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Decision Support in Collision Situations at Sea

  • Zbigniew Pietrzykowski (a1), Piotr Wołejsza (a1) and Piotr Borkowski (a1)

Abstract

The known navigational systems in use perform information functions and as such are helpful in the process of safe conduct of a vessel. One of the ways to assist in reducing the number of marine accidents is the development of systems which perform decision support functions, i.e. automatically generate solutions to collision situations. The use of information (and communication) technologies including knowledge engineering allows the generation of proposals for anti-collision manoeuvres taking into account the COLREGs. Demand for further enhancement of navigational safety by limiting human errors has initiated a trend to convert navigational information systems into decision support systems. The implementation of decision support systems will potentially reduce the number of human errors, which translates into a reduction of accidents at sea and their adverse consequences. This paper presents a summary of the research to date on the navigational decision support system NAVDEC. The system has been positively verified in laboratory conditions and in field tests – on a motor ferry and a sailing ship. Challenges associated with the development and implementation of such systems are outlined.

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Banaś, P., Pietrzykowski, Z. and Wójcik, A. (2013). A Model of Inference Processes in the Automatic Maritime Communication System. Communications in Computer and Information Science, 395, 714.
Borkowski, P. (2014). Ship course stabilization by feedback linearization with adaptive object model. Polish Maritime Research, 1(81), 1419.
Borkowski, P. and Zwierzewicz, Z. (2011). Ship course-keeping algorithm based on knowledge base. Intelligent Automation & Soft Computing, 17, 149163.
Fabri, S. and Kadrikamanathan, V. (2001). Functional Adaptive Control. An Intelligent Systems Approach. Springer.
Gucma, L. and Pietrzykowski, Z. (2006). Ship manoeuvring in restricted areas: An attempt to Quantify Dangerous situations Using a Probabilistic-Fuzzy Method, Journal of Navigation, 59, 251262.
Hansen, M., Jensen, T., Lehn-Schiøler, T., Melchild, K., Rasmussen, F. and Ennemark, F. (2013). Empirical Ship Domain Based on AIS Data., The Journal of Navigation, 66, 931940.
HELCOM. (2010). Report on shipping accidents in the Baltic Sea area during 2010, www.helcom.fi
Hwang, C.N. (2002). The Integrated Design of Fuzzy Collision-Avoidance and H[infinity] Autopilots on Ships. Journal of Navigation, 55(1), 117136.
Kokotos, D. and Linardatos, D. (2010). An application of data mining tools for the study of shipping safety in restricted waters. Safety Science, 49(2), 192197.
Lisowski, J. (2013). The sensitivity of computer support game algorithms of a safe ship control, International Journal Applied Mathematics and Computer Science , 23(2), 439446.
MAIB. (1999). Marine Accident Investigation Branch (MAIB) Annual Report. Department of the Environment Transport and Regions, United Kingdom.
Ming-Cheng, T. and Chao-Kuang, H. (2010). The study of ship collision avoidance route planning by ant colony algorithm, Journal of Marine Science and Technology , 18(5), 746756.
Ming-Cheng, T., Sheng-Long, K. and Chien-Min, S. (2010). Decision Support from Genetic Algorithms for Ship Collision Avoidance Route Planning and Alerts. Journal of Navigation, 63(1), 167182.
NAV 59/INF.2. (2013). Development of an e-navigation Strategy Implementation Plan. Report on research project in the field of e-navigation submitted by Poland, IMO.
NCSR 1/6. (2014). Development of an e-Navigation Strategy Implementation Plan. Report of the Correspondence Group on e-navigation submitted by Norway, IMO.
NCSR 2/6. (2015). e-navigation Strategy Implementation Plan. Report of the Correspondence Group on Harmonization of Guidelines related to e-navigation submitted by Australia, IMO.
