Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-27T11:22:47.530Z Has data issue: false hasContentIssue false
  • English
  • Français

Review of Collision Avoidance and Path Planning Methods for Ships in Close Range Encounters

Published online by Cambridge University Press:  15 June 2009

CheeKuang Tam ,
Richard Bucknall  and
Alistair Greig
CheeKuang Tam*
Affiliation:
(University College London)
Richard Bucknall
Affiliation:
(University College London)
*
(Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Efficient marine navigation through obstructions is still one of the many problems faced by the mariner. Many accidents can be traced to human error, recently increased traffic densities and the average cruise speed of ships impedes the collision avoidance decision making process further in the sense that decisions have to be made in reduced time. It seems logical that the decision making process be computerised and automated as a step forward to reduce the risk of collision. This article reviews the development of collision avoidance techniques and path planning for ships, particularly when engaged in close range encounters. In addition, previously published works have been categorised and their shortcomings highlighted in order to identify the ‘state of the art’ and issues in close range marine navigation.

Keywords

Path planningShip navigationCollision avoidance
Type
Research Article
Information
The Journal of Navigation , Volume 62 , Issue 3 , July 2009 , pp. 455 - 476
Copyright
Copyright © The Royal Institute of Navigation 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Benjamin, Michael & Curcio, Joseph (2004), ‘Colregs-based navigation of autonomous marine vehicles’, IEEE/OES autonomous underwater vehicles pp. 32–39.Google Scholar
Calvert, E. S. (1960), ‘Manoeuvres to ensure the avoidance of collision’, The Journal of Navigation, 13, 127–137.CrossRefGoogle Scholar
Calvert, E. S. (1961), ‘A comparison of two systems for avoiding collision’, The Journal of Navigation, 14, 387–401.Google Scholar
Cannell, W. P. (1981), ‘Collision avoidance as a game of co-ordination’, The Journal of Navigation, 34, 220–239.CrossRefGoogle Scholar
Chang, Ki-Yin, Jan, Gene Eu & Parberry, Ian (2003), ‘A method for searching optimal routes with collision avoidance on raster charts’, The Journal of Navigation, 56, 371–384.CrossRefGoogle Scholar
Churkin, Vladimir I. & Zhukov, Yuri I. (1998), ‘Procedures for ship collision avoidance’, OCEANS'98 Conference Proceedings 2, 857–860.CrossRefGoogle Scholar
Coenen, F. P., Smeaton, G. P. & Bole, A. G. (1989), ‘Knowledge-based collision avoidance’, The Journal of Navigation, 42, 107–116.CrossRefGoogle Scholar
Coldwell, T. G. (1983), ‘Marine traffic behaviour in restricted waters’, The Journal of Navigation, 36, 430–444.CrossRefGoogle Scholar
Colley, B. A. & Stockel, C. T. (1984), ‘A marine traffic flow and collision avoidance computer simulation’, Journal of Navigation, 37, 232–250.CrossRefGoogle Scholar
Colley, B. A., Curtis, R. G. & Stockel, C. T. (1983), ‘Manoeuvring times, domains and arenas’, The Journal of Navigation, 36, 324–328.CrossRefGoogle Scholar
Curtis, Robert G., Goodwin, Elisabeth M. & Konyn, Mark (1987), ‘The autonatic detection of reallife ship encounters’, The Journal of Navigation, 40, 355–365.CrossRefGoogle Scholar
Davis, P. V., Dove, M. J. & Stockel, C. T. (1980), ‘A computer simulation of marine traffic using domains and arenas’, The Journal of Navigation, 33, 215–222.CrossRefGoogle Scholar
Degré, T. & Lefèvre, X. (1981), ‘A collision avoidance system’, The Journal of Navigation, 34, 294–302.CrossRefGoogle Scholar
Dove, M. J., Burns, R. S. & Stockel, C. T. (1986), ‘An automatic collision avoidance and guidance system for marine vehicles in confined waters’, The Journal of Navigation, 39, 180–190.CrossRefGoogle Scholar
Fujii, Yahei & Tanaka, Kenichi (1971), ‘Studies in marine traffic engineering: Traffic capacity’, The Journal of Navigation, 24, 543–552.CrossRefGoogle Scholar
