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Application of Dempster–Shafer theory for the quantification and propagation of the uncertainty caused by the use of AIS data

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  • Talavera, Alejandro
  • Aguasca, Ricardo
  • Galván, Blas
  • Cacereño, Andrés

Abstract

This paper proposes a novel method to quantify the uncertainty inherent to the paths that ships will navigate in the future, from the information provided by the AIS system on the paths followed by the ships in the past. In the framework of the Dempster–Shafer theory, the proposed method analyzes the information contained in a known distribution of vessel traffic on a waterway to construct the corresponding Dempster–Shafer structure. From this structure, using the confidence limits of Kolmogorov–Smirnov, it is possible to estimate the evidential measures (belief and plausibility) of all possible distributions of traffic on that waterway.

Suggested Citation

  • Talavera, Alejandro & Aguasca, Ricardo & Galván, Blas & Cacereño, Andrés, 2013. "Application of Dempster–Shafer theory for the quantification and propagation of the uncertainty caused by the use of AIS data," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 95-105.
    • Handle: RePEc:eee:reensy:v:111:y:2013:i:c:p:95-105
    DOI: 10.1016/j.ress.2012.10.007
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    References listed on IDEAS

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    1. Goerlandt, Floris & Kujala, Pentti, 2011. "Traffic simulation based ship collision probability modeling," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 91-107.
    2. Montewka, Jakub & Hinz, Tomasz & Kujala, Pentti & Matusiak, Jerzy, 2010. "Probability modelling of vessel collisions," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 573-589.
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    Cited by:

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    2. Zhang, Mingyang & Montewka, Jakub & Manderbacka, Teemu & Kujala, Pentti & Hirdaris, Spyros, 2021. "A Big Data Analytics Method for the Evaluation of Ship - Ship Collision Risk reflecting Hydrometeorological Conditions," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Zhou, Jian-Lan & Lei, Yi & Chen, Yang, 2019. "A hybrid HEART method to estimate human error probabilities in locomotive driving process," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 80-89.
    4. Mazurek, J. & Lu, L. & Krata, P. & Montewka, J. & Krata, H. & Kujala, P., 2022. "An updated method identifying collision-prone locations for ships. A case study for oil tankers navigating in the Gulf of Finland," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
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    6. Gino J. Lim & Jaeyoung Cho & Selim Bora & Taofeek Biobaku & Hamid Parsaei, 2018. "Models and computational algorithms for maritime risk analysis: a review," Annals of Operations Research, Springer, vol. 271(2), pages 765-786, December.

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