NCSR 2/INF.10. (2015). e-navigation Strategy Implementation Plan. A study on ship operator centred collision prevention and alarm system submitted by the Republic of Korea, IMO.
Pietrzykowski, Z. (2010). Maritime Intelligent Transport Systems, Communications in Computer and Information Science, 104, 455462.
Pietrzykowski, Z., Banaś, P., Wójcik, A. and Szewczuk, T. (2013). Communication Automation in Maritime Transport, Monograph Navigational Problems - Marine Navigation and Safety of Sea transportation, 287291.
Pietrzykowski, Z., Banaś, P., Wójcik, A. and Szewczuk, T. (2014a). Information Exchange Automation in Maritime Transport, International Journal on Marine Navigation and Safety of Sea Transportation, 8, 189193.
Pietrzykowski, Z., Borkowski, P. and Wołejsza, P. (2012). Marine integrated navigational decision support system, Communications in Computer and Information Science, 329, 284292.
Pietrzykowski, Z., Magaj, J. and Maka, M. (2014b). Safe Ship Trajectory Determination in the ENC Environment, Communications in Computer and Information Science, 471, 130136.
Pietrzykowski, Z., Magaj, J., Wołejsza, P. and Chomski, J. (2010). Fuzzy logic in the navigational decision support process onboard a sea-going vessel, Lecture Notes in Computer Science, 6113, 185193.
Pietrzykowski, Z. and Uriasz, J. (2009). The ship domain – a criterion of navigational safety assessment in an open sea area. Journal of Navigation, 62, 93108.
Qingyang, X., Chuang, Z. and Ning, W. (2014). Multiobjective Optimization Based Vessel Collision Avoidance Strategy Optimization, Mathematical Problems in Engineering, Volume, Article ID 914689.
Śmierzchalski, R., Kuczkowski, Ł., Kolendo, P. and Jaworski, B. (2013). Distributed Evolutionary Algorithm for Path Planning in Navigation Situation, TransNav, The International Journal on Marine Navigation and Safety of Sea Transportation, 7(2), 293300,
Śmierzchalski, R. and Michalewicz, Z. (2000). Modelling of a ship trajectory in collision situations at sea by evolutionary algorithm. IEEE Transaction on Evolutionary Computation , 4(3), 227244.
Stateczny, A. and Kazimierski, W. (2008). Determining manoeuvre detection threshold of GRNN filter in the process of tracking in marine navigational radars, Proceedings of the International Radar Symposium, 242–245.
Stawicki, K. (2008). Modelling of last minute manoeuvre in collision situation at sea, Scientific Journal of Gdynia Maritime University, 22, 8091.
Szłapczyńska, J. (2013), Multicriteria Evolutionary Weather Routing Algorithm in Practice. TransNav, The International Journal on Marine Navigation and Safety of Sea Transportation, 7(1), 6165.
Szłapczyński, R. (2011). Evolutionary Sets of Safe Ship Trajectories: A New Approach to Collision Avoidance, Journal of Navigation, 64(1), 169181.
Tzannatos, E. and Kokotos, D. (2009). Analysis of accidents in Greek shipping during the pre-and post-ISM period. Marine Policy, 33(4), 679684.
Wang, Y. and Chin, H-Ch. (2016). An Empirically-Calibrated Ship Domain as a Safety Criterion for Navigation in Confined Waters. Journal of Navigation, 69(2), 257276.
Weintrit, A. (2009). The Electronic Chart Display and Information System (ECDIS): An Operational Handbook, CRC Press.
Wójcik, A., Banaś, P. and Pietrzykowski, Z. (2014). The schema of inference processes in a preliminary identification of navigational situation in maritime transport, Communications in Computer and Information Science, 471, 304312.
Wołejsza, P. (2013). Functionality of navigation decision supporting system – NAVDEC. Navigational Problems, 1, 4346.
Wołejsza, P. (2014). Navigation decision supporting system (NAVDEC) – testing in real condition, Annual of Navigation, 21, 177186.
Wołejsza, P., Magaj, J. and Gralak, R. (2013). Navigation Decision Supporting System (NAVDEC) - testing on full mission simulator. Annual of Navigation, 20, 149162.

Keywords

Decision Support in Collision Situations at Sea

  • Zbigniew Pietrzykowski (a1), Piotr Wołejsza (a1) and Piotr Borkowski (a1)

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