Garau, Bartolome, Alvarez, Alberto & Oliver, Gabriel (2005), ‘Path planning of autonomous underwater vehicles in current fields with complex spatial variability: an a* approach’, Proceedings of the 2005 IEEE International conference on robotics and automation, Barcelona, Spain pp. 194–198.Google Scholar
Goodwin, Elisabeth M. (1975), ‘A statistical study of ship domains’, The Journal of Navigation, 28, 328–341.Google Scholar
Gupta, Kamal K. (1998), ‘Overview and state of the art’, Practical motion planning in robotics: Current approaches and future directions pp. 3–8. John Wiley and Sons Ltd. ISBN: 0-471-98163-X.Google Scholar
Harry, Benford editor; William, A. Fox associate editor (1993), A Half century of maritime technology, 1943–1993 - written by a group of authorities, Jersey City, N.J.: Society of Naval Architects and Marine Engineers.Google Scholar
Hollingdale, S. H. (1961), ‘The mathematics of collision avoidance in two dimensions’, The Journal of Navigation, 14, 243–261.CrossRefGoogle Scholar
Holmes, J. D. (1980), ‘A statistical study of factors affecting navigation decision-making’, The Journal of Navigation, 33, 206–214.CrossRefGoogle Scholar
Hong, X., Harris, c. J. & Wilson, P. A. (1999), ‘Autonomous ship collision free trajectory navigation and control algorithms’, Proceedings of 1999 7th IEEE International Conference on Emerging Technologies and Factory Automation. ETFA '99. pp. 923–929.Google Scholar
Hwang, Cheng-Neng (2002), ‘The integrated design of fuzzy collision-avoidance and h1- autopilots on ships’, The Journal of Navigation, 55, 117–136.Google Scholar
Hwang, Cheng-Neng, Yang, Joe-Ming & Chiang, chung Yen (2001), ‘The design of fuzzy collision avoidance expert system implemented by h1-autopilot’, Journal of Marine Science and Technology 9, 25–37.CrossRefGoogle Scholar
Iijima, Yokito & Hagiwara, Hideki (1991), ‘Results of collision avoidance manouvre experiments using a knowledge-based autonomous piloting system’, The Journal of Navigation, 44, 194–204.CrossRefGoogle Scholar
IMO (2005), ‘Imo safety’. [Online; accessed 12-December-2005] http://www.imo.org/.Google Scholar
Ito, Masanori, Zhang, Feifei & Yoshida, Norimoto (1999), ‘Collision avoidance control of ship with genetic algorithm’, Proceedings of the 1999 IOOO international conference on control applications pp. 1791–1796.Google Scholar
James, M. K. (1986), ‘Modelling the decision process in computer simulation of ship navigation’, The Journal of Navigation, 39, 32–48.Google Scholar
Jones, K. D. (1974), ‘Application of a manoeuvre diagram to multi-ship encounters’, The Journal of Navigation, 27, 19–27.CrossRefGoogle Scholar
Jones, K. D. (1978), ‘Decision makin when using collisin avoidance systems’, The Journal of Navigation, 31, 272–282.Google Scholar
Kortenkamp, David, Bonasso, R. Peter & Murphy, Robin, eds (1998), Artificial Intelligence and Mobile Robots, American Association for Artificial Intelligence.Google Scholar
Lee, Han-Jin & Rhee, Key-Pyo (2001), ‘Development of collision avoidance system by using expert system and search algorithm’, Journal of International Shipbuilding Progress 48, 197–212.Google Scholar
Lee, Young-Il & Kim, Yong-Gi (2004), ‘A collision avoidance system for autonomous ship using fuzzy relational products and COLREGS’, Proceedings of Intelligent Data Engineering and Automated Learning (IDEAL) 2004: 5th International Conference, Exeter, UK. 25–27 August pp. 247–252.Google Scholar
Lisowski, J. (2006), ‘The dynamic game theory methods applied to ship control with minimum risk of collision’, WIT Transactions on ecology and the environment 91, 293–302.Google Scholar
Liu, YuoHong & Shi, Chao-Jian (2005), ‘A fuzzy-neural inference network for ship collision avoidance’, Proceedings of the 4th international conference on machine learning and cybernetics, Guangzhou, China.Google Scholar
