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Ship route planning using historical trajectories derived from AIS Data

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Ship route planning is one of the key issues in enhancing traffic safety and efficiency. Many route planning methods have been developed, but most of them are based on the information from charts. This paper proposes a method to generate shipping routes based on historical ship tracks. The ship's historical route information was obtained by processing the AIS data. From which the ship turning point was extracted and clustered as nodes. The ant colony algorithm was used to generate the optimize route. The ship AIS data of the Three Gorges dam area was selected as a case study. The ships’ optimized route was generated, and further compared with the actual ship's navigation trajectory. The results indicate that there is space of improvement for some of the trajectories, especially near the turning areas.
Twórcy
autor
  • Wuhan University of Technology, Wuhan, China
  • National Engineering Research Center for Water Transport Safety, Wuhan, China
autor
  • Wuhan University of Technology, Wuhan, China
  • National Engineering Research Center for Water Transport Safety, Wuhan, China
autor
  • Wuhan University of Technology, Wuhan, China
  • National Engineering Research Center for Water Transport Safety, Wuhan, China
autor
  • Wuhan University of Technology, Wuhan, China
  • National Engineering Research Center for Water Transport Safety, Wuhan, China
autor
  • ChangJiang Waterway Transportation Monitoring and Emergency Center, Wuhan, China
Bibliografia
  • 1. Dijkstra, E.W. 1959. A note on two problems in connexion with graphs. Numerische Mathematik 1: 269-271. - doi:10.1007/BF01386390
  • 2. Choi, M., Chung, H., Yamaguchi, H. & Nagakawa, K. 2015. Arctic sea route path planning based on an uncertain ice prediction model. Cold Regions Science and Technology 109: 61-69. - doi:10.1016j.coldregions.2014.10.001
  • 3. Kobayashi E., Asajima T., Sueyoshi N.: Advanced Navigation Route Optimization for an Oceangoing Vessel. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 5, No. 3, pp. 377-383, 2011
  • 4. Hänninen, M. & Kujala, P. 2014. Bayesian network modeling of Port State Control inspection findings and ship accident involvement. Expert Systems with Applications 41: 1632- 1646. - doi:10.1016/j.eswa.2013.08.060
  • 5. Lee, S.M., Roh, M., Kim, K.S., Jung, H. & Park, J. J. 2018. Method for a simultaneous determination of the path and the speed for ship route planning problems. Ocean Engineering 157: 301-312. - doi:10.1016/j.oceaneng.2018.03.068
  • 6. Mazaheri, A., Montewka, J. & Kujala, P. 2014. Modeling the risk of ship grounding - a literature review from a risk management perspective. WMU Journal of Maritime Affairs 13: 269-297. - doi:10.1007/s13437-013-0056-3
  • 7. Roh, M. 2013. Determination of an economical shipping route considering the effects of sea state for lower fuel consumption. International Journal of Naval Architecture and Ocean Engineering 5: 246-262. - doi:10.3744/JNAOE.2013.5.2.246
  • 8. Sang, L.Z., Wall, A., Mao, Z., Yan, X. & Wang, J. 2015. A novel method for restoring the trajectory of the inland waterway ship by using AIS data. Ocean Engineering 110: 183-194. - doi:10.1016/j.oceaneng.2015.10.021
  • 9. Tetreault, B.J. 2005. Use of the Automatic Identification System (AIS) for maritime domain awareness (MDA). Oceans. IEEE.
  • 10. Vettor, R. & Guedes Soares, C. 2016. Development of a ship weather routing system. Ocean Engineering 123: 1-14. - doi:10.1016/j.oceaneng.2016.06.035
  • 11. Wang, S., Gao, S. & Yang, W. 2017. Ship route extraction and clustering analysis based on automatic identification system data. 2017 Eighth International Conference on Intelligent Control and Information Processing (ICICIP). - doi:10.1109/ICICIP.2017.8113913
  • 12. Wang, Y., Zhang, J., Chen, X., Chu, X., & Yan, X. (2013). A spatial–temporal forensic analysis for inland–water ship collisions using AIS data. Safety Science, 57(Complete), 187-202. - doi:10.1016/j.ssci.2013.02.006
  • 13. Wang, Y., Zhang, J., Chen, X., Chu, X. & Yan, X. 2013. A spatial–temporal forensic analysis for inland–water ship collisions using AIS data. Safety Science 57: 187-202.
  • 14. Xiao, F., Ligteringen, H., Van Gulijk, C. & Ale, B. 2015. Comparison study on AIS data of ship traffic behavior. Ocean Engineering 95: 84-93. - doi:10.1016/j.oceaneng.2014.11.020
  • 15. Zhang, L., Meng, Q., Xiao, Z. & Fu, X. 2018. A novel ship trajectory reconstruction approach using AIS data. Ocean Engineering 159: 165-174. - doi:10.1016/j.oceaneng.2018.03.085
  • 16. Zhang, W., Goerlandt, F., Montewka J. & Kujala, P. 2015. A method for detecting possible near miss ship collisions from AIS data. Ocean Engineering 107: 60-69. - doi:10.1016/j.oceaneng.2015.07.046
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-274e5b3a-94d3-48bd-a00e-29f04c343bc0
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