Decision Making for Improving Maritime Traffic Safety Using Constraint Programming

Decision Making for Improving Maritime Traffic Safety Using Constraint Programming

Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
AI for Improving Human Well-being. Pages 5794-5800. https://doi.org/10.24963/ijcai.2019/803

Maritime navigational safety is of utmost importance to prevent vessel collisions in heavily trafficked ports, and avoid environmental costs. In case of a likely near miss among vessels, port traffic controllers provide assistance for safely navigating the waters, often at very short lead times. A better strategy is to avoid such situations from even happening. To achieve this, we a) formalize the decision model for traffic hotspot mitigation including realistic maritime navigational features and constraints through consultations with domain experts; and b) develop a constraint programming based scheduling approach to mitigate hotspots. We model the problem as a variant of the resource constrained project scheduling problem to adjust vessel movement schedules such that the average delay is minimized and navigational safety constraints are also satisfied. We conduct a thorough evaluation on key performance indicators using real world data, and demonstrate the effectiveness of our approach in mitigating high-risk situations.
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