The DOI matches its Crossref record.
Use of AIS Data to Characterise Marine Traffic Patterns and Ship Collision Risk off the Coast of Portugal
Abstract
This paper studies the risk of ship collision off the coast of Portugal based on Automatic Identification System (AIS) data, which is recorded and maintained by the Portuguese coastal Vessel Traffic Service (VTS) control centre (CCTMC). Computer programs for decoding, visualization and analysis of the AIS data have been developed. From analysis of the AIS data available, maritime traffic off the coast of Portugal is characterized and a statistical analysis of traffic in the Traffic Separation Schemes is provided. An algorithm has been developed to assess the risk profile and the relative importance of routes associated with ports. A method is proposed to calculate the collision risk from the assessment of the number of collision candidates by estimating future distances between ships based on their previous positions, courses and speeds, and comparing those distances with a defined collision diameter. Values of causation probability suggested in several studies are used to calculate the expected number of collisions in the period of time under investigation based on the number of collision candidates. The results of this study are then compared with the number of collisions that have occurred between 1997–2006, registered and maintained by the Portuguese Maritime Authority.
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Citations
Cited by
Ship trajectory uncertainty prediction based on a Gaussian Process model
Rong, H., Teixeira, A. P., & Guedes Soares, C. (2019) · Ocean Engineering · doi:10.1016/j.oceaneng.2019.04.024 · Cited by 313
Self-citationXiao, Z., Fu, X., Zhang, L., & Goh, R. S. M. (2020) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2019.2908191 · Cited by 205
Maritime Traffic Probabilistic Forecasting Based on Vessels’ Waterway Patterns and Motion Behaviors
Xiao, Z., Ponnambalam, L., Fu, X., & Zhang, W. (2017) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2681810 · Cited by 110
Metadata
- Authors
- Silveira, P. A. M., Teixeira, A. P., & Soares, C. G.
- Venue
- Journal of Navigation
- Publisher
- Cambridge University Press (CUP)
- Published
- 2013-08-09
- Volume
- 66
- Issue
- 6
- Pages
- 879-898
- ISSN
- 0373-4633 (ISSN-L)
- 1469-7785
- OpenAlex
- W2112514992
- Cited by
- 315
- References
- 0
- FWCI
- 12.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Use of AIS Data to Characterise Marine Traffic Patterns and Ship Collision Risk off the Coast of Portugal. https://app.cochat.ai/papers/10.1017/s0373463313000519
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- Silveira, P. A. M., Teixeira, A. P., & Soares, C. G. (2013). Use of AIS Data to Characterise Marine Traffic Patterns and Ship Collision Risk off the Coast of Portugal. Journal of Navigation. https://doi.org/10.1017/s0373463313000519
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.