An advanced method for detecting possible near miss ship collisions from AIS data
Research output: Contribution to journal › Article › Scientific › peer-review
- University of Washington
Maritime accidents have the potential to cause significant financial loss, injury, and damage to the environment. One approach to investigating maritime safety is to focus on near misses, that is, situations which did not lead to an accident but where an accident was narrowly avoided. Based on the principles of the traffic conflict technique, which ranks traffic encounters through a conflict severity hierarchy, this paper proposes a novel model for screening maritime traffic data for near miss ship-ship encounters, particularly for open sea and coastal restricted sea areas. Compared to previous methods, the proposed method has a greater specificity, leaving fewer possible near miss cases to be assessed by navigational experts in a contextualised traffic setting. This is achieved by including the effect of ship size through a ship domain, and by better accounting for the criticality of the encounter direction through the Minimum Distance To Collision concept compared to earlier proposed models. The factors included in the model and their relation are based on expert judgments and using knowledge from previous studies. Model parameters are derived from AIS data points from a reference encounter situation dataset. The developed model has been applied to traffic data from the Northern Baltic Sea. The model is subjected to a number of validity tests, the results of which suggest that the model is adequate for ranking and prioritizing encounters for further assessment in an expert judgment phase to identify near misses. Thus, it establishes a method to enable subsequent research into the validity of near miss information to make statements of maritime safety in relation to collision accidents.
|Number of pages||16|
|Publication status||Published - 15 Sep 2016|
|MoE publication type||A1 Journal article-refereed|
- AIS data, Maritime safety, Near miss, Ship-ship collision, Traffic conflict