A Probability-Based Reliability Model for Evaluating Ro-Ro Ferry Sailing Speed Compliance Using AIS Data
DOI:
https://doi.org/10.35870/ijsecs.v6i2.7589Keywords:
Automatic Identification System (AIS), Service-Speed Reliability, Probability Distribution, Weibull Distribution, Monte Carlo Simulation, Ro-Ro FerryAbstract
Automatic Identification System (AIS) data provide continuous operational records that can be transformed into computational indicators for evaluating maritime service performance. This study develops a simplified AIS-based probabilistic model for assessing Ro-Ro ferry service-speed reliability through sailing-speed compliance. Speed over Ground (SOG) observations were used to determine whether vessels operated within a predefined reliable speed range during sailing. The reliable speed range was defined as 7-9 knots, while sailing observations were identified using a simplified SOG filter of 3-15 knots. From 32,358 raw AIS messages collected between 1 January and 31 March 2026, 11,166 sailing observations were retained for analysis. The observation-based reliability was 35.63%, whereas the duration-based reliability was 36.63%, indicating that 324.76 of 886.64 estimated sailing hours were spent within the reliable speed range. Probability distribution fitting showed that the Weibull distribution provided the best parametric fit based on the lowest Akaike Information Criterion. The cumulative distribution function indicated a 35.88% probability of operating within the 7-9 knot range. Monte Carlo bootstrap resampling with 10,000 iterations produced a 95% confidence interval of 34.75-36.53% for observation-based reliability and 35.38-37.88% for duration-based reliability. The findings show that AIS data can support a reproducible and computationally simple screening approach for evaluating ferry service-speed reliability.
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Copyright (c) 2026 Hardiyanto Hardiyanto, Andri Nofiar. Am, Teguh Widodo, Supria Supria, Depandi Enda, Zulyani Zulyani
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