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Automated Traffic Route Identification through the Shared Nearest Neighbour Algorithm
April 2012
Santos12
In maritime transportation the automated identification of a diverse range of traffic routes is a key management issue for improving the maintenance of ports and ocean routes. This paper develops an approach for the automated identification of traffic routes based on clustering motion vectors rather thanreconstructed trajectories. The immediate benefit of the proposed approach is to avoid the reconstruction of trajectories. For clustering the moving objects, an adapted version of the Shared Nearest Neighbour algorithm is used. The motion vectors, with a position and a direction, are analysed in order to identify clusters of vectors that are moving towards the same direction. These clusters represent traffic routes and the preliminary results have shown to be promisingfor the automated identification of traffic routes with different shapes and densities, as well as for handling noise data.
In proceedings
Maribel Yasmina Santos, Joaquim Silva, João Moura Pires, Monica Wachowicz
15h AGILE International Conference on Geographic Information Science
Bridging the Geographic Information Sciences
Springer
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Maribel Yasmina Santos and Joaquim Silva and João Moura Pires and Monica Wachowicz, Automated Traffic Route Identification through the Shared Nearest Neighbour Algorithm, , 15h AGILE International Conference on Geographic Information Science, Bridging the Geographic Information Sciences, Springer, April 2012.
Maribel Yasmina Santos, Joaquim Silva, <a href="/people/members/view.php?code=542b14e1830dcf7566974fd36b6fccc7" class="author">João Moura Pires</a> and Monica Wachowicz, <b>Automated Traffic Route Identification through the Shared Nearest Neighbour Algorithm</b>, <u>15h AGILE International Conference on Geographic Information Science</u>, Bridging the Geographic Information Sciences, <a href="http://www.springer.com" title="Link to external entity..." target="_blank" class="publisher">Springer</a>, April 2012.
@inproceedings {Santos12, author = {Maribel Yasmina Santos and Joaquim Silva and Jo{\~a}o Moura Pires and Monica Wachowicz}, title = {Automated Traffic Route Identification through the Shared Nearest Neighbour Algorithm}, booktitle = {15h AGILE International Conference on Geographic Information Science}, series = {Bridging the Geographic Information Sciences}, publisher = {Springer}, abstract = {In maritime transportation the automated identification of a diverse range of traffic routes is a key management issue for improving the maintenance of ports and ocean routes. This paper develops an approach for the automated identification of traffic routes based on clustering motion vectors rather thanreconstructed trajectories. The immediate benefit of the proposed approach is to avoid the reconstruction of trajectories. For clustering the moving objects, an adapted version of the Shared Nearest Neighbour algorithm is used. The motion vectors, with a position and a direction, are analysed in order to identify clusters of vectors that are moving towards the same direction. These clusters represent traffic routes and the preliminary results have shown to be promisingfor the automated identification of traffic routes with different shapes and densities, as well as for handling noise data.}, month = {April}, year = {2012}, }
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