Navigational risk assessment of inland waters based on bi-directional PSO-LSTM algorithm and ship maneuvering characteristics

Lei Zhang, Yuxuan Zhu, Osiris A. Valdez Banda, Lei Du*, Langxiong Gan, Xiaobin Li

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

Inland waterways are characterized by various bends, complex intersections and high traffic density. This complex inland navigation environment brings challenges to vessel traffic service (VTS) in managing inland water traffic. We propose a method to assess navigational risk of inland waters based on bi-directional PSO-LSTM algorithm and ship maneuvering characteristics. First, a bi-directional PSO-LSTM based ship trajectory restoration model is established to repair the Automatic identification System (AIS) data. Subsequently, ship behavioral characteristics are extracted from these repaired AIS data, based on which the model of ship navigation risk assessment in inland waters is established using window approach. Several case studies are conducted to verify this proposed method. The promising results attest that this proposed bi-directional PSO-LSTM algorithm outperforms the traditional neural network and trajectory restoration models. In addition, this navigational risk assessment of inland waters can effectively identify complex waters with high navigational risks, which are consistent with the actual situation. This research helps support VTS in regulating ship traffic in inland waters, thereby ensuring the safety of ship navigation on inland waterways.

Original languageEnglish
Article number118628
Number of pages12
JournalOcean Engineering
Volume310
DOIs
Publication statusPublished - 15 Oct 2024
MoE publication typeA1 Journal article-refereed

Keywords

  • AIS data
  • Inland waters
  • Navigational risk assessment
  • Ship trajectory restoration

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