method for Risk Assessment and Simulation of Collision Avoidance for Vessels based on AIS. Algorithms 2018, 11, 204.
https://doi.org/10.3390/a11120204

Hilget, H., Baldauf, M. A common risk model for the assessment of encounter situations on board ships, Deutsche Hydrographische Zeitschrift. 49, pp.531–542. 1997.
https://doi.org/10.1007/bf02764347

Zaman, M.B.: Study on safety of navigation using automatic identification system for marine traffic area case study: Malacca Straits J Mar Eng Innovation and Research (IJMEIR), 1(1), pp. 26-31, 2016.
https://doi.org/10.12962/j25481479.v1i1.1462

Mou, J.; Ligteringen, H.; and Gan, L., A Study on collision avoidance in busy waterways by using AIS data. Journal of Ocean Engineering, Elsevier. Vol.37, No.5-6, pp.483-490, 2010.
https://doi.org/10.1016/j.oceaneng.2010.01.012

Refbacks

There are currently no refbacks.

Username
Password
Remember me