Risk assessment and mitigation measures of maritime navigation in the Caribbean Sea

Abstract

The Caribbean Sea, a vital maritime corridor with high vessel traffic and strategic access to the Panama Canal, faces growing navigational risks. This study develops a probabilistic risk assessment model incorporating vessel and environmental conditions, enhanced by an Artificial Neural Network to estimate incident probability. By leveraging Automatic Identification System (AIS) data and machine learning, mitigation scenarios were evaluated, confirming their effectiveness in reducing risk. The methodology advances traditional models by integrating multiple cause-related factors, offering a more comprehensive understanding of maritime safety. This research highlights the value of AIS and AI-driven approaches in enhancing risk mitigation and navigational resilience in the Caribbean Sea.