Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-13T04:40:50.746Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimating Navigation Patterns from AIS

Published online by Cambridge University Press:  07 October 2009

Karl Gunnar Aarsæther  and
Torgeir Moan
Karl Gunnar Aarsæther*
Affiliation:
(Norwegian University of Science and Technology)
Torgeir Moan
Affiliation:
(Norwegian University of Science and Technology)
*
(Email: aarsathe@ntnu.no)
Get access Rights & Permissions [Opens in a new window]

Abstract

The Automatic Identification System (AIS) has proven itself to be a valuable source for ship traffic information. Its introduction has reversed the previous situation with scarcity of precise data from ship traffic and has instead posed the reverse challenge of coping with an overabundance of data. The number of time-series available for ship traffic and manoeuvring analysis has increased from tens, or hundreds, to several thousands. Sifting through these data manually, either to find the salient features of traffic, or to provide statistical distributions of decision variables is an extremely time consuming procedure. In this paper we present the results of applying computer vision techniques to this problem and show how it is possible to automatically separate AIS data in order to obtain traffic statistics and prevailing features down to the scale of individual manoeuvres and how this procedure enables the production of a simplified ship traffic model.

Keywords

AISManoeuvre models
Type
Research Article
Information
The Journal of Navigation , Volume 62 , Issue 4 , October 2009 , pp. 587 - 607
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

Aarsæther, K. G. & Moan, T. (2007). Combined manoeuvring analysis, ais and full-mission simulation. In Advances in Marine Navigation and safety of sea transportation, Proceedings from the 7th International symposium on Navigation (pp. 51–56). Gdynia, Poland.Google Scholar
Azzalini, A. 1985. A class of distributions which include the normal ones. Scandinavian Journal of Statistics 12: 171–178Google Scholar
Brown, L. G. (1992). A survey of image registration techniques. ACM Computing Surveys, 24(4), 325–376.Google Scholar
Graveson, A. (2004). AIS – an inexact science. The Journal of Navigation, 57, 339–343.Google Scholar
Gucma, L. & Goryczko, E. (2007). The implementation of oil spill costs model in the southern baltic sea area to assess the possible losses due to ships collisions. In Advances in marine navigation and safety of sea transportation, Proceedings from the 7th International symposium on Navigation (pp. 583–585). Gdynia, Poland.Google Scholar
Gucma, L. & Przywarty, M. (2007). The model of oil spills due to ships collisions in southern baltic area. In Advances in marine navigation and safety of sea transportation, Proceedings from the 7th International symposium on Navigation (pp. 593–597). Gdynia, Poland.Google Scholar
Harati-Mokhtari, A., Wall, A., Brooks, P., & Wang, J. (2007). Automatic identification system (ais): Data reliability and human error implications. The Journal of Navigation, 60, 373–389.Google Scholar
Lützhöft, M. H. & Nyce, J. N. (2006). Piloting by heart and by chart. The Journal of Navigation, 59, 221–237. 25CrossRefGoogle Scholar
Nocedal, J. & Wright, S. J. (1999). Numerical Optimization. Berlin: Springer-Verlag.CrossRefGoogle Scholar
Norris, A. (2007). Ais implementation – success or failure. The Journal of Navigation, 60, 1–10.Google Scholar
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (2007). Numerical Recipes – The Art of Scientific Computing. Cambridge University Press.Google Scholar
Zitova, B. & Flusser, J. (2003). Image registration methods: A survey. Image and Vision Computing, 21, 977–1000.CrossRefGoogle Scholar