NDLI: Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

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Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

Content Provider	MDPI
Author	Du, Lei Banda, Osiris Valdez Goerlandt, Floris Kujala, Pentti Zhang, Weibin
Copyright Year	2021
Description	Ship collision is the most common type of accident in the Northern Baltic Sea, posing a risk to the safety of maritime transportation. Near miss detection from automatic identification system (AIS) data provides insight into maritime transportation safety. Collision risk always triggers a ship to maneuver for safe passing. Some frenetic rudder actions occur at the last moment before ship collision. However, the relationship between ship behavior and collision risk is not fully clarified. Therefore, this work proposes a novel method to improve near miss detection by analyzing ship behavior characteristic during the encounter process. The impact from the ship attributes (including ship size, type, and maneuverability), perceived risk of a navigator, traffic complexity, and traffic rule are considered to obtain insights into the ship behavior. The risk severity of the detected near miss is further quantified into four levels. This proposed method is then applied to traffic data from the Northern Baltic Sea. The promising results of near miss detection and the model validity test suggest that this work contributes to the development of preventive measures in maritime management to enhance to navigational safety, such as setting a precautionary area in the hotspot areas. Several advantages and limitations of the presented method for near miss detection are discussed.
Starting Page	180
e-ISSN	20771312
DOI	10.3390/jmse9020180
Journal	Journal of Marine Science and Engineering
Issue Number	2
Volume Number	9
Language	English
Publisher	MDPI
Publisher Date	2021-02-10
Access Restriction	Open
Subject Keyword	Journal of Marine Science and Engineering Marine Engineering Near Miss Ship Behavior Ais Data Northern Baltic Sea
Content Type	Text
Resource Type	Article

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