Information Unfitness of AIS

Felski, Andrzej; Jaskólski, Krzysztof · 2012 · Crossref

DOI: 10.2478/v10367-012-0002-z

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Summary

This paper investigates the reliability of dynamic data transmitted by the Automatic Identification System (AIS), specifically addressing concerns regarding its suitability for collision avoidance decision-making. While radar and ARPA systems are standard for collision avoidance, they suffer from limitations such as sea clutter, detection dead zones, and inaccuracies in bearing and distance. AIS is often proposed as a supplementary source of high-accuracy data derived from GNSS. However, practitioners have expressed skepticism regarding the consistency of AIS dynamic data. Although previous research focused on the integrity of static AIS data (Message No. 5), this study addresses a gap in the literature by analyzing the completeness and quality of dynamic information—specifically True Heading (HDG) and Rate of Turn (ROT)—which are critical for calculating Closest Point of Approach (CPA) and executing anti-collision maneuvers. The researchers conducted an analysis of AIS position reports (Messages 1, 2, and 3) recorded in the Gulf of Gdańsk. The study examined AIVDM text files containing recorded AIS messages over two distinct periods: a preliminary analysis of a single day in April 2006, and a more extensive study covering 49 selected days between April 2006 and January 2011. The methodology involved assessing the incompleteness of specific data fields within these messages. The authors defined "unfitness" based on two metrics: the percentage of AIVDM sentences containing incomplete information and the percentage of vessels responsible for transmitting such incomplete data. Statistical measures, including arithmetic means, medians, maximums, minimums, standard deviations, and variance, were calculated to evaluate the consistency of the data quality over time. The results indicate significant levels of data incompleteness, particularly for Rate of Turn and True Heading. In the initial 2006 analysis, approximately 23% of messages contained incomplete Rate of Turn data, originating from about 24% of ships. Incomplete True Heading data was found in roughly 16% of messages, associated with 19% of vessels. The extended study confirmed these trends, showing that while there was an imperceptible decrease in incompleteness rates in the 2010–2011 dataset compared to 2006, the issue remained prevalent. For instance, in the later period, the mean incompleteness for Rate of Turn sentences was 13.19%, affecting 23.36% of ships, while True Heading incompleteness averaged 13.58% of sentences, affecting 24.29% of ships. The data exhibited high variability, with standard deviations indicating significant fluctuations in data quality across different days and vessels. The study concludes that the application of AIS information for collision maneuvering is constrained by the frequent incompleteness of dynamic data fields. The high variance and persistent rates of missing or incorrect HDG and ROT values suggest that AIS data cannot be blindly trusted for critical decision-making without verification. The findings validate practitioner concerns regarding the "information unfitness" of AIS, highlighting that a substantial portion of vessels transmit incomplete dynamic data. This implies that reliance on AIS for automated collision avoidance systems requires careful consideration of data integrity, and further investigation is needed to understand the sources of these inconsistencies.

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