HomePage
 




 


 

ISSN 2083-6473
ISSN 2083-6481 (electronic version)
 

 

 

Editor-in-Chief

Associate Editor
Tomasz Neumann
 

Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
www http://www.transnav.eu
e-mail transnav@am.gdynia.pl
Multi-criteria ACO-based Algorithm for Ship's Trajectory Planning
1 Gdynia Maritime University, Gdynia, Poland
ABSTRACT: The paper presents a new approach for solving a path planning problem for ships in the environment with static and dynamic obstacles. The algorithm utilizes a heuristic method, classified to the group of Swarm Intelligence approaches, called the Ant Colony Optimization. The method is inspired by a collective behaviour of ant colonies. A group of agents - artificial ants searches through the solution space in order to find a safe, optimal trajectory for a ship. The problem is considered as a multi-criteria optimization task. The criteria taken into account during problem solving are: path safety, path length, the International Regulations for Preventing Collisions at Sea (COLREGs) compliance and path smoothness. The paper includes the description of the new multi-criteria ACO-based algorithm along with the presentation and discussion of simulation tests results.
REFERENCES
Ahn J.H., Rhee K.P., You Y.J. 2012: A study on the collision avoidance of a ship using neural networks and fuzzy logic, Applied Ocean Research, Vol. 37, pp. 162–173.
Escario, J. B., Jimenez, J. F. and Giron-Sierra, J. M. 2012: Optimisation of autonomous ship manoeuvres applying ant colony optimisation metaheuristic, Expert Systems with Applications, Vol. 39 (11), pp. 10120–10139.
Fossen T.I. 2011: Handbook of Marine Craft Hydrodynamics and Motion Control, 1st ed., John Wiley & Sons, Ltd.
Hornauer S., Hahn A. 2013: Towards Marine Collision Avoidance Based on Automatic Route Exchange, 9th IFAC Conference on Control Applications in Marine Systems, Vol. 46 (33), pp. 103–107.
Lazarowska A. 2013: Application of Ant Colony Optimization in Ship's Navigational Decision Support System, In: A. Weintrit (ed.), Navigational Problems, Marine Navigation and Safety of Sea Transportation, CRC Press/Balkema, London, UK, pp. 53–62.
Lisowski J. 2016b: The sensitivity of state differential game vessel traffic model, Polish Maritime Research, Vol. 23, Issue 2, pp. 14–18.
Liu Y., Bucknall R. 2015: Path planning algorithm for unmanned surface vehicle formations in a practical maritime environment, Ocean Engineering, Vol. 97, pp. 126–144.
Mohamed-Seghir M. 2016: Computational Intelligence Method for Ship Trajectory Planning, Proceedings of the 21st International Conference on Methods and Models in Automation and Robotics, pp. 1–6.
Naeem, W., Irwin, G., Yang, A. 2012: Colregs-based collision avoidance strategies for unmanned surface vehicles, Mechatronics, Vol. 22, pp. 669–678.
Perera L., J. Carvalho J., Guedes Soares C. 2011: Fuzzy logic based decision making system for collision avoidance of ocean navigation under critical collision conditions, Journal of Marine Science and Technology, Vol. 16 (1), pp. 84–99.
Simsir U., Amasyali M.F., Bal M., Celebi U.B., Ertugrul S. 2014: Decision support system for collision avoidance of vessels, Applied Soft Computing, Vol. 25, pp. 369–378.
Tam, C., Bucknall, R. 2010: Path-planning algorithm for ships in close-range encounters, Journal of Marine Science and Technology, Vol. 15, pp. 395–407.
Tam, C., Bucknall, R. 2013: Cooperative path planning algorithm for marine surface vessels, Ocean Engineering, Vol. 57, pp. 25–33.
Tsou, M., Hsueh, C. 2010: The study of ship collision avoidance route planning by ant colony algorithm, Journal of Marine Science and Technology-TAIWAN, Vol. 18, pp. 746–756.
Tsou, M., Kao, S., Su, C. 2010: Decision support from genetic algorithms for ship collision avoidance route planning and alerts, Journal of Navigation, Vol. 63, pp. 167–182.
Xue, Y., Clelland, D., Lee, B., Han, D. 2011: Automatic simulation of ship navigation, Ocean Engineering, Vol. 38, pp. 2290–2305.
Citation note:
Lazarowska A.: Multi-criteria ACO-based Algorithm for Ship's Trajectory Planning. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 11, No. 1, doi:10.12716/1001.11.01.02, pp. 31-36, 2017
Authors in other databases:

Other publications of authors:


File downloaded 479 times








Important: TransNav.eu cookie usage
The TransNav.eu website uses certain cookies. A cookie is a text-only string of information that the TransNav.EU website transfers to the cookie file of the browser on your computer. Cookies allow the TransNav.eu website to perform properly and remember your browsing history. Cookies also help a website to arrange content to match your preferred interests more quickly. Cookies alone cannot be used to identify you.
Akceptuję pliki cookies z tej strony