May, M. (1999), ‘Cognitive aspects of interface design and human-centered automation on the ship bridge: The example of arpa/ecdis integration’, People in control: An international conference on human interfaces in control rooms, cockpits and command centres pp. 394–399.Google Scholar
Merz, A. W. & Karmakar, J. S. (1976), ‘Collision avoidance systems and optimal turn manoeuvres’, The Journal of Navigation, 29, 160–174.Google Scholar
Miele, A., Wang, T., Chao, C. S. & Dabney, J. B. (1999), ‘Optimal control of a ship for collision avoidance manoeuvres’, Journal of Optimization Theory and Applications 103, 495–519.Google Scholar
Mitrofanov, O. (1968), ‘An anti-collision indicator’, The Journal of Navigation, 21, 163–170.Google Scholar
Moravec, Hans P. & Alberto, E. Elfes (1985), ‘High resolution map from wide angle sonar’, Proceedings of the IEEE International Conference on Robotics and Automation. Los Alamitos, California.Google Scholar
Morrel, J. S. (1961), ‘The physics of collision at sea’, The Journal of Navigation, 14, 163–184.CrossRefGoogle Scholar
Nathaniel, Bowditch LL.D. (1995), The American Practical Navigator, An epitome of navigation, 1995 edn, National imagery and mapping agency.Google Scholar
Pedersen, Egil, Inoue, Kinzo & Tsugane, Masanori (2002a), ‘Evaluation of a radar plot and display technique for anti-collision assessment of multiple targets in true vector representation by application of the environmental stress model’, Journal Japan Institute of Navigation, 106, 1–12.Google Scholar
Pedersen, Egil, Inoue, Kinzo & Tsugane, Masanori (2002b), ‘On decision making in connection with optimal anti-collision manoeuvres by high speed craft in waters congested by conventional speed vessels’, Journal Japan Institute of Navigation, 107, 177–183.Google Scholar
Petersen, Egil, Inoue, Kinzo & Tsugane, Masanori (2003), ‘Simulator studies on a collision avoidance display that facilitates efficient and precise assessment of evasive manoeuvres in congested waterways’, The Journal of Navigation, 56, 411–427.Google Scholar
Phillips, Robert (1975), ‘The avoidance of accidence at sea’, The Journal of Navigation, 28, 66–76.Google Scholar
Sharpey-Schafer, Commander J. M. (1955), ‘Collision at sea’, The Journal of Navigation, 8, 261–280.Google Scholar
Smeaton, G. P. & Coenen, F. P. (1990), ‘Developing an intellifent marine navigation system’, March, 95–103.Google Scholar
Smierzchalski, Roman (1999), ‘Evolutionary trajectory planning of ships in navigation traffic areas’, Journal of Marine Science and Technology 4, 1–6.CrossRefGoogle Scholar
Smierzchalski, Roman & Andrzej, Lebkowski (2006), ‘Intelligent ship steering system’, Proceedings of the 7th IFAC Conference on Manoeuvring and Control of Marine Craft.Google Scholar
Statheros, Thomas, Howells, Gareth & McDonald-Maier, Klaus (2008), ‘Autonomous ship collision avoidance navigation concepts, technologies and techniques’, The Journal of Navigation, 61, 129–142.Google Scholar
Szlapcynski, Rafal (2006a), ‘A new method of ship routing on raster grids, with turn penalties and collision avoidance’, The Journal of Navigation, 59, 27–42.Google Scholar
Szlapcynski, Rafal (2006b), ‘A unified measure of collision risk derived from the concept of a ship domain’, The Journal of Navigation, 59, 477–490.Google Scholar
Wepster, Captain A. (1969), ‘The future of merchant marine navigation’, The Journal of Navigation, 22, 92–107.Google Scholar
Wilson, P. A., Harris, C. J. & Hong, X. (2003), ‘A line of sight counteraction navigation algorithm for ship encounter collision avoidance’, The Journal of Navigation, 56, 111–121.Google Scholar
Wylie, Captain F. J. (1962), ‘Mathematics and the collision regulations’, The Journal of Navigation, 15, 104–112.Google Scholar
Zeng, Xiaoming (2003), ‘Evolution of the safe path for ship navigation’, Applied artificial intelligence 17:2, 87–104.Google Scholar
Zhu, XiaoLin, Xu, HanZhen & Lin, JunQing (2001), ‘Domain and its model based on neural networks’, The Journal of Navigation, 54, 97–103.Google Scholar