Advertisement

Ships' domains as collision risk at sea in the evolutionary method of trajectory planning

  • Roman Śmierzchalski

Abstract

The goal of this paper is to discuss the problem of avoiding collisions at sea from the perspective of an evolutionary process and representation in this problem the risk of collision. In an evolutionary method (EP/N Evolutionary Planer Navigator System) of generating paths of the ship in partially-known environments is presented. The evolutionary process which searches for a near-optimum trajectory in a collision situation takes into account a time parameter and the dynamic constraints, which treat to the risk of collision with meeting strange ships. The ship domain as a risk of the collision - shapes and dimensions of dynamic constrains depend on assumed safety conditions.

Keywords

ship control evolutionary computation modelling risk 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

7 References

  1. [1]
    Burns RS, An Intelligent Integrated Ship Guidance System. 2nd IFAC Workshop Control Applications in Marine Systems, Genova, Italy 1992.Google Scholar
  2. [2]
    Dove MJ, Burns RS, Stockel CT, An Automatic Collision Avoidance and Guidance System for Marine Vehicles in Confined Waters. Journal of Navigation, Vol. 39 1986.Google Scholar
  3. [3]
    Davis P.V., Dove M.J., Stockel C.T., Computer Simulation of Multiship Encounters, Journal of Navigation, 1982, Vol. 35.Google Scholar
  4. [4]
    Furuhashi T, Nakaoka K, Uchikawa Y, A Study on Classifier System for Finding Control Knowledge of Multi-Input Systems F. Herrera, J.L. Verdegay Editors. Genetic Algorithms and Soft Computing, Phisica-Verlang 1996.Google Scholar
  5. [5]
    Goodwin E.M., A statistical study of ship domains, Journal of Navigation, 1975, Vol. 31.Google Scholar
  6. [6]
    Hayashi S, Kuwajima S, Sotooka K, Yamakazi H, Murase H, A stranding avoidance system using radar image matching: development and experiment. Journal of Navigation, Vol. 44 1991.Google Scholar
  7. [7]
    Iijima Y, Hayashi S, Study towards a twenty-first century intelligent ship. Journal of Navigation, Vol. 44 1991.Google Scholar
  8. [8]
    Iijima Y, Hagiwara, H Results of Collision Avoidance Manoeuvre Experiments Using a Knowledge-Based Autonomous Piloting System. Journal of Navigation, Vol. 47, 1994.Google Scholar
  9. [9]
    Lenart, A.S., Collision Threat Parameters for a New Radar Display and Plot Technique, Journal of Navigation, 1983, Vol. 36.Google Scholar
  10. [10]
    Lin HS, Xiao J, Michalewicz Z, Evolutionary Algorithm for Path Planning in Mobile Robot Environment. Proceeding IEEE Int. Conference of Evolutionary Computation, Orlando, Florida, 1994.Google Scholar
  11. [11]
    Michalewicz Z, Genetic Algorithms + Data structures = Evolution Programs. Spriger-Verlang, 3rd edition 1996.Google Scholar
  12. [12]
    Michalewicz Z, Xiao J, Evaluation of Paths in Evolutionary Planner/Navigator. Proceedings of the International Workshop on Biologically Inspired Evolutionary Systems, Tokyo, Japan 1995.Google Scholar
  13. [13]
    Śmierzchalski R, The Application of the Dynamic Interactive Decision Analysis System to the Problem of Avoiding Collisions at the Sea (in Polish). 1st Conference “Awioniki”, Jawor, Poland, 1995.Google Scholar
  14. [14]
    Śmierzchalski R, The Decision Support System to Design the Safe Manoeuvre Avoiding Collision at Sea. 14th International Conference Information Systems Analysis and Synthesis, Orlando, USA, 1996.Google Scholar
  15. [15]
    Śmierzchalski R, Multi-Criterion Modeling the Collision Situation at Sea for Application in Decision Support. 3rd International Symp. on Methods and Models in Automation and Robotics, Miedzyzdroje, Poland 1996.Google Scholar
  16. [16]
    Śmierzchalski R, Trajectory planning for ship in collision situations at sea by evolutionary computation. 4th IFAC Conference on Manoeuvring and Control of Marine, Brijuni, Creotia, 1997.Google Scholar
  17. [17]
    Śmierzchalski R, Dynamic Aspect in Evolutionary Computation on Example of Avoiding Collision at Sea. 4th International Symp. on Methods and Models in Automation and Robotics, Międzyzdroje, Poland 1997.Google Scholar
  18. [18]
    Śmierzchalski R, Evolutionary Guidance System for Ship in Collisions Situation at Sea. 3rd IFAC Conference Intelligent Autonomous Vehicle, Madrid, Spain 1997.Google Scholar
  19. [19]
    Śmierzchalski R, Michalewicz Z, Adaptive Modeling of a Ship Trajectory in Collision Situations. 2nd IEEE World Congress on Computational Intelligence, Alaska, USA 1998.Google Scholar
  20. [20]
    Sudhendar H, Grabowski M, Evolution of Intelligent Shipboard Piloting Systems: A Distributed System for the St Lawrence Seaway. Journal of Navigation, Vol. 49 1996.Google Scholar
  21. [21]
    Wawruch R.: System of steering ship movement. Works of Navigational Department, Gdynia Maritime Academy, Gdynia 1998.Google Scholar
  22. [22]
    Trojanowski K, Michalewicz Z, Planning Path of Mobil Robot (in Polish). 1st Conference Evolutionary Algorithms, Murzasichle, Poland 1998.Google Scholar
  23. [23]
    Witt NA, Sutton R, Miller KM, Recent Technological Advances in the Control and Guidance of Ship. Journal of Navigation Vol. 47, 1994.Google Scholar
  24. [24]
    Xiao J, Michalewicz Z, Zhang L, Evolutionary Planner/Navigator: Operator Performance and Self-Tuning. Proceeding IEEE Int. Conference of Evolutionary Computation, Nagoya, Japan 1996.Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Roman Śmierzchalski
    • 1
  1. 1.Gdynia Maritime UniversityGdyniaPoland

Personalised recommendations